R3 by Maggie Chen

2 0 1 9

R3 R3

RESEARCH REVIEW & RELFECTIONS IN HUMAN BIOLOGY

TABLE OF CONTENTS

TARGETING BACE1 AS A THERAPY METHOD FOR ALZHEIMER’S DISEASE

ASD: EXAMINATION OF GUT MICROBIAL IMBALANCE ASSOCIATION WITH SOCIAL BEHAVIORAL DEFICITS, AND POTENTIAL TREATMENT METHODS

ALZHEIMER’S AS TYPE 3 DIABETES: MECHANISMS AND TREATMENT OF INSULIN RESISTANCE IN ALZHEIMER’S

A NEW MODULATOR FOR AGGRESSION-SEEKING BEHAVIOR IN MICE. WHAT IS ALL THE ΔFOSB ABOUT?

THE IMPORTANCE OF GLUCOCORTICOID RECEPTOR ACTIVATION IN THE ROLE OF MAJOR DEPRESSIVE DISORDER: A LITERATURE REVIEW ON THE HYPOTHALAMICPITUITARY-ADRENAL HYPOTHESIS OF DEPRESSION 34

THE ROLE OF UREA IN HUNTINGTON’S DISEASE 41

A NOVEL BDNF-LIKE PHARMACOLOGICAL AGENT TDP6 POTENTLY BINDS TRK2 RECEPTORS TO PROMOTE REMYELINATION AND OLIGODENDROCYTE DIFFERENTIATION IN THE CNS

TACKLING ANXIETY WITH LAVENDER: NEURONAL MECHANISMS OF LINALOOL

THE EFFECTS OF YOGA NIDRA AND SEATED MEDITATION ON STRESS, ANXIETY, PAIN, AND DEPRESSION

LINKING MICROGLIA FUNCTION AND LIPID SIGNALING IN ALZHEIMER’S DISEASE: THE LIPID PATHWAY AS NOT A CONSEQUENCE BUT A REGULATORY FACTOR

THE POTENTIAL INTERPLAY AMONG NEUROENDOCRINE ACTIVATION, NEUROBIOLOGICAL CHANGES, AND BEHAVIORAL ALTERATIONS IN SOCIAL ISOLATION

ARTPJ UNDERLIES INHIBITORY CONTROL MECHANISM DOMAIN GENERALLY IN ATTENTION REORIENTATION AND THEORY OF MIND: A TMS STUDY

DEPRESSION AND NEUROPATHIC PAIN: AN INVESTIGATION INTO FUTURE NOVEL TREATMENTS METHODS

TARGETING THE ACHILLES HEEL OF ZIKA VIRUS THROUGH ENGINEERED PEPTIDE

105

COMORBID ANIMAL MODEL OF DEPRESSION AND CHRONIC PAIN SHOWS LOSS OF MICROGLIA AND BDNF/CREB; SYMPTOMS REVERSED WITH DULOXETINE

111

REDUCING THE SEVERITY OF NEURODEGENERATIVE DISORDER SYMPTOMS WITH EXERCISE: SLOWING DOWN EARLY ONSET ALZHEIMERâ&#x20AC;&#x2122;S DISEASE

119

HOW A SMALL CHANNEL HOLDS THE KEY TO UNDERSTAND EPILEPSY

124

TOXOPLASMA GONDII PREFERENTIALLY TARGETS NEURONS IN THE CENTRAL NERVOUS SYSTEM

131

THE INTEGRATION OF SOCIAL INFLUENCES IN ANIMAL ADDICTION MODELS CAN CONTRIBUTE TO NOVEL TREATMENT OPTIONS FOR ADDICTION

139

STANDARD-DEVIATION DEPENDENT ADAPTIVE PREDICTION ERROR CODING IN THE HUMAN MIDBRAIN AND VENTRAL STRIATUM SUPPORTS LEARNING

147

MORE THAN JUST A SUGAR RUSH: THE IMPACT OF FRUCTOSE AND DIET-INDUCED INSULIN RESISTANCE ON THE ABILITY OF THE BRAIN TO RECOVER AFTER TRAUMATIC BRAIN INJURY

156

Designed by Maggie Chen Cover Image from Public Library of Science: Issue September 2012 Copyright ÂŠ 2019 Human Biology Program, University of Toronto, Toronto HMB300H1F

TARGETING BACE1 AS A THERAPY METHOD FOR ALZHEIMERâ&#x20AC;&#x2122;S DISEASE Elshaimaa Abdella Alzheimerâ&#x20AC;&#x2122;s Disease (AD) is a neurodegenerative disorder that causes dementia in older populations. No treatment is present and current methods aim to halt progression of the disease1. The Amyloid hypothesis suggests the accumulation amyloid beta protein (ABP) forming plaques outside the neuron as a cause to AD. Studies are aiming to prevent ABP production by targeting Beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). Since, BACE1 has many substrates and a large catalytic site, inhibition of this enzyme may result in adverse effects2,3,4. The original paper investigates the influence of BACE1 inhibitors (SCH1682496/LY2811376) on synaptic plasticity, and impairments in cognitive function. In vivo two-photon microscopy, and electrophysiological recordings were done on wildtype and BACE1 -/- knockout mice after orally providing BACE1 inhibitors. Although ABP levels went down, long term treatment reduced dendritic spine formation, synaptic connections, and LTP dependent synaptic plasticity which correlated to reduced performance in behavior tests2. Further studies found effects of BACE1 inhibition on astrogenesis and neurogenesis5, axon guidance6,7, muscle coordination8, memory, seizures9, etc. Some argue for the use of BACE1 inhibitors by suggesting multi-targeted drug approaches, changing the type of inhibitor, or altering timing and intervention methods. The controversy identifies the importance of understanding molecular mechanisms in BACE1 and substrates involved. Drug administration is dangerous when mechanisms are not fully understood. Evidence for and against BACE1 inhibition leaves to question whether is it a good idea targeting BACE1 as a possible therapeutic measure. Key words: Alzheimer Disease (AD), BACE1, Amyloid Precursor protein (APP), Amyloid Beta Plaques (ABP), Amyloid Hypothesis, synaptic plasticity, axon guidance, astrogenesis, neurogenesis, muscle coordination

Introduction

Alzheimer’s Disease (AD) is a complex neurodegenerative disorder that results in cognitive decline and Dementia. It is common at old age and although numbers are increasing, the specific cause is not well understood1. Hallmarks of AD are Amyloid Beta Plaques (ABP) outside nerve cells and tau protein forming neuronal tangles inside1,3,4. ABP arise from the accumulation of amyloid beta, a protein resulting from the cleavage of Amyloid Precursor Protein (APP) by BACE1 and γ-secretase. The presence of ABP in patients serves as a foundation towards the Amyloid Beta Hypothesis and suggests AD to be a result of increased production and reduced clearance of AB protein within the brain.2,3,4 The role of BACE1 as a rate limiting protease cleaving APP is thought to be a possible therapeutic target of manipulation to prevent accumulation of amyloid beta plaques2,10.

Overall, this brings to light the importance of understanding molecular procedures surrounding BACE1. It also brings forth the question of whether it is worth while trying to target this protease enzyme as a possible solution towards AD, when it is not clearly understood. MAJOR RESULTS

Although the use BACE1 inhibitors reduce the amounts of Amyloid beta in the cerebral spinal fluid2,3,4, it is unknown if it improves the well-being of the individual. With the rising interest in BACE1 inhibitors as a possible solution towards AD, there is increasing evidence stating otherwise.

To reiterate, the mechanisms and physiological functions of BACE1 are unknown. BACE1 includes a large active site, and so impairments in cognitive function following prolonged BACE1 inhibitor treatment suggests the role of BACE1 on alternate The rationale behind current therapy methods pathways as well2,9. involve inhibiting BACE1 as a possible solution to AD2,3,11,12. However, BACE1 has many substrates A recent 2018 double blind clinical study of and a large catalytic site and so inhibiting this Verubecestat (BACE1 inhibitor), was done on AD enzyme may cause adverse effects on cognitive patients with mild to moderate impairments with performance and brain structures2,3,4. The original a placebo control. Following treatment, it was paper investigates long term BACE1 inhibition found that cognitive and function properties did on structural and functional dynamics in the brain not improve and the study was ended early due to and cognitive performance. Results found long drug-related negative reactions18. While overall AB term treatment reduced dendritic spine formation, levels decreased, “therapeutic benefits” of BACE1 synaptic connections and plasticity which correlated inhibitors did not overshadow negative side effects. to impaired performance in behavior tests.2 Reactions included rashes, impaired motor control, weight loss, hair-color change, sleep disturbance, This idea falls in line with further studies and suicidal thoughts following treatment. investigating side effects of using BACE1 as an inhibitor. This includes effects on astrogenesis This served as a warning sign over the understanding and neurogenesis5, muscle coordination8, axon of BACE1 functions. Further studies show impacts guidance6,7, retinal pathology, myelination, spatial of inhibition. and working memory, epileptic like seizures, schizophrenic phenotypes9, and behavioral Astrogenesis and Neurogenesis symptoms associated with depression such as less exploratory behavior9,13. BACE1 was found to affect hippocampal astrogenesis through the Jag-1-Notch Pathway Regardless, studies still argue for the use of by directly impacting the cleavage of Jagged1 BACE1 inhibitors as a potential target towards (Jag1), a molecule involved in the Notch Signaling AD. Some suggest the use of a multi-target drug14, pathway. Notch plays a large role on inducing others suggest changing the type of inhibitor15 gene expression for differentiation of prosecutor or timing and intervention methods used during cells to astrocytes. It was found that BACE1 null treatment16,17. mice expressed higher levels of astrogenesis, and decreased neurogenesis within the Dentate 6

Gyrus. The lack of Jag1 cleavage increased the production of astrocytes and so offset the balance between astrogenesis and neurogenesis during development, altering brain functions. Note however, this pathway is more prominent in earlier stages of development5.

coordinating movement. Through various tests, overall results show Bace1−/− mutant mice to alter movement coordination through behavioral tests such as gait analysis, grid tests, and beam walking.

Figure 3. Amount of muscle spindles in control homozygous and heterozygous BACE1 mutant mice. Levels of spindles are shown to decrease with higher BACE1 inhibition. Image received from: www.ncbi.nlm.nih.gov/pmc/articles/PMC3715864/ Axon Guidance

Figure 1. Schematic Overview of BACE1 link within Jag-1-Notch Pathway. BACE1 cleaves Jag1 resulting in downstream mechanisms involved with Notch1 signaling to increase astrogenesis. Image received from: www.jbc.org/content/287/46/38408.long

Since, BACE1 was found to localize in presynaptic neurons, guidance molecules were suggested to be BACE1 substrates. A study finds BACE1 to be involved in axon guidance of olfactory sensory neurons (OSN), and glomerulus formation within the olfactory bulb. In vivo study of axon targeting was done on BACE1 -/- knock out mice and wildtype. Green fluorescent protein (GFP) was used to mark odorant-receptors and olfactory protein. Overall it was found, BACE1-/- mice produced a malformed glomerulus and had impaired OSNs targeting6. This was elaborated on within another study, and BACE1 inhibition was found to have effects on axon guidance in hippocampus Mossy Fiber Projections from the Dentate Gyrus to the CA3, in addition to inducing growth cone collapse. Specifically, it was linked with a neural cell adhesion molecule CHL1, and caused a loss-of-function CHL1 phenotype within knockout mice, suggesting the role as a substrate to BACE17.

Figure 2. Astrocyte amount (C) and Density (D) within the dentate gyrus in a molecular layer (Mo) and polymorph layer (Po) within control and mutant mice. Levels of astrocyte density is increased within mutant mice in both cases. Image received from: www.jbc.org/content/287/46/38408.long Muscle Coordination BACE1 influences muscle coordination through the formation and maturation of muscle spindles. It works with Ig-containing β1 Nrg1 (IgNrg1), an isoform of Neuregulin-1 (NRG1) involved in modulating the induction of muscle spindles, and 7

(A)

the pancreas, skin and brain9,15. Developmental Stages and Intervention A recent study found gradual BACE1 inhibition in mice through developmental stages reversed AB deposition, and improved changes in glial cells and synaptic functions.16

(B)

To do this they created conditional knockout mice with BACE1 flox (fl) to allow for the removal of BACE1 using Cre/lox based technology. This allowed for the gradual deletion of the gene as the mouse went through the developmental stages. Brain imaging to observe plaque deposition in the cerebral cortex, LTP recordings, and a contextual fear conditioning test was done to observe effects of the experiment. Overall, less amyloid beta plaques were observed, glial cells were not as effected, and Figure 4. CHL1 amounts in the olfactory Bulb (A) learning and behavior impairments were improved and Hippocampus (B). Results are based on an despite impairments in LTP recordings. However, immunoblot analysis with CHL1 antibody to identify the specific molecular cause of this are unknown16 concentrations in P7 and 3-month adult wildtype and BACE1−/− mutant mice, within the Olfactory Bulb (A) and Hippocampus (B). Levels of CHL1 are decreased in within BACE1−/− knockout mice in both P7 and Adult mice. Image received from: www. jbc.org/content/287/46/38408.long As mentioned previously in the original study, BACE1 inhibition impacted structural and functional dynamics of the brain, synaptic plasticity and cognitive function. Further studies also find BACE1 inhibition to impair retinal pathology, myelination, spatial and working memory, cause epileptic like seizures and schizophrenic phenotypes9, in addition to behavioral symptoms such as less exploratory behavior9,13. While this has caused reluctance in the investigation of BACE1 inhibitors as a possible approach to aid Alzheimer’s disease, others still see it as a possible therapeutic solution to AD.

Figure 5. Amount of plaque deposits within the cerebral cortex in sequential deletion of BACE1 through within conditional knockout mice. Number of plaques decreases with sequential deletion. Image received from: www.jbc.org/ content/287/46/38408.long

BACE2 as a Homologue Some have argued that inhibitors used to block BACE1 are also involved in blocking BACE2, a close homologue to BACE1. Unfortunately, mechanisms involved in BACE2 are not fully understood but are thought to be involved in serious side-effects on

Similarly, another recent study suggests that the reason why BACE1 inhibitors fail to aid cognitive decline is due to its usage in the late onset of the disease. It was found plaque formation was effected by the BACE1 inhibitor during initial phase of development, rather than the growth 8

phase.17 Experiments were done on transgenic mice and mutant mice and though in vivo twophoton imaging, immunohistochemistry assays, and protein analysis, a longitudinal approach was done to observe plaque formation kinetics and pathology before and throughout treatment. Even though plaque levels went down overall, the rate of plaque formation itself stayed high. It was found that preexisting plaques were responsible for inducing further plaque formation regardless of treatment. Instead, plaque formation was only effected if treatment was applied during the initial phase of beta amyloid deposition.17

a time Alzheimer symptoms also begin to show. Results raise to question to whether the inhibition of BACE1 does more harm than good. The clinical study of Verubecestat was a warning sign for this, as effects resulted in outcomes worse than ones seen in AD. That shows the dangers of administrating drugs when mechanisms are not fully understood.

DISCUSSION AND CONCLUSION

In conclusion, this leaves to question whether is it a good idea to continue targeting BACE1, when its functions are not understood and the hypothesis it is based on contains gaps in knowledge. Apart from forming plaques, molecular functions of amyloid beta are unknown19. It also sheds light on the need for understanding the physiological functions of BACE1, as its role may be more crucial to the brain then what is thought.

It is not understood why the study suggesting improvements in cognitive function with gradual inhibition of BACE1 through developmental stages, also sees impairments in LTP recordings16. Following this, impact on cognitive functions were not done in the study proposing its use during initial Apart from this, a recent review suggests the use of phases in development.17 The paper suggested multi-target drugs centered on BACE1 inhibitors, treatment can only work when an individual is at which works with amyloid beta production and cognitively normal conditions. However, since not additional AD pathways14. enough evidence is present to pinpoint early onset of AD, this procedure will be difficult and risky17.

BACE1 affects synaptic plasticity, astrogenesis and Neurogenesis, axon guidance6,7, muscle coordination8, etc. Some still see the use inhibitors as a possible approach to AD by suggesting a change in the type of inhibitor, timing or intervention methods in treatment. The common theme underlies the importance in understanding BACE1 molecular mechanisms, and the substrates and molecules surrounding it. This helps with a better understanding of pathways that can be CRITICAL ANALYSIS manipulated in AD to reduce its effects on alternate Further experiments should focus on understanding mechanisms within the brain. the functions of BACE1, its role on other substrates, Findings in the original paper shed light on this and and identifying the onset of Alzheimerâ&#x20AC;&#x2122;s Disease was a part of a series of studies going for or against earlier. BACE1 inhibition. Those going against it argue it is important in early development16,17. However, mechanisms such as Jag-Notch signaling pathway is more prominent in earlier stages of development, and postulated to be less active in adults.5 In addition, Axon guidance in the hippocampus7 and continuous regeneration of OSN6 was interpreted to also apply to neurons in the peripheral or central nervous system which undergoes neurogenesis and regeneration throughout development7. The same idea is present in muscle coordination and the role of BACE1 linked with NRG1, a mechanism crucial throughout all stages of development especially during injury recovery, and old age,

It is ironic that studies suggesting the use of BACE1 inhibitors recommend it to be within the initial phases of development16 or gradually17, while some studies against it warn BACE1 to be most crucial during early stages of development or throughout it. For instance, BACE1 plays a role in neurogenesis and regeneration, by aiding axon guidance mechanism and working with CHL17. This is also the case with its role with NRG1 for the formation and maturation of muscle spindles8, in addition to JAG1 for allowing the balance between astrogenesis 9

and neurogenesis5. All are within initial stages of development, and are largely impacted with the use of BACE1 inhibitors. Note all are also impaired at old age5,7,8, and found within AD which raises questions about the current understanding of BACE1.

The use of BACE1 during earlier stages of AD, is an issue for two reasons. The first being, lack of understanding in symptoms identifying AD onset. Second, AD patients have intact cognitive functions during earlier stages, and so inhibiting BACE1 is very risky if BACE1 mechanism are not fully understood. In addition, the implication on cognitive function was not clear within those studies17, and should be further investigated as well. Since both are new, further replication studies should be conducted as well. FUTURE EXPERIMENTS Future studies should involve understanding BACE1 molecular mechanisms and its role with substrates. One proposed study can investigate changes in BACE1 expression within mice with and without AD, and effects of gradual inhibition on cognitive function. Models will include the Octodon degus mice, a mouse model exhibiting AD naturally20, a transgenic mouse, and one that does not exhibit AD as a control. The first two are used to identify discrepancies that can result from genetic manipulation, but they are expected to behave the same. BACE1 inhibition will be done at initial and throughout progressive phases of development. NB-360 pellets will be provided as treatment at time intervals and soluble amyloid beta will be measured.17,21 Conditioned Fear Training will be done to examine cognitive function, as it is associated with learning and memory. Techniques such as in vivo magnetic resonance imaging can be done to look for plaque deposits and changes with treatment.22

with or without AD and treatment. BACE2 levels are observed to determine its effect following inhibition of BACE1, to determine if it plays a role in results9,15. BACE1 levels are investigated as they are associated with axon guidance6,7, astrogenesis5, regeneration5, muscle coordination8 etc. Since this is impaired in AD, perhaps increased levels of BACE1 are made to combat degradation of neuronal cells, rather than cause it. Its effect on amyloid beta may be the byproduct of an infinite loop, that results from the bodies response to ironically improve neuronal function. BACE1 expression values will be investigated in early phases of development in mice with AD, without AD, and with treatment. This will be done progressively throughout various stages of development. If what is suggested is a possibility, BACE1 should be upregulated in control and AD mice within early and later developmental stages. Cognitive function is expected to decrease in treatment conditions regardless of when it is given, since BACE1 is expected to serve an important role in development.

Overall this study should show the effects of BACE1 on cognitive function, and if targeting it can aid AD.

A microarray analysis will be done to investigate transcription levels of BACE1 and BACE2 to see if it is upregulated, downregulated or changed 10

REFERENCES 1. Scheltens P., Blennow K., et al. 2016. Alzheimer’s disease. Lancet. 388(10043):505-517 2. Filser S., Ovsepian S.V., et al. 2015. Pharmacological Inhibition of BACE1 Impairs Synaptic Plasticity and Cognitive Functions. Biol Psychiatry. 77(8):729-739 3. Evin G., Hince C. 2013. BACE1 as a Therapeutic Target in Alzheimer’s Disease: Rationale and Current Status. Drugs Aging. 30(10):755-764 4. Zhu K., Peters F., et al. 2018. Consequences of Pharmacological BACE Inhibition on Synaptic Structure and Function. Biol Psychiatry. 84(7):478-487 5. Hu X., He W. et al. 2013. BACE1 Regulates Hippocampal Astrogenesis via the Jagged1-Notch Pathway. Cell Rep. 4(1):40-49 6. Rajapaksha T.W, Eimer W.A, et al. 2011. The Alzheimer’s β-secretase enzyme BACE1 is required for accurate axon guidance of olfactory sensory neurons and normal glomerulus formation in the olfactory bulb. Mol Neurodegener. 6(1):88 7. Hitt B., Riordan S.M et al. 2012. β-Site Amyloid Precursor Protein (APP)-cleaving Enzyme 1 (BACE1)-deficient Mice Exhibit a Close Homolog of L1 (CHL1) Loss-of-function Phenotype Involving Axon Guidance Defects. J Biol Chem. 287(46):38408-38425 8. Cheret C., Willem M., et al. 2013. Bace1 and Neuregulin-1 cooperate to control formation and maintenance of muscle spindles. EMBO J. 32(14):2015-2028 9. Barao S., Moechars D., et al. 2016. BACE1 Physiological Functions May Limit Its Use as Therapeutic Target for Alzheimer’s Disease. Trends Neurosci. 39(3):158-169 10. May P.C, Dean R.A, et al. 2011. Robust Central Reduction of Amyloid-β in Humans with an Orally Available, Non-Peptidic β-Secretase Inhibitor. J Neurosci. 31(46):16507-16516 11. Vassar R, Kandalepas P.C. 2011. The β-secretase enzyme BACE1 as a therapeutic target for Alzheimer’s disease. Alzheimers Res Ther. 3(3):20-26 12. Bachurin S.O, Bovina E.V., et al. 2017. Drugs in Clinical Trials for Alzheimer’s Disease: The Major Trends. Med Res Rev. 37(5):1186-1225 13. Harrison S.M, Harper A.J. et al., 2003. BACE1 (beta-secretase) transgenic and knockout mice: identification of neurochemical deficits and behavioral changes. Mol Cell Neurosci. 24(4):646655 14. Prati F., Bottegoni G, et al. 2018. BACE-1 Inhibitors: From Recent Single-Target Molecules to Multitarget Compounds for Alzheimer’s Disease. J Med Chem. 61(3):619-637 15. Yan R.Q. 2017. Physiological Functions of the β-Site Amyloid Precursor Protein Cleaving Enzyme 1 and 2. Front Mol Neurosci. 10:97-109. 16. Hu X.Y., Das B, et al. 2018. BACE1 deletion in the adult mouse reverses preformed amyloid deposition and improves cognitive functions. J Exp Med. 215(3):927-940 17. Peters F., Salihoglu H. et al. 2018. BACE1 inhibition more effectively suppresses initiation than progression of β-amyloid pathology. Acta Neuropathol. 135(5):695-710 18. Egan M.F, Kost J., et al. 2018. Randomized Trial of Verubecestat for Mild-to-Moderate Alzheimer’s Disease. N Engl J Med. 378(18):1691-1703 19. Dawkins E., Small D.H. 2014. Insights into the physiological function of the β-amyloid precursor protein: beyond Alzheimer’s disease. J Neurochem. 129(5):756-769 20. Deacon R.M.J., Altimiras F.J., et al. 2015. Natural AD-Like Neuropathology in Octodon degus: Impaired Burrowing and Neuroinflammation. Curr Alzheimer Res. 12(4):314-322 21. Neumann U., Rueeger H., et al. 2015. A novel BACE inhibitor NB-360 shows a superior pharmacological profile and robust reduction of amyloid-β and neuroinflammation in APP transgenic mice. Mol Neurodegener.10(1):44-59 22. Wadghiri Y.Z., Hoang D.M., et al. 2012. In vivo magnetic resonance imaging of amyloid-β plaques in mice. Methods Mol Biol. 849:435-451

ASD: Examination of Gut Microbial Imbalance Association with Social Behavioral Deficits, and Potential Treatment Methods Raseel Abu-Hassan Maternal obesity has been associated with increased risk of neurodevelopmental disorders in the offspring, including autism spectrum disorder. Buffington et al. (2016) look at how with maternal regular diet, the offspring gut microbiome is normal, and their social behavior is normal. However, with maternal high fat diet, there was dysbiosis in the offspringâ&#x20AC;&#x2122;s gut microbiome and induced alterations in the offspring social behavior. Yet, it was found that with a treatment of Lactobacillus reuteri on the offspring of the maternal high fat diet, they started to exhibit normal characteristics in terms of gut microbiome and social behavior, similarly to the maternal regular diet. These findings provide a link between the gut microbiome and neurodevelopmental disorders and possible treatments for ASD symptoms. Key words: autism spectrum disorder (ASD); maternal high fat diet (MHFD); maternal regular diet (MRD); Lactobacillus (L.) reuteri; dysbiosis; gut-brain axis; gut microbiome

BACKGROUND AND INTRODUCTION

as Veillonellaceae bacterial group (KrajmalnikBrown et al., 2015). This shows that there is an association between the gut, gut bacteria and the presence ASD symptoms. With a vast group of studies supporting this association through the gut and the brain bidirectional communication system, called the gut-brain axis (Li & Zhou, 2016; Petra et al., 2015; Luna & Foster, 2015), it is indicated that the relationship between gut dysbiosis and neurobehavioral symptoms could influence the development of ASD symptoms.

Autism spectrum disorder (ASD) is a severe brain developmental disorder, characterized by the emergence of deficits in communication and social interaction, and the presence of stereotyped behaviors before the age of three. This causes significant influences of children in their development and their behaviors (Redcay and Courchesne, 2008). At the age of 1 and 2 of age, autism behavioral signs may appear such as defects in language development, social interaction and emotional reactivity (Lord and Risi, 2000). It is still unknown how changes in gut microbiota could influence brain development and function. While ASD diagnoses are increasing worldwide (Lai Moreover, there is currently no treatment for et al., 2013), the cause of ASD is relatively unknown. autism. However, in a mouse model of autism, it Previously, most research was aimed at finding was found that the mouse had a gut microbiota the relationship between ASD and genetics. Twin different from healthy mice, and by adjusting their studies in children in Denmark, Finland, Iceland, gut microbiome, they saw improvements in ASD Norway and Sweden found that monozygotic twins related symptoms (Hsiao et al., 2013). This suggests had 91% accordance for autism while dizygotic a potential treatment for autism by targeting the had 0% (Steffenburg et al., 1989). However, in a gut microbiome. large twin study it was found among twins, 55% of the variance in autism was accounted by the With the increase prevalence of obesity in the environment (Hallmayer et al. 2011). Currently, population (Pozza & Isidori, 2018; Hales et al., it is proposed that the cause of ASD also has an 2018), the consequences of maternal obesity environmental influence, leading to a growth in are important to understand especially with studies looking at potential environmental factors the concerns in offspring brain and behavioral that cause ASD in individuals. Recently, it was seen functions. Moreover, there is a need for more that there was an increased risk of developmental research to be looking at whether these factors disorders such as ASD in maternal prepregnancy really influence ASD by eliminating the influence obesity and maternal diabetes (Li et al., 2016). of any other factors. Therefore Buffington et Moreover, Schultz and his colleagues looked at al. looked at the influence of maternal diet and potential causes after birth, studying the influence gut microbiota on the risk of ASD in mice under of the babyâ&#x20AC;&#x2122;s nutrition on their risk of developing laboratory settings. They reported an association ASD. They found that the risk for autistic disorder between maternal high-fat diet (MHFD)-induced increased in the absence of breastfeeding and in obesity in mice and dysbiosis in the offspringâ&#x20AC;&#x2122;s gut infants fed formula without docosahexaenoic acid/ microbiome, which induced deficits in the offspring arachidonic acid supplementation (Schultz et al., social behavior. Nevertheless, it was found that 2006). These studies suggest the link between the treatment of Lactobacillus (L.) reuteri on MHFD nutrition and the development of the brain. This offspring corrected gut microbiome and social caused for more studies to look more specifically behavior, similarly to the maternal regular (MR) at the relationship between the gut and the brain. diet. These findings provide a link between the gut microbiome and neurodevelopmental disorders Coincidentally, individuals with ASD experience and possible treatments for ASD. greater prevalence of GI symptoms, such as diarrhea and constipation (McElhanon et al., MAJOR RESULTS 2014). Moreover, in patients with autism with minimal GI symptoms, there is a change in the Impaired Social Behaviors and Dysbiosis of the Gut intestinal microbiota with lower levels of bacteria Microbiota in MHFD Offspring in the Coprococcus genera and Prevotella, as well 13

Buffington and her colleagues fed Female mice high fat diet (HFD) or regular diet (RD) for eight weeks to investigate the effects maternal dietinduced obesity on offspring neurodevelopment. They then studied the social behavior of the MHFD and the maternal regular diet (MRD) offspring. They assessed sociability, reciprocal interactions and social novelty and found that the MHFD offspring displayed social deficit as they had fewer reciprocal social interactions, no preference for social novelty and had impaired sociability compared to MRD offspring.

(Gilbert, 2015). This microbiome has been associated with many neurodevelopmental functions and disorders (Li, 2017). There have been multiple studies indicating the health benefits of fecal microbiota transplantation to change a sick recipient’s microbial composition (Smits at al., 2013; Bakken et al., 2011). As mice are coprophagic (Ridaura et al., 2013), to test the possible benefits of fecal microbiota transplantation in healthy mice and mice that exhibit ASD symptoms, one MHFD offspring was co-housed with three MRD offspring. To test the difference, the controls consisted of co-housing four MHFD offspring in one cage, and co-housing four MRD offspring in another. Results showed that co-housed MRD and MHFD offspring together lead to a correction of the MHFD mice reciprocal social interactions, sociability, preference for social novelty, and bacterial phylogenetic profile to resemble that of MRD mice (Buffington et al., 2016).

Figure 1 A) social interaction task representation B and C) MHFD offspring had reduced social interaction compared to MRD offspring D and E) MHFD offspring spent less time interacting with a mouse in the sociability test, and in the social novelty test MHFD offspring had no preference for social novelty compared to the MRD offspring

There is also evidence to show that maternal diet alters offspring’s gut microbiome (Ma et al.,2014) and that ASD patients have dysbiosis in their gut biome (McElhanon et al., 2014; Krajmalnik-Brown et al., 2015; Hsiao et al., 2013). Buffington and her colleagues used 16s rRNA gene sequencing on the offspring feces to examine whether maternal diet caused an alteration in the offspring’s gut microbiota. They found that both MHFD and MRD offspring had Bacteroidetes and Firmicutes dominated gut microbiota. However, the bacterial communities’ structures were different and, compared to MRD microbiota, the MHFD offspring had a reduced microbiota diversity. Overall, a high fat diet in mothers caused a change in their microbiome diversity, similarly to what was observed in their offspring. This shows an association between the mother and the offspring, showing that maternal diet could have consequences on the offspring’s health and development after delivery. Gut Microbiota Mediate MHFD-Induced Social Deficits

Figure 2 A) co-housing representation B) co-housing groups C-F) co-housed MHFD offspring lead to higher reciprocal social interactions, sociability and preference for social novelty compared to MHFD offspring While co-housing may have relieved some symptoms of ASD, it didn’t seem to have an effect on all symptoms including repetitive behaviors. Rescue marble burying is a perseverative and repetitive behavioral task. Intriguingly, this behavior was increased in GF mice and fecal microbial transplants from either MRD or MHFD offspring did not correct this repetitive behavior. Moreover, this behavior was not restored when co-housing MHFD with MRD offspring. Therefore, the gut microbiome is not responsible for all ASD symptoms, such as repetitive behaviors.

Every individual has a unique gut microbiome 14

Correction in Social Behavior Deficit of Germ- promotes oxytocin levels in the brain (Donaldson Free Mice with the Colonization of Microbiota and Young, 2008). Buffington et al. examined this from MRD, but Not MHFD Mice relationship by introducing L. reuteri into the diet of the MHFD offspring. This treatment exhibited to Studies have shown that signaling mechanisms are improve the preference for social novelty and the initiated by microbial colonization, which affect sociability very significantly in the MHFD offspring. neuronal circuits involved in behavior (Heijtz et Still, the L. reuteri treatment did not change MRD al., 2011). To examine whether a specific bacterial offspring social behavior, probably because they species is responsible for social deficit behaviors already have L. reuteri in their gut microbiome. (Dinan et al., 2015), Buffington and her colleagues Treatment with L. johnsonii (another Lactobacillus looked at whether germ free (GF) mice would then species) did not rescue MHFD offspring social have impaired social behaviors. Two groups were behaviors like with L. reuteri treatment, making a created, and fecal microbiota transplantation was clear indication that L. reuteri is specific to social preformed between the MDR offspring and GF behavior. Nevertheless, L. reuteri treatment did mice, and between the MHFD offspring and GF not restore all ASD related symptoms as in MHFD mice. They found that the GF mice with microbiota offspring, it had no effect in improving anxiety. from the MHFD offspring remained with the socially This indicates that while L. reuteri can correct some impaired characteristics while the GF mice with ASD symptoms in relation to social behaviors, it is the MRD offspring microbiota had normal social not a solution for all ASD symptoms. behavior. This shows that there is an association between the microbiome and the behavior as social CONCLUSION/DISCUSSION behavior was effectively improved by microbial reconstitution. Buffington et al. (2016) came to the overall conclusion that their findings provide possible treatments for ASD by finding a link between the gut microbiome and neurodevelopmental disorders. MHFD offspring displayed dysbiosis and social defects, as they had fewer reciprocal social interactions, no preference for social novelty and had impaired sociability compared to MRD offspring. Through co-housing, they were able to see that microbial reconstitution effectively improved social behavior. They were also able to Figure 3 A-D) GF mice showed reduced reciprocal link L. reuteri to social behavior and was able to social interaction, preference for social novelty, and see how L. reuteri treatment can release certain deficits in sociability compared to the control group ASD symptoms in relation to social behaviors. Social The authors also acknowledge that their results correspond with many other studies, especially when stating that ASD relates to gut microbiome From the MHFD and MRD offspring, metagenomic and that the maternal diet plays a strong role in shotgun sequencing was performed on their fecal this association and in affecting the risk of ASD samples to examine if the MHFD offspring had symptoms in their offspring. Buffington and her a specific bacterial species absent from its gut colleagues took it one step further by linking these microbiome. Analysis showed that in the MHFD findings together to find the association between offspring microbiota, there were many differences the microbiome and the brain, to find the possible in bacterial species, L. reuteri being the most cause of ASD behavioral symptoms. Treatment with L. reuteri Behavior in MHFD Offspring

Reverses

dramatically reduced. Oxytocin is a very important hormone in regulating social behaviors (Neumann & Unlike other studies done in this field, Buffington Landgraf, 2012). Studies have shown that L. reuteri et al. directed the research to find a possible 15

treatment that hasnâ&#x20AC;&#x2122;t been regarded before. Not only did they look at fecal microbial transplants, but they identified and specifically looked at the influence of one specific bacterium to see the effect on ASD symptoms. By doing this, they were able to attempt to narrow down the treatment by finding a direct link between the microbiome and neurodevelopment of the brain. Even though they were not able to find the treatment for all ASD symptoms, there were able to take the treatment one step further. They found a specific source for a certain symptom of ASD, opening up more possibilities of finding other bacterial species that are responsible for other symptoms, and possibly a specific bacterial species that is responsible for almost all ASD symptoms. This opens up to possible probiotic treatments for individuals with ASD to reverse their behavioral deficits (Buffington et al., 2016).

equivalent to the same degree when administered to humans.

Other elements that were not examined was the function of the immune system in ASD symptoms. It has been identified in many studies that the gut microbiota regulates the homeostasis of the immune system, which is essential for health (Wu & Wu, 2012). Moreover, many studies have found that autism is liked to maternal viral exposure as well as immune abnormalities in the offspring with ASD (Warren et al., 1986; Stubbs et al., 1977). Thus, if the gut microbiome is affecting ASD symptoms, it could be also affecting it indirectly through the immune system. This factor should be analyzed and considered as probiotics could have an alternative indirect effect that could be constituting the change in behavior that was observed.

These possibilities have not been considered in this study and could open up further research in manipulating ASD treatments to find a treatment Buffington et al. (2016) focus on how ASD that reverses ASD symptoms. symptoms of social deficits in offspring could originate from maternal diet, and how microbial FUTURE DIRECTIONS reconstitution could reverse these symptoms. This research paves an alternative root in looking Researchers should look at testing other strains for treatments for neurodevelopmental disorders. of bacteria to see the possible effects of specific Buffington and her colleagues mention that when microbiome on behavior and brain hormones. By looking at the difference between the microbiome carefully selecting a combination of different stains of MHFD offspring and MRD offspring, there were and species of bacteria, we could create a probiotic many species of bacteria that differed significantly. treatment that may be useful to treat ASD patients Yet, they only looked at the L. reuteri as it had the in a quick and non-invasive method. greatest difference. Even though other bacterial species may not differ as significantly as L. reuteri Moreover, to make this experiment more related in the gut microbiome, it could still have an effect to humans, human factors could be introduced on the brain hormones and its development. Many and tested out. Instead of testing the possible factors were not considered when examining the effects on mice and mice microbiome, a humanimpact of L. reuteri. For example, whether L. reuteri like microbiome could be created. Using GF impacted other bacterial species and whether that mice and human fecal transplantation from ASD might have caused the treatment effect, instead patients and healthy patients, two different groups of L. reuteri itself causing it. Looking that the could be made to compare. Then we could test fecal sample after the treatment might have been actual human microbiome and look at the effects beneficial to examine how the gut microbiota could and changes of the brain and behavior, to create have changed. a treatment that is more suitable and beneficial to humans. For instance, humans might have Model organisms are not always the exact another dominant bacterial species that differ representation on how the human body will react between patients with ASD symptoms and healthy and function to certain conditions. As this study individuals. This microbiota could affect multiple is focusing on creating treatments for humans, symptoms of ASD and could cause a larger effect the possible treatments found in mice may not be 16 CRITICAL ANALYSIS

on the brain function. Humans and mice are very different, and it is possible that the reason L. reuteri was more dominant in the gut of mice, was because mice have some conditions that allow L. reuteri to grow better, however this might not be the case in humans. Therefore, it is important to make this experiment as close to human effects as possible to find the best treatment. Even though some bacterial species do not cause any differences in ASD symptoms, this can allow researchers to eliminate bacterial species that would not be included in the probiotic treatment, making it more specific and effective than giving general gut microbiota from a healthy individual to an individual with ASD symptoms. Moreover, various doses of probiotics could be given to see if they are effective at certain amounts. The reason that L. reuteri was not able to treat all symptoms of ASD could have been due to the concentration of it in the gut. Therefore, more research could be conducted to see the possible effect to devise the best treatment that will give optimal results.

As mentioned by other studies, the gut-brain axis is mediated by the vagus nerve (Davari et al., 2013). To test whether the gut microbiome causes a direct influence on the brain function, thus ASD behavioral deficits, the vagus nerve could be cut to stop the direct communication between the gut and the brain. If the benefits are no longer seen, then we could associate the gut microbiome change with the brain function and behavior more strongly. However, if the benefits still persist in the correction of the ASD symptoms, then it is possible that the gut microbiome indirectly affect the brain and behavior, and other factors such as the immune system could be considered to find a more applicable and constructive treatment.

REFERENCES 1. Buffington, S. A., Di Prisco, G. V., Auchtung, T. A., Ajami, N. J., Petrosino, J. F., & Costa-Mattioli, M. (2016). Microbial reconstitution reverses maternal diet-induced social and synaptic deficits in offspring. Cell, 165(7), 1762-1775. 2. Redcay, E., & Courchesne, E. (2008). Deviant functional magnetic resonance imaging patterns of brain activity to speech in 2–3-year-old children with autism spectrum disorder. Biological psychiatry, 64(7), 589-598. 3. Lord, C., & Risi, S. (2000). Diagnosis of autism spectrum disorders in young children. Autism spectrum disorders: A transactional developmental perspective, 9, 11-30. 4. Lai, M. C., Lombardo, M. V., Suckling, J., Ruigrok, A. N., Chakrabarti, B., Ecker, C., ... & MRC AIMS Consortium. (2013). Biological sex affects the neurobiology of autism. Brain, 136(9), 27992815. 5. Steffenburg, S., Gillberg, C., Hellgren, L., Andersson, L., Gillberg, I. C., Jakobsson, G., & Bohman, M. (1989). A twin study of autism in Denmark, Finland, Iceland, Norway and Sweden. Journal of Child Psychology and Psychiatry, 30(3), 405-416. 6. Hallmayer, J., Cleveland, S., Torres, A., Phillips, J., Cohen, B., Torigoe, T., ... & Lotspeich, L. (2011). Genetic heritability and shared environmental factors among twin pairs with autism. Archives of general psychiatry, 68(11), 1095-1102. 7. Li, M., Fallin, M. D., Riley, A., Landa, R., Walker, S. O., Silverstein, M., ... & Hong, X. (2016). The association of maternal obesity and diabetes with autism and other developmental disabilities. Pediatrics, 137(2), e20152206. 8. Schultz, S. T., Klonoff-Cohen, H. S., Wingard, D. L., Akshoomoff, N. A., Macera, C. A., Ji, M., & Bacher, C. (2006). Breastfeeding, infant formula supplementation, and Autistic Disorder: the results of a parent survey. International breastfeeding journal, 1(1), 16. 9. McElhanon, B. O., McCracken, C., Karpen, S., & Sharp, W. G. (2014). Gastrointestinal symptoms in autism spectrum disorder: a meta-analysis. Pediatrics, 133(5), 872-883. 10. Buffington, S. A., Di Prisco, G. V., Auchtung, T. A., Ajami, N. J., Petrosino, J. F., & Costa-Mattioli, M. (2016). Microbial reconstitution reverses maternal diet-induced social and synaptic deficits in offspring. Cell, 165(7), 1762-1775. 11. Krajmalnik-Brown, R., Lozupone, C., Kang, D. W., & Adams, J. B. (2015). Gut bacteria in children with autism spectrum disorders: challenges and promise of studying how a complex community influences a complex disease. Microbial ecology in health and disease, 26(1), 26914. 12. Li, Q., & Zhou, J. M. (2016). The microbiota–gut–brain axis and its potential therapeutic role in autism spectrum disorder. Neuroscience, 324, 131-139. 13. Petra, A. I., Panagiotidou, S., Hatziagelaki, E., Stewart, J. M., Conti, P., & Theoharides, T. C. (2015). Gut-microbiota-brain axis and its effect on neuropsychiatric disorders with suspected immune dysregulation. Clinical therapeutics, 37(5), 984-995. 14. Luna, R. A., & Foster, J. A. (2015). Gut brain axis: diet microbiota interactions and implications for modulation of anxiety and depression. Current opinion in biotechnology, 32, 35-41. 15. Hsiao, E. Y., McBride, S. W., Hsien, S., Sharon, G., Hyde, E. R., McCue, T., ... & Patterson, P. H. (2013). The microbiota modulates gut physiology and behavioral abnormalities associated with autism. Cell, 155(7), 1451. 16. Pozza, C., & Isidori, A. M. (2018). What’s Behind the Obesity Epidemic. In Imaging in Bariatric Surgery (pp. 1-8). Springer, Cham. 17. Hales, C. M., Fryar, C. D., Carroll, M. D., Freedman, D. S., & Ogden, C. L. (2018). Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007-2008 to 2015-2016. Jama, 319(16), 1723-1725. 18. Ma, J., Prince, A. L., Bader, D., Hu, M., Ganu, R., Baquero, K., ... & Aagaard, K. M. (2014). Highfat maternal diet during pregnancy persistently alters the offspring microbiome in a primate model. Nature communications, 5, 3889. 19. Gilbert, J. A. (2015). Our unique microbial identity. Genome biology, 16(1), 97.

20. Li, Q., Han, Y., Dy, A. B. C., & Hagerman, R. J. (2017). The gut microbiota and autism spectrum disorders. Frontiers in cellular neuroscience, 11, 120. 21. Smits, L. P., Bouter, K. E., de Vos, W. M., Borody, T. J., & Nieuwdorp, M. (2013). Therapeutic potential of fecal microbiota transplantation. Gastroenterology, 145(5), 946-953. 22. Bakken, J. S., Borody, T., Brandt, L. J., Brill, J. V., Demarco, D. C., Franzos, M. A., ... & Moore, T. A. (2011). Treating Clostridium difficile infection with fecal microbiota transplantation. Clinical Gastroenterology and Hepatology, 9(12), 1044-1049. 23. Ridaura, V. K., Faith, J. J., Rey, F. E., Cheng, J., Duncan, A. E., Kau, A. L., ... & Muehlbauer, M. J. (2013). Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science, 341(6150), 1241214. 24. Heijtz, R. D., Wang, S., Anuar, F., Qian, Y., Björkholm, B., Samuelsson, A., ... & Pettersson, S. (2011). Normal gut microbiota modulates brain development and behavior. Proceedings of the National Academy of Sciences, 108(7), 3047-3052. 25. Dinan, T. G., Stilling, R. M., Stanton, C., & Cryan, J. F. (2015). Collective unconscious: how gut microbes shape human behavior. Journal of psychiatric research, 63, 1-9. 26. Neumann, I. D., & Landgraf, R. (2012). Balance of brain oxytocin and vasopressin: implications for anxiety, depression, and social behaviors. Trends in neurosciences, 35(11), 649-659. 27. Donaldson, Z. R., & Young, L. J. (2008). Oxytocin, vasopressin, and the neurogenetics of sociality. Science, 322(5903), 900-904. 28. Wu, H. J., & Wu, E. (2012). The role of gut microbiota in immune homeostasis and autoimmunity. Gut microbes, 3(1), 4-14. 29. Warren, R. P., Margaretten, N. C., Pace, N. C., & Foster, A. (1986). Immune abnormalities in patients with autism. Journal of autism and developmental disorders, 16(2), 189-197. 30. Stubbs, E. G., Crawford, M. L., Burger, D. R., & Vandenbark, A. A. (1977). Depressed lymphocyte responsiveness in autistic children. Journal of autism and childhood schizophrenia, 7(1), 49-55. 31. Davari, S. A. E. I. D. E. H., Talaei, S. A., & Alaei, H. O. J. A. T. O. L. L. A. H. (2013). Probiotics treatment improves diabetes-induced impairment of synaptic activity and cognitive function: behavioral and electrophysiological proofs for microbiome–gut–brain axis. Neuroscience, 240, 287-296.

Alzheimer’s as Type 3 Diabetes: Mechanisms and Treatment of Insulin Resistance in Alzheimer’s Juanita Atton Diabetes and Alzheimer’s disease (AD) are two age-related diseases that are increasing in interest within the field of neuroscience, due to numerous studies indicating that patients with Type 2 diabetes (T2D) have increased risk for developing AD. Insulin resistance and decreased efficiency of signaling are hallmarks of both diseases and are known to be implicated with advancing the progression of AD pathologies. Researchers aiming to find solutions for AD symptoms have identified intranasal insulin delivery as a possible therapeutic line of treatment, due to its ability to promote amyloid-ß degradation and thus reduce its cytotoxic effect on cells. Although initially promising, long-term administration of long-lasting insulin detemir utilized in some studies shows possible negative effects by inducing hyperinsulinemia which can exacerbate the existing cognitive problems seen in AD. Alternative approaches aim to utilize pre-existing T2D medications to help induce insulin sensitivity in the brain and avoid insulin saturation. This review provides a brief overview of the interaction of insulin with amyloid-ß (Aß) fibers and how it influences the memory deficits observed in AD, as well as potential applications of insulin and T2D medications to help diminish the progression of AD symptoms.

(Fernandez & Torres-Alemán, 2012), which are areas highly implicated in memory processing Introduction (Lee, Kuo, Huang, & Hsu, 2009; Stanley, Macauley, & Holtzman, 2016). This fact helps to explain The onset of senesce brings about many profound the cognitive deficits observed in both of these changes to individuals, ranging from decreased disorders. activity levels to memory problems, all of which are symptoms commonly linked to overall changes in Although amyloid-ß (Aß) plaques have been long metabolism. Higher cognitive processing needed recognized to be a major histological marker of AD to perform memory tasks comes with considerable (Masters et al., 1985), emerging research has shown energy costs. Although it accounts for only 2% of that a reduction of cerebral glucose metabolism body weight, the brain has the greatest amount of due to insulin resistance can also contribute to the glucose consumption in the body in comparison to aggregation of these proteins (Liu et al., 2015). other organs (Mergenthaler, Lindauer, Dienel, & Brain insulin resistance is not dependent on the Meisel, 2013). Glucose is recruited to brain areas presence of T2D (Umegaki, 2013); however, it’s involved in cognitive tasks in order to deliver the presence further exacerbates Aß accumulation that necessary nutrients for optimal cell activity (Attwell is already present. Insulin signaling has widespread et al., 2010; Tarumi & Zhang, 2018). Several effects in neuronal maintenance, neurotransmitter studies show that metabolic processes needed for regulation and signaling mechanisms underlying proper functioning are markedly different in older long-term potentiation and memory (Reger et al., individuals, such as a decrease in cerebral blood 2008). Its widespread distribution in the brain adds flow, glucose metabolism in the brain (Peters, to the complexity of attempting to understand its 2006) and insulin signaling needed to maintain signaling in mediating cognitive processes (Stanley glucose homeostasis. et al., 2016). Much emerging research has focused on understanding the relationship between insulin Early changes in olfaction seen in older individuals and AD-progression in attempts to develop can be attributed to aspects of insulin signaling possible therapeutic treatments to help slow down dysregulation and insulin resistance (Fernandez & the progression of the disease. Some research (Lee Torres-Alemán, 2012). Smell being closely linked et al., 2009) has focused on the ability of insulin with taste causes profound changes in food and insulin growth factor-1 (IGF-1) to inhibit Aß preferences of older adults. Often these food oligomer formation whereas other research (Liu et preferences result in adding more condiments to al., 2015) has focused on low-density lipoprotein food, such as sugar, in order for them to become receptor-related protein 1 (LRP1) and their Aß palatable. The combination of these changes in clearance mechanisms. food preferences combined with decreased insulin signaling places older individuals at a very high risk In a research study by Craft et al (2017), researchers of developing T2D. utilize insulin administration as a potential therapy for AD. Due to the high concentration of Insulin dysregulation and diabetes are becoming insulin receptors found within the olfactory bulb more prevalent topics in neuroscience due to the (Fernandez & Torres-Alemán, 2012), researchers high incidence of comorbidity of type 2 diabetes utilize an intranasal route allowing for quick and easy (T2D) with other age-related neurologically- delivery into the brain. Researchers demonstrate linked disorders. It has been found that individuals how insulin therapy can help alleviate symptoms with diabetes have up to a 2-fold higher risk of of memory decline by reducing levels of Aß in the developing Alzheimer’s disease (AD) (Ott et al., CSF as well as slowing the progression of neural 1999). These two diseases share many pathological atrophy in areas associated with AD. features such as a decrease in cerebral glucose metabolism, increased insulin resistance and RESULTS cognitive decline (Liu et al., 2015). Insulin receptors are known to be highly concentrated in the All participants in the study (Craft et al., 2017) were olfactory bulb, hypothalamus, and hippocampus screened for eligibility based on cognitive testing 21

utilizing Mini-Mental State Examination (MMSE) scores (Folstein, Folstein, & McHugh, 1975). All participants showed scores at or below 15 and thus were considered impaired. Participants were also screened for other conditions such as traumatic brain injury, neurologic disorders, psychiatric disorders and diabetes. It was hypothesized that longer-lasting insulin, due to its greater lipophilicity, would be better absorbed by the brain and induce a greater cognitive benefit (Craft et al., 2017). Effects of treatment conditions were compared to placebos, utilizing cerebrospinal fluid (CSF) biomarkers as well as nuclear imaging and cognitive assessment reports. The present study showed that regular insulin had marked effects on AD pathology compared to both longlasting detemir and placebo subgroups (Craft et al., 2017) (Fig. 1).

Areas such as the parietal cortex, cingulum and hippocampus are highly active during periods of high-level memory engagement (Wang et al., 2015). Hippocampal atrophy is known to underlie episodic memory impairment which is exacerbated by the disruption of the cingulum bundle due to gray-matter atrophy (Villain et al., 2008), all effects seen during AD pathology.

Figure 2. Graphs depicting the changes in brain volume (cm3) for AD-related ROIs. Increased volumes can be seen in four ROIS for the regular insulin-treated group including L superior parietal, R mid cingulum, L cuneus, R parahippocampal gyrus. Figure adapted from Craft et al. (2017) Regular insulin treatment was associated with increased cerebral volumes in all of these ROIs which Figure 1. Plot representing the changes of delayed was correlated with improved memory at both 2 memory composite scores for placebo, regular and 4-months of treatment (Fig. 2). Insulin-treated insulin and detemir-treated groups. There exists individuals performed better in memory analyses a significant difference in delayed memory for the testing delayed story recall, which is a measure of regular insulin-treated group indicating improved verbal memory (Craft et al., 2017). However, no memory at both 2 and 4-month testing. significant difference was seen in treatment groups Figure adapted from Craft et al. (2017) compared to placebo for ADAS-Cog12 measures looking at language, praxis and orientation (Craft Researchers identified several regions of interest et al., 2017) since these regions associated with (ROIs) such as left and right middle cingulum, left increased volumes are not implicated with that cuneus, hippocampus, right superior frontal and type of processing. parietal regions (Craft et al., 2017) (Fig. 2). All of Furthermore, regular insulin showed an improved these regions are known to be functionally relevant CSF biomarker profile by lowering the CSF tau181/ to cognitive processing as they are connected to AĂ&#x;42 ratio (Craft et al., 2017). This ratio has been the default mode network (DMN) (Wang et al., previously identified as a sensitive biomarker for AD 2015). The DMN is a network of interconnected (Harari et al., 2014) and a possible way to identify brain regions with highly integrated white-matter AD pathology prior to the onset of symptoms. The tract connectivity showing temporal synchrony presence of phosphorylated Tau at Serine 181 and during resting state fMRI scans (Mevel, ChĂŠtelat, AĂ&#x;42 help discriminate AD from other types of Eustache, & Desgranges, 2011). dementia (Hampel et al., 2010) and indicate the 22

abnormal deposition of proteins in the brain which patients is a compensatory increase in insulin impair neuronal signalling. secretion (hyperinsulinemia) in response to the reduced action of insulin in peripheral tissues CONCLUSION & DISCUSSION (Goldstein, 2002). In vitro studies have shown that high insulin levels can impede the clearance of Aß In previous work, Craft and colleagues had reported from the extracellular space by directly affecting that treatment with regular insulin improved the enzymes and mechanisms required for this memory in adults with MCI and AD (Craft et al., process to occur (Stanley et al., 2016). Both insulin 2012). The current study aimed to extend these and Aß are degraded by the same insulin degrading findings by examining the possible enhanced enzyme (IDE) which shows higher affinity for insulin. effects of long-lasting detemir therapy utilizing In the presence of high insulin levels this enzyme structural MRI and CSF AD-related biomarkers. will preferentially bind and degrade insulin (Qiu et Present results suggest that regular insulin is more al., 1998), leaving behind Aß proteins to aggregate successful than long-lasting detemir to alleviate overtime. symptoms of MCI and AD in terms of memory tests and objective measures of structural integrity and Furthermore, high insulin levels caused by AD biomarkers. Researchers initially believed that hyperinsulinemia have been known to induce Aß the lipophilicity of detemir would allow it to bypass fibril formation by activating GM1 ganglioside the BBB more efficiently and its reversible albumin clustering (Yamamoto et al., 2012). Participants binding abilities would delay its absorption over in the Craft study (Craft et al., 2017) assigned to longer periods of time (Craft et al., 2017). Contrary the detemir treatment show a potential indication to their beliefs, results suggest that the efficacy of of the detrimental effects of prolonged insulin long-lasting detemir actually decreased over long- exposure as seen from their slightly decreased term administration. cerebral volumes in ROIs (Fig. 2), although researchers claim there is no statistical increase in Regular insulin treatment was associated with their Tau181/Aß42 levels. preserved or increased volumes in several ROIs associated with AD pathology, such as hippocampal FUTURE DIRECTIONS regions. There is also a reported improvement in the CSF biomarker profile, raising the possibility Although insulin therapy may appear as a promising that insulin not only alleviates symptoms but also treatment for AD, researchers should refrain from targets and modifies the pathological processes using these methods due to their potentially underlying AD progression. adverse effects. It is important to note that while T2D is associated with increased risk for developing CRITICAL ANALYSIS AD, individuals with comorbid T2D and AD exhibit delayed progression of cognitive decline than In the Craft et al study (2017), insulin delivery patients with AD alone (Morris & Burns, 2012), was believed to prevent Aß accumulation by possibly due to the use of certain anti-diabetic promoting its clearance from the extracellular medications. Craft and colleagues chose to exclude space (Gasparini et al., 2001; Mullins, Diehl, Chia, diabetic individuals from their study; however, & Kapogiannis, 2017) thus reducing its cytotoxic further studies should consider their inclusion as effects and alleviating the symptoms of AD. In an they could potentially show increased benefits due attempt to understand why the long-lasting detemir to possible synergistic effects of treatment drugs. treatment failed to show the expected results, Researchers should thus aim to seek treatments that researchers briefly identify but do not elaborate can target metabolic deficits present in both AD upon a possible effect of hyperinsulinemia (Craft and T2D without inducing further AD pathology. In et al., 2017) in their study. fact, some studies have begun to study the effects of T2D medications such as Rosiglitazone to treat Insulin is required for proper metabolic and brain AD pathology. functioning; however, a consequence of insulin resistance seen in older individuals as well as T2D Rosiglitazone is a high-affinity peroxisome 23

proliferator-activated receptor (PPAR) selective could allow studies to administer Rosiglitazone agonist for the γ receptor component. PPARγ under careful supervision for pro-inflammatory acts a ligand-activated transcription factor that microglia in patients with early disease progression. decreases peripheral insulin sensitivity (Deeks & Keam, 2007) in T2D patients. Rosiglitazone has been seen to promote Aß clearance as well as the reduction of inflammation seen in AD brains by inducing PPARγ activity (Escribano et al., 2010). It also has the ability activate microglia exhibiting a neuroprotective phenotype, which promote amyloid phagocytosis by expressing IDE and other Aß clearance enzymes (Escribano et al., 2010). Results from these experiments could be very promising in the development of therapeutic agents by reducing the insulin resistance and cognitive decline present in both AD and T2D. Patients undergoing treatment would be expected to show diminished levels of Aß in CSF samples, as well possible preserved cerebral volumes due to the decrease of cytotoxic Aß levels. Furthermore, patients would also be expected to show improved or preserved memory abilities when tested using the MMSE. However, there exists a limit to the effectiveness of this treatment as prolonged exposure to microglia activating drugs could cause researchers to see a decrease in their neuroprotective mechanisms and a shift to their pro-inflammatory phenotype (Streit, 2005). Studies should ensure proper screening of individuals to carefully analyze the stage of AD the patient is currently in to avoid harmful activation of inflammatory responses within microglia for patients in late stages of disease progression. Treatment should be avoided for patients within late stages of the disease as they already possess large amounts of activated microglia secreting proinflammatory cytokines (Mandrekar & Landreth, 2010). Patients undergoing such treatments should undergo careful monitoring for the presence of inflammatory markers in CSF samples should microglia revert to a neurotoxic phenotype. 11CPK11195 markers have been identified as a possible candidate for the screening of activated microglia for in vivo studies (Passamonti et al., 2018). PET studies have shown increased levels of the marker in ROIs associated with AD such as the hippocampus and temporo-parietal cortices (Passamonti et al., 2018). Utilizing these techniques 24

REFERENCES 1. Attwell, D., Buchan, A. M., Charpak, S., Lauritzen, M., MacVicar, B. A., & Newman, E. A. (2010). Glial and neuronal control of brain blood flow. Nature, 468(7321), 232. https://doi.org/10.1038/ nature09613 2. Claxton, A., Baker, L. D., Hanson, A., Trittschuh, E. H., Cholerton, B., Morgan, A., … Craft, S. (2015). Long-acting intranasal insulin detemir improves cognition for adults with mild cognitive impairment or early-stage Alzheimer’s disease dementia. Journal of Alzheimer’s Disease: JAD, 44(3), 897–906. https://doi.org/10.3233/JAD-141791 3. Craft, S., Baker, L. D., Montine, T. J., Minoshima, S., Watson, G. S., Claxton, A., … Gerton, B. (2012). Intranasal insulin therapy for Alzheimer disease and amnestic mild cognitive impairment: a pilot clinical trial. Archives of Neurology, 69(1), 29–38. https://doi.org/10.1001/archneurol.2011.233 4. Craft, S., Claxton, A., Baker, L. D., Hanson, A. J., Cholerton, B., Trittschuh, E. H., … Friedman, S. (2017). Effects of Regular and Long-Acting Insulin on Cognition and Alzheimer’s Disease Biomarkers: A Pilot Clinical Trial. Journal of Alzheimer’s Disease, 57(4), 1325–1334. https://doi. org/10.3233/JAD-161256 5. Deeks, E. D., & Keam, S. J. (2007). Rosiglitazone : a review of its use in type 2 diabetes mellitus. Drugs, 67(18), 2747–2779. https://doi.org/10.2165/00003495-200767180-00008 6. Escribano, L., Simón, A.-M., Gimeno, E., Cuadrado-Tejedor, M., López de Maturana, R., García-Osta, A., … Frechilla, D. (2010). Rosiglitazone Rescues Memory Impairment in Alzheimer’s Transgenic Mice: Mechanisms Involving a Reduced Amyloid and Tau Pathology. Neuropsychopharmacology, 35(7), 1593–1604. https://doi.org/10.1038/npp.2010.32 7. Fernandez, A. M., & Torres-Alemán, I. (2012). The many faces of insulin-like peptide signalling in the brain. Nature Reviews Neuroscience, 13(4), 225–239. https://doi.org/10.1038/nrn3209 8. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198. https://doi.org/10.1016/0022-3956(75)90026-6 9. Gasparini, L., Gouras, G. K., Wang, R., Gross, R. S., Beal, M. F., Greengard, P., & Xu, H. (2001). Stimulation of β-Amyloid Precursor Protein Trafficking by Insulin Reduces Intraneuronal β-Amyloid and Requires Mitogen-Activated Protein Kinase Signaling. The Journal of Neuroscience, 21(8), 2561–2570. https://doi.org/10.1523/JNEUROSCI.21-08-02561.2001 10. Goldstein, B. J. (2002). Insulin resistance as the core defect in type 2 diabetes mellitus. The American Journal of Cardiology, 90(5A), 3G-10G. 11. Hampel, H., Blennow, K., Shaw, L. M., Hoessler, Y. C., Zetterberg, H., & Trojanowski, J. Q. (2010). Total and phosphorylated tau protein as biological markers of Alzheimer’s disease. Experimental Gerontology, 45(1), 30–40. https://doi.org/10.1016/j.exger.2009.10.010 12. Harari, O., Cruchaga, C., Kauwe, J. S. K., Ainscough, B. J., Bales, K., Pickering, E. H., … Goate, A. M. (2014). Phosphorylated Tau-Aβ42 Ratio as a Continuous Trait for Biomarker Discovery for Early-Stage Alzheimer’s Disease in Multiplex Immunoassay Panels of Cerebrospinal Fluid. Biological Psychiatry, 75(9), 723–731. https://doi.org/10.1016/j.biopsych.2013.11.032 13. Lee, C.-C., Kuo, Y.-M., Huang, C.-C., & Hsu, K.-S. (2009). Insulin rescues amyloid β-induced impairment of hippocampal long-term potentiation. Neurobiology of Aging, 30(3), 377–387. https://doi.org/10.1016/j.neurobiolaging.2007.06.014 14. Liu, C.-C., Hu, J., Tsai, C.-W., Yue, M., Melrose, H. L., Kanekiyo, T., & Bu, G. (2015). Neuronal LRP1 Regulates Glucose Metabolism and Insulin Signaling in the Brain. Journal of Neuroscience, 35(14), 5851–5859. https://doi.org/10.1523/JNEUROSCI.5180-14.2015 15. Mandrekar, S., & Landreth, G. E. (2010). Microglia and Inflammation in Alzheimer’s Disease. CNS & Neurological Disorders Drug Targets, 9(2), 156–167. 16. Masters, C. L., Multhaup, G., Simms, G., Pottgiesser, J., Martins, R. N., & Beyreuther, K. (1985). Neuronal origin of a cerebral amyloid: neurofibrillary tangles of Alzheimer’s disease contain the same protein as the amyloid of plaque cores and blood vessels. The EMBO Journal, 4(11), 2757–2763. 17. Mergenthaler, P., Lindauer, U., Dienel, G. A., & Meisel, A. (2013). Sugar for the brain: the role

of glucose in physiological and pathological brain function. Trends in Neurosciences, 36(10), 587–597. https://doi.org/10.1016/j.tins.2013.07.001 18. Mevel, K., Chételat, G., Eustache, F., & Desgranges, B. (2011). The Default Mode Network in Healthy Aging and Alzheimer’s Disease [Research article]. https://doi.org/10.4061/2011/535816 19. Morris, J. K., & Burns, J. M. (2012). Insulin: An Emerging Treatment for Alzheimer’s Disease Dementia? Current Neurology and Neuroscience Reports, 12(5), 520–527. https://doi. org/10.1007/s11910-012-0297-0 20. Mullins, R. J., Diehl, T. C., Chia, C. W., & Kapogiannis, D. (2017). Insulin Resistance as a Link between Amyloid-Beta and Tau Pathologies in Alzheimer’s Disease. Frontiers in Aging Neuroscience, 9. https://doi.org/10.3389/fnagi.2017.00118 21. Ott, A., Stolk, R. P., Van Harskamp, F., Pols, H. A. P., Hofman, A., & Breteler, M. M. B. (1999). Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology, 53(9), 1937–1942. 22. Passamonti, L., Rodríguez, P. V., Hong, Y. T., Allinson, K. S. J., Bevan-Jones, W. R., Williamson, D., … Rowe, J. B. (2018). [11C]PK11195 binding in Alzheimer disease and progressive supranuclear palsy. Neurology, 90(22), e1989–e1996. https://doi.org/10.1212/WNL.0000000000005610 23. Peters, R. (2006). Ageing and the brain. Postgraduate Medical Journal, 82(964), 84–88. https:// doi.org/10.1136/pgmj.2005.036665 24. Qiu, W. Q., Walsh, D. M., Ye, Z., Vekrellis, K., Zhang, J., Podlisny, M. B., … Selkoe, D. J. (1998). Insulin-degrading Enzyme Regulates Extracellular Levels of Amyloid β-Protein by Degradation. Journal of Biological Chemistry, 273(49), 32730–32738. https://doi.org/10.1074/jbc.273.49.32730 25. Reger, M. A., Watson, G. S., Green, P. S., Wilkinson, C. W., Baker, L. D., Cholerton, B., … Breitner, J. C. S. (2008). Intranasal insulin improves cognition and modulates β-amyloid in early AD, 9. 26. Stanley, M., Macauley, S. L., & Holtzman, D. M. (2016). Changes in insulin and insulin signaling in Alzheimer’s disease: cause or consequence? Journal of Experimental Medicine, 213(8), 1375– 1385. https://doi.org/10.1084/jem.20160493 27. Streit, W. J. (2005). Microglia and neuroprotection: implications for Alzheimer’s disease. Brain Research Reviews, 48(2), 234–239. https://doi.org/10.1016/j.brainresrev.2004.12.013 28. Tarumi, T., & Zhang, R. (2018). Cerebral blood flow in normal aging adults: cardiovascular determinants, clinical implications, and aerobic fitness. Journal of Neurochemistry, 144(5), 595– 608. https://doi.org/10.1111/jnc.14234 29. Umegaki, H. (2013). Insulin resistance in the brain: A new therapeutic target for Alzheimer’s disease. Journal of Diabetes Investigation, 4(2), 150–151. https://doi.org/10.1111/jdi.12027 30. Villain, N., Desgranges, B., Viader, F., Sayette, V. de la, Mézenge, F., Landeau, B., … Chételat, G. (2008). Relationships between Hippocampal Atrophy, White Matter Disruption, and Gray Matter Hypometabolism in Alzheimer’s Disease. Journal of Neuroscience, 28(24), 6174–6181. https://doi.org/10.1523/JNEUROSCI.1392-08.2008 31. Wang, W.-Y., Yu, J.-T., Liu, Y., Yin, R.-H., Wang, H.-F., Wang, J., … Tan, L. (2015). Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease. Translational Neurodegeneration, 4(1). https://doi.org/10.1186/s40035-015-0027-z 32. Yamamoto, N., Matsubara, T., Sobue, K., Tanida, M., Kasahara, R., Naruse, K., … Suzuki, K. (2012). Brain insulin resistance accelerates Aβ fibrillogenesis by inducing GM1 ganglioside clustering in the presynaptic membranes. Journal of Neurochemistry, 121(4), 619–628. https:// doi.org/10.1111/j.1471-4159.2012.07668.x

A new modulator for aggression-seeking behavior in mice. What is all the ΔFosB about? Gabriel Blanco Gomez Aggression is an evolutionary advantageous behavior that has been conserved in various species as an adaptive trait. Recent studies have shown that aggression displays many similarities to other reward mechanisms such as mating, feeding and drug consumption. More recently, studies have shown that the reinforcement of aggressive behaviors can be highly addictive in mice models as it leads to changes in the Nucleus Accumbens (NAc), the reward center of the brain. Nevertheless, despite these advancements, the molecular mechanisms that modulate aggression-seeking behaviors are widely understudied. A recent study by Alayesin et al (2018) proposed that expression of ΔFosB, a transcriptional regulator, can play an important role in modulating aggression in male mice models. ΔFosB accumulation in the NAc has been previously linked to increases in reward drive, drug consumption, resilience and antidepressant responses. In this study, it was found that overexpression of ΔFosB in the NAc intensified aggressive behavior in male mice. Understanding this novel link between ΔFosB expression and aggressive behavior in individuals can prove to be crucial for elucidating the underlying mechanisms of aggression. This review seeks to shed light onto some of the proposed molecular mechanisms behind aggression while also discussing the obstacles faced by current aggression models. Aggression has been identified under the

Aggression and the brain

Starting in the early 1950s, numerous studies have sought to understand the neural mechanisms that cause aggressive behaviors and motivation in individuals [7]. Studies on intermale-aggression in mammals have identified many brain regions that are associated with regulating aggression including the hypothalamus [4], Medial preoptic area (MPOA) [6], brain stem [11], amygdala [4] and the Prefrontal cortex [9]. Despite these association studies, evidence for the activation of these areas Figure 1. Visual abstract to represent the experiment is not extensive and the underlying molecular carried out by Alayesin et al with regards to the mechanisms are not well understood [8]. role of ΔFosB in modulating Intermale aggression. In this experiment, the authors found that ΔFosB In recent years, there has been increasing number expression was correlated with aggressive behavior of studies that have linked aggression-seeking in mice. In addition, they further studied this relation behaviors to the reward systems in the brain. In by virally inducing ΔFosB ovexpression. They found mice models, scientists have linked aggression to that increases in ΔFosB expression resulted in stimulation of dopaminergic neurons in the Ventral increased aggressive behavior while suppression Tegmental Area (VTA) and neural activity within the decreased aggression. This study is the first to show NAc [6], [9]–[11]. These brain areas have been wellstudied and characterized as important mediators an important link between ΔFosB and aggression. of reward and motivation in various drug models. Studies done on cocaine and nicotine consumption INTRODUCTION have also found that addiction develops through Aggressive behavior in animals and humans has the mesolimbic pathway where input from the been documented for centuries [2]–[4]. This VTA to the NAc is critical for reward modulation. social behavior has been deemed evolutionary [2], [10], [11]. As a result, there appears to be a advantageous as it aids in survival and link between aggression and the neuronal circuity reproductive success. Nevertheless, excessive responsible for reward. and insensitive voluntary aggression can have negative consequences for individuals and society [2]. Although multiple brain areas and neural mechanisms have been proposed for aggression, this area of research remains understudied. To date, most of the literature has focused on innate attacking behaviors and natural territorial aggression [5], [6]. However, there has been a recent shift in focus to explore the role of aggression in reward systems, notably its expression in the NAc. This review will seek to shed light onto some of the current pathways associated with aggressive behavior, while also exploring its interaction with the brain’s reward system. Moreover, this review will explore the current literature regarding the role of ΔFosB as a modulator for reward-seeking behaviors in the brain and assess the validity of the findings posed by Alayesin et al. [1]

ΔFosB as a novel mechanism for aggression reward Although aggression is a complex behavior that integrates connections from multiple brain regions, Alayesin et al recently found that aggression is mainly controlled by the NAc via the expression of ΔFosB. Previous studies on reward systems and addiction have shown that reward is associated with changes in cell structure and the transcription factors that regulate gene expression [2], [4]. One of these transcription factors is ΔFosB. In drug intoxication models, ΔFosB has been shown to interact with the Jun family proteins to form the AP-1 complex, which in turn regulates gene expression and can lead to structural alterations in neurons [2]. A conglomerate of studies have shown that accumulation of ΔFosB

in the NAc is observed following chronic drug exposure [2], [11]–[13]. In these studies, ΔFosB expression promoted self-administration and enhanced reinforcement in addicted mice. [3], [6]. Similarly, high expression of ΔFosB has also been linked to resilience, enhanced sexual behavior and anti-depressant responses [7], [8], [12]. Thus, the role ΔFosB as a modulator of reward and addiction is consistent across the literature. Given the molecular pathways regulated by ΔFosB expression, the findings from Alayesin et al’s experiment are significant as they are the first to propose a direct link between aggression and ΔFosB expression in the NAc. Moreover, these findings also display the fundamental similarities that exist between aggression-seeking behavior and the pathways related to drug abuse and addiction.

Figure 2. Western Blot analysis of extracted mRNA from NAc tissue. Based on protein band comparisons, it is shown that ΔFosB mRNA levels are significantly higher in AGG individuals in comparison to NON individuals. Protein bands densities were also normalized to β-actin. ΔFosB overexpression in the NAc increases aggressive behavior in AGG mice

Following Alayesin et al’s initial findings that ΔFosB expression correlated to aggression levels, the MAJOR RESULTS authors of this paper decided to virally induce Aggressive mice (AGG) show an increase in global ΔFosB overexpression in AGG mice using the AAV-ΔFosB vector. They then quantified ΔFosB expression aggressive behavior using a resident-intruder test Using Western Blot analysis, Alayesin and his team to see changes in the intensity of aggression. were able to show that aggressive mice (AGG) displayed higher expression of ΔFosB mRNA in Consistent with the previous findings, they found the NAc (Fig. 2). On the other hand, the authors that ΔFosB overexpression resulted in increased found that non-aggressive (NON) mice had aggression in male mice, compared to pre-viral relatively lower levels of ΔFosB mRNA expression njection levels (Fig.3). in the NAc (Fig.2). It should be noted that these two groups (AGG vs NON) where characterized using a resident-intruder test (RI). In this test, an individual (intruder) was placed on the cage of another mouse (resident) to instigate a territorial fight. Experimenters then recorded attack latency, number of attack bouts and attack duration to assess aggression levels (Figure 1). [1], [10]. These findings are significant as they showed, presumably for the first time that there are differences in the ΔFosB expression of aggressive and non-aggressive mice. In addition, qPCR analysis also showed that mice who were more likely to attack first (more aggressive) showed even higher levels of ΔFosB mRNA expression. Thus, suggesting that there is a positive correlation between ΔFosB expression in the NAc and aggressive behavior.

Figure 3. ΔFosB overexpression in AGG results in increased aggression. AGG mice after virallyinduced ΔFosB overexpression (red) showed decreased attack latency, increased number of bouts and increased attack duration compared to AGG mice before viral injection (white). The positive correlation between ΔFosB expression in the NAc and aggression shares many similarities to previous studies on natural reward systems. ΔFosB expression and accumulation in the NAc has

been found to promote rewarding behaviors such as wheel-running, high-fat food intake and drug use [5], [10], [14], [15]. A similar study on natural reward had also found that virally-induced ΔFosB overexpression in sexually experienced male mice was correlated with enhanced sexual behavior and increased sucrose self-administration [11]. This further reiterates the idea that ΔFosB is important for reward in the brain and in the context of aggression, it acts as a modulator for reward. Can aggressive-seeking behavior be addictive?

spent on the paired-context suggesting that ΔFosB overexpression can negatively regulate aggression-seeking behaviors in a CPP model (Fig.5). These findings are not consistent with the existing literature regarding ΔFosB expression. Previous studies on cocaine and sexual motivation in mice have shown that ΔFosB induction in the NAc results in an increase in CPP for a paired stimulus [20], [18] In other words, ΔFosB expression increases the amount of time that an individual spends in a chamber that has been paired to a pleasant context.llllllllllllllllllllllllllllllllllllllllllllllllllllllllllll

Aggression-seeking behavior has been found to share fundamental characteristics with addiction and substance abuse [2], [10], [13]. Mice and humans have been documented to display “Appetite Aggression”, in other words, they find pleasure in bullying other “weaker” individuals. [14] In addition, highly aggressive mice also show some of the core markers of addiction: high motivation to seek reward despite consequences, reward sensitization and high relapse rates [2], [4], [12]. These characteristics suggest that there might be a link between aggression and addiction. In order to test this link, the authors used a Conditioned Place Preference Test (CPP). In this test, they wanted to see how much time AGG and NON mice spent in an intruder paired chamber and an intruder unpaired chamber after conditioning. They found that AGG mice spent more time in the chamber where they were previously given an intruder to fight compared to a neutral chamber. On the other hand, they found that NON mice spent more time in the intruder unpaired context (Fig 4). This is consistent with previous data on aggression-seeking behavior. In a study by Martinez et al it was found that in an operant conditioning model, successful intermale aggression acted as a reinforcer in mice. Aggression-seeking mice learned to lever press in exchange for the opportunity to attack a more docile mouse [16], suggesting a clear preference for aggressive environments. ΔFosB overexpression in the NAc attenuates Conditioned Place Preference for intruder context Surprisingly, it was found that inducing ΔFosB overexpression in AGG mice lead to less time

Figure 4 (first) Non-aggressive mice have a preference for the intruder unpaired context (lower CPP score) while Aggressive mice AGG have a preference for the intruder paired control (higher CPP score). Figure 5 (second). This figure displays the heat map of AGG mice prior to viral infection (top) and following viral-infection (bottom). The heat map shows that pre-infection mice displayed a preference for the intruder-paired context while ΔFosB overexpression mice did not show any statistically significant preference for either context.

CONCLUSION

Research on mice models has shown that aggressionseeking behaviors display similar characteristics to drug use and motivated reward. Nevertheless, the underlying molecular mechanisms that motivate aggression are not clear. Alayesin et al presented a novel finding shedding light onto some of the molecular components that help control and modulate aggression. By analyzing tissue from the NAc of aggressive mice, Alayesin et al found that there was a positive correlation between the intensity of aggression (# of attacks, attack latency, attack duration) and the levels of ΔFosB expression in the NAc. Moreover, they found that increasing and suppressing ΔFosB expression in the NAc could either promote or attenuate aggressive behavior. However, using a CPP test, Alayesin et al were unable to find a link between ΔFosB expression and reward-seeking behaviors. Paradoxically, they found that ΔFosB overexpression had the opposite effect as it attenuated preference for an intruderpaired context, suggesting that ΔFosB may have cell-specific functions. One of the fundamental goals of neuroscience is to understand the biological processes that generate behavioral responses. These findings are significant because they reveal a novel link between a transcription factor (biological) and an aggressive response (behavioral). ΔFosB expression has been strongly linked to the regulation of both natural (sex, food, etc) and artificial (cocaine, nicotine, etc.) rewards, and thus it is not surprising that it is also a modulator for aggression. [7]–[9]. Although this study was successful in identifying a possible regulator, there is still little knowledge about the downstream effectors of ΔFosB. Previous studies suggest that ΔFosB acts as a regulator of GluA2, one of the tetramer subunits of AMPA receptors [3], [10], [11]. This is particularly important because recent studies have found that AMPA receptor antagonists can inhibit aggression in mice [12]. Thus, ΔFosB could modulate aggression by upregulating GluA2 synthesis, which appears to be necessary for aggressive behavior. However, these interactions are not fully understood and future studies should aim to find targets downstream of ΔFosB.

can help identity new targets for future research on aggression and set the foundations for new studies. This knowledge can not only elucidate on how aggression is controlled and modulated in normal individuals, but it can also help uncover the basis for neuropsychiatric disorders where many of these control systems seem to be disrupted. There are currently very little therapeutic options to combat aggression in affected individuals. However, these findings can open an avenue for the development of new treatments that can reduce aggression and violence, a prominent issue in today’s society [8]. CRITICAL ANALYSIS Alayesin et al presented a novel mechanism for aggression in their study. They found that ΔFosB expression in the NAc was positively correlated to the intensity of aggression in male mice. These findings are consistent with other studies regarding the role of ΔFosB on reward. Similar to aggression, ΔFosB accumulation in the NAc has been found to promote other rewarding behaviors such as sucrose-intake, cocaine, alcohol and sex [21], [10], [25], [15]. However, one phenomenon that was not fully investigated in this study was the role of ΔFosB on the different cell types within the NAc. 95% of all neurons in this brain region are medium spiny neurons (MSNs), of which some are D1 Dopamine receptor dominant (D1-MSNs) or D2 receptor dominant (D2-MSNs) [29] Research on reward systems has found that ΔFosB expression reacts differently in these subpopulations. Given that viral-mediated induction was done globally, it would be interesting to further explore the role of ΔFosB in these subpopulations.

The authors of this study also found a contradicting effect of ΔFosB in the reward-seeking behavior of mice. Paradoxically, ΔFosB expression attenuated the preference for an intruder-paired context in the CPP test. Contrary to Alayesin et al, studies on cocaine and sexual motivation have shown that ΔFosB induction In the NAc increases CPP for a paired environment, reiterating reinforcement behaviors [15], [28]. This discrepancy could be due to various reasons. One possible confounding factor might be the method used to assess reward-seeking. Earlier studies on aggression found that conditioning using resident victory as a Understanding the molecular basis for aggression reinforcement is very “fragile” and easily affected by 31

changes to environmental cues [8], [14]. Researchers found that in the context of aggression, a CPP test is not a reliable measure. They found that mice preferences changed drastically based on the color of the room (as opposed to the aggressionpaired chamber) [14]. More accurate experiments to study aggression-seeking behaviors should be carried out by the authors. These include selfadministration, extinction and relapse [2], [15].

Finally, studies using ΔFosB knockout mice have found that ΔFosB has a pleiotropic effect on behavior [16]. This poses a problem for the replication of many experiments. Some factors that can affect the expression of ΔFosB are gender and species-type [26] In this study, the authors looked only at intermale aggression of CD-1 mice, a strain known to be very aggressive [8]. Given these variables, the authors should try to replicate their findings by exploring the interplay between aggression and ΔFosB in female mice and other more docile species. This will not only provide more understating regarding the mechanisms affecting ΔFosB, but it will also help validate the universality of these findings. Interestingly, aggression-seeking behavior has been well documented in female hamsters [27]. FUTURE DIRECTIONS Alayesin et al globally expressed ΔFosB in the NAc to see its effects on aggression, however, they did not look at cell-type specific differences within the NAc. As previously mentioned, the NAc is composed of two subpopulations, D1-MSNs and D2-MSNs [29].

ΔFosB induction in each group. This should allow the visualization of ΔFosB in only D1-MSNs neurons or D2-MSNs neurons and thus provide a more accurate accounts of ΔFosB’s role in aggression.

Research on medium spiny neurons within the NAc has shown that chronic exposure to cocaine results in an increase in ΔFosB expression in D1MSNs [5]. On the other hand, studies on natural rewards have shown that ΔFosB overexpression in D2-MSNs leads to an inhibition of sexual drive and sucrose self-administration [6]. Given the strong connection that exists between aggression and reward mechanisms [3], [10], [13], [18] one should expect to see that ΔFosB overexpression in D1-MSNs-Cre mice would lead to increases in aggression, while ΔFosB overexpression in D2MSNs-Cre mice should lead to less aggression. Moreover, these Cre transgenic mice lines should also undergo the CPP test. In Alayesin et al’s initial experiment, there were major discrepancies between their findings and the current literature on aggression. They found that ΔFosB overexpression decreased preference for the aggression-paired context. Using these cre-lines, the authors can explore if these contradictory findings were due to differences in cell-type expression of ΔFosB. As discussed, ΔFosB can also have inhibitory effects on reward mechanism when expressed in D2-MSNs.

To further corroborate these results, other tests that measure reward-seeking behavior can also be used, For instance, using a nose-poke self-administration paradigm in which mice can get access to docile weaker intruders, one can measure relapse rates. Once again, given that aggression shares many Previous studies on ΔFosB expression have found similarities to reward and addiction, it is expected that many of its effects are dependent on cell- that mice induced with ΔFosB expression should specific properties [18]. Global induction of ΔFosB display higher relapse rates. in the NAc can create very complex phenotypes that might make it harder to study the specific Finally, it should be noted that ΔFosB is a mechanisms that ΔFosB exerts on aggression. To transcription factor that regulates the expression assess this problem, future studies could use Cre of many genes both inside and outside the NAc. transgenic cell lines. In these experiments, two ΔFosB expression is not localized to only one area different lines, a D1-MSN-Cre and D2-MSN-Cre of the brain but it is rather expressed in various lines could be crossed to CD-1 females to generate regions [18]. As a result, it can interact with multiple progeny with the Cre-recombinase transgene. pathways in the brain. If these future suggested Subsequently, these two groups (D1 and D2) studies continue to display contradictory results, it should be injected using a viral vector with Cre- might be an indication that ΔFosB is interacting with depedent ΔFosB expression to see the effects of other related pathways. Studies on depression and 32

stress have shown that Î&#x201D;FosB can lead to resilience and anti-depression effects in certain environments but in others it can exacerbate depression-like symptoms [3], [16], [19]. Ultimately, behavior results from the complex interaction between genes and the environment, an interaction that future studies should explore.

REFERENCES 1. H. Aleyasin et al., “Cell-Type-Specific Role of ΔFosB in Nucleus Accumbens In Modulating Intermale Aggression,” J. Neurosci., vol. 38, no. 26, pp. 5913–5924, Jun. 2018. 2. H. Aleyasin, M. E. Flanigan, and S. J. Russo, “Neurocircuitry of aggression and aggression seeking behavior: nose poking into brain circuitry controlling aggression,” Current Opinion in Neurobiology, vol. 49, pp. 184–191, Apr. 2018. 3. C.-H. Chang, Y.-H. Hsiao, Y.-W. Chen, Y.-J. Yu, and P.-W. Gean, “Social isolation-induced increase in NMDA receptors in the hippocampus exacerbates emotional dysregulation in mice,” Hippocampus, vol. 25, no. 4, pp. 474–485, Apr. 2015. 4. R. El Rawas et al., “Preventive role of social interaction for cocaine conditioned place preference: correlation with FosB/DeltaFosB and pCREB expression in rat mesocorticolimbic areas,” Front Behav Neurosci, vol. 6, Mar. 2012. 5. S. A. Golden et al., “Persistent conditioned place preference to aggression experience in adult male sexually-experienced CD-1 mice,” Genes Brain Behav, vol. 16, no. 1, pp. 44–55, Jan. 2017. 6. B. A. Grueter, A. J. Robison, R. L. Neve, E. J. Nestler, and R. C. Malenka, “∆FosB differentially modulates nucleus accumbens direct and indirect pathway function,” PNAS, vol. 110, no. 5, pp. 1923–1928, Jan. 2013. 7. T. Kikusui, “Analysis of Male Aggressive and Sexual Behavior in Mice,” in Pheromone Signaling: Methods and Protocols, K. Touhara, Ed. Totowa, NJ: Humana Press, 2013, pp. 307–318. 8. M. Martínez, F. Guillén-Salazar, A. Salvador, and V. M. Simón, “Successful intermale aggression and conditioned place preference in mice,” Physiology & Behavior, vol. 58, no. 2, pp. 323–328, Aug. 1995. 9. M. E. May and C. H. Kennedy, “AGGRESSION AS POSITIVE REINFORCEMENT IN MICE UNDER VARIOUS RATIO- AND TIME-BASED REINFORCEMENT SCHEDULES,” J Exp Anal Behav, vol. 91, no. 2, pp. 185–196, Mar. 2009. 10. J. A. McHenry et al., “The role of ΔfosB in the medial preoptic area: Differential effects of mating and cocaine history,” Behavioral Neuroscience, vol. 130, no. 5, pp. 469–478, 2016. 11. E. J. Nestler, “ΔFosB: a transcriptional regulator of stress and antidepressant responses,” Eur J Pharmacol, vol. 753, pp. 66–72, Apr. 2015. 12. V. Niederkofler et al., “Identification of Serotonergic Neuronal Modules that Affect Aggressive Behavior,” Cell Reports, vol. 17, no. 8, pp. 1934–1949, 2016. 13. O. V. Perepelkina, A. Y. Tarassova, N. M. Surina, I. G. Lilp, V. A. Golibrodo, and I. I. Poletaeva, “Intermale aggression in mice, selected for the cognitive trait,” Dokl Biol Sci, vol. 475, no. 1, pp. 151–153, Jul. 2017. 14. J. K. Ruffle, “Molecular neurobiology of addiction: what’s all the (Δ)FosB about?,” The American Journal of Drug and Alcohol Abuse, vol. 40, no. 6, pp. 428–437, Nov. 2014. 15. A. Takahashi, “Control of intermale aggression by medial prefrontal cortex activation in the mouse,” PloS one, vol. 9, no. 4, p. e94657, 2014. 16. D. L. Wallace et al., “THE INFLUENCE OF ΔFOSB IN THE NUCLEUS ACCUMBENS ON NATURAL REWARD-RELATED BEHAVIOR,” J Neurosci, vol. 28, no. 41, pp. 10272–10277, Oct. 2008. 17. J. Wang, S. Fanous, E. F. Terwilliger, C. E. Bass, R. P. Hammer Jr, and E. M. Nikulina, “BDNF Overexpression in the Ventral Tegmental Area Prolongs Social Defeat Stress-induced CrossSensitization to Amphetamine and Increases ΔFosB Expression in Mesocorticolimbic Regions of Rats,” Neuropsychopharmacology, vol. 38, no. 11, pp. 2286–2296, Oct. 2013. 18. K. ZAHO, “Pleiotropic impact of constitutive fosB inactivation on nicotine-induced behavioral alterations and stress-related traits in mice. - PubMed - NCBI.” [Online]. Available: https://wwwncbi-nlm-nih-gov.myaccess.library.utoronto.ca/pubmed/17468183. [Accessed: 10-Dec-2018]. 19. “Pleiotropic impact of constitutive fosB inactivation on nicotine-induced behavioral alterations and stress-related traits in mice. - PubMed - NCBI.” . 20. M. Zelikowsky et al., “The Neuropeptide Tac2 Controls a Distributed Brain State Induced by

Chronic Social Isolation Stress,” Cell, vol. 173, no. 5, pp. 1265-1279.e19, May 2018. 21. A. L. Falkner, L. Grosenick, T. J. Davidson, K. Deisseroth, and D. Lin, “Hypothalamic control of male aggression-seeking behavior,” Nature Neuroscience, vol. 19, no. 4, pp. 596–604, Apr. 2016. 22. P. Antion Rogert, “Compulsive Addiction-like Aggressive Behavior in Mice,” Biological Psychiatry, vol. 82, no. 4, pp. 239–248, Aug. 2017. 23. C.-H. Chang, C.-L. Su, and P.-W. Gean, “Mechanism underlying NMDA blockade-induced inhibition of aggression in post-weaning socially isolated mice,” Neuropharmacology, vol. 143, pp. 95–105, Dec. 2018. 24. M. H. Couppis and C. H. Kennedy, “The rewarding effect of aggression is reduced by nucleus accumbens dopamine receptor antagonism in mice,” Psychopharmacology (Berl.), vol. 197, no. 3, pp. 449–456, Apr. 2008. 25. E. W. Fish, J. F. DeBold, and K. A. Miczek, “Escalated aggression as a reward: corticosterone and GABA<Subscript>A</Subscript> receptor positive modulators in mice,” Psychopharmacology, vol. 182, no. 1, pp. 116–127, Oct. 2005. 26. O. R. Floody and D. W. Pfaff, “Aggressive behavior in female hamsters: the hormonal basis for fluctuations in female aggressiveness correlated with estrous state,” J Comp Physiol Psychol, vol. 91, no. 3, pp. 443–464, Jun. 1977. 27. K. P. Lesch and U. Merschdorf, “Impulsivity, aggression, and serotonin: a molecular psychobiological perspective,” Behav Sci Law, vol. 18, no. 5, pp. 581–604, 2000. 28. R. J. Nelson and B. C. Trainor, “Neural mechanisms of aggression,” Nat. Rev. Neurosci., vol. 8, no. 7, pp. 536–546, Jul. 2007. 29. M. Rodríguez-Arias et al., “Role of CB2 receptors in social and aggressive behavior in male mice,” Psychopharmacology (Berl.), vol. 232, no. 16, pp. 3019–3031, Aug. 2015.

The Importance of Glucocorticoid Receptor Activation in the Role of Major Depressive Disorder: A Literature Review on the Hypothalamic-PituitaryAdrenal Hypothesis of Depression Samantha De Sousa Major depressive disorder (MDD) is a mood disorder that has been studied over many years to obtain evidence through various experiments in order to understand its complex effects on the brain. Stress has been determined as a key focal point in understanding why one experiences depressive-like behaviours and how the onset of MDD may come as a result of the overactivation of the hypothalamic-pituitary-adrenal (HPA) axis. Despite the variety of studies on this mood disorder, no study has targeted a direct association between glucocorticoid receptor (GR) and decreasing hippocampal astrocytes. The researchers in their primary article, Lou et al., 2018, aim to show how increased glucocorticoids (GCs) lead to more GR activation and able to explain if GR causes the suppression of astrocyte proliferation in the hippocampus. The authors of Lou et al., 2018 used two different experiments; in one the animal models were exposed to chronic unpredictable stress (CUS) for 28 days, and in the other, animal models were exposed to corticosterone (CORT) for 21 days. Glial fibrillary acidic protein (GFAP) expression was measured through immunofluorescence as a method to indicate a change in the number of astrocytes in the hippocampus. The CUS mice were seen to experience behaviours related to anhedonia â&#x20AC;&#x201C; a lack of pleasure/enjoyment; which was seen through behavioural tests like sucrose preference and the open field test. CORT levels were observed to have increased in both animal models which caused increased GR activation and a decrease in GFAP expression and hippocampal astrocytes. Mifepristone, a GR antagonist, weakened depressive like behaviours and reversed the decrease in GFAP expression within the hippocampus. Keywords: glucocorticoids, depression, glucocorticoid receptor, GFAP, astrocytes, glial cells, hippocampus, CUS, corticosterone, mifepristone, behaviour, stress, HPA axis

INTRODUCTION

Major depressive disorder (MDD) is a worldwide phenomenon that affects numerous populations and has a prevalence of 6.7 percent in the United States (Rajkowska & Stockmeier, 2013). This chronic and progressive neurological disorder has sparked the interest of scientists because of its extreme symptoms including recurring episodes of sadness, as well as a frequent loss of interest and pleasure – anhedonia, and altered brain function (Belleau, Treadway, & Pizzagalli, 2018; Ma et al., n.d.; Rajkowska & Stockmeier, 2013). The complexity of this illness has posed several questions for researchers to answer, as it does not have a single source of causation, but instead a plethora of etiologies including genetic factors, environmental factors, and in some cases, sporadic onset (Rajkowska & Stockmeier, 2013).

(Ma et al., n.d.). The authors indicate that the overexpression of glucocorticoid hormones caused by continuous stress can induce symptoms of depression with regards to the circadian clock and premature aging but do not indicate its importance in brain morphology and hippocampal volume of neurons and glial cells, specifically astrocytes (Ma et al., n.d.). Glucocorticoid receptor (GR) activation also needs to be further addressed in its role in the HPA axis and causation of depression.

In the 2018 study published by Lou et al., the authors provide additional research to MDD and the HPA hypothesis. GC levels and GR activation are the focal point in their experiment and how an increase in them leads to a difference in astrocyte numbers within the brain through evidence of glial fibrillary acidic proteins (GFAPs) expression seen in the CA3 and denate gyrus (DG) regions of the hippocampus (Lou et al., 2018). Previous Stress is encountered in every day living. The studies have not been able to show a relationship relationship between psychosocial stressors and between increased GR activation and a decrease in their effects on the brain of depressives seem to be hippocampal astrocytes (Lou et al., 2018). associated with the development of MDD (Canet, Chevallier, Zussy, Desrumaux, & Givalois, 2018; Two experiments were performed – mice were Soria et al., 2018). Numerous primary literature exposed to chronic uncontrollable stress (CUS) or and reviews have focused on this hormonal CORT injections (Lou et al., 2018). Mifepristone causation of depression in what is known to be the was administered on day 21 of the CUS experiment hypothalamus-pituitary-adrenal (HPA) hypothesis or on day 18 for the CORT injected mice and (Holsboer, 2000). This hypothesis predominantly effects were assessed through multiple behaviour focuses on the imbalance of glucocorticoids in the tests (Lou et al., 2018). The results show that brain. The hypothesis came about when several chronic stress and elevated GCs lead to increased clinical observations were made involving stress GR activation and a decrease in GFAP expression levels of adrenocorticotropic hormone (ACTH) and within the hippocampus, indicating a decrease in cortisol secretion increases in depressed individuals hippocampal astrocytes (Lou et al., 2018). (Holsboer, 2000). MAJOR RESULTS Glucocorticoids (GCs) are stress hormones controlled by the HPA axis (Canet et al., 2018; Unemura et al., Chronic stress induces depressive behaviours 2012). In their study, Ma et al., n.d. illustrate that though the increase of GC levels and GR continuous injections of corticosterone (CORT) – activation the primary stress hormone in mice – proved to overthrow the negative feedback of homeostasis in the HPA axis and induce depressive behaviour. Lou et al., 2018 used their research to support This behaviour was tested through two behaviour the HPA hypothesis of depression. In performing tests; a tail suspension test and sucrose preference two experiments, i) the CUS model, and ii) the test. The CORT injected mice when compared CORT injection model, the mice experienced to the control, showed an increase in immobility increased chronic stress in the brain which led to when suspended by the tail and a decrease in increased GC expression and thus increased levels sucrose preference – these behaviours show signs of GR activation (Lou et al., 2018). In order to see of depression-like symptoms including anhedonia the effects of CUS, the researchers performed 37

behavioural tests like sucrose preference (Fig. 1), where CUS mice showed a lack of interest in sucrose preference (Lou et al., 2018). When exposed to an open field test, the number of times they were crossing and rearing decreased when compared to the control (Lou et al., 2018). These behaviours are all examples of mice experiencing anhedonia – a common sign of depression.

Figure 1; The behaviour expressed by the control (CTR) group vs. CUS group in a) sucrose preference b-c) an open field test). Also indicates how mifepristone reverses the depressive behaviours in the CUS mice. Figure adapted from “Glucocorticoid receptor activation induces decrease of hippocampal astrocyte number in rats,” by Lou, Y.-X., Li, J., Wang, Z.-Z., Xia, C.-Y., & Chen, N.-H. (2018). Psychopharmacology, 235(9), 2529–2540.

Figure 1 also describes the effects of mifepristone; a GR antagonist also known as RU486 and how it reverses the effects of the CUS that was forced on the mice model (Lou et al., 2018). The CORT injected mice experienced a decrease in sucrose preference as well; seen in Figure 2.

when the mice were treated with mifepristone (CM CORT + mifepristone (grey bar) Figure adapted from “Glucocorticoid receptor activation induces decrease of hippocampal astrocyte number in rats,” by Lou, Y.-X., Li, J., Wang, Z.-Z., Xia, C.-Y., & Chen, N.-H. (2018). Psychopharmacology, 235(9), Mifepristone blocks the effects of increased CORT levels in mice Mifepristone has said to be a key target in treating depression because of its affects on GR activation (Zhang et al., 2018). Other studies have seen mifepristone treat stress induced animal models – however, its affect on astrocyte volume in the hippocampus has never been studied before (Lou et al., 2018). In their experiment, Lou et al., 2018 sought answers to indicate whether or not mifepristone can reverse astrocyte reduction through GR blocking in CUS and CORT injected mice. Figure 1 and 2 shows that mifepristone reversed the affects of anhedonia in the CUS mice and the CORT injected mice when compared to the placebo (vehicle) (Fig. 1) or the control (Fig. 2). Increased GR activation leads to a decrease in GFAP expression and astrocyte volume in the hippocampus The increase in CORT levels seen in both the CUS mice and CORT injected mice led to an increase in GR activation (Lou et al., 2018). Overexpressed GCs seen in the mice after being exposed to CUS for 28 days caused a decrease in hippocampal astrocyte levels within the CA3 area and DG area of the hippocampus (Lou et al., 2018) (Fig. 3). This result was analyzed through immunofluorescence to determine the changes in glial cells (Lou et al., 2018). The decrease in hippocampal astrocytes were reversed by mifepristone (Fig. 3). The number of GFAP positive cells significantly lessened in the CORT injected mice which indicated less hippocampal astrocytes (Fig. 4).

Figure 2; The CORT injected mice experience a decrease in sucrose behaviour which is a sign of anhedonia – this behaviour deficit is reversed 38

Figure 4; The number of GFAP positive cells shown al., 2012) (Fig. 6). in the CA3 and DG areas of the hippocampus after the mice were subjected to CORT injections. A reduction in GFAP cells mean less astrocytes present in the hippocampus. Mifepristone increased the GFAP expression (grey bar). Figure adapted from “Glucocorticoid receptor activation induces decrease of hippocampal astrocyte number in rats,” by Lou, Y.-X., Li, J., Wang, Z.-Z., Xia, C.-Y., & Chen, N.-H. (2018). Psychopharmacology, 235(9), 2529–2540.

Figure 5; The administered ACTH for 14 days caused the number of GFAP positive cells to decrease and cause a reduction of astrocytes in the hippocampus. Figure adapted from “Glucocorticoids decrease astrocyte numbers by reducing glucocorticoid receptor expression in vitro and in vivo,” by Unemura, K., Kume, T., Kondo, M., Maeda, Y., Izumi, Y., & Akaike, A. (2012). Journal of Pharmacological Sciences, 119(1), 30–39. Figure 6; MTT assay was done after the administration of CORT to measure astrocyte activity. The more CORT the animals were given, the less cell activity, meaning there was a reduction in astrocytes.

Figure 6; MTT assay was done after the administration of CORT to measure astrocyte activity. The more CORT the animals were given, the less cell activity, meaning there was a reduction in astrocytes. Figure adapted from “Glucocorticoids decrease astrocyte numbers by reducing glucocorticoid receptor expression in vitro and in vivo,” by Unemura, K., Kume, T., Kondo, M., Maeda, Y., Izumi, Y., & Akaike, A. (2012). Journal of Pharmacological Sciences, 119(1), 30–39.

Overall, these results support the HPA hypothesis of depression. The relationship of stress and depression is one that has been studied for years and often there have been gaps in research. Lou et al., 2018 have been able to answer some of these questions with their results including, how GC and In a similar study, researchers administered GR activation could be related to the onset of adrenocorticotropic hormone (ACTH) in mice for anhedonia and depressive behaviours, as well as approximately 14 days and observed its effects how astrocyte plasticity adds to brain morphology on the mice GFAP expression and astrocyte levels observed in depressed brains (Lou et al., 2018). (Unemura et al., 2012). Astrocyte levels decreased in the prefrontal cortex (Fig. 5) (Unemura et al., DISCUSSION 2012). The researchers also subjected the mice to a glucocorticoid treatment of CORT for 72 The aforementioned results by Lou et al., 2018 hours which also led less astrocytes (Unemura et 39

include that mice subjected to chronic stress either through CUS or continuous injections of CORT led (increased GCs) to increased corticosterone hormone levels in the mice which induced anhedonia like behaviours as seen through several behaviour tests. The depressive behaviours were weakened through an GR antagonist, mifepristone (Lou et al., 2018). The more GR activity in the brain caused a decrease in GFAP expression which portrays a reduction in hippocampal astrocyte volume (Lou et al., 2018). The authors concluded that the decrease in astrocytes found in the hippocampus may be correlated with the increased activation of GR due to the exposure to chronic stress and thus more GC hormone circulating the HPA axis. Prior studies have explored the effects of depression, in relation to the morphology and neuroplasticity in the types of nerve cells found in the brain, including astrocytes and neurons (Belleau et al., 2018; Cobb et al., 2016; Iwata et al., 2011). Astrocytes are said to be the most dominating type of glial cell in the brain and is important for the nervous system to properly work (Bender et al., 2016; Rajkowska & Stockmeier, 2013; Wang et al., 2017). Due to its importance in proper functioning, the role of astrocytes in mental illness is pivotal to understand when discussing neuroplasticity (Bender et al., 2016). Scientists have sought out to see how stress affects the brain though methods like chronic exposure to stress. Evidence shows that this hormonal exposure through glucocorticoids may indeed rework the brain’s morphology (Bender et al., 2016). Stress can cause multiple regions of the brain to undergo astocyte alteration (Bian et al., 2012), which can be seen through the main biomarker for mature astroyctes, GFAPs (Rajkowska & Stockmeier, 2013; Wang et al., 2017). MDD has been known to cause a decrease in hippocampal astrocytes and GFAP expression, seen through experiments with chronic stress and animal models (Rajkowska & Stockmeier, 2013). A study done by Czeh et al., 2006, outlined in Bender et al., 2016’s review, provided fundamental evidence that astrocytes are altered when the brain is continuously exposed to stress. In their study, adult male tree shrews were exposed to stress for about 5 weeks and the results showed a decrease

in GFAP positive cells located in the hippocampus. Bian et al., 2012’s study also indicates the reduction in GFAP expression in the both the prefrontal cortex and hippocampus, which specifies a difference in astrocyte density. In addition, studies looking at the brain through neuroimaging techniques have showed that individuals with MDD, both antemortem and postmortem, have a smaller hippocampal volume and prefrontal cortex (Belleau et al., 2018; Cobb et al., 2016; Iwata et al., 2011). Cobb et al., 2016 performed a study between individuals diagnosed with MDD who are undergoing antidepressant treatment and those who are not. Their results portray a decrease in astrocytes and GFAP expression in the hilus and CA2/3 region of the hippocampus.

However, further research into the relationship between increased GC levels and how it affects the relationship between GFAP expression and astrocyte density needed to be done in order to fully understand the changes in hippocampal volume reported by other studies (Belleau et al., 2018; Cobb et al., 2016). Lou et al., 2018’s study was able to show that increased GC and GR levels directly resulted in a decrease in hippocampal volume and GFAP expression because of the reduction in astrocytes in the CA3 and DG regions. A review done by Canet et al., suggests that an increase in GCs influences leads to an increase in GR activation which may be a leading cause to the onset of MDD, but how this GR activation induces depressed remains unanswered. The paper by Lou et al., 2018 is able to provide insight to the answer through different experiments both testing depressive like behaviours in animal models and brain morphology/neuronal plasticity in depressed mice. Mifepristone showed to have to worked in treating depressive behaviours (Canet et al., 2018). Although, studies indicating the GR antagonist’s role in reversing the depletion of certain nerve cells were still not done. Lou et al., 2018’s paper not only supports the evidence of other studies indicating the effective treatment of depressive behaviours, but in addition was able to show the treatment’s capability in reversing astrocyte reduction and increasing GFAP expression.

CRITICAL ANALYSIS GR activation did lead to a decrease in GFAP expression which reflects astrocyte plasticity as there was a reduction in hippocampal astrocytes (Lou et al., 2018). The researchers focused more on the relationship between GR activation and hippocampal astrocytes as a curious point in MDD (Lou et al., 2018). A limitation to this study is the failure to provide mechanistic evidence in why there is a correlation between GR activation and decreased astrocytes (Lou et al., 2018). The authors focused on the direct link between GR activation in astrocytes in the hippocampus but did not explain or study how this might be related – what kind of biological signalling/mechanistic pathways may be leading to decreased astrocytes? Why does reduced astrocyte volume induces depressive-like behaviours in the animal models?

While the results compiled in the researchers’ study supported their own hypothesis, as well as the HPA hypothesis, another study, despite some results being similar, did have contradictory opinions to the role of GR activation in the reduction of astrocytes. The study was done by Unemura et al., 2012, where they injected ACTH and their results suggested that in the areas where there was a decrease in astrocytes, there was also a decrease in GR activation, rather then an increase in GR as hypothesized by Lou et al., 2018. In order to address this contrast in primary literature, future studies should that looks at how GR activation may or may not play a role in depression and astrocyte depletion. FUTURE DIRECTIONS Inflammation has been previously associated with disorders involving chronic exposure to psychosocial stress (Liu, Wang, & Jiang, 2017; Zhang et al., 2018). In an attempt to understand the biological mechanisms behind GR activation and decreased GFAP/astrocyte expression, future experiments should set out to find if mice that undergo chronic stress by CUS or other by other forced stress methods such as isolation, experience inflammation in areas responsible for the regulatory control of hormones and homeostasis in the HPA axis. Inflammation could be a reason as to why

researchers in their paper Lou et al., 2018 saw an increase in GR activation in the brains of the mice. Stress has been known to cause inflammation in the brains due to the secretion of cytokines (Bian et al., 2012). Distinguishing whether or not this cytokine release influences GR activation could be an approach in understanding how hippocampal astrocyte volume and GR activation are related. In addition, another experiment future studies could conduct would be to focus on the functions of astrocytes in the brain when GR activation increases. As previously mentioned, astrocytes are one of the most important astrocytes in proper brain functioning (Bender et al., 2016; Rajkowska & Stockmeier, 2013). Astrocytes are known to release neurotrophins, which keep the brain healthy (Zhang et al., 2018). Measuring levels of neuotrophins in the brain when chronic stress is implemented in the mice models could be a futuristic approach in determining if this neurtrophin release is a direct cause of MDD. Furthermore, there is a mineralcorticoid receptor (MR) pathway in the HPA axis that also regulates glucocorticoid levels (Zhang et al., 2018). Astrocytes can have both GRs and MRs (Zhang et al., 2018). Lou et al., 2018’s, did not look at the MR activation pathway and if increased stress experienced by the animal models affected MR activation. Looking at how that MR activation would link GFAP expression and astrocyte proliferation in the brains of depressed individuals could be a future research approach. This experiment should be done to see if an MR antagonist can reverse the effects of GFAP expression reduction and hippocampal astrocyte volume by blocking MRs, like mifepristone was able to block the GRs expressed in the animal models. More evidence on treatment options could be obtained and would indicate which pathway; MR or GR, would be most effective in treating patients with MDD.

REFERENCES 1. Belleau, E. L., Treadway, M. T., & Pizzagalli, D. A. (2018). The Impact of Stress and Major Depressive Disorder on Hippocampal and Medial Prefrontal Cortex Morphology. Biological Psychiatry. https://doi.org/10.1016/j.biopsych.2018.09.031 2. Bender, C. L., Calfa, G. D., & Molina, V. A. (2016). Astrocyte plasticity induced by emotional stress: A new partner in psychiatric physiopathology? Progress in Neuro-Psychopharmacology and Biological Psychiatry, 65, 68–77. https://doi.org/10.1016/j.pnpbp.2015.08.005 3. Bian, Y., Pan, Z., Hou, Z., Huang, C., Li, W., & Zhao, B. (2012). Learning, memory, and glial cell changes following recovery from chronic unpredictable stress. Brain Research Bulletin, 88(5), 471–476. https://doi.org/10.1016/j.brainresbull.2012.04.008 4. Canet, G., Chevallier, N., Zussy, C., Desrumaux, C., & Givalois, L. (2018). Central Role of Glucocorticoid Receptors in Alzheimer’s Disease and Depression. Frontiers in Neuroscience, 12. https://doi.org/10.3389/fnins.2018.00739 5. Cobb, J. A., O’Neill, K., Milner, J., Mahajan, G. J., Lawrence, T. J., May, W. L., … Stockmeier, C. A. (2016). Density of GFAP-immunoreactive astrocytes is decreased in left hippocampi in major depressive disorder. Neuroscience, 316, 209–220. https://doi.org/10.1016/j. neuroscience.2015.12.044 6. Holsboer, F. (2000). The Corticosteroid Receptor Hypothesis of Depression. Neuropsychopharmacology, 23(5), 477–501. https://doi.org/10.1016/S0893-133X(00)00159-7 7. Iwata, M., Shirayama, Y., Ishida, H., Hazama, G., & Nakagome, K. (2011). Hippocampal astrocytes are necessary for antidepressant treatment of learned helplessness rats. Hippocampus, 21(8), 877–884. https://doi.org/10.1002/hipo.20803 8. Liu, Y.-Z., Wang, Y.-X., & Jiang, C.-L. (2017). Inflammation: The Common Pathway of Stress-Related Diseases. Frontiers in Human Neuroscience, 11. https://doi.org/10.3389/fnhum.2017.00316 9. Lou, Y.-X., Li, J., Wang, Z.-Z., Xia, C.-Y., & Chen, N.-H. (2018). Glucocorticoid receptor activation induces decrease of hippocampal astrocyte number in rats. Psychopharmacology, 235(9), 2529– 2540. https://doi.org/10.1007/s00213-018-4936-2 10. Ma, L., Shen, Q., Yang, S., Xie, X., Xiao, Q., Yu, C., … Fu, Z. (n.d.). Effect of chronic corticosteroneinduced depression on circadian rhythms and age-related phenotypes in mice, 11. 11. Rajkowska, G., & Stockmeier, C. A. (2013). Astrocyte pathology in major depressive disorder: insights from human postmortem brain tissue. Current Drug Targets, 14(11), 1225–1236. 12. Soria, V., González-Rodríguez, A., Huerta-Ramos, E., Usall, J., Cobo, J., Bioque, M., … Labad, J. (2018). Targeting hypothalamic-pituitary-adrenal axis hormones and sex steroids for improving cognition in major mood disorders and schizophrenia: a systematic review and narrative synthesis. Psychoneuroendocrinology, 93, 8–19. https://doi.org/10.1016/j.psyneuen.2018.04.012 13. Unemura, K., Kume, T., Kondo, M., Maeda, Y., Izumi, Y., & Akaike, A. (2012). Glucocorticoids Decrease Astrocyte Numbers by Reducing Glucocorticoid Receptor Expression In Vitro and In Vivo. Journal of Pharmacological Sciences, 119(1), 30–39. https://doi.org/10.1254/jphs.12047FP 14. Wang, Q., Jie, W., Liu, J.-H., Yang, J.-M., & Gao, T.-M. (2017). An astroglial basis of major depressive disorder? An overview. Glia, 65(8), 1227–1250. https://doi.org/10.1002/glia.23143 15. Zhang, Y.-P., Wang, H.-Y., Zhang, C., Liu, B.-P., Peng, Z.-L., Li, Y.-Y., … Song, C. (2018). Mifepristone attenuates depression-like changes induced by chronic central administration of interleukin-1β in rats. Behavioural Brain Research, 347, 436–445. https://doi.org/10.1016/j.bbr.2018.03.033

The Role of Urea in Huntingtonâ&#x20AC;&#x2122;s Disease Neeraj Dhaliwal Huntingtonâ&#x20AC;&#x2122;s Disease (HD) is a debilitating neurodegenerative disorder that is inherited in an autosomal dominant manner (Walker, 2007). The genetic mutation that underlies this condition is an expansion of CAG (glutamine) repeats in the N-terminus of the HTT gene, resulting in a mutated huntingtin protein. This protein normally contains glutamine repeats, however the mutated form is characterized by 35 or more of these repeats. It has been found that the number of polyglutamine repeats in a patient is correlated with the onset of symptoms; a higher number of repeats indicates earlier onset of this disease. Like many other neurodegenerative diseases, the mutated protein of interest in this disorder forms aggregations within the brain, which may explain the correlation between the amount of polyglutamine repeats and the onset of symptoms. Symptoms of HD include chorea, which is movement in an involuntary and unpredictable fashion, as well as weight loss, cognitive declines, and changes in behavior or personality. What makes this disease incredibly troubling is that symptoms typically arise after one has had children and is likely to have already passed on their mutation to the next generation (Walker, 2007). Additionally, the age of onset appears to become earlier with each passing generation, due to the increasing size and instability of the CAG repeat (Trottier, 1994). This outlines the importance of taking a family history in the medical field as well as being aware of the symptoms associated with HD. Although the mutation underlying HD has been well-defined, not much else is known about this disorder and there is currently no known cure. A study by Handley et al. (2017) investigates the metabolic effects of HD by sequencing the RNA of striatal tissue in sheep possessing a mutated human HTT transgene. In this prodromal model with minimal symptoms and low cell loss, they found increased levels of urea as well as the urea transporter SLC14A1 in striatal tissue and other areas of the brain. Additionally, they observed increased levels of urea in the brain of post-mortem humans who were in the early stages of HD. This finding acts as a starting point for finding a cure or treatment for HD; if high levels of this metabolite underlie the pathogenesis and mechanism of this disease, urea may be an important target for drug therapy. Key words: Huntingtonâ&#x20AC;&#x2122;s Disease, HTT, huntingtin, glutamine, neurodegeneration, urea, metabolism, prodromal, sheep, striatum

BACKGROUND muscle loss. The authors of this study demonstrated that this observation was not due to increased muscle movements, as they used models who had Huntington’s disease (HD) is a neurodegenerative early stages of HD (Goodman et al., 2008). This disorder that was originally described and named indicates that there may be some sort of metabolic after George Huntington in the late 1800s (Novak mechanism that results in weight loss (Goodman and Tabrizi, 2011). It is known that Huntington’s et al., 2008). Additionally, a study by Graham et al. disease (HD) is caused by a mutation in the HTT (2018) found increased levels of acylcarnitine and gene (Novak and Tabrizi, 2011). This mutation is creatinine in deceased HD patients, which further characterized by an expansion of the CAG repeat suggests that energy metabolism is affected in this in this gene and its resulting protein (Novak and disease. Tabrizi, 2011). Huntington’s disease often becomes symptomatic later in life, mostly after affected Considering the symptoms of HD that appear to individuals have had children (Novak and Tabrizi, be related to metabolism and the fact that the 2011). After the onset of symptoms, HD becomes mechanism behind HD is unknown, Handley et al. fatal within fifteen to thirty years (Novak and (2017) created a transgenic sheep line to study this Tabrizi, 2011). disease. They called this sheep line OVT73; these animals express a human HTT transgene with a While much is known about the genetics of polyglutamine expansion of 73 repeats (Handley this disease, the mechanism underlying the et al., 2017). These sheep are a prodromal model, pathogenesis of HD is not yet understood and which means that they are in the early stages of the downstream effects of the HTT gene mutation HD and have not yet experienced symptoms are unclear (Walker, 2007). While the huntingtin or neuronal cell loss (Handley et al., 2017). The protein is expressed all over the body, levels of this authors of this study performed RNA sequencing protein are the highest in the striatum of the brain on the striatal tissue of this model and found that and within the testes (Schulte and Littleton, 2011). the urea transporter SLC14A1 was present at In HD, it appears that spiny neurons in the striatum higher levels compared to controls (Handley et al., undergo degeneration, although the mechanism 2017). They also observed increased levels of urea behind this observation is unknown (Schulte and itself (Handley et al., 2017). Additionally, Handley Littleton, 2011). et al. (2017) studied the brains of post-mortem humans with HD, and used biochemical assays Although HD is characterized as a neurodegenerative and gas chromatography mass spectrometry disorder and many symptoms are neurological in to examine urea levels in these individuals. As nature, there are also widespread impacts of this expected, they found increased levels of urea and disease on the body. For example, HD patients the urea transporter in these post-mortem HD often experience weight loss and muscle wasting patients as well (Handley et al., 2017). Notably, (cachexia); this indicates that a mutation of the both the sheep and human cases that Handley et huntingtin protein may have an extensive metabolic al. (2017) examined had low levels of neuronal cell effect (van der Burg, Bjorkqvist & Brundin, 2009). loss. This is of importance, as this finding indicates A variety of studies published in the past have that increased urea levels are not observed due to focused on finding the mechanism that underlies cell death in HD patients (Handley et al., 2017). these metabolic effects with the hope of finding a While this study did not find a mechanism for why potential treatment for Huntington’s disease and or how urea levels are increased in Huntington’s slowing its progression. The symptom of weight disease and how this may be related to the loss is of interest to many research groups, since HD mutated huntingtin protein, this finding may help patients commonly have an increased appetite and the scientific community find a target for treatment. should theoretically experience weight gain (Trejo et al., 2004). A study by Goodman et al. (2008) MAJOR RESULTS was one of the first to confirm that a negative energy balance and increased energy expenditure The major finding of the study conducted by is present in HD cases, which produces weight and 44 INTRODUCTION INFORMATION

AND

Handley et al. (2017) is that urea and its transporter are elevated in the striatal tissue of prodromal sheep as well as in deceased human subjects. Since these models are representative of the early stages of HD where cell loss is minimal, this finding cannot be explained by cell loss (Handley et al., 2017). This finding suggests that decreasing the levels of urea in the brain may be a useful target for the treatment of HD symptoms (Handley et al., 2017).

expressed, Handley et al. (2017) also observed an increase in the gene expression of an ammonia transporter, RHCG. As shown in Figure 2, the expression of these two transporters appears to be correlated. This is evidence that the urea cycle may contribute to the symptoms observed in HD, as ammonia is a precursor to urea in this process (Handley et al., 2017).

SLC14A1 Expression in Sheep Models of HD

Handley et al. (2017) completed a biochemical assay of the cerebellum and superior frontal gyrus of deceased human subjects with low amounts of neuronal cell loss. As evident in Figure 3, they found that levels of urea were higher in post-mortem HD patients than in controls Handley et al., 2017). Additionally, they completed a western blot using a polyclonal antibody against the urea transporter, and found that this transporter was increased in HD patients compared to controls (Handley et al., 2017). These results are in line to those observed in the OVT73 sheep line.

After sequencing the RNA of striatal tissue in their sheep model, Handley et al. (2017) found increased levels of a gene that codes for a urea transporter in HD sheep compared to control sheep. As evident in Figure 1, levels of this gene, SLC14A1, are significantly higher in HD sheep.

Urea Levels in Post-mortem Human HD Patients

Figure 1. Increased expression of the gene SLC14A1 in different regions of the striatum of OVT73 HD sheep. This gene encodes for a transmembrane urea transporter. Figure Adapted from Handley et al. (2017). Proceedings of the National Academy of Sciences of the United States of America, 114(52), Figure 2. Expression of SLC14A1 and RHCG in E11293-E11302. control vs. OVT73 sheep. In OVT73 sheep, increased expression of SLC14A1 is correlated with increased expression of RHCG, however this relationship is Urea Levels in Sheep Models of HD not observed in control sheep. Figure Adapted Similar to the expression of the urea transporter from Handley et al. (2017). Proceedings of the gene SLC14A, levels of urea appear to be increased National Academy of Sciences of the United States in the striatum of HD sheep compared to controls of America, 114(52), E11293-E11302. (Handley et al., 2017). Levels of Ammonia and Urea Transporters in Sheep Models of HD In addition to the finding that the gene encoding for a urea transporter in HD sheep is increasingly 45

further research is essential in finding a cure for this debilitating disease. DISCUSSION AND CONCLUSION

Figure 3. Increased levels of urea in the cerebellum and superior frontal gyrus of deceased HD patients with minimal neuronal cell loss, as compared to healthy controls. Figure Adapted from Handley et al. (2017). Proceedings of the National Academy of Sciences of the United States of America, 114(52), E11293-E11302. Relevance and Comparison to Other Literature

A major conclusion derived from the study completed by Handley et al. (2017) is that levels of urea and its transporter are high in both sheep and human models of Huntingtonâ&#x20AC;&#x2122;s disease. Importantly, these results are seen in early stages of pathogenesis, meaning that cell loss is minimal in these cases. This indicates that the increases in urea are not observed due to cell loss. This may be postulated because cell death results in the breakdown of excess proteins, which are converted to urea and excreted in the urine via the urea cycle (Handley et al., 2017). However, the results of this study indicate that this is not likely to be the case. Instead, Handley et al., suggest that increased levels of urea are observed due to excess protein catabolism in order to provide excess energy, as an altered energy balance and increased energy expenditure is seen in HD patients. However, Handley et al. (2017) have not studied this possibility in detail as of present. If this were the case, it would make sense that elevated urea is observed, as the urea cycle would be occurring in a dysregulated manner (Bireley, Van Hove, Gallagher & Fenton, 2012).

Handley et al. (2017) are one of the first groups to find elevations in urea in models of Huntingtonâ&#x20AC;&#x2122;s disease. It does not appear that any other available literature has found disputing results. The available research on HD and urea seems to be in line with the results of the study by Handley et al. (2017). The study by Handley et al. (2017) was one of the Patassini et al. (2015) found an increased level of first to find a correlation between urea and HD in urea in post-mortem HD patients; their observation a prodromal model. The impact of this finding is was that this elevation can be seen all over the brain, of great breadth, as elevations in this metabolite rather than in only the cerebellum and superior provide a novel avenue for HD research. If the frontal gyrus. Interestingly, neither of these studies mechanism underlying this observation can be found an increased level of urea in human striatal found, scientists may be able to create a therapy to tissue, which is said to be majorly impacted in HD; either slow the development of HD or to fully cure rather, this observation was found to be widespread this disease. As there is no available treatment or in the brain (Handley et al., 2017; Patassini et al., cure for this fatal disorder, and there is little to no 2015). Additionally, Bichell et al. (2017) have found information known about the mechanism behind that a cofactor for an enzyme in the urea cycle HD, it is vital to direct scientific research towards is reduced in HD. This cofactor, manganese, is this path. The findings of the study completed by important for the function of arginase, an enzyme Handley et al. (2017) provide a great starting point that is vital in the urea cycle (Bichell et al., 2017). in solving the many mysteries of this disease. Bichell et al. (2017) observed decreased activity of this enzyme, which may explain the increased levels As described previously, there are many studies that of urea in the brain of HD patients. The currently fall in line with the results of Handley et al.â&#x20AC;&#x2122;s (2017) available scientific literature suggests that urea research article. Bichell et al. (2017) found that the and other components of the urea cycle may be cofactor (manganese) of an important enzyme in good targets for the treatment of HD, which is why 46

the urea cycle is decreased in HD patients. This provides insight regarding the component of the urea cycle that may be altered in HD, which brings the scientific community closer to finding a mechanism for this disease. Additionally, Chiang et al. (2007) found that levels of a transcription factor called C/EBPalpha are decreased in mice suffering from HD. This transcription factor is important in the function of the urea cycle, and restoring this transcription factor to baseline levels may be another target for HD treatment (Chiang et al., 2007). Furthermore, this group found that ammonia levels are high in HD mice, suggesting that the urea cycle is not functioning effectively (Chiang et al., 2007). Increased levels of ammonia in the body are often treated with a low protein diet, so this may be a worthwhile dietary treatment to study in relation to the control of HD symptoms (Chen et al., 2015). Another study by the same group suggests that the A2A adenosine receptor can rescue the ineffectiveness of the urea cycle in mice; this may be another drug target to examine in the future (Chiang et al., 2009). CRITICAL ANALYSIS

urea in the brain of HD patients or models remain unaffected by this inhibitor, this may indicate that another component of the urea cycle is perturbed in HD development. The role of ammonia should be further studied in addition to urea. Ammonia is toxic to the brain, and its presence may play a role in HD development (Chen et al., 2015). However, Handley et al. (2017) were unable to measure ammonia levels in their models of HD. They did find increased expression of a gene that encodes for an ammonia transporter (RHCG), so the study of ammonia itself is a plausible next step (Handley et al., 2017).

Moreover, the use of a sheep model is unique in this study. Because of the large size of this model, it is difficult to create enough animals to retrieve results of strong statistical significance. The study by Handley et al. (2017) only used six OVT73 sheep and six control sheep. If they had used a murine or zebrafish model instead, they may have been able to use a greater sample size and get results with better significance and applicability to the human population. This would also make it easier to apply different drug treatments in further studies, as different groups of mice or zebrafish can be easily separated and altered in different ways while still maintaining statistical significance (Hersch & Ferrante, 2004). However, a sheep model may have been chosen by this group due to the comparable organ and body size to humans.

While the study by Handley et al. (2017) provides a starting point for the development of a therapy for HD, further studies are required for the scientific community to get to this point. This article provides a strong basis for urea as a target for treatment, and there do not appear to be any discrepancies with other literature that is currently available. However, this study did not examine the mechanism by FUTURE DIRECTIONS which urea levels are increased. It is important to determine whether the urea cycle is involved, and The next step for the authors of this study it is vital to discover the exact component of this should be to determine the mechanism behind process that is altered in HD. the elevated urea observed in their research. As described previously, this may be done using urea By further studying the mechanism behind HD transporter inhibitors. Additionally, inhibitors of and its relation to the urea cycle, Handley et al. enzymes involved in the urea cycle may be used (2017) may be able to determine a target for drug to find the component of this process that causes treatment. Since this study indicated an increase the symptoms observed in HD. For example, an in urea as well as the urea transporter in striatal inhibitor for arginase such as nor-NOHA may be tissue, Handley et al. may choose to use a urea used to examine the effects of the urea cycle; if transporter inhibitor to determine whether urea is the symptoms associated with HD are still present directly involved in HD development. For example, after this inhibition, this may indicate that arginase they may choose to use fluorenones to inhibit is not involved in the development of HD (Pudlo, the UT-B transporter encoded by SLC14A1 and Demougeot & Girard-Thernier, 2017). However, examine the effects of this treatment on urea and a caveat to this experiment would be that these HD development (Lee et al., 2015). If levels of 47

transporters will also impact the liver and other areas of the body where the urea cycle is vital for the processing of urine and the breakdown of proteins. If a property specific to transporters within the brain could be exploited to develop a more specific inhibitor, this approach may be plausible.

able to eliminate urea as a potential target for the treatment of Huntingtonâ&#x20AC;&#x2122;s disease.

Regardless of the results of these proposed experiments, the researchers will be able to get closer to their goal of finding a drug or therapy to treat Huntingtonâ&#x20AC;&#x2122;s disease. By discovering Another interesting idea to explore may be the elevation of urea and its transporter in HD the effect of diet on HD development and the models and post-mortem humans, Handley et al. management of symptoms. Chen et al. (2015) (2017) have made immense progress in the future suggested a low protein diet as a way to manage treatment of this fatal disease. the levels of ammonia and other components of the urea cycle in the brain and blood. Handley et al.â&#x20AC;&#x2122;s group may examine the effect of nutrition on urea levels by feeding their sheep model a low protein and high fat/carbohydrate diet. If OVT73 sheep given a low protein diet have decreased urea levels and HD symptoms compared to OVT73 sheep fed a high protein diet, a non-pharmaceutical treatment for HD involving changes to the diet may be discovered. These sheep should also be compared to control sheep models who are fed high protein and low protein diets to determine whether or not a mutation in the HTT gene plays a role in the potential observations of this experiment. However, it is important to keep in mind that HD patients often experience muscle wasting and weight loss; it will be vital to find a balance between energy balance and protein intake in the diet, thus allowing patients to receive adequate amounts of nutrients. Finally, a genetic modification experiment using CRISPR-Cas9 may be an interesting way to determine the role of the HTT gene in the elevation of urea. Handley et al. may start with a OVT73 sheep that shows early symptoms of HD with little cell loss and high levels of urea in the striatal tissue. Then, they may use CRISPR-Cas9 to replace the mutated HTT gene with a wild type copy of the gene. It is expected that the symptoms associated with HD will be eliminated. However, this experiment would also help the authors determine if the elevated urea that they observed in their study is directly related to the HTT gene and the huntingtin protein. If they see a decrease in urea after genetic modification and restoration of this gene to the wild type form, they will be more confident in their finding that urea is related to HD development. If they notice that urea remains elevated in the striatal tissue of the wild type (ex-mutant) sheep, they will be 48

REFERENCES 1. Bichell, T.J.V., Wegrzynowicz, M., Tipps, K.G., Bradley, E.M., Uhouse, M.A., Bryan, M.,… Bowman, A.B. (2017). Reduced bioavailable manganese causes striatal urea cycle pathology in Huntington’s disease mouse model. 2. Bireley, W.R., Van Hove, J.L.K., Gallagher, R.C., Fenton, L.Z. (2012). Urea cycle disorders: brain MRI and neurological outcome. Pediatric Radiology, 42(4), 455-462. 3. Chen, C-M., Lin, Y-S., Wu, Y-R., Chen, P., Tsai, F-J., Yang, C-L.,…Soong, B-W. (2015). High protein diet and Huntington’s disease. PLoS ONE, 10(5): e0127654. 4. Chiang, C-M., Chen, H-M., Lee, Y-H., Chang, H-H., Wu, Y-C., Soong, B-W,…Chern, Y. (2007) Dysregulation of C/EBPalpha by mutant Huntingtin causes the urea cycle deficiency in Huntington’s Disease. Human Molecular Genetics, 16(1): 483-498. 5. Chiang, C-M., Chen, H-M., Lai, H-L., Chen, H-W., Chou, S-Y., Chen, C-M,, Tsai, F-J., Chern, Y. (2009). The A2A adenosine receptor rescues the urea cycle deficiency of Huntington’s disease by enhancing the activity of the ubiquitin-proteasome system. Human Molecular Genetics, 18(16): 2929-2942. 6. Goodman, A.O.G., Murgatroyd, P.R., Medina-Gomez, G., Wood, N.I., Finer, N., Vidal-Puig, A.J., Morton, A.J., Barker, R.A. (2008). The metabolic profile of early Huntington’s disease – a combined human and transgenic mouse study. Experimental Neurology, 210(2), 691-698. 7. Graham, S.F., Pan, X., Yilmaz, A., Macias, S., Robinson, A., Mann, D., Green, B.D. (2018). Targeted biochemical profiling of brain from Huntington’s disease patients reveals novel metabolic pathways of interest. BBA – Molecular Basis of Disease, 1864(7): 2430-2437. 8. Handley, R.R., Reid, S.J., Brauning, R., Maclean P., Mears, E.R., Fourie,…Snell, R.G. (2017) Brain urea increase is an early Huntington’s disease pathogenic event observed in a prodromal transgenic sheep model and HD cases. Proceedings of the National Academy of Sciences of the United States of America, 114(52), E11293-E11302. 9. Hersch, S.M., Ferrante, R.J. (2004). Translating therapies for Huntington’s disease from genetic animal models to clinical trials. NeuroRx, 1(3): 298-306. 10. Novak, M.J.U, Tabrizi, S.J. (2011). Huntington’s disease: Clinical representation and treatment. International Review of Neurobiology, 98, 297-323. 11. Patassini, S., Begley, P., Reid, S.J., Xu, J., Church, S.J., Curtis, M.,…Cooper, G.J.S. (2015). Identification of elevated urea as a severe, ubiquitous metabolic defect in the brain of patients with Huntington’s Disease. Biochemical and Biophysical Research Communications, 468(1-2), 161-166. 12. Pudlo, M., Demougeot, C., Girard-Thernier, C. (2017). Arginase inhibitors: A rational approach over one century. Medicinal Research Reviews, 37(3), 475-513. 13. Schulte, J., Littleton, J.T. (2011). The biological function of the Huntingtin protein and its relevance to Huntington’s Disease pathology. Current Trends in Neurology, 5, 65-78. 14. Trejo, A., Tarrats, R.M., Alonso, M.E., Boll, M.C., Ochoa, A., Velasquez, L. (2004). Assessment of the nutritional status of patients with Huntington’s disease. Nutrition, 20(2), 192-196. 15. Trottier, Y., Biancalana, V., Mandel, J.L. (1994). Instability of CAG repeats in Huntington’s disease: Relation to parental transmission and age of onset. Journal of Medical Genetics, 31(5): 377-382. 16. van der Burg, J.M.M., Bjorkqvist, M., Brundin, P. (2009). Beyond the brain: widespread pathology in Huntington’s disease. The Lancet Neurology, 8(8), 765-774. 17. Walker, F.O. (2007). Huntington’s disease. The Lancet, 367(9557), 218-228.

A novel BDNF-like pharmacological agent TDP6 potently binds Trk2 receptors to promote remyelination and oligodendrocyte differentiation in the CNS Dholakia AS Multiple sclerosis (MS) is a neurodegenerative disease that causes white matter degradation within the central nervous system (CNS). While MS has no present cure, there is great interest in harnessing regenerative remyelination mechanisms for therapeutic use, particularly through brain-derived neurotrophic factor (BDNF) mediated activation of tropomyosin receptor kinases (TrK). Specifically, BDNF has been identified as the native TrkB agonist, promoting cell survival and differentiation through signalling of the Atk and ERK pathways. BDNF does not however readily cross the blood brain barrier (BBB), and is thus an ineffective pharmacological agent. In this study, the authors identify the re-myelinating effects of exogenous BDNF and a novel BDNF mimetic, tricyclic dimeric peptide 6 (TDP6) in oligodendrocytes (OD) and oligodendrocyte progenitor cells (OPC) following cuprizoneinduced (CPZ) demyelination. TDP6 has previously shown to readily cross the BBB and more effectively stimulate TrkB receptors compared to BDNF in vitro. Similarly, TDP6 promoted greater TrkB auto-phosphorylation and was associated with promoting OPC differentiation and proliferation post-myelin injury compared to BDNF in vivo. TPD6 remyelination and associated events were verified to be TrkB-dependent in concordance with previous literature. Ultimately, TDP6 was verified to more effectively bind and activate TrkB in vivo. TDP6-TrkB signalling initiated a more diverse range of remyelinating and associated events compared to native BDNF, including OPC differentiation and proliferation. Ultimately, these results indicate the promise of TDP6 as a therapeutic drug agent in the treatment of progressive MS. Key words: multiple sclerosis (MS), remyelination, brain-derived neurotrophic factor (BDNF), tricyclic dimeric peptide 6 (TDP6), tropomyosin kinase receptor 2 (Trk2), oligodendrocyte

Introduction

Multiple sclerosis (MS) is an autoimmune disease that targets and destroys myelinated neurons in the central nervous system (CNS). In particular, T cells incorrectly identify myelin basic protein (MBP) expressed by oligodendrocytes (OD), and induce disruptions in myelin evoking the sensorimotor, cognitive, and emotional impairments associated with the disease1. Studying MS is of particular interest due to its above average epidemiological representation in North America, and its lack of cure or effective therapy1,2.

inducing OPC differentiation in promyelination6,10.

Development of a BDNF drug agent has however been unfruitful. BDNF is a bulky, lipophobic protein, that do not readily cross the blood brain barrier (BBB) to reach target receptors. Thus, there is great research interest in the development of more lightweight and/or lipophilic neurotrophinlike mimetics that accomplish the same functions as BDNF12. Particularly, the tricyclic dimeric peptide dimer 6 (TDP6) was of interest to Wong et al13,14. Using in vitro models, Wong et al. have shown TDP6â&#x20AC;&#x2122;s increased effectiveness in engaging TrkB receptors compared to BDNF, as well as its Interestingly, in milder remit/relapse forms of ability to drive OPC differentiation, increase myelin MS, patients are noted to exhibit remyelination sheath thickness and proportion of myelination events post-lesioning, suggesting the existence axon segments13,14. of inherent regenerative mechanisms2,3,4. In progressive MS, however, remyelination Despite these promising results, there is limited mechanisms such as oligodendrocyte precursor literature beyond TDP6 in cell culture. In this cell (OPC) differentiation are either inefficient paper, the work of Fletcher et al. is reviewed15. or absent3,4. It is thus of interest to identify and Fletcher et al. expand knowledge on the in vivo develop pharmacological agents that manipulate effects of the TDP6 mimetic on CNS myelin the bodyâ&#x20AC;&#x2122;s reparative capabilities in response to repair in TrkB-WT and TrkB-KO mice following demyelinating events. CPZ-induced demyelination. Both BDNF and TDP6 were exogenously administered via Brain-derived neurotrophic factor (BDNF) has intracerebroventricular delivery for 7 days, after been identified as a promyelinating factor within which samples of corpus callosum were taken. the CNS5. BDNF binds to tropomyosin receptor Fletcher et al. found that both TDP6 and BDNF kinase (TrK) causing autophosphorylation of were able to increase myelin sheet thickness after TrK2 isotype, which induces distant downstream demyelination compared to control. TDP6 however effectors such as Atk and ERK, which have both more effectively activated TrkB receptors, and implicated in neuronal differentiation and cell enhanced OPC proliferation and differentiation survival6. Pertinently, BDNF can act directly on OD compared to BDNF/control. Remyelination to promote myelination, but must signal TrkB7. responses in TDP6-treated mice were established Multiple authors have demonstrated BDNF-Trk2 as TrkB-dependent. interaction drives OD-mediated axon remyelination in murine models following experimentally induced Ultimately, Fletcher et al. were able to demonstrate demyelination with cuprizone (CPZ)8. VonDrann et that TDP6 was more effective and holistic in al. (2011) showed that endogenous BDNF induced remyelination processes post-injury compared CNS remyelination and enhanced proliferation and to BDNF. These results indicate a potential differentiation of OPCs in response to remyelination. therapeutic use for TDP6 in the repair of white BDNF-KO mice otherwise presented an attenuated matter lesions seen in patients with progressive remyelination response. Similarly, Linker et al. MS and encourage further study of similar small (2010) showed the neuroprotective effects of drug molecule agonists. exogenous BDNF on white matter integrity and against progression of induced MS10. BDNF and MATERIALS AND METHODS TrkB are thus of interest as druggable factors that may alleviate symptoms and prevent relapse. Cuprizone feeding and intracerebroventricular Furthermore, it was demonstrated that activation delivery of the downstream effector, ERK is necessary for 51

At around 8 weeks, mice either received 0.2% CPZ/normal chow or normal chow as healthy control (HC) for 6 weeks. Mice from both cohorts were randomly sacrificed for brain tissue sample to verify CPS-induced demyelination undergo surgery. The remaining CPZ-fed mice underwent cannula implantation surgery and one of BDNF (4uM/0.1%BSA aCSF), TDP6 (40uM/ aCSF), or aCSF-only control was administered intracerebroventricularly over 7 days.

indicated by decreased levels of Hoechst and Olig2+ expression, but no change in OPC PDGFRa marker expression. Demyelination events did however induce compensatory astrocytosis and microgliosis, as indicated by increased GFAP+ and Iba1+ staining.

Sample preparation, immunofluorescence, and cell count Corpus callosum tissue was processed and stained using various immunofluorescent primary antibodies. Myelin basic protein (MBP), a marker for OD myelination, was identified with rat anti-MBP+. Washing with rabbit anti-Olig2+ in conjunction with either Hoerscht counterstain, mouse anti-CC1+, or goat anti-PDGFRa was used to identify fully mature OD, OPCs, and post-mitotic (immature) OD. To identify TrkB and pTrkB expression levels, TrkB and phosphorylated TrkB (pTrkB) samples were permeabilized with Triton-X 100 buffer, then washed with primary rabbit anti-TrkB and antipTrkBS478. Immunofluorescing cells were manually counted over a constrained region of interest15,16 and results were reported in cell densities and equated with expression level. Mice breeding

Fig. 1 â&#x20AC;&#x201C; d) Cuprizone-induced demyelination acts independently of TrkB. e) f) g) Cuprizone-induced demyelination results in initial decreases in OG cell density, but does not affect MBP expression in OPC populations. All figures (1-4; see below) taken from source (Fletcher et al., 2018)15 BDNF and TDP6 promotes remyelination in OD, but only TDP6 promotes differentiation events post-myelin injury

TrkB-WT mice were derived from standard female C57BL/6 mice. To derive TrkB-KO mice, 8-10 week Treatment with exogenous BDNF and TDP6 shows old progeny of CNPaseCre+/- were mated with overall OD cell density, indicated by increases TrkBfl/fl mice at an unspecified age. in MBP+ expression compared to aCSF control, as seen in Fig. 2 (below) TDP6 indicates greater mature and immature OD cell density in the corpus RESULTS callosum compared to both BDNF and control Cuprizone treatment induced demyelination, treatments, as indicated by increased Hoechst and including reduction in OD, but not OPC cell CC1+ staining (not shown). It is worth noting, that both OD subtypes are post-mitotic, and thus noncounts. replicative. Interestingly, OPC cell counts were MBP+ expression was significantly reduced not significantly higher in either BDNF and TDP6 in CPZ cohorts compared to HC. There was cohorts compared to control. Astrocytosis and no significant difference of extent of MBP+ gliosis was not induced by either BDNF or TDP6 expression/demyelination between WT and TrkB- treatment (not shown). KO cohorts. Cuprizone induced a slight reduction in differentiated OD cell density in the CPZ cohort, 52

TDP6 and BDNF promote phosphorylation in ODs

TrkB

receptor

Fig. 3 – a) TDP6 significantly increases phosphorylation of the TrkB receptor compared to BDNF/control b) c) TDP6 nor BDNF induce significant phosphorylation of TrkB in OPC, but both are associated with increases in pTrKB in ODs.

TrkB autophosphorylation is a downstream step of BDNF/ TDP6-mediated binding and receptor activation. Generally, BDNF and TDP6 treatment caused slightly greater proportions of cells to express pTrkB, indicated via anti-pTrkB staining (not shown), suggesting induced activation of the TrkB receptor (see Fig. 3). This result was expected, as TDP6 has been shown to be a more effective exogenous ligand to TrkB. pTrkB expression was associated with remyelination events, and was largely upregulated in CC1+ expressing OD, in both BDNF and TDP6 cohorts as expected. Surprisingly, while there was a tangible increase in pTrkB in OPCs in the TDP6 cohort compared to BDNF and aCSF cohorts, this result was not significant.

Fig. 4 – In TrkB-KO mice, there is no change in b) MBP expression; c) e) OD cell density or; d) OPC cell density upon TDP6 treatment. Reparative mechanisms are TrkB-receptor dependent. Labelling from source (a) not shown).

DISCUSSION

Re-myelination and OPC differentiation and proliferation is TrkB-dependent

While both BDNF and TDP6 activation of TrkB receptors induce simple remyelination events, only TDP6 induces OPC differentiation and proliferation in response to myelin destruction. Furthermore, TDP6 more potently activates TrkB, indicated by greater TrkB phosphorylation compared to BDNF/ control. The authors were able to expand TDP6 reparative capabilities to pre-clinical in vivo models, bolstering its potential as a therapeutic drug agent in progressive MS.

In TrkB-KO mice, TDP6 was unable to induce remyelination in ODs or differentiation of OPCs after insult, as indicated by no change in MBP expression versus control (See Fig. 4). TDP6 treatment exhibited no increase in either Hoechststained or CC1+-expressing ODs cell densities compared to aCSF control. Furthermore, TDP6 treatment did not cause proliferation and/or differentiation of OPCs, as there was no significant difference in cell count compared to control. These results contradict the findings seen in WT (TrkB-expressing) mice, thus establishing that the reparative processes require TDP6mediated TrkB-activation. Interestingly, the frequency of myelinated axons increases in TrkB-KO mice after TDP6 treatment. This discrepant finding may however be attributed to error when crossing Cre-recombinant lines (Cre recombinase is never fully expressed).

Fig. 2 – TDP6 treatment induces differentiation of OPC populations, but not necessary proliferation. a) b) TDP6 treatment is associated with greater cell counts in non-proliferative OD. c) TDP6 treatment is not associated with increases in OPC populations, but may promote their differentiation.

Interestingly, overall OD cell density increased despite being non-replicative cells, and thus TrkB targeting will obviously not induce OD proliferation. Increases in ODs can thus implicitly be attributed to TDP6-TrkB-mediated induction of OPC proliferation and differentiation. Thus, the lack of TDP6-induced increase in OPC cell density may suggest that both self-renewal and commitment processes were promoted in the OPC population. Evidence for OPC differentiation is inconclusive due to a non-significant increase in PDGFRa (OPC cell count), despite positive association between pTrkB expression and differentiation. This discrepancy can however be attributed to small sample size and may be ameliorated with repeated trials. Ultimately, the authors were able to show that the BDNF-mimetic, TDP6 interacts with TrkB receptors in the corpus callosum to drive myelin repair following white matter lesion. Fletcher et al. were able to show TDP6’s enhanced action in increasing myelin sheath thickness and driving OPC proliferation and differentiation. Perhaps most

promising, previous in vitro data was successfully may be offered as Fletcher et al.’s study was the replicated in vivo, showcasing TDP6’s potential as first to explore TDP6 in live animal models; the BBB a therapeutic drug agent in treating MS. may have been forgone to control for externalities, such that TPD6-induced in vivo CNS remyelination CRITICAL ANALYSIS events could be directly identified. If TDP6 is further pursued as a pharmacological solution, clinical The experimental design of the study was trials including the study of drug metabolism, comprehensive. Experiments mostly had proper routes of administration, and effects on wholecontrols, for example inclusion of normal chow HC body physiology must also be considered. during demyelination, and ICV delivery of aCSF (control) during TDP6/BDNF treatments. Due FUTURE DIRECTIONS diligence was performed in verifying demyelination protocol with CPZ against control, as well as if TrkB Immediate follow-up experiments primarily involve knockdown impacted CPZ-induced demyelination western blots to quantify changes in MBP, pTrkB, (which it did not). The data may have further pERK, and the OD/OPC markers (Olig2, PDGFRa, benefitted through a comparison of MBP CC1) at the protein level. One could expect to see expression in the HC (no CPZ/demyelination) and fainter anti-MBP bands (lower protein expression) TDP6/BDNF mice to determine a relative extent of in CPZ mice compared to HC, but no difference in remyelinated tissue. MBP bands between WT and TrkB-KO mice within CPZ and HC cohorts. ICV treatment with BDNF and Previous literature had also explored downstream TDP6 would reflect stronger MBP and pTrkB bands TrkB targets such as ERK, which is involved in vs saline control in the CPZ cohort. If consistent driving OPC differentiation. The mechanism behind with previous data, only TDP6-treated CPZ mice OPC differentiation was not however rigorously are expected to demonstrate increased protein explained in this manuscript. Thus, studying expression of Olig2, CC1, and particularly PDGFRa downstream TrkB pathways, particularly changes in if TDP6-TrkB truly mediates OPC differentiation. An ERK/pERK may elucidate and justify claims made in additional ERK1/2 western blot was performed by discussion. Generally, more quantitative methods, Wong et al., where ERK1/2 protein was upregulated such as measuring changes in protein expression during TrkB activation and differentiation in OD14. would bolster the data presented by Fletcher et al. Increase ERK phosphorylation would also be expected. Replicating these results would further Concerningly, unlike other BDNF/TrkB- justify the OPC differentiation in remyelination remyelination studies, the authors did not seem responses as hypothesized by this study. to account for endogenous BDNF. While CPZ treatment reduces BDNF protein levels in the Further in vivo studies could compare routes of corpus callosum9, basal BDNF levels in BDNF+/+ TDP6 administration and whole-body physiology. mice conferred greater myelin protection Not all routes of drug administration yield similar compared to BDNF+/- mice9. Similarly, BDNF+/- mice effects for the same drug, mostly due to metabolic are often used when studying TrkB pathways and discrepancies, and should be optimized for when OPC differentiation to avoid confound9,10. BDNF+/- developing a clinical TDP6 solution. TrkB is also mice were neither used nor addressed in Fletcher expressed peripherally in B cells, and BDNF et al.’s work, and thus basal BDNF data may have have been shown to drive B cell maturation and confounded results. proliferation17. Neurotrophins have also been associated with promoting B-cell tumour growth Furthermore, intracerebroventricular delivery of and survival18,19, and this potential adverse effect BDNF/TDP6 does not fully represent practical or must be accounted for when transitioning from conventional in vivo drug administration (ex. oral animal to human models. administration). The rationale for studying TDP6 TDP6’s purported ability to more readily cross was due to its improved ability to cross the BBB the BBB versus its BDNF counterpart should versus BDNF; this was completely bypassed by also be studied, perhaps using positron-emitted virtue of ICV delivery. Despite this flaw, leniency tomography (PET). An animal model could be fed 54

radioactive tracer versions of BDNF and TDP6, whose uptake may be visualized via PET, reflecting their ability to cross BBB. Stronger intracerebral TDP6 signals would be expected compared to BDNF, verifying TDP6â&#x20AC;&#x2122;s greater capability of crossing the BBB. This would justify TDP6 as a stronger drug candidate in the treatment of MS compared to BDNF.

R3 REFERENCES 1. Wang K, Song F, Fernandez-Escobar A, Luo G, Wang JH, Sun Y. The Properties of Cytokines in Multiple Sclerosis: Pros and Cons. Am J Med Sci. 2018 Dec;356(6):552-560. 2. Niehaus A1, Shi J, Grzenkowski M, Diers-Fenger M, Archelos J, Hartung HP, Toyka K, Brück W, Trotter J. Patients with active relapsing-remitting multiple sclerosis synthesize antibodies recognizing oligodendrocyte progenitor cell surface protein: implications for remyelination. Ann Neurol. 2000 Sep;48(3):362-71. 3. Huang JK, Fancy SPJ, Zhao C, Rowitch DH, Ffrench-Constant C, Franklin RJM. Myelin Regeneration in Multiple Sclerosis: Targeting Endogenous Stem Cells. Neurotherapeutics. 2011 Oct;8(4):650-658. 4. Barateiro A, Fernandes A. Temporal oligodendrocyte lineage progression: In vitro models of proliferation, differentiation and myelination. Biochem Biophys Acta. 2014 Sep;1843(9):19171929. 5. Xiao J1, Kilpatrick TJ, Murray SS. The role of neurotrophins in the regulation of myelin development. Neurosignals. 2009;17(4):265-76. 6. Chao MV. Neurotrophins and their receptors: a convergence point for many signalling pathways. Nat Rev Neurosci. 2003 Apr;4(4):299-309. 7. Xiao J, Wong AW, Willingham MM, van den Buuse M, Kilpatrick TJ, Murray SS. Brain-Derived Neurotrophic Factor Promotes Central Nervous System Myelination via a Direct Effect upon Oligodendrocytes. Neurosignals 2010;18:186–202. 8. Chan JR, Cosgaya JM, Wu YJ, Shooter EM. Neurotrophins are key mediators of the myelination program in the peripheral nervous system. Proc Natl Acad Sci U.S.A. 2001 Dec 4;98(25):1466114668. 9. VonDran MW, Singh H, Honeywell JZ, Dreyfus CF. Levels of BDNF Impact Oligodendrocyte Lineage Cells following a Cuprizone Lesion. J Neurosci. 2011;31(4):14182-14190. 10. Linker RA, Lee D, Demir S, Wiese S, Kruse N, Sigilenti I, Gerhardt E, Neumann H, Sendtner M, Luhder F et al. Functional role of brain-derived neurotrophic factor in neuroprotective autoimmunity: therapeutic implications in a model of multiple sclerosis. Brain. 2010;133(8):22482263. 11. Li Z, Theus MH, Wei L. Role of ERK 1/2 signaling in neuronal differentiation of cultured embryonic stem cells. Dev Growth Differ. 2006;48(8):513-523. 12. Wehrman T, He X, Raab B, Dukipatti A, Blau H, Garcia KC. Structural and mechanistic insights into nerve growth factor interactions with the TrkA and p75 receptors. Neuron. 2007 Jan 4;53(1):25-38. 13. Wong AW, Xiao J, Kemper D, Kilpatrick TJ, Murray SS. 2013. Oligodendroglial expression of TrkB independently regulates myelination and progenitor cell proliferation. J Neurosci. 2013 Mar 13;33(11):4947-4957. 14. Wong AW, Giuffrida L, Wood R, Peckham H, Gonsalvez D, Murray SS, Hughes RA, Xiao J. TDP6, a brain-derived neurotrophic factor-based trkB peptide mimetic, promotes oligodendrocyte myelination. Mol Cell Neurosci. 2014 Nov;63:132-40. 15. Fletcher JL, Wood RJ, Nguyen J, Norman EML, Jun CMK2, Prawdiuk AR, Biemond M, Nguyen HTH, Northfield SE, Hughes RA, Gonsalvez DG, Xiao J, Murray SS. Targeting TrkB with a BrainDerived Neurotrophic Factor Mimetic Promotes Myelin Repair in the Brain. J Neurosci. 2018 Aug 8;38(32):7088-7099. 16. Fletcher JL, Kondagari GS, Vite CH, Williamson P, Rosanne MT. Oligodendrocyte Loss Over the Disease Course in the Canine Model of the Lysosomal Storage Disease Fucosidosis. J Neuropathol Exp Neurl. 2014;73(6):536-547. 17. Hillis J, O’Dwyer M, Gorman AM. Neurotrophins and B-cell malignancies. Cell Mol Life Sci. 2016;73(1):41-56. 18. Pearse RN, Swendeman Sl, Li Y, Rafii D, Hempstead BL. A neurotrophin axis in myeloma: TrkB and BDNF promote tumor-cell survival. Blood. 2005;105(11):4429-4436. 19. Xia D, Li W, Zhang L, Qian H, Yao S, Qi X. RNA interference-mediated knockdown of brainderived neurotrophic factor (BDNF) promotes cell cycle arrest and apoptosis in B-cell lymphoma cells. Neoplasma. 2014;61(5):523-532.

Tackling Anxiety with Lavender: Neuronal Mechanisms of Linalool Meghan Lees Anxiety is the most widespread mental illness, and the development of safe and effective treatments is ongoing. Conventional pharmacological drugs, which are often prescribed, come with a host of potentially negative effects. In some cases, adverse effects associated with these treatments can be more harmful than helpful, so more traditional medicines have gained traction in current research due to their safe qualities and probable efficacy. Commonly used for anxiety-reducing purposes are essential oils in aromatherapy, such as lavender essential oil. A chief component of lavender oil, linalool, has consistently been shown to possess potent anxiolytic effects. In the study of focus, linalool odour was used to elicit these effects, as confirmed using classical behavioural tests for anxiety, the Light/Dark box test and elevated plus-maze test. Not only were anxiolytic effects of linalool odour observed, but the comparison to anosmic mice demonstrated that olfactory input is necessary. Further, by using a GABAA receptor benzodiazepine site antagonist, flumazenil, and 5-HT1A serotonin receptor antagonist, WAY100635, the authors concluded that linaloolâ&#x20AC;&#x2122;s anxiolytic effects are mediated through a GABAergic pathway, not a serotonergic pathway. Though this is suggested based on their results, it remains to be confirmed. As the authors mention, the 5-HT1A receptor and serotonergic system generally play a major role in anxiolytic effects, so it is rather surprising that their results are contradictory in the case of linalool. Likewise, its detailed mechanism of action has not been yet been elucidated. Linalool has promising potential for clinical applications, thus accumulating additional knowledge is important. Key words: linalool, anxiety, anxiolytic, mental health disorders, lavender, odour, benzodiazepine, flumazenil, 3-methylindole, WAY100635, behaviour, GABAA receptors, GABAergic, elevated plus maze, Light/Dark box, mice, anosmia, serotonergic, 5-HT1A receptor

INTRODUCTION Currently, mental health disorders are a prevailing concern, especially in the developed world. Approximately 43 million adults in the United States were diagnosed with a mental health disorder in 2014, with only an estimated 13% of those individuals receiving treatment (Asher, Gerkin, & Gaynes, 2017). Among mental health disorders, generalized anxiety disorder (GAD) is rampant, with about 5 â&#x20AC;&#x201C; 8% of US healthcare visits being associated with GAD and about one in nine individuals having experienced the disorder (Asher et al., 2017). The disorder primarily affects the youth and is characterized by constitutive and excessive fear or avoidance of perceived threats (Craske & Stein, 2016). Anxiety disorders can greatly impair oneâ&#x20AC;&#x2122;s ability to function or hinder quality of life, and they may exist comorbidly with substance abuse or mood disorders, such as depression, hence effective treatments are highly sought after (Craske & Stein, 2016). Typical treatments for anxiety disorders, including GAD, social anxiety disorder (SAD), and panic disorder with/without agoraphobia (PDA), consist of both pharmacotherapy and psychotherapy (Bandelow, Michaelis, & Wedekind, 2017). That being said, there is substantial undertreatment of anxiety disorders, perhaps due to social or even self-stigmatization (Ociskova et al., 2018). Among treatment methods, the most common anxiolytic drugs include selective serotonin reuptake inhibitors (SSRIs), selective serotonin norepinephrine reuptake inhibitors (SNRIs), azapirones, tricyclic antidepressants (TCSs), pregabalin, and benzodiazepines (BDZs) (Bandelow et al., 2017). Nonetheless, as with many drugs, side effects are inevitable. Among these are nausea, nervousness, insomnia, sedation, sexual dysfunction, impaired motor function, and a slew of other unwanted symptoms (Bandelow et al., 2017). On occasion, these adverse effects can be intolerable, and thus, development of new treatment methods or drugs is crucial.

with minimal or mild side effects, if used improperly, making them attractive in comparison to their pharmacological counterparts. These essential oils are used in multiple facets, although their use in olfactory and psycho-aromatherapy are of emphasis (Ali et al., 2015). Typical oils used to treat anxiety and stress-related issues are derived from flowers, such as geranium, ylang ylang, chamomile, clary sage, and lavender (Ali et al., 2015). A common chemical constituent of these concentrated aromatic extracts is linalool, a natural terpene alcohol with two enantiomeric forms, coriandrol and licareol (Aprotosoaie, HÄ&#x192;ncianu, Costache, & Miron, 2014). Apart from its numerous physiological effects, linalool has potent effects in the central nervous system, including analgesic, anxiolytic, and sedative activity (Aprotosoaie et al., 2014). Lavender, containing a high concentration of linalool, has been a focus of various studies on anxiolytic-like effects. Study methods have ranged from the Geller conflict test, social interaction test, open field test, light/ dark test, and elevated plus-maze task in different rodent models (Sousa, Hocayen, Andrade, & Andreatini, 2015). Results of previous studies confirm that lavender and its major compound, linalool, indeed mediate anxiolytic effects. It has also been established that linalool effects are dependent on dosage and exposure time (V. M. Linck et al., 2010). In a study conducted by Linck et al. (2010), inhalation of 3% linalool induced anxiolytic effects in mice, while increasing social interaction and decreasing aggressive behaviour. However, higher concentrations did impose amnesic effects, impairing memory, as per the step down inhibitory avoidance test (V. M. Linck et al., 2010). Despite the ascertained anxiolytic effects of linalool and lavender essential oil, the specific neurobiological mechanisms and pathways that are involved are not well understood. Some debate and contradictions do exist between studies, and therefore, the area requires more attention.

A recently published study by Harada et al. (2018) While pharmaceuticals play a key role in the examines the anxiolytic effects of linalool odour treatment of anxiety, traditional medicines or inhalation through the use of classical anxiety complementary alternative therapies are proven tests of behaviour, in mice. Using the Light/Dark effective. Among more traditional therapies, box test and elevated plus-maze test, the authors aromatherapy has been one gaining momentum. were able to confirm the anxiolytic effects of the Plant-derived therapeutic agents are associated odour (Harada, Kashiwadani, Kanmura, & Kuwaki, 58

2018). Due to mice’s inherent aversion to bright areas and their exploratory behaviour, along with thigmotaxis, these tests are useful for analyzing anxiety in rodents (Wei, Yang, Wang, & Wu, 2007). Additionally, to address the lack of knowledge on the neuronal mechanisms underlying linalool’s effects, they induced anosmia in certain mice and did not detect the same effects (Harada et al., 2018). Moreover, it was found that olfactory-induced effects were mediated by the BDZ-binding site of gamma-aminobutyric acid (GABA)A receptors, based on the attenuation of anxiolytic effects with the site’s antagonist, flumazenil (Harada et al., 2018). These findings may be applicable to further development of effective anxiety treatments, a substantial necessity, given the prevalence of anxiety disorders. Furthermore, the study serves as meaningful contribution to standing information and a foundation for future research. MATERIALS AND METHODS

air simply had chambers with untreated filter paper (Harada et al., 2018). Classical Behavioural Tests for Anxiety

Light/Dark Box Test Video footage of mice behaviour in a partitioned box with a light and dark compartment was used to measure the number of entries into the light box and amount of time spent in the light box (Harada et al., 2018). Elevated Plus-Maze (EPM) Test Similarly, video footage of mice behaviour on a contraption consisting of two open arms and two closed arms (with walls) in the shape of a plus, elevated off the floor, was used to measure entries into the open arms and time spent in the open arms (Harada et al., 2018). Accelerated Rotarod Test

Model Organisms

To test for motor coordination and rule out deficits, the time that mice remained on a rotating bar with C57BL/6N wild type male mice were used, and living steady increasing speed was measured. conditions of the animals and experimentation were controlled for (Harada et al., 2018). Anosmia Test Drugs

An olfactory habituation/dishabituation test was performed to verify anosmia in mice treated with Cercine®, containing the BDZ, diazepam, was 3-MI. Anosmic mice were either placed in a cage used as an established anxiolytic drug for positive with a cotton swab soaked in 20 mL of water or 20 control. Flumazenil, a specific antagonist for the mL of linalool. The number of approaches and time BDZ-binding site of GABAA receptors (GABAARs) spent sniffing cotton swabs was recorded. was used to inhibit binding to the BDZ site, and WAY100635, an antagonist for the serotonin 1A receptor (5-HT1AR). A dilution of Tween80 in MAJOR RESULTS saline solution was used as a vehicle (VEH) for the aforementioned drugs. 3-methylindole (3-MI) was The primary results of the recent investigation used to induce anosmia in mice, by intraperitoneal conducted by Harada et al. (2018) confirmed the injection. Corn oil was used as the VEH for 3-MI anxiolytic effects of linalool odour, as previously evidenced, as well as suggested novel findings (Harada et al., 2018). that linalool-odourized air functions via olfactory input and is mediated by BDZ-sensitive GABAARs. Linalool Inhalation To test the anxiolytic effects of the linalool odour, classical anxiety-related behavioural tests were Exposure to linalool odour was facilitated by placing employed, involving the Light/Dark box test and an acryl cage in an odour chamber containing the EPM test. Reduced anxiety in mice is depicted linalool-treated filter paper with ten-fold increases by more entries into or time spent in the light in linalool doses from 0 – 2,000 mL. Mice were compartment of the Light/Dark box (Harada et exposed for 30 minutes. Mice not exposed to the al., 2018). Likewise, less anxious mice will exhibit 59

a greater number of entries and time spent out in Figure 1. Light/Dark box test for anxiety behaviour in mice the open arms of the EPM apparatus (Harada et treated with negative control (saline), positive control (diazepam), Tween diluent, 1% linalool, or 3% linalool. al., 2018). Anxiolytic Effects of Linalool Odour Firstly, the authors compared the anxiolytic effects between three groups of mice; one was exposed to linalool-odourized air, another exposed to odourless air (control group), and the last injected with the BDZ, diazepam (positive control). Based on the Light/Dark box and EPM tests, mice that inhaled linalool odour showed a marked increase in the time spent in and number of entries into both the light box and open arms (Harada et al., 2018). Harada et al. not only support the anxiolytic effects of linalool, but also the fact that it is dose-dependent and does not hamper muscle coordination, as previously determined by two previous studies correlating linalool and anxiety attenuation (V. M. Linck et al., 2010; Souto-Maior et al., 2011). As portrayed in Figure 1, Linck et al. (2010) were able to show that a particular concentration of linalool induced anxiolytic effects in mice, as demonstrated in the standard Light/Box test. Souto-Maior et al. (2011) established that linalool oxide, an alcohol formed from linalool, produces anxiolytic effects comparable to diazepam. In yet another study, Tsang et al. (2013) portray the anxiolytic outcomes of linalool-containing lavender oil using the EPM test and open field test. They compared the effects of lavender oil to a tranquilizing drug, chlordiazepoxide, and found that the two worked similarly in reducing anxiety (Tsang et al., 2013). These works are supported by the findings of Harada et al. (2018).

(A) Amount of time spent (s) in the light zone. (B) Number of crossings into the light compartment. White bars depict injection of substances, while grey bars depict inhalation administration. | Figure origin: Linck et al. (2010). Effects of inhaled Linalool in anxiety, social interaction and aggressive behavior in mice. Phytomedicine, 17(8), 679â&#x20AC;&#x201C;683.

Linalool Odourâ&#x20AC;&#x2122;s Anxiolytic Effects Require Olfaction Apart from the increase in exploratory behaviour in both the Light/Dark box and EPM tests, indicating reduced anxiety, Harada et al. (2018) determined that these effects were elicited by olfactory input of linalool odour. Anosmia was induced through destruction of olfactory epithelium with 3-MI and affirmed by the olfactory habituation/ dishabituation test (Tsang et al., 2013). Anosmic mice exposed to linalool odour showed no signs of anxiolytic effects by the Light/Dark box nor EPM tests (Harada et al., 2018). The results of this experiment are represented by Figure 2, which displays mice behaviour in the Light/Dark box test. The effects were analogous for the EPM test, with no significant differences in 3-MI-administered anosmic mice exposed to linalool compared to the control. As will be further discussed, not all studies have produced the same results, as some indicate anosmia has no impact on the anxiolytic effects.

Figure 2. Light/Dark box test for anxiety behaviour in mice administered corn oil vehicle (VEH) or anosmia-inducing 3-MI. (A) Amount of time spent (s) in the light zone. (B) Number of entries into the light box. The control groups were exposed to odourless air, while the linalool groups were exposed to 200 mL of linalool. | Figure origin: Harada et al. (2018). Linalool Odor-Induced Anxiolytic Effects in Mice. Frontiers in Behavioral Neuroscience, 12.

Neuronal Circuit Involved in Anxiolytic Effects of Linalool Odour 60

As stated, BDZs and azapirones are common drugs for anxiety treatment, and they function through the neurotransmitter receptors, GABAARs and 5-HT1AR (Bandelow et al., 2017). By injecting groups of mice with inhibitors for these receptors, the authors were able to conclude the receptormediated pathways through which linalool may function. Flumazenil, a BDZ-binding site antagonist for GABAARs, and WAY100635, an antagonist of the 5-HT1AR, were injected into separate groups, then the typical EPM test was performed (Harada et al., 2018). As seen in Figure 3, the results suggest that linalool odour works through the GABAARs’ BDZ sites to produce anxiolytic effects because mice administered flumazenil and exposed to linalool showed abolishment of reduced anxiety (Harada et al., 2018). Interestingly, a prior study conducted by Cline et al. (2008) did not obtain the same results when treating mice with flumazenil and linalool. As seen in Figure 4, there is no significant decrease in the ratio of time spent in open arms compared to the total, implying linalool-induced anxiolysis is not mediated by GABAARs (Cline M et al., 2008). Despite this apparent contradiction, an investigation carried out by Milanos, Elsharif, Janzen, Buettner, and Villmann (2017) supports the current findings of Harada et al. (2018). As linalool is metabolized in the body, its derivatives work in a neurotropic pathway through GABAARs in an allosteric manner, signifying that linalool works in the GABAergic pathway (Milanos, Elsharif, Janzen, Buettner, & Villmann, 2017).

Figure 3. EPM test for anxiety behaviour in mice administered Tween80 in saline (VEH), flumazenil (Flu), or WAY100635 (WAY). (A) Amount of time spent (s) in open arms. (B) Number of entries into open arms. The control groups were exposed to odourless air, while the linalool groups were exposed to 200 mL of linalool. | Figure origin: Harada et al. (2018). Linalool Odor-Induced Anxiolytic Effects in Mice. Frontiers in Behavioral Neuroscience, 12.

Figure 3. EPM test for anxiety behaviour in mice treated with Tween vehicle (control), linalool, positive control (midazolam), and flumazenil-linalool. Mean ratio of time spent in open arms versus total time (s). | Figure origin: Cline et al. (2008). Investigation of the anxiolytic effects of linalool, a lavender extract, in the male Sprague-Dawley rat. AANA Journal, 76(1), 47–52.

CONCLUSIONS AND DISCUSSION In the present reviewed study by Harada et al. (2018), several major conclusions were reached. Firstly, the authors establish that linalool indeed displays anxiolytic properties, without causing motor impairment and working in a dosedependent manner (Harada et al., 2018). In addition, by generating anosmic mice, lacking a sense of smell, they were able to conclude that linalool requires olfactory input to have an effect on anxiety reduction (Harada et al., 2018). Lastly, the authors’ final protocol, involving a group of mice treated with a GABAAR BDZ-site antagonist, proposed that linalool works through the BDZ site of GABAARs to induce anxiolysis (Harada et al., 2018). These outcomes bear meaningful relevance to various scientific fields, especially behavioural neuroscience. The culmination of knowledge throughout the years has been commendable, however, we still have much to understand about disorders of the mind. With the increased pace of life, it seems that mental illness has been on the rise. Also growing, is the body of research on said disorders. Anxiety disorders are among the most pervasive, and they are debilitating for some (Bandelow et al., 2017). Along with clinical or chronic anxiety disorders, the feeling of acute anxiety and stress can be similarly harmful or have the potential to escalate. Treatments for such

disorders are available, although research continues in order to foster improved efficacy, availability, and reduction in associated harm (Craske & Stein, 2016). As well, some patients are opposed to using pharmacological drugs, or they may not have the financial means or access to psychotherapy.

using a blocker of the 5-HT1AR, it was concluded that this specific pathway is likely not involved in linalool’s effects (Harada et al., 2018). Thus, further studies involving linalool’s anxiolytic effects should involve the proposal that linalool’s effects are mediated by BDZ-responsive GABAARs.

With that, the quest for effective alternative methods of treatment is important. Herein, Harada et al. (2018) contribute to the knowledge on linalool as an anxiolytic agent. Linalool has been characterized to possess anxiolytic qualities, and it has long been used in traditional medicines around the world (Aprotosoaie et al., 2014). The experiments of Harada et al. (2018) clearly depicted the anxiolytic effects of linalool odour in mice, which overturn Cline et al.’s (2008) inability to demonstrate its effects. Though there is consensus among the scientific community that linalool induces anxiolysis, Harada et al. (2018) sought to fill the gap in the knowledge of neuronal pathways involved in its mechanisms of action. Primarily, they wished to look at the typical pathways targeted with anxiety drugs, including the GABAergic and serotonergic routes of neurotransmission (Bandelow et al., 2017).

The recently published research by Harada et al. (2018) possesses value in this field, as it serves as a basis for potential clinical uses of linalool as a treatment. Linalool may have applications in treating acute, mild, or chronic, severe anxiety, or in certain scenarios in which anxiety may be affiliated, such as stress-inducing medical operations. Knowing the molecular mechanisms of the compound are especially important to investigate its efficacy in different clinical applications, as well as better infer adverse interactions it may have with other drugs.

While previous studies involved assessing the effects of inhaled linalool vapour on alleviating anxiety, the clear indication that olfactory input is required was not demonstrated (V. M. Linck et al., 2010; Takahashi et al., 2011). Harada et al. (2018) managed to confirm this using a novel protocol to show that mice without olfaction did not experience reduced anxiety upon exposure to linalool odour. This is in opposition to previous findings, in which zinc-induced anosmic mice were tested for anxiety after linalool exposure by the marble burying test (Chioca, Ferro, et al., 2013).

CRITICAL ANALYSIS The study under consideration by Harada et al. (2018) instilled specific pre-established or assumed points, while it proposed a novel mechanism of action for linalool. The majority of original studies and review papers are in favour of the notion that linalool indeed has anxiolytic properties. Whereas two study were unable to observe its anxiolytic effects, most studies have been able to reproduce these findings (Cline M et al., 2008; dos Santos et al., 2018). Among the papers that corroborate these results, a variety of methods were used to determine anxious behaviour; those being, the EPM task, Light/Dark box, marble burying, open field task, grooming, or defaecation behaviour. Certain behavioural tests may be more reliable indicators of anxiety-like behaviour, and due to the differences in behaviour exhibited in each test, it is difficult to directly compare the results of some studies. A strength of Harada et al.’s (2018) study is that they use a variety of protocols to substantiate their conclusions, such as their use of both the Light/ Dark box and EPM test. Experiments by dos Santos et al. (2018) support the fact that linalool does not impair motor functions, although, they did not observe the anxiolytic effect of linalool, which was administered intraperitoneally. The researchers argued that this is the potential reason they were unable to see anxiolytic behaviour in their treated mice, as most studies use the inhalation method

In contrast to Cline et al.’s (2008) study, Harada et al. (2018) were able to demonstrate that pretreatment with flumazenil, a blocker of the BDZ site of GABAARs, eliminated the effects of linalool exposure. Although, the mechanism by which linalool functions in this pathway has yet to be elucidated. It is suggested that linalool eventually works through allosteric activation of these receptors, hence this should be studied more in depth (Milanos et al., 2017). Upon testing the effects of linalool on the serotonergic pathway, by 62

along with higher doses or exposure to linalool Harada and co-authors. Yet another study reaches (dos Santos et al., 2018). an essentially opposite conclusion, based on their findings (Chioca, Ferro, et al., 2013). Chioca et al. This bring us to a deduction made by Harada et (2013) assessed the role of GABAA and 5-HT1A al. (2018) that linalool vapour requires olfactory receptors in lavender essential oil’s anxiolytic-like senses to induce anxiolytic effects, based on effects by using picrotoxin to inhibit GABAARs the abolishment of linalool-induced anxiolytic and WAY100635 as a 5-HT1AR antagonist. From effects following olfactory epithelium deprivation their results, it was concluded the serotonergic by 3-MI. Though this may be true for linalool system, likely involving the 5-HT1AR, is important odour, a retrospective case series, clinical trial in modulating the effects of lavender oil, but study, and double-blind study show that linalool- that the BDZ-responsive GABAAR is not needed concentrated lavender oil capsules administered (Chioca, Ferro, et al., 2013). Harada et al.’s (2018) orally can have corresponding anxiolytic outcomes conclusion was practically the inverse, thus it is in humans (Bradley, Brown, Chu, & Lea, 2009; difficult to know the definitive answer. Both groups Fißler & Quante, 2014; Woelk & Schläfke, 2010). used WAY100635 as a 5-HT1AR antagonist, but Consequently, the route of administration and the each group used a different GABAAR antagonist, pathways through which linalool works may not flumazenil or picrotoxin. Chioca et al. (2013) be limited to olfactory input, though most studies performed behavioural tests of anxiety along with using rodent models use this route of exposure. molecular assays to assess the neurotransmitter Even within rodent studies, there is inconsistency in systems involved in linalool’s effect’s, whereas the findings, as another study using zinc to induce Harada et al. (2018) based their conclusions on anosmia in mice concludes that anxiolytic effects behavioural tests. Consequently, the authors of linalool inhalation, as observed in the marble should perform further tests to clarify which burying task, are not impaired in the anosmic neurotransmission pathways in fact participates in group (Chioca, Antunes, Ferro, Losso, & Andreatini, the effects of linalool. 2013). Based on this particular observation, the olfactory system would be deemed insignificant FUTURE DIRECTIONS for the effects of linalool. Harada et al. (2018) were meticulous in their methodology to make sure Based on the critical analysis, there remains gaps 3-MI-administered mice were indeed rendered in the knowledge of linalool’s mechanism of action. anosmic, making their findings more reputable. For instance, it is plausible that linalool functions An important consideration in studying the in two or more parallel pathways, such as in both implications of anosmia is that olfactory deficits the GABAergic and serotonergic pathways, or in themselves can elicit anxiety-like behaviour in routes other than olfaction, however, future studies mice, which may confound results (Glinka et al., are necessary to elucidate this. 2012). Because there is some incongruity in which method of linalool administration is most efficient, The first point that requires additional clarification research should be conducted to compare the is whether linalool inhalation requires olfactory options at hand. input to exhibit anxiolytic-like effects. As of now, anosmic mice, produced by olfactory epithelium Based on the results using flumazenil, it was damage using zinc or 3-MI, have been used to infer concluded that linalool’s anxiolytic effects are the importance of olfaction in linalool’s execution. mediated by the GABAergic system, and more As mentioned, the sense of smell is important specifically, through BDZ-sensitive GABAARs for animals, and thus, lesions and deficits in this (Harada et al., 2018). This is possibly the most modality can prompt a range of behavioural controversial of the findings, as several papers changes in an animal, including anxiety. Due to pose discrepancies with this conclusion. First, Cline this variable, the results may be swayed, leading et al. (2008) not only failed to observe anxiolytic to misinterpretation. Perhaps a more important effects of linalool, but they were also unable to experiment to conduct is a comparison of delivery support their hypothesis that linalool affects the methods, including inhalation (vapour exposure), GABAA receptor, a major inference settled by oral administration, dermal absorption, and 63

intraperitoneal administration. Inhalation of linalool odour has been the traditional method of use in aromatherapy, and its effects in mice have typically relied on inhalation, so it may be hypothesized that inhalation is indeed the most simple, efficacious, or safe method of administration. To examine the effects of each delivery method on anxiety, the authors may perform behavioural analysis on mice to analyze anxiety-related behaviours, including the open field exploration, elevated plus-maze, Light/Dark box, and social interaction tests (Lezak, Missig, & Carlezon Jr, 2017). Authors may also consider the use of a zero maze test, rather than EPM, in order to solely infer anxiety-like behaviour without the confound of decision-making. In addition to behavioural tests, physiological screening for anxiety biomarkers may complement (Maron & Nutt, 2017). We would expect the most effective means of administration to be associated with the greatest decrease in indicators of anxiety. In order to advance linalool’s potential use in a clinical setting, the mechanisms of action must be expounded. As most studies on linalool and anxiolytic effects have stated, further studies are fundamental to understand the detailed molecular targets of linalool in the nervous system. Seemingly, several studies have concluded conceivable pathways in which linalool functions, but the gap in understanding remains as different papers deliver conflicting results. A similar experiment to one using a medicinal plant bioflavonoid, rutin, could be performed using linalool exposure, in which the effects of flumazenil, a BDZ-GABAAR antagonist, are compared to picrotoxin, a chloride channel GABAAR antagonist (Hernandez-leon, González-trujano, & Fernández-guasti, 2017). This experiment would contribute to our understanding of whether or not the GABAARs and/or the BDZ site modulate the anxiolytic effects of linalool. With these treatments, researchers may employ standard behavioural tests. If blocking GABAergic transmission using these drugs affects the anxiolytic-like effects of linalool exposure, the experimenters would conclude that linalool works through the GABAA BDZ site, chloride channel, or neither.

of tests and assays to do so. Selective antagonists of the 5-HT1AR, WAY100365 or WAY100135, could be used to replicate behavioural tests of linalool and anxiety to inform whether the serotonergic system is key in mediating linalool’s actions. As well, a serotonin transporter (SERT) assay may be performed, and based on the extent to which linalool blocks [H3]-Citalopram (SSRI) binding to SERT, the researchers may confirm or deny linalool’s actions in the serotonergic pathway (López, Nielsen, Solas, Ramírez, & Jäger, 2017). Finally, serotonin concentrations may be compared between control and linalool-treated groups to further support or reject its role in serotonergic neurotransmission, depending on whether it increases or decreases/ does not change serotonin levels, respectively. Another point for further study is based on a transient statement made by Harada et al. (2018) in which they deduce that effects of linalool odour produced anxiolytic rather than sedative effects, based on the fact that total distance moved by mice was not affected by linalool. In other studies, linalool has been shown to induce sedative effects in mice (V. de M. Linck et al., 2009). Using the notions of dose-dependency and exposure time, the effects of linalool on sedation should be investigated, by looking at sleep time and locomotor activity. Understanding the dose-response relationship and effects elicited by linalool may better inform its use for different purposes. As an anxiolytic treatment, sedative effects may not be desired, so comparing sedative and anxiolytic effects may importantly allude to the threshold differences for each effect. Though considerable research has been conducted to investigate linalool’s role in the nervous system, and especially its role in reducing anxiety-like behaviour, there is still room for understanding its mechanisms of action in greater depth.

To confirm whether linalool works through the serotonergic system, and more specifically through the 5-HT1AR pathway, researchers may use a variety 64

REFERENCES 1. Ali, B., Al-Wabel, N. A., Shams, S., Ahamad, A., Khan, S. A., & Anwar, F. (2015). Essential oils used in aromatherapy: A systemic review. Asian Pacific Journal of Tropical Biomedicine, 5(8), 601–611. https://doi.org/10.1016/j.apjtb.2015.05.007 2. Aprotosoaie, A. C., Hăncianu, M., Costache, I.-I., & Miron, A. (2014). Linalool: a review on a key odorant molecule with valuable biological properties. Flavour and Fragrance Journal, 29(4), 193–219. https://doi.org/10.1002/ffj.3197 3. Asher, G. N., Gerkin, J., & Gaynes, B. N. (2017). Complementary Therapies for Mental Health Disorders. Medical Clinics of North America, 101(5), 847–864. https://doi.org/10.1016/j. mcna.2017.04.004 4. Bandelow, B., Michaelis, S., & Wedekind, D. (2017). Treatment of anxiety disorders. Dialogues in Clinical Neuroscience, 19(2), 93–107. 5. Bradley, B. F., Brown, S. L., Chu, S., & Lea, R. W. (2009). Effects of orally administered lavender essential oil on responses to anxiety-provoking film clips. Human Psychopharmacology: Clinical and Experimental, 24(4), 319–330. https://doi.org/10.1002/hup.1016 6. Chioca, L. R., Antunes, V. D. C., Ferro, M. M., Losso, E. M., & Andreatini, R. (2013). Anosmia does not impair the anxiolytic-like effect of lavender essential oil inhalation in mice. Life Sciences, 92(20–21), 971–975. https://doi.org/10.1016/j.lfs.2013.03.012 7. Chioca, L. R., Ferro, M. M., Baretta, I. P., Oliveira, S. M., Silva, C. R., Ferreira, J., … Andreatini, R. (2013). Anxiolytic-like effect of lavender essential oil inhalation in mice: Participation of serotonergic but not GABAA/benzodiazepine neurotransmission. Journal of Ethnopharmacology, 147(2), 412–418. https://doi.org/10.1016/j.jep.2013.03.028 8. Cline M, Taylor JE, Flores J, Bracken S, McCall S, & Ceremuga TE. (2008). Investigation of the anxiolytic effects of linalool, a lavender extract, in the male Sprague-Dawley rat. AANA Journal, 76(1), 47–52. 9. Craske, M. G., & Stein, M. B. (2016). Anxiety. The Lancet, 388(10063), 3048–3059. https://doi. org/10.1016/S0140-6736(16)30381-6 10. dos Santos, É. R. Q., Maia, C. S. F., Fontes Junior, E. A., Melo, A. S., Pinheiro, B. G., & Maia, J. G. S. (2018). Linalool-rich essential oils from the Amazon display antidepressant-type effect in rodents. Journal of Ethnopharmacology, 212, 43–49. https://doi.org/10.1016/j.jep.2017.10.013 11. Fißler, M., & Quante, A. (2014). A case series on the use of lavendula oil capsules in patients suffering from major depressive disorder and symptoms of psychomotor agitation, insomnia and anxiety. Complementary Therapies in Medicine, 22(1), 63–69. https://doi.org/10.1016/j. ctim.2013.11.008 12. Glinka, M. E., Samuels, B. A., Diodato, A., Teillon, J., Mei, D. F., Shykind, B. M., … Fleischmann, A. (2012). Olfactory Deficits Cause Anxiety-Like Behaviors in Mice. Journal of Neuroscience, 32(19), 6718–6725. https://doi.org/10.1523/JNEUROSCI.4287-11.2012 13. Harada, H., Kashiwadani, H., Kanmura, Y., & Kuwaki, T. (2018). Linalool Odor-Induced Anxiolytic Effects in Mice. Frontiers in Behavioral Neuroscience, 12. https://doi.org/10.3389/ fnbeh.2018.00241 14. Hernandez-leon, A., González-trujano, M. E., & Fernández-guasti, A. (2017). The anxiolyticlike effect of rutin in rats involves Gabaa receptors in the basolateral amygdala. Behavioural Pharmacology, 28(4), 303–312. https://doi.org/10.1097/FBP.0000000000000290 15. Lezak, K. R., Missig, G., & Carlezon Jr, W. A. (2017). Behavioral methods to study anxiety in rodents. Dialogues in Clinical Neuroscience, 19(2), 181–191. 16. Linck, V. de M., Silva, A. L. da, Figueiro, M., Piato, A. L., Herrmann, A. P., Birck, F. D., … Elisabetsky, E. (2009). Inhaled linalool-induced sedation in mice. Phytomedicine: International Journal of Phytotherapy & Phytopharmacology, 16(4), 303-. 17. Linck, V. M., da Silva, A. L., Figueiró, M., Caramão, E. B., Moreno, P. R. H., & Elisabetsky, E. (2010). Effects of inhaled Linalool in anxiety, social interaction and aggressive behavior in mice. Phytomedicine, 17(8), 679–683. https://doi.org/10.1016/j.phymed.2009.10.002

18. López, V., Nielsen, B., Solas, M., Ramírez, M. J., & Jäger, A. K. (2017). Exploring Pharmacological Mechanisms of Lavender (Lavandula angustifolia) Essential Oil on Central Nervous System Targets. Frontiers in Pharmacology, 8. https://doi.org/10.3389/fphar.2017.00280 19. Maron, E., & Nutt, D. (2017). Biological markers of generalized anxiety disorder. Dialogues in Clinical Neuroscience, 19(2), 147–158. 20. Milanos, S., Elsharif, S. A., Janzen, D., Buettner, A., & Villmann, C. (2017). Metabolic Products of Linalool and Modulation of GABAA Receptors. Frontiers in Chemistry, 5. https://doi. org/10.3389/fchem.2017.00046 21. Ociskova, M., Prasko, J., Vrbova, K., Kasalova, P., Holubova, M., Grambal, A., & Machu, K. (2018, January 26). Self-stigma and treatment effectiveness in patients with anxiety disorders &ndash; a mediation analysis. https://doi.org/10.2147/NDT.S152208 22. Sousa, D. P. de, Hocayen, P. de A. S., Andrade, L. N., & Andreatini, R. (2015). A Systematic Review of the Anxiolytic-Like Effects of Essential Oils in Animal Models. Molecules, 20(10), 18620–18660. 23. Souto-Maior, F. N., Carvalho, F. L. de, Morais, L. C. S. L. de, Netto, S. M., de Sousa, D. P., & Almeida, R. N. de. (2011). Anxiolytic-like effects of inhaled linalool oxide in experimental mouse anxiety models. Pharmacology Biochemistry and Behavior, 100(2), 259–263. https://doi. org/10.1016/j.pbb.2011.08.029 24. Takahashi, M., Satou, T., Ohashi, M., Hayashi, S., Sadamoto, K., & Koike, K. (2011). Interspecies comparison of chemical composition and anxiolytic-like effects of lavender oils upon inhalation. Natural Product Communications, 6(11), 1769–1774. 25. Tsang, H. W. H., Lo, S. C. L., Chan, C. C. H., Ho, T. Y. C., Fung, K. M. T., Chan, A. H. L., & Au, D. W. H. (2013). Neurophysiological and behavioural effects of lavender oil in rats with experimentally induced anxiety: Lavender oil on anxiety of rats. Flavour and Fragrance Journal, 28(3), 168–173. https://doi.org/10.1002/ffj.3148 26. Wei, X.-Y., Yang, J.-Y., Wang, J.-H., & Wu, C.-F. (2007). Anxiolytic effect of saponins from Panax quinquefolium in mice. Journal of Ethnopharmacology, 111(3), 613–618. https://doi. org/10.1016/j.jep.2007.01.009 27. Woelk, H., & Schläfke, S. (2010). A multi-center, double-blind, randomised study of the Lavender oil preparation Silexan in comparison to Lorazepam for generalized anxiety disorder. Phytomedicine, 17(2), 94–99. https://doi.org/10.1016/j.phymed.2009.10.006

The Effects of Yoga Nidra and Seated Meditation on Stress, Anxiety, Pain, and Depression Rebecca S. F. Levin Yoga Nidra and seated mindfulness meditation have sparked the interest of many neuroscientists in the last few years, as researchers have started to link a connection between these practices and mental well-being. In a study conducted by Ferreira-Vorkapic et. al (2018), the effects of Yoga Nidra and seated mindfulness meditation were assessed based on the factors of depression, anxiety, and stress on a group of 60 college professors. The results of this study concluded that those who practiced either activity showed an increase in mental well-being overall compared to the control, who did not alter their routines. However, those who practiced Yoga Nidra yielded better results than those who practiced seated meditation with regards to the anxiety factor. Rates of anxiety and depression have been on the rise recently. Though many medications have been developed to help people live with these disorders, they have shown to be costly and often lead to dependence. Thus, researchers are working on a variety of therapies to work in conjunction with or in placement of drugs. The results of this study and studies like it provide hope for those suffering with anxiety and depression, as these practices may give them a coping method that, unlike drugs and other developed therapies, will not result in dependence, is cost effective, and can be practiced in the comfort of their own home. Ironically, very little is currently known regarding the mechanisms behind the reported positive effects that yoga and meditation have on the brain and mental health, despite the fact that they are both very ancient practices. Key words: Yoga Nidra, seated meditation, depression, yoga, stress, pain, anxiety, stressinduced, mindfulness, mind-body

INTRODUCTION

Background Mindfulness meditation is more than learning how to be aware of one’s sensory input, thoughts and emotions; it is also the ability to control psychological and physiological reactions to these stimuli (Hölzel et. al, 2015). Mindfulness meditation has been shown to cause physical changes in specific brain regions in a number of studies, as described in an article by Hölzel et. all (2015). In particular, changes can be seen in areas of the prefrontal cortex and amygdala (emotional regulation), sensory cortices and insula (bodily awareness), and the hippocampus (learning and memory), among others (Hölzel et. al, 2015).

mouse model was used to show how social defeat stress lead to depression-like phenotypes in young mice. Another meta-analysis was conducted that gave an overview of various brain region alterations, endocrine hormones changes, and effects on the immune system that are shown to be caused by prolonged stress, and that ultimately result in depression (Cui et. al, 2015).

Chronic pain is often comorbid with depression, as they are both risk factors for each other (Chen et. al, 2016; Daskalaki et. al, 2017). The link between the two was studied and described in a group of elderly test subjects, as the comorbidity is commonly found in elderly people (Daskalaki et. al, 2017). The comorbidity is thought to be due, at least in part, to similar areas of brain activity Through this practice of regulating mental that are involved with both prolonged pain and responses to present situations, and through the depression (Doan, 2015). physical changes that the brain has been found to undergo during practice, it has been shown that Researchers are attempting to use single mindfulness meditation is effective in reducing and treatment solutions, such as the administration of managing stress (Hölzel et. al, 2015; Pascoe et. al, “cannabinomimetic” drugs to treat both pain and 2017). depression simultaneously, as the endocannabinoid system has been found to be involved in both Yoga Nidra is a meditative practice where an conditions (Chen et. al, 2016) individual experiences an intermediate state between wakefulness and sleep (Ferreira-Vorkapic Since stress and pain may both be risk factors for et. al, 2018). Unlike seated meditation, this form of the development of depression, which is currently yoga is practiced in the supine position. According the most common disability (Daskalaki et. al, to research described in an article by Agrawal et. 2017), finding more accessible, cost effective, and al (2011), the practice of Yoga Nidra can lead to less invasive methods of treatment are extremely the stimulation of the pituitary gland to release important. Yoga Nidra and mindfulness meditation endorphins and encephalin, which are known as may therefore become effective coping techniques our bodies’ natural painkillers. for individuals who experience stress and physical pain, as studies have displayed that they can effectively decrease the likelihood of developing Relevance depression, while also modulating stress and pain. Mood disorders, such as depression and anxiety have been becoming more and more prevalent, which is why research on the subjects has been accelerating as well. Thus far, there has been conclusive research that chronic stress is a major factor that may lead to depression (Kim et. al, 2017).

Yoga Nidra on Pain In terms of the effects of Yoga Nidra on pain perception, it has been shown in various studies to be beneficial in reducing the pain effects of a variety of sources. Various studies have shown that Yoga Nidra helps to reduce pain perception.

One study in support of the previous statement was conducted by Dayrit et. al (2014) in which a In one study on patients undergoing colonoscopy, listening to a recording of guided instructions of 68

a Yoga Nidra practice helped to reduce perceived 2018). pain (Feng et. al, 2018). Additionally, a study was conducted on individuals living with lumbar spondylitis (inflammation causing severe pain in the spine). Various forms of yoga, including Yoga Nidra, were tested and compared to a control group. It was concluded that these yoga practices aided test subjects in managing their pain caused by lumbar spondylitis (Bansal, et. al, 2017). Finally, the effects Yoga Nidra have also been tested in women suffering from menstrual disorders. Among other physiological improvements of symptoms, the practice was found to improve the symptoms of pain that stemmed from the varying disorders (Agrawal et. al, 2011). Yoga Nidra on Stress Previously to the current article, a pilot study conducted by Anderson et. al (2017) investigated the effects of Yoga Nidra on individuals in a high-stress occupation (psychiatric nurses). After practicing Yoga Nidra over the course of 6 weeks, it was observed through psychological evaluations that their symptoms of stress were greatly reduced. A meta-analysis by Goldsmith and Li (2012) was also conducted on 35 studies that tested the effects of yoga on stress symptoms. 25 of these studies showed evidence of yoga practices being beneficial in improving stress symptoms on test subjects. However, Goldsmith and Li critiqued that these studies lacked robustness; at most, the studies merely provided weak evidence that yoga can improve stress symptoms. Goldsmith and Li therefore urged that future studies with less restrictions and larger test populations should be conducted. Mindfulness Meditation on Stress The present article is one of few that have begun to explore the effects of mindfulness meditation on stress levels.

RESULTS Methods In the present article, the effects of Yoga Nidra and seated meditation were recorded on 60 college professors for 3 months. The professors were divided equally and randomly into three test groups as follows: one group practiced Yoga Nidra, one practiced seated meditation, and the final group acted as a control and did not practice either of the two. The professors had psychological evaluations to assess anxiety, stress, and depression once at the start of the experiment, and once after the 3-month period. Finally, the data was compared. Five different tests were used to assess the changes in anxiety, stress, and depression in the college professor participants: the Beck Anxiety Inventory (BAI), Hamilton Anxiety Rating Scale (HAM-A), Body Sensations Questionnaire (BSQ), Beck Depression Inventory (BDI), and Stress Symptoms Inventory for Adults Lipp (ISSL). BAI, BDI, HAM-A: The results of the BAI and BDI variables as well as the HAM-A indicated that both intervention groups showed significant improvements when compared to the control group. A significant reduction in anxiety and depressive symptoms were observed. Additionally, the Yoga Nidra group showed the most intragroup improvement between the first and second psychological assessments. BSQ, ISSL: The results of the BSQ and ISSL variable showed progress in both intervention groups when compared to the control. In both groups, a noteworthy improvement was observed between the first and second psychological assessments, as indicated by their increase in sensation awareness, and decrease in their symptoms of stress. Additionally, the meditation group showed a larger improvement between assessments for the BSQ test.

In one study, symptoms of PTSD in post-911 war veterans showed a significant decrease after the implementation of mind-body therapies, including meditation, in six test groups (Braun and Cushing, 69

Overall:

In general, the results of the psychological tests showed a significant increase in mental well-being in the test subjects for the meditation and Yoga Nidra intervention groups between the pre- and post-experiment psychological assessments. Both groups, in comparison to the control, showed significant improvements. However, overall, Yoga Nidra showed more effectiveness in the majority of the tests when compared to the meditation group. Previous Studies on Yoga Nidra and Meditation Figure. 1 shows the overall results of the study on Stress conducted in the present article by FerreiraIn the primary article by Anderson et. al (2017), Vorkapic et. all (2018). Both intervention groups a similar pilot study was described, wherein the show significant improvement in stress, depression, effects of Yoga Nidra on stress were studied and anxiety (based off of the 5 psychological tests) on a small group of psychiatric nurses. Pre- and between the pre- and post-experiment evaluations. post-session stress levels were recorded using a Both intervention groups also show significant Likert scale, and the participants also completed improvement compared to the control. The Yoga questionnaires on their muscle tension and sleep Nidra group (â&#x20AC;&#x153;Relaxationâ&#x20AC;? in the figure) showed more overall improvement compared to the patterns. meditation group. Participants reported having a reduced stress level after each session, as well as relieved muscle DISCUSSION tension. The present article determined that Yoga Nidra Though a separate set of tests from the ones and seated meditation both showed positive described in the current article were used to assess improvements in the stress levels of a group of stress levels, the results were in line with those college professors when compared to the control. found in the current article. Furthermore, Yoga Nidra showed to be the more beneficial practice when compared to seated In an article by Braun and Cushing (2018), a meditation. meta-analysis was described of studies observing the effects of mind-body therapies (including The authors suspect that both Yoga Nidra and meditation) on post-911 veterans suffering from seated meditation were effective because they PTSD. All groups had psychological assessments both affect the body in physiologically similar ways pre- and post-experiment. The results indicated (i.e. effects on neurotransmission, para/sympathetic that in 6 of the 9 trials, the intervention group pathways, etc.). They also hypothesize that the reported significant decreases in PTSD symptoms. reason why Yoga Nidra fared better than seated Additionally, each of the single-group studies meditation may be due to a couple of factors: reported improvements in PTSD symptoms in the first is that the physical posture of the body intervention groups between the pre and post- in seated meditation is more difficult to maintain experiment evaluations. when compared to the supine position of Yoga Nidra; the second factor is that meditation requires This meta-analysis falls in line with the results of mental concentration, which some may find very the current article, as it indicates that mind-body difficult, whereas Yoga Nidra only requires the practices, such as meditation, have benefits on the following of simple instructions. psyche of those suffering from high amounts of stress. The findings of the present study are unsurprising, 70

as they are in line with similar articles. They help to point further research in the direction of determining which (if any) alternative therapies may be beneficial.

to compare different forms in order to determine which one(s) may have the most optimal results. More studies should be conducted in which many forms of mind-body practices are compared.

While stress on its own is unpleasant and debilitating, when prolonged, it is also a major risk factor for the development of depression (Kim et. al, 2017). Recent research states that the main treatments for depression include cognitive behavioural therapy (CBT) and some pharmacological treatments, such as anti-depressants (Tiller, 2013). CBT, while it has been proven effective, is a very time consuming treatment that requires much cognitive effort in order understand the disorder, learn coping strategies, and practice adjusting certain behaviours and thought processes in a clinical setting over many sessions (Tiller, 2013). Pharmacological treatments have also shown to have positive effects, however, they do require an adjustment period to find the right drug dosage/ combination, as well as patients often suffer from negative side-effects. Patients may also be subject to withdrawal symptoms should they forget to take their meditation for even one day. Pharmaceuticals are also very economically costly.

One major flaw in this study is the small test sample size of 60 people, with only 20 people per test group. While the results of the study are in line with other similar research, a larger sample size would have been ideal for more robust results. Unfortunately, the most similar research also has significantly low sample sizes, as in the study on the effects of Yoga Nidra on psychiatric nurses, which only had 9 participants (Anderson et. al, 2017).

Alternatively, mind-body practices such as Yoga Nidra and seated meditation, can be practiced independently (after a few introductory sessions) in the comfort of oneâ&#x20AC;&#x2122;s own home. Additionally, since they do not require the direct altercation of physiological processes in the body to the level of drug administration, they therefore do not cause any quantifiable side effects or withdrawal symptoms. Thus, patients may find that mind-body practices are a more enjoyable treatment to their depression/anxiety disorders compared to the mainstream treatments that currently exist.

It is clear that future studies need to acquire more statistically relevant sample sizes in order to provide more meaningful results and make stronger conclusions. In the Discussion section of the present article, the authors mentioned that no previous studies had assessed the impact of Yoga Nidra on stressful professions. As previously mentioned, one was completed a year prior with psychiatric nurses (an arguably taxing profession) (Anderson et. al, 2017). This demonstrates a disappointing lack of previous research into the subject, which might have provided some insight on how better to conduct the study and what results might have been expected. Interestingly, in another paragraph, the authors stated in contradiction to their previous statement that the results of the seated meditation group fell in line with a number of previous studies, however no citations were given for reference of these studies.

There also appears to be a significant likelihood CRITICAL ANALYSIS of subjectivity in the psychological assessment portions of the study, as most of the tests used (BAI, Overall, the present article shows promising results BDI, HAM-A, BSQ) are personal questionnaires in for the future of alternative therapies to mental which the participant answers questions pertaining disorders. The study is unique to previous research to symptoms of anxiety or depression (depending as it compares the effects of two very different on which test) (Jackson-Koku, 2016; Julian, 2011). mind-body practices, rather than just assessing Since participants were able to assess themselves, one, whereas most other articles have only chosen there could have been a lack of accuracy in reporting to focus on one specific type of practice compared symptoms. Additionally, the questionnaire by to a control. It is important to not just study the nature is dependent on the participantsâ&#x20AC;&#x2122; abilities to individual effects of these different practices, but interpret questions correctly. 71

Moreover, since there was a lack of blindness in this study, it is possible that part of the reason that the test group participants showed improvements in their test results could have been because they expected to improve. In other words, it is possible that a placebo may have played a role in the results. One experimental flaw that was acknowledged by the authors is that the only demographic difference between the test groups was the number of years of education. In general, the Yoga Nidra group participants tended to have more years of education than the seated meditation group participants. The authors hypothesized that this might have given them an advantage to having better results by being able to better interpret instructions during practice sessions compared to the meditation group. To build on top of that, it may have also influenced their ability to answer the psychological questionnaires more accurately.

groups and the data of all seated meditation groups and comparing them to the combined data of all control groups. In other words, one might consider each college to be a separate trial.

If seated meditation and/or Yoga Nidra were effective, then one would see overall decreases in stress symptoms across all or most of the test groups when compared to their corresponding control groups within their college. Additionally, improvements within the test groups individually would be observed. If the mind-body practices were not effective, then a large portion of the test groups would show no intragroup improvement, and/or no significant improvement compared to the controls.

To go even further into the research, the same study as described above could be applied to many other professions that are objectively considered FUTURE DIRECTIONS to be high-stress professions. On this much larger scale, the data collected from multiple professions In order to progress this research, there are could be compared. some factors to be taken into consideration when designing future studies, including other If Yoga Nidra and/or seated meditation were professions, and other forms of mind-body effective, then the results pertaining to each practices. profession should look very similar, indicating improved intragroup results of test groups and It seems the issue regarding small sample sizes in a improved results of tests groups when compared couple of the studies mentioned in this paper were to the controls. due to study designers choosing to find a group within the same profession and from one location If Yoga Nidra and/or seated meditation were not (i.e. one college, or one hospital). In designing a effective, then one would either see mixed results future study, it would be beneficial to collect data between professions or similar results in which no from a wider source, i.e. multiple colleges within a intragroup or intergroup improvement is observed. region. Each college would have their own control group, and test groups. Once all of the data is As mentioned in the critical analysis section, collected, one could assess intra-college data and improvement in the method of assessing stress also compare inter-college data as a whole. levels in the psychological examination portions of It is acknowledged that there are factors that the study is needed. One suggestion is to add a differentiate the colleges, such as differences physical examination portion to the test, in which in number of responsibilities per professor, physiological indicators of stress are assessed, such differences in time commitments, and differences as blood pressure, resting heart rate, and hormone in general expectations of professors set by their levels (Jenkins et. al, 2017). This would alleviate college authorities. the sole dependence of the test resultsâ&#x20AC;&#x2122; accuracy on participantsâ&#x20AC;&#x2122; abilities to self-assess and interpret The error that might have occurred due to these questions on the questionnaires. factors is eliminated because test groups are only compared to the controls within their own colleges, In the previous section, the issue of blindness was rather than combining the data of all Yoga Nidra raised. Given that the participants must answer 72

questions pertaining to stress, depression, and anxiety at the start and end of the study, it is quite obvious as to why most of them would be participating in meditative practices. In other words, they may easily assume that the study is observing how these practices impact levels of stress, and expect these practices to improve their stress symptoms. In attempts to decrease the obviousness and thus increase the blindness of the purpose behind the study, additional sets of questions or tests pertaining to random subjects that are unrelated to the study may steer their minds away from the true intentions of the study. For example, a researcher could give them the fake hypothesis that in practicing Yoga Nidra or seated meditation, one can improve their sense of pitch (in relation to music). In this case, in addition to the existing methods of assessment of stress, depression, and anxiety, participants could receive questionnaires on their experiences, capabilities, and relationships with forms of music, and may also be tested on their ability to match/identify pitch. Of course, this is a random example, and any fake hypothesis or set of tests within reason could be used. This increase in blindness would also reduce any error to the data that may result from a placebo. Lastly, as mentioned in the previous section, it was unique that the current article did not only compare the effects of one mind-body practice to a control, but also compared a second to the control, as well as compared the two practices to each other. In future studies, it would be beneficial to test the effects of even more forms of mind-body practices, such as tai chi, qigong and also other forms of yoga, to compare them to each other in order to find the most optimal form(s) if there is/are one(s) (Burge et. al, 2013).

R3 REFERENCES 1. Anderson, R., Mammen, K., Paul, P., Pletch, A., & Pulia, K. (2017). Using Yoga Nidra to Improve Stress in Psychiatric Nurses in a Pilot Study. Journal of Alternative and Complementary Medicine (New York, N.Y.), 23(6), 494–495. https://doi.org/10.1089/acm.2017.0046 2. Cushing, R. E., & Braun, K. L. (2018). Mind-Body Therapy for Military Veterans with PostTraumatic Stress Disorder: A Systematic Review. Journal of Alternative and Complementary Medicine (New York, N.Y.), 24(2), 106–114. https://doi.org/10.1089/acm.2017.0176 3. Doan, L., Manders, T., & Wang, J. (2015). Neuroplasticity underlying the comorbidity of pain and depression. Neural Plasticity, 2015, 504691. https://doi.org/10.1155/2015/504691 4. Ferreira-Vorkapic, C., Borba-Pinheiro, C. J., Marchioro, M., & Santana, D. (2018). The Impact of Yoga Nidra and Seated Meditation on the Mental Health of College Professors. International Journal of Yoga, 11(3), 215–223. https://doi.org/10.4103/ijoy.IJOY_57_17 5. Huang, W.-J., Chen, W.-W., & Zhang, X. (2016). Endocannabinoid system: Role in depression, reward and pain control (Review). Molecular Medicine Reports, 14(4), 2899–2903. https://doi. org/10.3892/mmr.2016.5585 6. Iñiguez, S. D., Riggs, L. M., Nieto, S. J., Dayrit, G., Zamora, N. N., Shawhan, K. L., … Warren, B. L. (2014). Social defeat stress induces a depression-like phenotype in adolescent male c57BL/6 mice. Stress (Amsterdam, Netherlands), 17(3), 247–255. https://doi.org/10.3109/10253890.2014 .910650 7. Jackson-Koku, G. (2016). Beck Depression Inventory. Occupational Medicine (Oxford, England), 66(2), 174–175. https://doi.org/10.1093/occmed/kqv087 8. Julian, L. J. (2011). Measures of anxiety: State-Trait Anxiety Inventory (STAI), Beck Anxiety Inventory (BAI), and Hospital Anxiety and Depression Scale-Anxiety (HADS-A). Arthritis Care & Research, 63 Suppl 11, S467-472. https://doi.org/10.1002/acr.20561 9. Kim, S. H., Schneider, S. M., Kravitz, L., Mermier, C., & Burge, M. R. (2013). Mind-body practices for posttraumatic stress disorder. Journal of Investigative Medicine: The Official Publication of the American Federation for Clinical Research, 61(5), 827–834. https://doi.org/10.2310/ JIM.0b013e3182906862 10. Li, A. W., & Goldsmith, C.-A. W. (2012). The effects of yoga on anxiety and stress. Alternative Medicine Review: A Journal of Clinical Therapeutic, 17(1), 21–35. 11. Li, L., Shu, W., Li, Z., Liu, Q., Wang, H., Feng, B., & Ouyang, Y.-Q. (2018). Using Yoga Nidra Recordings for Pain Management in Patients Undergoing Colonoscopy. Pain Management Nursing: Official Journal of the American Society of Pain Management Nurses. https://doi. org/10.1016/j.pmn.2018.04.005 12. Manik, R. K., Mahapatra, A. K., Gartia, R., Bansal, S., & Patnaik, A. (2017). Effect of Selected Yogic Practices on Pain and Disability in Patients with Lumbar Spondylitis. International Journal of Yoga, 10(2), 81–87. https://doi.org/10.4103/0973-6131.205516 13. Pascoe, M. C., Thompson, D. R., Jenkins, Z. M., & Ski, C. F. (2017). Mindfulness mediates the physiological markers of stress: Systematic review and meta-analysis. Journal of Psychiatric Research, 95, 156–178. https://doi.org/10.1016/j.jpsychires.2017.08.004 14. Rani, K., Tiwari, S. C., Singh, U., Agrawal, G. G., & Srivastava, N. (2011). Six-month trial of Yoga Nidra in menstrual disorder patients: Effects on somatoform symptoms. Industrial Psychiatry Journal, 20(2), 97–102. https://doi.org/10.4103/0972-6748.102489 15. Seo, J.-S., Wei, J., Qin, L., Kim, Y., Yan, Z., & Greengard, P. (2017). Cellular and molecular basis for stress-induced depression. Molecular Psychiatry, 22(10), 1440–1447. https://doi.org/10.1038/ mp.2016.118 16. Tang, Y.-Y., Hölzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews. Neuroscience, 16(4), 213–225. https://doi.org/10.1038/nrn3916 17. Tiller, J. W. G. (2013). Depression and anxiety. The Medical Journal of Australia, 199(6 Suppl), S28-31. 18. Yang, L., Zhao, Y., Wang, Y., Liu, L., Zhang, X., Li, B., & Cui, R. (2015). The Effects of Psychological Stress on Depression. Current Neuropharmacology, 13(4), 494–504. 19. Zis, P., Daskalaki, A., Bountouni, I., Sykioti, P., Varrassi, G., & Paladini, A. (2017). Depression and chronic pain in the elderly: links and management challenges. Clinical Interventions in Aging, 12, 709–720. https://doi.org/10.2147/CIA.S113576

Linking Microglia Function and Lipid Signaling in Alzheimer’s Disease: the lipid pathway as not a consequence but a regulatory factor Jia Li Alzheimer’s disease (AD) is a fatal neurodegenerative disorder with symptoms of progressive memory loss, behavioral abnormality, and cognitive impairments. Neurological hallmarks of AD include loss of synapses and neurons, and intraneuronal accumulation of hyperphosphorylated tau in the form of neurofibrillary tangles (NFTs), as well as plaques consisting largely of aggregated amyloid β-peptide (Aβ). Unfortunately, the linkage between cognitive dysfunction and the disease’s two well-studied pathologies, Aβ and tau aggregation, remains not fully understood. However, Alois Alzheimer, who initially described AD in 1906, also included a third pathological hallmark, which has been largely ignored. AD brains also display a higher occurrence of adipose inclusions and lipose granules, suggesting abnormal lipid metabolism and signaling. Post-mortem studies show biochemical differences of lipid composition between AD and control brain tissues. In a research study done by Wang et al. (2015), the triggering receptor expressed on myeloid cells 2 (TREM2) was studied in 5XFAD mouse models of Alzheimer’s to uncover the consequences of atypical lipid signaling in AD. TREM2 is expressed on the surface of microglia, and triggers an intracellular protein tyrosine phosphorylation response. This receptor is a sensor for a wide variety of lipids, including damage-associated lipids in AD. Previous studies reveal that the R47H mutation of TREM2 is correlated with increased risk of disease. Results demonstrate that functional TREM2 is required for appropriate microglial response to Aβ deposition. These findings provide a novel link between lipids and proper microglial function in Alzheimer’s disease, which introduces lipids as a new potential regulatory and therapeutic mechanism. Key words: Alzheimer’s disease (AD), neurodegenerative, neurofibrillary tangles (NFTs), TREM2, amyloid β-peptide (Aβ), lipid signaling, lipid metabolism, R47H mutation

BACKGROUND/INTRODUCTION

The brain is highly enriched in lipids, which can be diagnostic biomarkers of age-related neurogenerative disorders1. Studies have established that almost all families of lipids are implicated in AD risk and progression, but the link between lipid metabolism and AD was strengthened when the ε4 variant of the apolipoprotein E (APOE), a regulator of both cholesterol and triglyceride metabolism, was identified as the strongest risk factor of Alzheimer’s disease2. ApoE4 binds Aβ and affects its aggregation and modulation. Additionally, other lipids are involved in the trafficking of membrane-bound proteins, protecting cellular membranes from cytotoxic entities, and altering aggregation propensities2. Microglial cells are the resident “microphages” of the brain whose dynamic turnover is responsible for the organ’s innate immune response. These cells enter a hyperactive state when neurodegeneration or aging occurs3. In AD, microglial cells proliferate and are activated, concentrating around Aβ plaques. It is uncertain that whether these histopathological changes, or microgliosis, the intense reaction of microglia against insults, is beneficial or detrimental4. AD’s hallmark, β-amyloidosis results from an imbalance between Aβ deposition and clearance. Mutations of the amyloid precursor protein (APP) or its processing enzymes can result in increased β-site cleavage, favoring production4. On one hand, microglia delay the progression of AD by phagocytosing Aβ and releasing degrative enzymes3. Assisting with restoration of normal brain environment is essential, as damaged-cells can become potent inflammatory stimuli and cause further tissue damage. On the other hand, if overactivated in response to stimulation, microglial cells can initiate too potent a reaction, cause synapse engulfment, or secrete inflammatory factors that injure neurons by activating other neurotoxic astrocytes. Activated microglia can be both a neuroprotective and neurodegenerative force3, indicating that microglial dysfunction as a contributing factor of AD pathogenesis4.

a mutated TREM2 receptor, where the missense R47H (arginine-47-histidine) mutation (carried by less than 0.5% of the population) increases AD risk by nearly threefold. The mutation is a loss-offunction mutation that impairs TREM2-mediated microglial activation, but as of 2015, ligands of the TREM2 receptors involved in AD disease mediation has yet to be identified5,6.

The trigger receptor expressed on myeloid cells 2 (TREM2) is a member of the immunoglobulin superfamily of receptors, and its dysfunction has attributed to a variety of diseases, including Nasu-Hakola disease (NHD), dementia, stroke, and other neurodegenerative disorders7. TREM2 initiates signal transduction pathways that promotes microglial chemotaxis, phagocytosis, survival and proliferation4. Because inflammation, characterized by elevated proinflammatory cytokines and microgliosis, is a common feature of neurodegenerative diseases, the inflammatory response is hypothesized to be promoted by the aggregation of abnormal proteins or repeated cellular damage. The microglial receptor TREM2 is thought to respond to AD-specific molecular patterns and AD-associated ligands7. Collectively, these data support the view that microglia normally operate protectively4. However, the link between TREM2-supported microglia function and lipid signaling has not been well-studied. Wang et al. (2015) used the 5XFAD mouse model of AD, and contrasted the effects of both TREM2 deficiency and haplosufficiency on microglial activation and function to controls mice. The results of the paper showed a link between microglial response and lipid signaling, suggesting that lipid-activated pathways are crucial to Aβ clearance. TREM2 senses lipids that interact with fibrillary Aβ, and the R47H mutation impairs the receptor’s lipid ligand recognition abilities. Additionally, the researchers also characterized TREM2 as playing an important role in sustaining the microglial response to Aβ plaques6. The paper recognizes lipids as a novel regulation mechanism of Alzheimer’s disease progression and alleviation with high therapeutic potential.

A majority of AD risk genes or factors are expressed or upregulated in microglia4. GWAS studies have MAJOR RESULTS identified both common and rare variants. The Wang et al. (2015) paper studied one such risk gene, 76

TREM2 as a modulator of Aβ aggregation

Previously in a 2014 paper by Ulrich et al., TREM2’s influence on Alzheimer’s susceptibility is studied8. Using APPPS1-21 mice with rapid Aβ deposition, the loss of one functional trem2 allele significantly decreased the number and size of plaqueassociated microglia, suggesting that the receptor is crucial for microglial response. The mechanisms underlying TREM2 involvement has yet to be described6. Wang et al. examined Aβ deposition in both TREM2 deficient (TREM2-/-) and haplosufficient (TREM2+/-) 5XFAD mice. Antibody (mAb) staining against Aβ reveals increased Aβ accumulation in the hippocampal region. Moreover, the loss of layer V cortical neurons, a feature of 5XFAD, is more prominent in TREM2 deficient mice, as indicated by examination of neuronal densities (see Figure 1). Symptoms such as memory loss and cognitive impairment can be linked to the functions of these pathologically effected brain regions. TREM2+/mice possessed an intermediate phenotype that failed to produce statistically significant results (p = 0.104). Data implicates TREM2 involvement in AD, and supports the previously established hypothesis that functional TREM2 receptor absence on the surface of microglia has influences on Aβ aggregation.

Figure 1. Observed accelerated disease phenotypes in TREM2deficient mice. Absence of TREM2 results in increased hippocampus Aβ deposition and increased loss of layer V cortical neurons. Top: antibody staining (mAb) on matching hippocampal coronal sections of three groups of mice (5XFAD control, 5XFAD TREM2 haplosufficient, and 5XFAD TREM2 deficient) show increased Aβ accumulation in the absence of TREM2. Bottom: densities of layer V cortical neurons from matching coronal sections in 8.5-month old mice, stained with cresyl violet. Figure adapted from Wang et al. 2015.

Effects on microgliosis and plaque association Microglial cells provide the mechanism behind the lack of TREM2 impacting protein aggregation. TREM2 is explicitly expressed in microglia by RNA sequencing data9 under a steady-state. Upon injury or damage, TREM2 expression is found to be upregulated in 5XFAD mice microglia6. Microgliosis involves the proliferation and expansion, and morphological transformation into an active state6, which includes a partial retraction of processes and an increase in cell body size10. The authors found TREM2 deficiency did not have a direct effect on the phagocytosis of plaques, but rather microglial association and morphological changes (see Figure 2).

Figure 2. TREM2 deficiency diminishes the capacity of microglia to cluster around plaques and activation. In panel A, the heatmap shows levels microglial association with Aβ plaques, shown as white squares. Panels F, G shows surface area of microglial cell bodies and process length (bigger cell bodies and shorter processes indicate activation) Panel H shows the distance between microglial cells and the nearest Aβ plaque. Figure adapted from Wang et al. 2015.

In addition to reduced association with plaques, microgliosis levels are significantly reduced in the absence of TREM2 (see Figure 3). Additionally, microglial survival is impacted, as significantly fewer microglia could be recovered from the hippocampus and cortices of TREM2-/- mice than control 5XFAD mice.

The authors next sought to identify the ligands of TREM2 that trigger signaling and microglial activation. TREM2 has been known to bind to carbohydrates, anion bacterial products and phospholipids12. Lipid ligands of particular interest were phosphatidylserine (PS) which indicate damage in neural and glial cells; additionally, sphingomyelin (SM) is released by damaged myelin. By transfecting human TREM2 in reporter cells that express GFP, differing extents of receptor activation in response to different lipid ligands can be seen. Additionally, R47H reporter cells were also generated and differences in responses to a variety of ligands was examined (see Figure 4). If mutated, TREM2 response was reduced. CONCLUSIONS/DISCUSSION Wang et al. (2015) demonstrated that TREM2 deficiency in 5XFAD mice affects three factors crucial for microglia-mediated Aβ plaque clearance. Microgliosis levels are decreased, the association between microglial cells and Aβ plaques is reduced (as well as subsequent Aβ clearance), and the lipid sensing mechanism is impaired if TREM2 is nonfunctional, or mutated. Collectively, we can conclude that TREM2 functions protectively against AD in a damage-associated lipid pathway that activates microglial cells appropriately during pathological damage.

Figure 3. Reduced microgliosis in TREM2-deficient 5XFAD mice. Iba-1 (red) staining for microglia and X-34 (green) staining for Aβ plaques at 40x magnification, in both the hippocampus and the cortex. Graphs show the amount of microgliosis surrounding plaques of similar size in the hippocampus (top) and cortex (bottom); Iba-1 staining for active microglia is significantly reduced in the TREM2-/- models.

Unlike other papers studying potential causes or regulatory pathways of AD, Wang et al. took a different approach to elucidating a novel contributing factor to AD and studied a pathway that has been largely attributed as a consequence, and not a cause of Alzheimer’s disease. We see a promising linkage formed between lipid metabolism and microglial-mediated Aβ plaque clearance. The mechanism behind TREM2-activated microgliosis is studied, and the receptor is now established as crucial to the neuron’s innate response to halting AD progression.

TREM2 as a lipid sensor and the R47H mutation

microglial response has been studied, it is still uncertain if the reactive microgliosis involves resident microglia or myeloid cells derived from peripheral blood monocytes13. Perhaps more than one type of cells can contribute to the triggered response. Additionally, AD models mice varying age were examined and produced questionable results. In older (8-month old) mice, results are consistent with the hypothesized protective nature of TREM2. However, in younger, 4-month old mice models with knocked out TREM2, hippocampal Aβ accumulation was reduced, and TREM2 deficiency seems to protect against AD progression and symptom appearance12. FUTURE DIRECTIONS

Figure 4. Lipid sensing abilities of TREM2 is significantly reduced in the R47H mutation. Top: TREM2 reporter cells’ response to different lipid ligands at differing concentrations. Bottom: reporter activity significantly reduced in response to lipids PS and SM when mutated. Figure adapted from Wang et al. 2015.

CRITICAL ANALYSIS Wang et al. (2015) focused on the two main observed phenotypes in AD, abnormal lipid metabolism and disease-activated microglial cells, and links the two visible pathologies using TREM2. This establishes the TREM2-lipid pathway as not a consequence, as believed previously, but a contributing factor, regulator, and signaling mechanism to AD progression or Aβ clearance. Lipids were investigated as a primary ligand of TREM2 involved in Alzheimer’s disease progression. The authors of the paper studied lipid sensing abilities of TREM2 wild type and mutated receptors. However, lipid pathways were never explicitly addressed in TREM2-/- mice, and only demonstrated in transfected cells. Further investigations are needed to fully establish the functional link between reduced microglial response, TREM2 receptors, and lipid ligands such as PS, SM.

The proposal that TREM2 dependent microglial response may rely on the recruitment of other blood monocytes can be tested using anti-TREM2 staining. This can determine if monocytes or other cells express TREM2 and may also respond to lipid ligands associated with AD in the bloodstream. Additionally, we can assess the ability of blood monocytes and other TREM2-expressing cells to infiltrate the brain and contribute to the existing pool of microglial cells. If results align with the hypothesis that resident microglial cells are solely responsible for Aβ-associated response, we would expect to see minimal anti-TREM2 staining in blood monocytes, or evidence that the blood brain barrier prevents the entry of TREM2-carrying agents. Opposite results would indicate that we cannot conclude that microglia are the major contributors to the reaction detected in 5XFAD mice, suggesting that an alternate lipid pathway is in effect.

Previous experiments show that TREM2 binding is inhibited in the presence of anionic bacterial products, suggesting a charge-dependent binding mechanism12. Additionally, consistent with the hypothesis that TREM2 has great affinities for anionic substrates, the extracellular domain of the receptor was found to be rich in arginine residues with high salt-bridge forming potentials6. Wang et al. (2015) provided results that the R47H mutation has significantly less effects on sphingomyelin (SM) Other conflicting literature state that the TREM2 than phosphatidylserine (PS). Different binding receptor is not exclusively expressed on microglial affinities may explain the varied extent of reduced cells11. Although TREM2 deficiency’s effects on receptor activation due to the R47H mutation. 79

Structural studies by crystallography can be used to validate the model of preferential ligand binding. We would expect results to indicate that the R47H mutation is near the active site, changes protein conformation, changes interactions between subunits, or inhibits conformational changes, all of which may alter ligand binding differently based on specific amino acid interactions. On the other hand, structural analysis may suggest that the R47H mutation is not responsible for the differential effects of the mutation on different ligands, and that some other mutation or mechanism must be studied. Sustaining the positive response is vital for potential therapy advancements. In order to translate the paperâ&#x20AC;&#x2122;s findings to clinical settings, treatments such as maintaining increased TREM2 expression in AD patients, or ensuring proper signaling conduction and detection of lipid ligands must also be addressed in the future.

REFERENCES 1. Paolo, G. Kim, TW. Linking lipids to Alzheimer’s disease: cholesterol and beyond. Nat Rev Neruosci. 2011 May; 12(5): 284-296 2. Wong, MW. Braidy, N. Poljak, A. Pickford, R. Thambisetty, M. Sachdev, PS. Dysregulation of lipids in Alzheimer’s disease and their role as potential biomarkers. Alzheimer’s & Dementia. 2017; 13: 810-827 3. Solito, E. Sastre, M. Microglial function in Alzheimer’s disease. Frontiers in Pharmalocogy. 2012. doi: 10.3389/fphar.2012.00014 4. Hansen, DV. Hanson, JE. Sheng, M. Microglia in Alzheimer’s disease. J. Cell Biol. December 1, 2017. 217(2): 459-472 5. Rosenthal, SL. Bamne, N. Wang, X. Berman, S. Snitz, BE et al. More evidence for association of a rare TREM2 mutation (R47H) with Alzheimer’s disease risk. Neurobiol Aging. August 2015; 36(8): 2443.e21-2443.e26 6. Wang, Y. Cella, M. Mallinson, K. Ulrich, JD. Young, KL et al. TREM2 lipid sensing sustains the microglial response in an Alzheimer’s disease model. Cell. March 12, 2015; 160: 1061-1071. 7. Walter, J. The triggering receptor expressed on myeloid cells 2: a molecular link of neuroinflammation and neurodegenerative diseases. The Journal of Biological Chemistry. 2016; 291(9): 4334-4341 8. Ulrich, JD. Finn, MB. Wang, Y. Shen, A. Mahan, TE. Jiang H. Stewart, FR. Piccio, L. Colonna, M. Holtzman, D. Altered microglial response to Aβ plaques in APPPS-21 mice heterozygous for TREM2. Molecular Neurodegeneration. 2014; 9:20-29 9. Butovsky, O. Jedrychowski, MP. Moore, CS. Cialic, R. et al. Identification of a unique TGF-β dependent molecular and functional signature in microglia. Nat Neurosci. 2014 January; 17(1): 131-143 10. Clayton, KA. Enoo, AA. Ikezu T. Alzheimer’s disease: the role of microglia in brain homeostasis and proteopathy. Front. Neurosci. 11:680 11. Daws, MR. Sullam, PM. Niemi, EC. Chen, ET et al. Pattern recognition by TREM2: binding of anionic ligands. The Journal of Immunology. 2003. 171: 594-599 12. Wang, Y. Ulland, TK. Ulrich, JD. Song, W et al. TREM2-mediated early microglial response limits diffusion and toxicity of amyloid plaques. J. Exp. Med. 2016. 213 (5):667-675 13. Zheng, H. Jia, L. Liu, C. Rong, Z. et al. TREM2 promotes microglial survival by activating Wnt/βcatenin pathway. The Journal of Neuroscience. 2017. 37(7): 1772-1784 14. Hippius, H. Neundorfer, G. The discovery of Alzheimer’s disease. Dialogues Clin Neurosci. 2003; 5:101-108 15. Li, JT. Zhang, Y. TREM2 regulates innate immunity in Alzheimer’s disease. Journal of Neuroinflammation. 2018; 15:107-114

The Potential Interplay among Neuroendocrine Activation, Neurobiological Changes, and Behavioral Alterations in Social Isolation Jinze Liu Exposure to chronic stress has been implicated in neurodegenerative disturbances such as anxiety and depression. Previous research has observed changes in neuroplasticity-related signaling pathways and neurotransmitters in animal models of social deprivation. Fluctuation in cortical and hippocampal expressions of brain-derived neurotrophic factor (BDNF) and metabotropic glutamate receptors (mGluRs) may be relevant to neurobehavioral alterations. However, no simple relationship appears to exist between prolonged social stress and the underlying molecular mechanism. Mixed research findings of both hypoactivity and hyperactivity in hypothalamic-pituitary-adrenal (HPA) axis that induced by prolonged stressor require further clarifications. The current study aimed to systematically examine the involvement of neuroplasticity-related genes, neuroendocrine activation as well as emotional behaviors in adult mice model of social isolation. Open field test and tail suspension test demonstrated anxious- and depressive-like phenotypes in socially reared mice. A decrease in blood corticosterone levels in adrenal gland assessed post-mortem indicated hypoactivity of stress effector system under the influence of chronic stress. Moreover, the behavior alterations and neuroendocrine malfunctioning are associated with reduced hippocampal and prefrontal cortical levels of several significant neuroplasticity-related genes. Key words: chronic stress; brain-derived neurotrophic factor (BDFN); metabotropic glutamate receptors (mGluRs); hypothalamic-pituitary-adrenal (HPA) axis

BACKGROUND & INTRODUCTION

In everyday life, organisms are often exposed to brief stressful experiences which mostly can be adequately overcome and beneficial to growth and learning. However, prolonged or intermittent exposure to uncontrollable life stressors, together with genetic vulnerability and biobehavioral risk factors may interact to contribute to neuropsychiatric disturbances (Kendler, Kessler, Neale, Heath, & Eaves, 1993; Kendler KS, Gardner CO, 2006)integrated etiologic model for the prediction of episodes of major depression in an epidemiologic sample of women. METHOD: Both members of 680 female-female twin pairs of known zygosity from a population-based register were assessed three times at greater than 1-year intervals. The last two assessments included a structured interview evaluation for presence of episodes of major depression, defined by DSM-III-R, in the preceding year. The final structural equation model contained nine predictor variables: genetic factors, parental warmth, childhood parental loss, lifetime traumas, neuroticism, social support, past depressive episodes, recent difficulties, and recent stressful life events. RESULTS: The bestfitting model predicted 50.1% of the variance in the liability to major depression. The strongest predictors of this liability were, in descending order, 1. A rising of life-course perspective research has emphasized the effects of maltreatment, life adversity, and social stress during development on the progression of emotional disorders, including anxiety and depression (Leskelä et al., 2006; Mcewen & Gianaros, 2010). Animal models are used to understand the associations between stressors in the social environments and maladaptive deteriorations on the body and the brain. Previous studies have demonstrated behavioral deficits and neurochemical alterations in rodents that were reared in persistent social deprivation or chronic restraint stress (Berry et al., 2012; Chiba et al., 2012).

the level of protein expression of brain-derived neurotrophic factor (BDNF), a neuroplasticity regulatory neurotrophin, has been observed decreased in the hippocampus and increased in the medial prefrontal cortex of social-isolated rodents (Shao, Han, Shao, & Wang, 2013; Sun et al., 2013). Also, it was reported that metabotropic glutamate receptors (mGluRs) such as mGluR1 and mGluR5 levels decreased in the dorsal PFC under the influence of chronic stressor (Melendez, Gregory, Bardo, & Kalivas, 2004). A more systematic assay is needed to investigate the involvement of the BDNF gene and other neuroplasticity-related genes in various brain regions using the paradigm of social isolation. Concerning a big picture, it is well-established that an organism’s body copes with real or perceived stress by activating a hormonal response system, hypothalamic-pituitary-adrenal (HPA) axis to restore internal stability. Primarily, a stress hormone (i.e., corticosterone in animals and cortisol in human and) is secreted from the cortex of the adrenal glands as the end product of the cascade, (Herman & Cullinan, 1997)probably via brainstem catecholaminergic projections. By contrast, stressors requiring interpretation by higher brain structures (‘processive’ stressors. In essence, the potential explanation underlines the trajectory of ill health is that while initially adaptive, overwhelmingly mobilized molecular pathways in response to the homeostatic pressure induced by the chronic stress may cause pronounced alterations in the physiological milieu (Herman, 2013). However, the directionality of the changes remain obscure due to controversies in hypo- or hyper-activity of the HPA axis functioning (Holsboer, von Bardeleben, Wiedemann, Müller, & Stalla, 1987; Kunugi, Hori, Adachi, & Numakawa, 2010).

Taken altogether, the study of Ieraci, Mallei, & Popoli (2016) aimed to conduct an integrative and comprehensive experiment for assessing 1) whether the social isolation induced emotional Although the molecular mechanisms that triggered behaviors, 2) the underlying molecular mechanism by social isolation are not fully unraveled, some of in term of changes in expressions of gene involved the changes may have translational relevance in in neuronal plasticity and neurotransmitters that characteristics of human psychiatric disorders. Of were relevant to stress-related disorders, and particular importance is the potential functional 3) HPA axis activation in socially isolated adult changes in neuroplasticity-related signaling mice. Moreover, the potential interplay among pathways and neurotransmitters. Specifically, neuroendocrine activation, neurobiological 83

changes, and social isolation-induced behavioral alterations was also of interest. Behavioral tests were used to embody anxious- and depressivelike phenotypes. Plasma corticosterone level and adrenal weight were assessed to address the mixed results of the adaptive function of the HPA axis. Moreover, the mRNA levels of BDNF, regulations of other neuroplasticity-related genes such as early growth response factor gene (Egr-1), C-Fos, and Arc, as well as change in glutamate receptors (mGluR1, mGluR2, mGluR5) were measured in hippocampus and PFC neurons. MAJOR RESULTS Chronic Social Isolation Induced Anxious- and Depressive-like Behaviors.

Social isolation paradigm was enforced for four weeks on adult male mice to assess if chronic social stress would induce behavior modifications that were in parallel with the characteristics of human neuropsychiatric disorders. An anxiogenic effect of the chronic social isolation has been observed in SI mice during the open field test. They spent significantly lower percentages of time in the center of the open arena and they were markedly more active than the control group by having greater total travel distance. Moreover, the SI group showed the depressive phenotype of giving up struggles and spending more time immobilized compare to the GH group in the tail suspension test. The results were in line with other research findings which suggest an implication between social stress-induced behaviors and emotional disturbances (Amiri et al., 2015; Grippo et al., 2007).

spent significantly shorter time in the center, travelled significantly more total distance in OPT, and immobilized significantly longer time in TST. Expression Levels of Neuroplasticity-Related Genes Reduced in the HPC and the PFC. Levels of mGluR1 and mGluR2 Reduced Only in the PFC of Socially Isolated Mice.

The expression levels of various neuroplasticityrelated genes and metabotropic glutamate receptors in HPC and PFC neurons were assessed to gain more understandings of the molecular mechanism underlying the social isolation-induced neurobehavioral alterations. In both the HPC and PFC of SI mice, levels of BDNF-7 mRNA transcript and levels of c-Fos, Arc, and Egr-1 were reduced significantly compared to those of GH mice. It was notable that the downregulation of the immediate early genes (IEGs) were consistent with past literature (Matsumoto, Ono, Ouchi, Tsushima, & Murakami, 2012; Pisu et al., 2016). Moreover, the results demonstrated decreased levels of mGluR1 and mGluR2 only in PFC neurons of SI mice, which were in line with previous data reporting an effect of chronic stress on attenuating the function of the metabotropic glutamate receptors (Ago et al., 2013).

Figure 2. Levels of BDNF-7 mRNA transcript reduced in neurons of both HPC and PFC.

Figure 1. Compared to the control group, SI group 84

the local BDNF translation and synaptic activation.

Figure 3. mRNA levels of c-Fos, Arc, and Egr-1 reduced in both HPC and PFC. mGluR2 and mGluR2 mRNA levels reduced in PFC but not HPC. Level of Plasma Corticosterone Decreased in Socially Isolated Mice. The CORT level in the plasma of SI mice significantly reduced compared to the baseline of GH mice, supporting results of previous work done on SI adult male rat and female mice (Adzic et al., 2009; Martin & Brown, 2010). Also, there was a reduced ratio between the left and right adrenal glands in SI mice, indicating a hypoactivity of the HPA axis caused by the chronic stress. CONCLUSIONS & DISCUSSIONS

The current study was in support of the idea that chronic social stress-induced behaviors in rodents were in parallel to anxious and depressive phenotypes in human (Amiri et al., 2015; Grippo et al., 2007). The use of adult male mice model made it more unique as the findings suggested that the deleterious effect of social stress was not limited to the post-weaning period. The result of the reduced level of CORT added empirical evidence to the line of research indicating a hypoactive reaction of HPA axis in adaptive to stress (Adzic et al., 2009; Martin & Brown, 2010). Intriguingly, the suggestion that the social isolation model of adult male mice could be suitable for studying PTSD shed new light on the future clinical study. Furthermore, the study was among a few helped to understand more about the molecular mechanisms of social stress-induced behavioral and neuroendocrinal alterations. The authors’ novel interpretation on the finding of decreased mRNA level of the BDNF7 splice variant in socially-isolated mice provided insight into other work suggesting that disrupted BDNF function may be involved in anxious- and depressive-like behaviors (Berry et al., 2012; Chiba et al., 2012). CRITICAL ANAYLSIS

In the primary study, SI male mice spent less center time in the open field arena, exhibited hyperactivity in response to the novel environment, and immobilized most of the time in the tail suspension test compared to the GH mice. The findings were important for characterizing the consequences of social isolation on mice’ behaviors in adulthood. Also, reduced level of plasma corticosterone and abnormality in the weight ratio of the two sides of the adrenal glands revealed a hypofunction of the HPA axis in response to the chronic social stress. The authors suggested an association between the adult mice model of social isolation and patients with posttraumatic stress disorder (PTSD) in term of similar neuroendocrine profiles. Moreover, the results showed downregulations of the expressions of several neuroplasticity-related genes and reduction of metabotropic glutamate receptors. It is proposed that reduced BDNF-7 transcript mRNA levels may relate to behavioral dysfunctions of SI mice due to its potentially important role in

As the research used male mice model to study anxious and depressive phenotypes, the authors should also include tests that can measure behaviors of mice which have been believed to show the core symptoms of human neuropsychiatric disturbances. For example, animals’ responsiveness to a reward indicated by the sucrose preference test may demonstrate anhedonia in depression profile (American Psychiatric Association [APA], 2000). Also, neophobia in anxiety profile can be further examined by assessing animals’ exploratory response in an elevated plus maze (Parker & Morinan, 1986). Moreover, the reduction of GluR1 and mGluR2 expression in the PFC but not HPC of the isolation reared mice is not consistent with other work. Notably, Kawasaki and his colleagues (2011) suggested an association between the increased function of the group II metabotropic glutamate receptor (mGluR2/3) in both the PFC and HPC of the social-deprived mice and the morbific mechanism

underlying their depressive-like behaviors. Also, relevant works have observed decreased dorsal prefrontal cortex protein levels of mGluR1 and mGluR5 as well as an increase in mGluR6 in the medial PFC of rats rearing in isolation (Levine et al., 2007; Melendez et al., 2004). The authors should analyze gene expressions in subdivisions of the PFC and HPC and further address whether the change in the metabotropic glutamate receptors plays a role in the behavioral alterations in sociallyisolated mice. FUTURE DIRECTIONS Future study should focus on the effect of social isolation stress on the group I metabotropic glutamate receptors (mGluR1, mGluR5) and group II metabotropic glutamate receptors (mGluR2/3) protein immunoreactivity in the different sub-areas of the PFC and HPC. Also, further examination is needed to uncover the association between the disruption in the function of metabotropic glutamate receptors and abnormal behaviors observed in social-deprived mice.

to the experimental group. It is expected that the behavioral alterations can be reversed by the drugs, indicating that change in mGluRs is critical for the behavioral deficits. The experiment fills in the gap of existing literature by systematically reassuring the stress-induced changes in mGluRs in different subdivisions of PFC and HPC and further uncovering its role in abnormal behaviors of isolation reared mice. If the experiment does not work, it may indicate that the glutamatergic system contributes more to cognitive deficits (Melendez et al., 2004) rather than behavioral plasticity. It also can be the case that the chronic social deprivation rearing causes re-structure and changes to miceâ&#x20AC;&#x2122;s hippocampus and cortex, and leads to an alteration in glutamate function in a long-term (Lapiz et al., 2003)including hyperactivity in response to novelty and amphetamine and altered responses to conditioning. These are associated with alterations in the central aminergic neurotransmitter functions in the mesolimbic areas and other brain regions. Isolation-reared rats have enhanced presynaptic dopamine (DA.

In addition to the measurements of miceâ&#x20AC;&#x2122;s behavioral despair (tail suspension test) and emotional unease (open field test), their depressive- and anxious-like states such as anhedonia and neophobia should also be assessed by sucrose preference test and elevated plus maze. It is expected that the isolated mice should have lower sucrose consumption due to developed anhedonia compared to the control group. In the elevated plus maze, the isolation-reared mice should spend more time in the closed arms of the maze and entry less frequently into the open arms. After the behavioral tests, brains samples of subdivisions of the PFC (e.g., medial, dorsal, ventral) and the HPC (e.g., dorsal, ventral, dentate gyrus, CA1, and CA3) can be obtained and undergo tissue homogenization, electrophoresis and immunoblotting to detect mGluR1, mGluR2/3, and mGluR5 proteins. The results should in support of previous literature that demonstrates a functional change of mGluRs in PFC and HPC in general as well as differential modulations of gene expression in different subdivisions in neurons of socially-isolated mice compared to the control group. If so, the agonist of mGluRs can be administrated intraperitoneally 86

REFERENCES 1. Adzic, M., Djordjevic, J., Djordjevic, A., Niciforovic, A., Demonacos, C., Radojcic, M., & KrsticDemonacos, M. (2009). Acute or chronic stress induce cell compartment-specific phosphorylation of glucocorticoid receptor and alter its transcriptional activity in Wistar rat brain. Journal of Endocrinology. https://doi.org/10.1677/JOE-08-0509 2. Ago, Y., Yano, K., Araki, R., Hiramatsu, N., Kita, Y., Kawasaki, T., … Matsuda, T. (2013). Metabotropic glutamate 2/3 receptor antagonists improve behavioral and prefrontal dopaminergic alterations in the chronic corticosterone-induced depression model in mice. Neuropharmacology. https:// doi.org/10.1016/j.neuropharm.2012.09.008 3. American Psychiatric Association [APA]. (2000). DSM-IV. Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.). https://doi.org/10.1176 4. Amiri, S., Haj-Mirzaian, A., Rahimi-balaei, M., Razmi, A., Kordjazy, N., Shirzadian, A., … Dehpour, A. R. (2015). Co-occurrence of anxiety and depressive-like behaviors following adolescent social isolation in male mice; possible role of nitrergic system. Physiology and Behavior. https://doi. org/10.1016/j.physbeh.2015.03.032 5. Berry, A., Bellisario, V., Capoccia, S., Tirassa, P., Calza, A., Alleva, E., & Cirulli, F. (2012). Social deprivation stress is a triggering factor for the emergence of anxiety- and depression-like behaviours and leads to reduced brain BDNF levels in C57BL/6J mice. Psychoneuroendocrinology. https://doi.org/10.1016/j.psyneuen.2011.09.007 6. Chiba, S., Numakawa, T., Ninomiya, M., Richards, M. C., Wakabayashi, C., & Kunugi, H. (2012). Chronic restraint stress causes anxiety- and depression-like behaviors, downregulates glucocorticoid receptor expression, and attenuates glutamate release induced by brainderived neurotrophic factor in the prefrontal cortex. Progress in Neuro-Psychopharmacology and Biological Psychiatry. https://doi.org/10.1016/j.pnpbp.2012.05.018 7. Grippo, A. J., Gerena, D., Huang, J., Kumar, N., Shah, M., Ughreja, R., & Sue Carter, C. (2007). Social isolation induces behavioral and neuroendocrine disturbances relevant to depression in female and male prairie voles. Psychoneuroendocrinology. https://doi.org/10.1016/j. psyneuen.2007.07.004 8. Herman, J. P. (2013). Neural control of chronic stress adaptation. Frontiers in Behavioral Neuroscience. https://doi.org/10.3389/fnbeh.2013.00061 9. Herman, J. P., & Cullinan, W. E. (1997). Neurocircuitry of stress: central control of the hypothalamo–pituitary–adrenocortical axis. Trends in Neurosciences. https://doi.org/10.1016/ S0166-2236(96)10069-2 10. Holsboer, F., von Bardeleben, U., Wiedemann, K., Müller, O. A., & Stalla, G. K. (1987). Serial assessment of corticotropin-releasing hormone response after dexamethasone in depression Implications for pathophysiology of DST nonsuppression. Biological Psychiatry. https://doi. org/10.1016/0006-3223(87)90237-X 11. Ieraci, A., Mallei, A., & Popoli, M. (2016). Social Isolation Stress Induces Anxious-DepressiveLike Behavior and Alterations of Neuroplasticity-Related Genes in Adult Male Mice. Neural Plasticity. https://doi.org/10.1155/2016/6212983 12. Kawasaki, T., Ago, Y., Yano, K., Araki, R., Washida, Y., Onoe, H., … Matsuda, T. (2011). Increased binding of cortical and hippocampal group II metabotropic glutamate receptors in isolationreared mice. Neuropharmacology. https://doi.org/10.1016/j.neuropharm.2010.10.009 13. Kendler, K. S., Kessler, R. C., Neale, M. C., Heath, A. C., & Eaves, L. J. (1993). The prediction of major depression in women: Toward an integrated etiologic model. American Journal of Psychiatry. https://doi.org/10.1176/ajp.150.8.1139 14. Kendler KS, Gardner CO, P. C. (2006). Toward a comprehensive developmental model for major depression in men. Am J Psychiatry. https://doi.org/10.1176/appi.ajp.159.7.1133 15. Kunugi, H., Hori, H., Adachi, N., & Numakawa, T. (2010). Interface between hypothalamicpituitary-adrenal axis and brain-derived neurotrophic factor in depression. Psychiatry and Clinical Neurosciences. https://doi.org/10.1111/j.1440-1819.2010.02135.x

16. Lapiz, M. D. S., Fulford, A., Muchimapura, S., Mason, R., Parker, T., & Marsden, C. A. (2003). Influence of postweaning social isolation in the rat on brain development, contioned behavior, and neurotransmission. Neuroscience and Behavioral Physiology. https://doi. org/10.1023/A:1021171129766 17. Leskelä, U., Rytsälä, H., Komulainen, E., Melartin, T., Sokero, P., Lestelä-Mielonen, P., & Isometsä, E. T. (2006). The influence of adversity and perceived social support on the outcome of major depressive disorder in subjects with different levels of depressive symptoms. Psychological Medicine. https://doi.org/10.1017/S0033291706007276 18. Levine, J. B., Youngs, R. M., MacDonald, M. L., Chu, M., Leeder, A. D., Berthiaume, F., & Konradi, C. (2007). Isolation rearing and hyperlocomotion are associated with reduced immediate early gene expression levels in the medial prefrontal cortex. Neuroscience. https://doi.org/10.1016/j. neuroscience.2006.11.063 19. Martin, A. L., & Brown, R. E. (2010). The lonely mouse: Verification of a separation-induced model of depression in female mice. Behavioural Brain Research. https://doi.org/10.1016/j. bbr.2009.10.006 20. Matsumoto, K., Ono, K., Ouchi, H., Tsushima, R., & Murakami, Y. (2012). Social isolation stress down-regulates cortical early growth response 1 (Egr-1) expression in mice. Neuroscience Research. https://doi.org/10.1016/j.neures.2012.04.004 21. Mcewen, B. S., & Gianaros, P. J. (2010). Central role of the brain in stress and adaptation: Links to socioeconomic status, health, and disease. Annals of the New York Academy of Sciences. https://doi.org/10.1111/j.1749-6632.2009.05331.x 22. Melendez, R. I., Gregory, M. L., Bardo, M. T., & Kalivas, P. W. (2004). Impoverished rearing environment alters metabotropic glutamate receptor expression and function in the prefrontal cortex. Neuropsychopharmacology. https://doi.org/10.1038/sj.npp.1300507 23. Parker, V., & Morinan, A. (1986). The socially-isolated rat as a model for anxiety. Neuropharmacology. https://doi.org/10.1016/0028-3908(86)90224-8 24. Pisu, M. G., Garau, A., Boero, G., Biggio, F., Pibiri, V., Dore, R., … Serra, M. (2016). Sex differences in the outcome of juvenile social isolation on HPA axis function in rats. Neuroscience. https:// doi.org/10.1016/j.neuroscience.2016.02.009 25. Shao, F., Han, X., Shao, S., & Wang, W. W. (2013). Adolescent social isolation influences cognitive function in adult rats. Neural Regeneration Research. https://doi.org/10.3969/j.issn.16735374.2013.11.008 26. Sun, H., Jia, N., Guan, L., Su, Q., Wang, D., Li, H., & Zhu, Z. (2013). Involvement of NR1, NR2A different expression in brain regions in anxiety-like behavior of prenatally stressed offspring. Behavioural Brain Research. https://doi.org/10.1016/j.bbr.2013.08.044 27.

arTPJ underlies inhibitory control mechanism domain generally in attention reorientation and theory of mind: a TMS study Tong Liu Previous neuroimaging researches have shown that anterior right temporoparietal junction (arTPJ) is activated similarly in a common inhibitory control process during attention reorientation and theory of mind, but those type of studies lack the required causal power. Previous transcranial magnetic stimulation (TMS) studied had the causal power but did not test the domain generality of arTPJ functions. The current study aimed to causally test if arTPJ underlies inhibitory control mechanisms in a domain general fashion by using TMS to deactivate the region and test participantsâ&#x20AC;&#x2122; performances in attention reorientation and theory of mind tasks. In both tasks, performance became worse with TMS deactivation when inhibitory control was required, and the performance decrease are correlated between the two tasks. This suggested a common inhibitory control mechanism afforded by arTPJ in both tasks. However, the above conclusion could be challenged due to the poor spatial resolution of TMS. It was possible that two separate regions, each affording a type of inhibitory control are both activated. Two follow-up experiments were proposed to address the problem.

Introduction

The ability to inhibit some behaviours, responses or mindsets is very important to many cognitive processes. Developmentally, following the emergence of inhibitory control as an executive function, many other abilities also start to develop, such as symbolic thinking and theory of mind. Anterior right temporoparietal junction (arTPJ) is a region possibly responsible for the inhibitory functions, which is tightly linked to many cognitive processes with an inhibitory control component in it. Previous researches have shown that arTPJ was important to attention reorientation, which involved inhibiting automatic attention towards salient stimuli and focus on the task-relevant ones instead (Decety and Lamm, 2007). Theory of mind, the ability to understand others’ belief, also involves inhibitory control. A more salient perspective of self needs to be inhibited before one can reason about perspective of others, especially when what they believe is different from reality (Carlson, Moses, & Breton, 2002). Previous research indicated that the inhibition of a salient perspective also involved arTPJ (Hartwright, Apperly, & Hansen, 2012). In a review article pooling previous researches on arTPJ together, the researchers found that the same region is responsible for inhibitory control not just in one domain, but across many different and seemingly unrelated higher-order cognitive tasks (Krall et al., 2015). However, almost all of the above studies are neuroimaging studies. It has been repeatedly suggested that researchers need to be careful interpreting neuroimaging results, as they only show the correlation between a mental task and brain regions activated (Iacoboni, 2009; Ruff et al., 2007). Therefore, neuroimaging correlational evidences are not sufficient to make causal conclusions. Transcranial magnetic stimulation (TMS) studies could temporarily deactivate a specific brain region and test its effect on the mental processes, which is a viable follow-up manipulation to test for causations (Uddin, MolnarSzakacs, Zaidel, & Iacoboni, 2006).

Torriero, Oliveri, & Caltagirone, 2008), were found to be disrupted due to the deactivation. The results could suggest a causal explanation of the role of arTPJ on higher mental processes. However, although previous neuroimaging researches suggested a domain general inhibitory control mechanism located in arTPJ, each of those TMS studies regarded only one kind of cognitive ability. In sum, previous neuroimaging studies in arTPJ could not show its causal role across many cognitive processes, and TMS studies failed to capture its domain-generality in inhibitory control. The question is if there is an experiment to test and possibly support both the domain-generality and the causality of the inhibitory control function played by arTPJ at the same time. In a 2016 study by Krall et al., the researchers tried to disrupt arTPJ functioning with TMS in two tasks: attention reorientation and theory of mind, and then looked for correlation in the degree of disruption, in order to answer the above question. In the attention reorientation task, a salient arrow cue pointed either to the left or to the right. A target could appear at either side of the arrow. The target was considered valid if it appeared at where the arrow was pointing to, and invalid if it appeared opposite to the direction of the arrow. Participants were asked to locate if the target was at the left or right of the arrow by pressing buttons. In theory of mind tasks, participants were asked to answer questions based on a cartoon, some of which required taking the mindset of the characters (false-belief conditions) and the others didn’t (true-belief conditions). It has been reasoned that attending to invalid targets and answering false-belief questions would require inhibitory control. The researchers deactivated arTPJ with TMS and compared the result to that of control group with only vertex stimulation. They found that deactivating arTPJ with TMS would disrupt the tasks requiring inhibitory control only, and the disruption in two tasks are correlated. This would causally suggest that arTPJ is important to inhibitory control in a domain general fashion. Major Results

There have been studies deactivating arTPJ with TMS, and higher-order mental activities, such as In the attention reorientation task, inhibitory control morality (Young, Camprodon, Hauser, Pascual- was required when trying to attend to the invalid Leone, & Saxe, 2010) and theory of mind (Costa, target. When seeing a salient cue like an arrow, 90

attention would be automatically shifted to where neuroimaging, but with greater causal power. the arrow was pointing to, even if the arrow cannot always predict target location (Tipples, 2002). Therefore, when trying to locate invalid targets, this automatic attention orientation towards the salient cue needed to be inhibited (Butler & Zacks, 2006). After arTPJ was deactivated with TMS, the performance, as measured by reaction time and response accuracy, became worse compared with the vertex stimulation group when the targets were invalid, but had no change when the targets were valid (figure 1a). This suggests that the inhibitory control when locating invalid targets described above was carried out by arTPJ in the attention reorientation task. In the theory of mind task, inhibitory control was required when trying to answer false-belief questions. The perspective from oneself is always the more salient one, but in order to reason about false-belief questions, participants would need to take the characters’ perspective, especially when the characters may not know what the viewer know. As the result, the more salient perspective of self must be inhibited to answer false-belief questions correctly (Carlton et al., 2002). When the inhibitory control mechanism is diminished, such as in children with specific brain injuries, the theory of mind ability would also suffer (Dennis, Agostino, Roncadin, & Levin, 2009). After arTPJ was deactivated with TMS, the performance, as measured by response error rate, became higher for false-belief questions compared with the vertex stimulation group, but had no change for true-belief ones (figure 1b). This suggests that the inhibitory control when reasoning about false-beliefs described above was carried out by arTPJ in the theory of mind task.

Discussion The current research found that using TMS to deactivate arTPJ would disrupt the ability to reorient attention away from salient cues, and to inhibit the self perspective to reason about other’s beliefs. Moreover, the disruption of the two abilities correlate with each other. The result suggest that both attention reorientation and theory of mind share a common inhibitory control mechanism, for which arTPJ is responsible. The researchers offered a possible explanation for the exact mechanism of how arTPJ carries out the inhibitory control function. They applied the “circuit breaker theory” and argue that arTPJ could breach the salience-driven expectation about a situation, and thus initiate an attention reorientation. More specifically, the dorsal attentional network for focused attention is breached and the ventral attentional network for diffused attention is triggered (Corbetta, Patel, & Shulman, 2008). The current finding that a common inhibitory control mechanism underlying theory of mind and attentional control could extend the theory. It is possible that the circuit breaker theory applies not only in attention, but also in other domains where breaking of expectation is needed.

Last but not least, the effect of arTPJ deactivation on the performance disruption for both tasks are correlated to one another (figure 1c). This further suggests that attention reorientation and theory of mind reasoning share the same inhibitory control mechanism, and when that mechanism is temporarily deactivated, both abilities will be Critical analysis similarly affected. Previously, a common activated brain region was found for the two abilities across In this study, significant impairment of attention many neuroimaging studies (Krall et al., 2015). reorienting ability and theory of mind ability was The current interpretation fits previous results in 91

found comparing the inhibition of arTPJ and control, suggesting that arTPJ plays a crucial role in attention reorienting and false belief. In this discussion section of this paper, the experimenters address one possible attack against their finding, which is the limited spatial resolution of TMS might not have exclusively stimulated the arTPJ as intended, which is to say that the posterior rTPJ might also be inhibited due to some ‘spillover’ of stimulation. The experimenter dismissed this counter-argument with the evidence that the spatial spread of direct TMS stimulation is approximately 3 to 4 mm (Valero-Cabré, Payne, & Pascual-Leone, 2007; Valero-Cabré, Payne, Rushmore, Lomber, & Pascual-Leone, 2005) while the two activation peaks of anterior RTPJ and posterior RTPJ is located 16.64 mm apart, thus the spill-over modulatory effect on posterior RTPJ should be considered minor (Krall et al., 2016).

reviewed experiment, but have participants do both attention reorienting and false belief tasks in a fMRI scanner. TMS technique will not be practiced. This way, experimenters can investigate with more specificity which brain regions will be activated during different tasks. Both a univariate analysis for the region of activation, and a multivariate analysis for the specific pattern of activation within a region will be carried out. If a different pattern of activation could be observed for the attention reorientation task and for the theory of mind task, it could provide evidence that the arTPJ is constituted by distinct smaller regions. Otherwise, it would seem that the sub-division of arTPJ will not harm the reviewed experiment.

As mentioned in the introduction, more research is needed to give causal power to the neuroimaging study. Since TMS does not have the required spatial resolution, behavioural manipulations could be However, even when the posterior RTPJ’s applied instead before a reliable and noninvasive activation is addressed, the spatial resolution of technique to deactivate more specific regions of TMS cannot be ignored. There have been studies the brain is developed. Again, the exact same kind suggesting that the RTPJ could be further divided of testing batteries will be used in this experiment. into subregions by their structural and functional The participants will first randomly do one of the connectivity (Mars, 2011), which is to say that the two tasks. However, they now need to do the task RTPJ may an overarching regions that constitutes repeatedly, to a point where they are fatigue, and of many smaller regions, each has a function of its performance on the current task starts to become own. In this case, the overarching functions of RTPJ worse. After that, the remaining task will be done in social cognition and attention reorientation tasks normally. Those in the control group will do other could actually be the functions of the sub-regions. cognitive demanding tasks without requirements For example, distinct subregions of RTPJ could on inhibitory control, for example, arithmetic tasks. be responsible for the attention-reorientation task Participants will be divided into four groups: those and false belief tasks, but due to the limited spatial who got fatigue with the attention reorientation resolution of TMS, we could not distinguish them task and tested on theory of mind task, those and only see them as a whole, and consequently who got fatigue with theory of mind task and could not make the distinction between the tested on attention reorientation task, and those functions either. who got fatigue in arithmetic tasks and tested on the theory of mind task and those who also got Future direction fatigue in arithmetic tasks and tested on attention reorientation task. If when participants got fatigue An important future direction is to investigate the in one of the two tasks requiring inhibitory control challenge that different subregions in arTPJ have perform worse in the other task than those who distinct functions. The experimenter would need got fatigue in the control task, it would provide a technique with higher spatial resolution, such evidence that the attention reorientation and as functional magnetic resonance imaging(fMRI) theory of mind at least partially share a common rather than keep using TMS. inhibitory control mechanism, arguably caused by arTPJ. Otherwise, it would suggest that the control A possible approach is to test the hypothesis that mechanisms in the two abilities are different, and the arPTJ is constituted by distinct subregions. the reviewed result was only found due to the To do that, the experimenters could replicate the limited spatial resolution of TMS. 92

Reference 1. Butler, K. M., & Zacks, R. T. (2006). Age deficits in the control of prepotent responses: Evidence for an inhibitory decline. Psychology and Aging, 21(3), 638. 2. Carlson, S. M., Moses, L. J., & Breton, C. (2002). How specific is the relation between executive function and theory of mind? Contributions of inhibitory control and working memory. Infant and Child Development, 11(2), 73–92. 3. Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: from environment to theory of mind. Neuron, 58(3), 306–324. 4. Costa, A., Torriero, S., Oliveri, M., & Caltagirone, C. (2008). Prefrontal and temporo-parietal involvement in taking others’ perspective: TMS evidence. Behavioural Neurology, 19(1–2), 71– 74. 5. Decety, J., & Lamm, C. (2007). The Role of the Right Temporoparietal Junction in Social Interaction: How Low-Level Computational Processes Contribute to Meta-Cognition. The Neuroscientist, 13(6), 580–593. 6. Dennis, M., Agostino, A., Roncadin, C., & Levin, H. (2009). Theory of mind depends on domaingeneral executive functions of working memory and cognitive inhibition in children with traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 31(7), 835–847. 7. Hartwright, C. E., Apperly, I. A., & Hansen, P. C. (2012). Multiple roles for executive control in belief–desire reasoning: Distinct neural networks are recruited for self perspective inhibition and complexity of reasoning. NeuroImage, 61(4), 921–930. 8. Iacoboni, M. (2009). Imitation, empathy, and mirror neurons. Annual Review of Psychology, 60, 653–670. 9. Krall, S. C., Rottschy, C., Oberwelland, E., Bzdok, D., Fox, P. T., Eickhoff, S. B., … Konrad, K. (2015). The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis. Brain Structure and Function, 220(2), 587–604. 10. Krall, Sarah C., Volz, L. J., Oberwelland, E., Grefkes, C., Fink, G. R., & Konrad, K. (2016). The right temporoparietal junction in attention and social interaction: A transcranial magnetic stimulation study: RTPJ-TMS in Attention and Social Interaction. Human Brain Mapping, 37(2), 796–807. 11. Mars, R. B., Sallet, J., Schuffelgen, U., Jbabdi, S., Toni, I., & Rushworth, M. F. S. (2012). ConnectivityBased Subdivisions of the Human Right “Temporoparietal Junction Area”: Evidence for Different Areas Participating in Different Cortical Networks. Cerebral Cortex, 22(8), 1894–1903. 12. Ruff, C. C., Bestmann, S., Blankenburg, F., Bjoertomt, O., Josephs, O., Weiskopf, N., … Driver, J. (2007). Distinct causal influences of parietal versus frontal areas on human visual cortex: evidence from concurrent TMS–fMRI. Cerebral Cortex, 18(4), 817–827. 13. Tipples, J. (2002). Eye gaze is not unique: Automatic orienting in response to uninformative arrows. Psychonomic Bulletin & Review, 9(2), 314–318. 14. Uddin, L. Q., Molnar-Szakacs, I., Zaidel, E., & Iacoboni, M. (2006). rTMS to the right inferior parietal lobule disrupts self–other discrimination. Social Cognitive and Affective Neuroscience, 1(1), 65–71. 15. Valero-Cabré, A., Payne, B. R., & Pascual-Leone, A. (2007). Opposite impact on 14 C-2deoxyglucose brain metabolism following patterns of high and low frequency repetitive transcranial magnetic stimulation in the posterior parietal cortex. Experimental Brain Research, 176(4), 603–615. 16. Valero-Cabré, A., Payne, B. R., Rushmore, J., Lomber, S. G., & Pascual-Leone, A. (2005). Impact of repetitive transcranial magnetic stimulation of the parietal cortex on metabolic brain activity: a 14 C-2DG tracing study in the cat. Experimental Brain Research, 163(1), 1–12. 17. Young, L., Camprodon, J. A., Hauser, M., Pascual-Leone, A., & Saxe, R. (2010). Disruption of the right temporoparietal junction with transcranial magnetic stimulation reduces the role of beliefs in moral judgments. Proceedings of the National Academy of Sciences, 107(15), 6753–6758.

Depression and Neuropathic Pain: An Investigation into Future Novel Treatments Methods Michael Morton1 Depression and neuropathic pain are often comorbid in their presentations in individuals. Many antidepressants have been developed to target depression and some have also been used to effectively treat neuropathic pain. These include selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs) medications. Endocannabinoids have also been implicated in helping to alleviate both neuropathic pain and depressive-like behaviours. Ways to increase endocannabinoid signaling have since been investigated. One way is through inhibition of fatty acid amide hydrolases. Through this inhibition, endocannabinoid signaling is more robust and their antinociceptive effects are better felt. There is also a relationship between depression, pain, endocannabinoids, and neuronal changes in the hippocampus. However, the effects of fatty acid amide inhibition or increased endocannabinoid signaling as a treatment for pain induced depression is still being investigated. In a recent study done by Jiang et al. (2018) using rat models, the impacts of fatty acid amide hydrolase (FAAH) inhibition was investigated. Both a systemic and peripheral FAAH inhibitor were investigated for their efficacy in treating pain-induced depression. It was found that the systematic FAAH inhibitor improved depressive like behaviours induced by neuropathic pain. This improvement in depressive-like behaviours was independent of the antinociceptive actions of the peripheral FAAH inhibitor. Jiang et al. (2018) also determined that the systemic FAAH inhibitor had more impact on hippocampal neuronal change and proliferation and it was better able to reverse the negative changes induced via neuropathic pain and depression. These results suggest that inhibition of fatty acid amide hydrolase through systemic mechanisms could be an alternative therapeutic treatment for individuals with comorbid pain and depression. Key words: depression; neuropathic pain; fatty acid amide (FAA); fatty acid amide hydrolase (FAAH); endocannabinoids; antidepressants; therapeutic treatment; URB597; URB937

Introduction Background

Depression is a phenomenon that has been investigated by many researchers, with increasing focus on finding effective treatment methods. Throughout these studies, neuropathic pain has come about as both a comorbidity and a potential cause for depression (Nicholson & Verma, 2004). Individuals suffering from neuropathic pain are often already suffering from a mood disorder and, with the onset of the pain, the disorderâ&#x20AC;&#x2122;s effects become more robust. They can also develop the disorder alongside the progression of their pain (Nicholson & Verma, 2004). As a result of this, research has investigated using antidepressants as a treatment for both depression and neuropathic pain. Some of the typical pharmacological treatments for depression include: serotonin norepinephrine reuptake inhibitors (SNRIs), selective serotonin reuptake inhibitors (SSRIs), and tricyclic antidepressants (TCAs) [Saarto & Wiffen, 2007; Nicholson & Verma, 2004]. Neuropathic Pain Endocannabinoids

Treatments

and

Antidepressants have been found to also treat neuropathic pain with TCAs and SSRIs being the most effective in treating standalone neuropathic pain (Saarto & Wiffen, 2007; Nicholson & Verma, 2004). These antidepressants have since been used to treat depression-pain comorbidities, with varying effectiveness (Nicholson & Verma, 2004). The endocannabinoid system has also been implicated in treating pain. Endocannabinoid signaling is involved in the nociceptive pathway and impacts antinociception and downregulation of pain (Luongo, Maione, & Di Marzo, 2014; Kwilasz, Abdullah, Poliks, Litchman, & Negus, 2014). This effect persists across many animal models. Endocannabinoids can also reduce neuropathic pain induced by anitneoplastic drugs (Vera, Cabezos, MartĂn, & Abalo, 2013). Specifically, the cannabinoid receptor 1 and 2 subtypes (CB1 & CB2, respectively) have been targets of interest for further research (Desroches, Charron, Bouchard, & Beaulieu, 2014; Brownjohn & Ashton, 2012). These

receptors are activated by either 2-arachidonyl glycerol (2-AG) or anadamide (AEA) and display a dose-response relationship with antinociception (Desroches et al., 2014). AEA is degraded by the enzyme fatty acid amide hydrolase (FAAH). Targeting this degradation has been implicated as a way to increase endocannabinoid signaling (Hama et al., 2014). By decreasing FAAH activity, AEA levels remain unaffected, leading to increased endocannabinoid signaling in the nociceptive pathway. (Hama et al., 2014; Cravatt et al., 2001). This has led to the investigation of FAAH inhibition as a treatment for pain (Cravatt et al., 2001). The co-morbid link between neuropathic pain and depression has also sparked research into the potential role of endocannabinoids for antidepressant effects. CB1 Receptor Implications

In a study using diabetic male Wistar rats, AEA induced an improvement in the depression-like behaviour exhibited by these rats, as measured by the Forced Swim Test (FST). It was also able to induce neuroprotective and neuroadaptive changes and improve depressive-like behaviours by acting as a CB1 receptor agonist (de Morais et al., 2016). In another study using rat models, the FAAH inhibitor URB597, which acts on CB1 receptors and prevents the degradation of AEA, was also able to elicit antidepressant-like effects (Gobbi et al., 2005). It impacted rat performance on the Tail Suspension Test (TST) and FST, resulting in performance similar to non-depressed controls (Gobbi et al., 2005). Furthermore, URB597 increased the firing of norepinephrine neuron firing in the locus ceruleus and serotonergic neurons in the dorsal raphe nucleus (Gobbi et al., 2005). Reduced activity of these neurotransmitters has been associated with the development of depression. Therefore, URB597â&#x20AC;&#x2122;s ability to increase this activity displayed antidepressant characteristics (Gobbi et al., 2005). As endocannabinoids primarily function by activating the CB1 receptor, increasing this signaling pathway can help to improve mood and displays an antidepressant effect (Zhou et al., 2017). In particular, blocking the CB1 pathway via genetic modifications or drugs leads to depression-like behaviour, and development of symptoms like anhedonia, decreased appetite,

weight loss, and low libido, all of which are associated with depression (Zhou et al., 2017). In humans, genetic polymorphisms in CB1 receptors and drug induced endocannabinoid signaling pathway damage increase the risk for depression development and antidepressant resistance (Zhou et al., 2017). Additionally, in depressed Wistar Kyoto rats, CB1 receptor expression was decreased in the hippocampus, dorsal striatum, and nucleus accumbens (Smaga et al., 2017). This caused dysregulation of the endocannabinoid system, and led to depression pathogenesis (Smaga et al., 2017) The results of both animal and human studies have shown that the endocannabinoid signaling pathway, specifically the CB1 receptor signaling pathway, is related to depression development, and posits an area for antidepressant targeting (Zhou et al., 2017).

Antidepressant Effects of Cannabinoids and Endocannabinoids

decrease in hippocampal neurogenesis and neuronal proliferation (Malberg, 2004). As a result, depressed patients have reduced hippocampal volume, especially in the dentate gyrus (Malberg, 2004). This relationship between depression and adult hippocampal cell neurogenesis has implicated neurogenesis in the pathophysiology of depression (Malberg, 2004). Similarly, neuropathic pain involves changes in the adult hippocampus. In both animal and human studies, pain caused hippocampal volume loss, pathophysiolgocial changes in the hippocampus, and increased neurodegeneration (Fasick, Spengler, Samankan, Nader, & Ignatowski, 2015). Neuropathic pain is also correlated with reduced neurogenesis and decreased neuroplasticity marker expression (Dellarole et al., 2014; Tyrtyshnaia, Manzhulo, Sultanov, & Ermolenko, 2017). These all show an interaction of depression and neuropathic pain in hippocampal volume and neurogenesis changes. As a result, research has investigated targeting these hippocampal changes for use in depression treatment Many antidepressant medications increase neural proliferation and hippocampal brain derived neurotrophic factor (BDNF) levels. This contributes to both hippocampal neuron turnover and survival (Sairanen, Lucas, Ernfors, CastrĂŠn, & CastrĂŠn, 2005). SNRIs have shown both an improvement of depression symptoms as well as increased cAMP levels and growth factor expression, increasing hippocampal neuron survival and proliferation (Fasick et al., 2015).

Endocannabinoid signaling has also been investigated in reversing the effects of pain and depression on the hippocampus. Endocannabinoid signaling has been shown to enhance hippocampal synaptic plasticity and neuronal proliferation (Zhou et al., 2017). Chronic application of a CB1 receptor agonist increased nerve growth in rats (Zhou et al., 2017) and elevated AEA levels, which caused increased cell proliferation in the mouse hippocampus (Cravatt et al., 2001). Cannabinoids have also been found to increase BDNF levels in the hippocampus, providing a neural protective factor (Zhou et al., 2017). In a study using mouse neural stem cells, CB1 and CB2 receptors were found to be highly expressed. With activation of these receptors, proliferation of neural stem cells was greatly increased, indicating that endocannabinoid signaling pathways stimulate neural proliferation from precursor cells (Molina-Holgado et al., 2007).

Interestingly, activation of this same endocannabinoid system can have antidepressant effects. In addition to the information discussed above, also inhibits monoamine oxidase (MAO) activity, allowing for it to alter monoamine levels in the brain. Cannabinoids also produce effects similar to TCAs and SSRIs by modifying the reuptake of serotonin and norepinephrine. Inhibiting FAAH degradation of AEA activates CB1 dependent serotonin and norepinephrine neurons in the brain (Zhou et al., 2017). Additionally, an antidepressant-like effect was elicited with activation of CB1 receptors in the dentate gyrus of a rat hippocampus. This points to the hippocampal endocannabinoid signaling pathway as a target for antidepressant treatment (McLaughlin, Hill, Morrish, Gorzalka, 2007). This evidence suggests that endocannabinoids, and the CB1 signaling pathway, have biologically similar effects to Jiang et al. Study traditional antidepressant medications.

Hippocampal Changes and Endocannabinoid Despite the comorbidity of depression and pain, and the involvement of endocannabinoids in both, Involvement much of the research existing focuses on these Of final interest are hippocampal changes in pain-depression conditions separately. Little investigation has been comorbid individuals. Depressed individuals exhibit a done involving endocannabinoid signaling in pain 96

induced depression, or using endocannabinoid signaling as a possible treatment method for pain-induced depression. In their study, Jiang et al. (2018) investigated the effects that FAAH inhibition would have on AEA endocannabinoid signaling, and its treatment efficacy on neuropathic pain-induced depression. They investigated both the systematic FAAH inhibitor URB597 and the peripheral FAAH inhibitor URB937. Male Wistar rats with chronic constriction injury (CCI) to the sciatic nerve (inducing depression) were treated with either URB597 or URB937. Various depression tests were used to determine any changes in depressive-like behaviour before and after treatment. Their findings indicated that URB597 was better able to improve depressivelike behaviours caused by neuropathic pain, and it also increased hippocampal neurogenesis. This pointed to systemic FAAH inhibitors as possible antidepressant treatments and helped to further the research on treatment of comorbid depression and pain (Jiang et al., 2018).

increased both serum and hippocampal AEA levels (URB937 only increased serum levels). Additionally, URB597 prevented CCI-induced destruction of BDNF mRNA and was also able to increase levels of this mRNA in the CCI rats (Jiang et al., 2018). Of final interest is the finding that URB597 was able to reverse the CCI-mediated decrease in CB1 receptor mRNA levels in the hippocampus while also increasing the levels of AEA mRNA (Jiang et al., 2018).

MAJOR RESULTS

Figure 1. Adapted from Jiang et al. (2018) Anesthesia and Analgesia, 127(6), 1-11. CCI-induced depressed rats treated with URB597 showed a statistically significant change in their depressive like behaviours. URB597 was able to decrease the latency to feed in the novelty suppressed feeding test (NSFT; C) and the immobility in the forced swim test (FST; D) in CCI-induced depressed rats. URB597 was also able to relieve CCI induced mechanical hypersensitivity in the Von Frey Test (VFT; A) URB597 did not have an impact on the distance travelled during the open field test (OFT; B). URB937 did not show any significant changes with treatment in CCI-induced depressed rats.

In their study, Jiang et al. (2018) used male Wistar rats with CCI to their sciatic nerve. This CCI was able to induce neuropathic pain in these rats, as well as contribute to the development of depressivelike behaviours. The CCI significantly impacted immobility and passivity in the forced swim test (FST) and decreased the latency to feed in the novelty suppressed feeding test (NSFT). Both of these measures indicate that the rats exhibited depressive-like behavior 15 and 29 days post CCI (Jiang et al., 2018). After CCI and the induction of depression in the rats, some were administered the systemic FAAH inhibitor URB597 while others were administered the peripheral FAAH inhibitor URB937. FST and NSFT were then re-completed 29 days post-surgery in the rats after treament with an FAAH inhibitor. Any changes in depressive-like behavior was recorded. (Jiang et al., 2018). One of their major findings revealed that URB597 lessened depressive-like behaviours in the rats by decreasing their immobility time in the FST and their latency to feed in the NSFT. Interestingly, URB937 did not have this same effect (Jiang et al., 2018). In terms of hippocampal changes, URB597

Figure 2. Adapted from Jiang et al. (2018) 97

Anesthesia and Analgesia, 127(6), 1-11. Rats with neuropathic (CCI) induced depression treated with URB597 showed increased the levels of AEA mRNA in the hippocampus and serum. URB597 was also able to reverse the decrease in CB1 receptor mRNA in the hippocampus caused by CCI. URB937, aside from increasing serum AEA levels, had no other significant effects in control or CCI-induced b depression rats. The antidepressant effect of FAAH inhibitors, specifically URB597, was under investigation in Jiang et al.’s (2018) study. They found that it had a robust antidepressant effect, almost always significantly reversing negative performance in the FST and NSFT, as well as increasing AEA and CB1 mRNA levels. In a similar study, Kwilasz et al. (2014) investigated the effects of URB597 in pain-stimulated and pain-depressed rats. They found that it was able to increase both the brain and plasma levels of AEA (Kwilasz et al, 2014). This fell in line with Jiang et al.’s (2018) findings, providing support for their increase in plasma and hippocampal AEA levels with URB597 treatment. In addition, URB597 treatment was also found to decrease depressive-like symptoms in female rats with THC induced depression (Realini et al., 2011). Rats treated with URB597 showed decreased passivity in the FST, as well as decreased anhedonia and increased social activity (Realini et al., 2011). These results echo those obtained in Jiang et al.’s study, showing the antidepressant effects elicited by URB597. Overall, Jiang et al.’s (2018) findings in pain-induced depressed rat models align with the preexisting literature. They showed that systemic FAAH inhibition elicits antidepressant like effects and that endocannabinoid signaling and CB1 receptor pathways have treatment implications in both neuropathic pain and depression. However, their findings of the efficacy of systemic FAAH inhibition as a treatment for pain induced depression is a novel finding, furthering the literature on this comorbidity

. a

Figure 3. Adapted from Realini et al. (2011) Neuropharmacology, 60, 235-243. Female rats with THC induced depression were treated with URB597 and subjected to the first swim test. Overall, female rats treated with showed less passivity in the FST (a), with a robust decrease in immobility compared to control and non-treated rats (b).

CONCLUSIONS The major conclusion of Jiang et al.’s (2018) study was that URB597, a systemic FAAH inhibitor, helped to improve depressive-like behaviours induced by neuropathic pain, as well as contributed to increased hippocampal neurogenesis and enhanced endocannabinoid signaling. This finding suggests that URB597 could be an alternative therapeutic treatment to pain-depression comorbidities. They also implicated FAAH as a possible antidepressant drug target, mainly through systemic inhibition (Jiang et al., 2018). The pre-existing literature indicated that URB597 has been previously used to treat neuropathic pain and stress-induced depression, but not for the treatment of pain-induced depression, as done in the current study. Literature has also indicated that CCI or stress-induced depression causes a decrease in overall hippocampal neurogenesis, as well as a decrease in endocannabinoid signaling and CB1 receptor mRNA. Through treatment with URB597, these effects were reversed in the current study. There was also a robust increase in CB1 receptor mRNA levels and enhanced overall hippocampal neurogenesis (Jiang et al., 2018). The obtained results aligned with literature previously reviewed

as well as with other experimental findings the exists to suggest an effect of URB597 or systemic authors consulted before undertaking the current FAAH inhibition on comorbid pain-depression, study. allowing this study to contribute to the literature on this topic, as well as suggest novel therapeutic Interestingly, the effects of URB597 on both techniques. neuropathic pain and stress-induced depression were known, but its efficacy was contested based CRITICAL ANALYSIS on the theory that it was acting via peripheral antinociception. The authors acknowledged this by using a peripheral FAAH inhibitor (URB937) and Jiang et al.’s (2018) study investigated the were able to show that there was a segregation therapeutic efficacy of systemic FAAH inhibition on between the antinociceptive and antidepressant comorbid pain and depression. Their experimental effects of URB597 (Jiang et al., 2018). URB597 results indicated a considerable therapeutic effect suppressed neuropathic pain via peripheral on both neuropathic pain and depressive-like endocannabinoids signaling pathways and behaviour in rat models. This provided further provided antidepressant effects through cortical insight into novel antidepressant treatments with and limbic areas (Jiang et al., 2018). These results efficacy in treating comorbid pain-depression. helped to better understand the mechanism of Jiang et al.’s (2018) results also supported action of URB597 as both an antidepressant and previous findings that URB597 and systemic FAAH analgesic. They also echoed results of similar studies inhibition was effective in modulating the effects previously reviewed indicating antinociceptive of neuropathic pain and improving depressive-like effects of URB597 (Luongo et al., 2014; Kwilasz et behaviours. Further investigation into the use of FAAH inhibition as an antidepressant drug target, al., 2014; Desroches et al., 2014). rather than a systemic inhibitor, is still needed. The authors also indicated that, at normal Additionally, Jiang et al.’s (2018) experiment clinical dosages, antidepressant medications involved the injection of URB597 and URB937 15 only marginally help to facilitate hippocampal days after CCI causing neuropathic pain. The delay neurogenesis in depressed patients (Jiang et al., between pain induction and the administration of 2018). In using URB597, hippocampal neurogenesis URB597 or URB937 could impact its effects. Indeed, in pain-induced depressed rats was markedly studies have shown that URB597 administration increased, echoing literature finding that URB597 had an impact on AEA levels in the brain facilitates hippocampal neurogenesis through (Cravatt & Litchman, 2003), as well as on overall endocannabinoid signaling. This helps it to reverse endocannabinoid and CB1 receptor levels (Kwilasz the negative effects of depression or neuropathic et al., 2014), within 2 hours of administration. pain (Jiang et al, 2018; Zhou et al., 2017; Molina- Different or more pronounced impacts on Holgado et al., 2007). The authors believed that this depressive behaviour and pain perception could increased hippocampal neurogenesis with URB597 be identified with drug administration closer to treatment contributed to its antidepressant effects CCI. The authors themselves indicated this as a limitation to their study, and they suggested other (Jiang et al., 2018). studies examine the impact of time delays on The results obtained in Jiang et al.’s (2018) study URB597 or URB937 effects (Jiang et al., 2018). indicate a new finding, as URB597 and FAAH inhibition have been looked at to treat neuropathic Furthermore, the authors determined that URB597 pain and depression separately, but not together. had on impact on hippocampal neurogenesis. In using neuropathic pain to induce depression, It sufficiently increased neurogenesis, as well as both the antinociceptive and antidepressant increased AEA mediated CB1 receptor activation. effects of URB597 were able to be investigated. However, the authors did not investigate whether The findings obtained also suggested the use of preventing hippocampal neurogenesis would systemic FAAH inhibitors as potential alternatives block the antidepressant effects of URB597 (Jiang to antidepressants for treating pain-depression et al., 2018). In mediating hippocampal changes, comorbidities (Jiang et al., 2018). Little literature URB597 was found to increase the levels of BDNF 99

mRNA and BrdU+ cells in the hippocampus of the dentate gyrus (Jiang et al., 2018). Antidepressant medications have also been implicated in increases in BDNF levels and BrdU+ cell populations (Sairanen et al., 2005). As there is a similarity in the effects both medications have on hippocampal neurogenesis, the authors should investigate whether URB597 elicits its antidepressant effects through solely hippocampal changes or in conjunction with alternative mechanisms. Understanding the mechanism of action of URB597 as an antidepressant can help to better understand whether FAAH inhibition should be a target of antidepressant medications, or if URB597 or other similar systemic inhibitors alone are sufficient to induce antidepressant effects. Although their study was focused on the effects of URB597, the authors could also investigate how URB597â&#x20AC;&#x2122;s antidepressant effects compare to other commonly used antidepressants, such as SSRIs, SNRIs, or TCAs. These antidepressants have been used to treat both neuropathic pain and depression, but their effects on pain modulation have been independent of their effects on depression (Saarto & Wiffen, 2007). URB597, conversely, was able to modulate both pain perception and depressivelike behaviour in the rat models used in this study. This suggests that it could be an alternative antidepressant therapy. By further investigating how comparable the effects of URB597 are to clinically supported antidepressant treatments, it can help determine whether FAAH inhibition is an appropriate area for novel depression therapeutic treatments. It would also help to determine whether URB597 could be more effective in modulating pain induced depressive-like behaviours.

used antidepressant medications in stress-induced depression models. However, more investigation should be done to see if these comparable effects persist in pain-induced depression models, with different dosages (higher or lower), and with shorter or longer treatment administration periods. The efficacy of URB597 as an adjunctive medication to other therapies, such as cognitive behavioural therapy (CBT), for treating both stress-induced and pain-induced depression also indicates an area of further research, as antidepressant medications are also used as adjunctive therapies.

The results obtained in this experiment echo the literature reviewed, as systemic FAAH inhibition was able to augment both neuropathic pain symptoms and depression symptoms in rat models upon injection (Jiang et al., 2018). Separately, effects of FAAH inhibition on pain and on stressinduced depression have been presented, and in these studies, there was a noticeable reduction in related symptoms for both conditions. In combining pain and depression Jiang et al. (2018) were able to further support the effects of FAAH inhibition on pain and stress-induced depression separately, as well as present the novel finding that it has a considerable impact on pain-induced depression. FUTURE DIRECTIONS Future research into the use of systemic FAAH inhibition as an effective antidepressant treatment still remains to be completed. This research should investigate if time delays between systemic inhibitor administration and depression induction adversely impacts treatment efficacy, as well as how treatment efficacy compares to clinically used antidepressant medications. These studies will help to better understand whether systemic FAAH inhibitors, such as URB597, should be used as antidepressant treatments and how well they compare to currently used antidepressants. Jiang et al.â&#x20AC;&#x2122;s (2018) study was able to show that URB597 elicits robust antidepressant effects, echoing the results obtained in previous studies using stress-induced depression, but that these antidepressant effects were still pronounced in pain-induced depression. Daily administration of URB597 intraperitoneally was sufficient to elicit noticeable effects, so a similar method should be

Indeed, URB597 elicits similar antidepressant effects to the TCA imipramine. It was also able to amplify the effects of imipramine when applied in an inactive form (Adamczyk, Golda, McCreary, Filip, & PrzegaliĹ&#x201E;ski, 2008). A similar effect was noted with the commonly used SSRI fluoxetine. URB597 treatment generated a decrease in immobility during the FST in depressed rat models comparable to that of fluoxetine. This experiment also observed an interaction between URB597 and the serotoninergic system (Umathe, Manna, & Jain, 2011). Overall, this indicates that URB597 has comparable effects to commonly 100

used in other studies. A future study could involve intraperitoneal administration of URB597, as well as commonly used antidepressants, such as SSRIs, SNRIs, or TCAs. The effects of these drugs can then be investigated, and the impacts of differing dosages, temporal delays, and treatment length and persistence can be observed. This can help researchers to better understand if URB597 is a potent antidepressant, and if its effects are truly comparable to other antidepressant medications. Additionally, side effects of the drugs should also be observed to see if URB597 has similar side effects to commonly used antidepressant medications.

suggest that inhibition of FAAH can be a possible drug target for novel antidepressants. If other inhibitors do not elicit comparable effects to URB597, it could indicate that URB597 mediates depressive-like behaviour in a unique way, such as through the interaction of endocannabinoid signaling, hippocampal neurogenesis changes, and neurotransmission systems (as it has been implicated in the serotonergic system). The mechanism these inhibitors target (the endocannabinoid signaling pathway) should also be further investigated for its possible involvement in the pathology of depression.

As Jiang et al. (2018) indicated in their article, experimental limitations included the delay between CCI and drug administration and the inability to test whether prevention of hippocampal neurogenesis would impact the antidepressant effects of URB597. These areas should be investigated, as they can provide further insight into the efficacy of URB597 as an antidepressant. To test if the temporal delay has an impact, a future study could involve CCI to the sciatic nerve (as done in the original study), and the administration of URB597 earlier than 15 days post-surgery. If URB597’s antidepressant effects are noticeable immediately upon administration, then closer administration should see a quick reversal in depressive-like behaviours. This reversal should also persist with further treatment. This would indicate that URB597 could be an appropriate treatment for newly diagnosed individuals as it would be able to quickly mediate depressive-like behaviours. However, if URB597 does not have any noticeably different effects with earlier administration, it can suggest that its actions are independent of the temporal delay between depression or pain induction and treatment administration.

If URB597 is comparable to antidepressant therapies, then similar effects on depressive like behaviours should be noted across treatment dosages and windows. For instance, if similar dosages of URB597 and an SSRI (such as citalopram) were administered intraperitoneally, their effects on rat depressionlike behavior should be comparable. If URB597 is able to elicit a superior therapeutic effect than citalopram with no more adverse side effects, then the argument can be made for its use as a novel antidepressant therapy. However, if the effects are less effective, then URB597 could be ruled out as a possible antidepressant therapy. However, more Investigating the impacts of blocking hippocampal investigation should still be done to determine if neurogenesis would help to better understand the FAAH inhibition would still be a suitable target. mechanism of action of URB597 in treating depression. With Additionally, a dosage dependent effect on URB597 treatment efficacy is an important point for investigation. If at increasing dosages URB597 elicits better antidepressant effects than citalopram, it could suggest it be used for treatment resistant or high tolerance depressed individuals. If the opposite effect occurs (decreased dosages of URB597 elicit better antidepressant effects), then it could be an appropriate first choice therapy for newly diagnosed individuals. Further, if treatment effects persist for longer periods of time before adaptation or resistance occurs, then URB597 could posit an effective adjunctive medication to cognitive based therapies. Determining these comparable effects of systemic FAAH inhibitors can help researchers to better understand if they would be an appropriate antidepressant therapy, and if their efficacy is as robust and long lasting as typically used antidepressant medications. In addition to comparing URB597’s antidepressant effects to commonly used treatments, investigation into other FAAH inhibitors should also be conducted. The potential therapeutic effects of URB597 and PF-3845 (another FAAH inhibitor) could be compared to each other and to other commonly used antidepressants. This would help to better understand if FAAH inhibitors alone have a potent antidepressant effect, especially if both drugs elicit the same response. If effects elicited by other systemic inhibitors are comparable, it can

administration, URB597 was able to reverse the negative effects of CCI on hippocampal neurogenesis as well as increase proliferation and development (Jiang et al., 2018). This also correlated with noticeable antidepressant effects. If UBR597’s antidepressant effects are reduced or eliminated with prevention of hippocampal neurogenesis, which can be done by a technique like X ray irradiation (Saxe et al., 2006), then one can presume that it is integral to the efficacy of URB597’s antidepressant effects. If URB597 is still able to elicit antidepressant effects independent of this, then it suggests that the endocannabinoid signaling pathway, specifically the CB1 receptor pathway, is a likely explanation for its mechanism of action. This can help to develop further antidepressant treatments that target this area and determine if their effects are comparable to both URB597 and other clinically used antidepressant medications. Upon further investigation of URB597’s efficacy in depressed rat models, researchers will be able to better understand its treatment efficacy and mechanism of action. They will also be able to better determine any side effects with increasing treatment dosages and durations. If no apparently significant therapeutic effects are observed with further research, then URB597, and potentially FAAH systemic inhibitors as a whole, can be ruled out as novel antidepressant therapies. If significant therapeutic effects are still noted upon further

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investigation, a logical next step from rat models would be to investigate the effects of URB597 on depressed human patients. As SSRIs, SNRIs, and TCAs all have similar effects in rats and humans, this same trend is hypothesized to appear in human models. Upon investigating its efficacy in human trials, researchers will be better able to determine its use as a novel antidepressant therapy.

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REFERENCES 1. Adamczyk, P., Golda, A., McCreary, A. C., Filip, M., & Przegaliński, E. (2008). Activation of endocannabinoid transmission induces antidepressant-like effects in rats. 2. Journal of Physiology and Pharmacology, 59(2), 217–228. 3. Cravatt, B. F., Demarest, K., Patricelli, M. P., Bracey, M. H., Giang, D. K., Martin, B. R., & Lichtman, A. H. (2001). Supersensitivity to anandamide and enhanced endogenous cannabinoid signaling in mice lacking fatty acid amide hydrolase. Proceedings of the National Academy of Sciences, 98(16), 9371–9376. https://doi.org/10.1073/pnas.161191698 4. Cravatt, Benjamin F, & Lichtman, A. H. (2003). Fatty acid amide hydrolase: an emerging therapeutic target in the endocannabinoid system. Current Opinion in Chemical Biology, 7(4), 469–475. https://doi.org/10.1016/S1367-5931(03)00079-6 5. de Morais, H., de Souza, C. P., da Silva, L. M., Ferreira, D. M., Baggio, C. H., Vanvossen, A. C., … Zanoveli, J. M. (2016). Anandamide reverses depressive-like behavior, neurochemical abnormalities and oxidative-stress parameters in streptozotocin-diabetic rats: Role of CB1 receptors. European Neuropsychopharmacology, 26(10), 1590–1600. https://doi.org/10.1016/j. euroneuro.2016.08.007 6. Dellarole, A., Morton, P., Brambilla, R., Walters, W., Summers, S., Bernardes, D., … Bethea, J. R. (2014). Neuropathic pain-induced depressive-like behavior and hippocampal neurogenesis and plasticity are dependent on TNFR1 signaling. Brain, Behavior, and Immunity, 41, 65–81. https://doi.org/10.1016/j.bbi.2014.04.003 7. Desroches, J., Charron, S., Bouchard, J.-F., & Beaulieu, P. (2014). Endocannabinoids decrease neuropathic pain-related behavior in mice through the activation of one or both peripheral CB1 and CB2 receptors. Neuropharmacology, 77, 441–452. htts://doi.org/10.1016/j. neuropharm.2013.10.006 8. Fasick, V., Spengler, R. N., Samankan, S., Nader, N. D., & Ignatowski, T. A. (2015). The hippocampus and TNF: Common links between chronic pain and depression. Neuroscience & Biobehavioral Reviews, 53, 139–159. https://doi.org/10.1016/j.neubiorev.2015.03.014 9. Gobbi, G., Bambico, F. R., Mangieri, R., Bortolato, M., Campolongo, P., Solinas, M., … Piomelli, D. (2005). Antidepressant-like activity and modulation of brain monoaminergic transmission by blockade of anandamide hydrolysis. Proceedings of the National Academy of Sciences, 102(51), 18620–18625. https://doi.org/10.1073/pnas.0509591102 10. Hama, A. T., Germano, P., Varghese, M. S., Cravatt, B. F., Milne, G. T., Pearson, J. P., & Sagen, J. (2014). Fatty Acid Amide Hydrolase (FAAH) Inhibitors Exert Pharmacological Effects, but Lack Antinociceptive Efficacy in Rats with Neuropathic Spinal Cord Injury Pain. PLoS ONE, 9(5), e96396. https://doi.org/10.1371/journal.pone.0096396 11. Jiang, H., Ke, B., Liu, J., Ma, G., Hai, K., Gong, D., … Zhou, C. (2018). Inhibition of Fatty Acid Amide Hydrolase Improves Depressive-Like Behaviors Independent of Its Peripheral Antinociceptive Effects in a Rat Model of Neuropathic Pain: Anesthesia & Analgesia, 127(6), 1–11. https://doi. org/10.1213/ANE.0000000000003563 12. Kwilasz, A. J., Abdullah, R. A., Poklis, J. L., Lichtman, A. H., & Negus, S. S. (2014). Effects of the fatty acid amide hydrolase inhibitor URB597 on pain-stimulated and pain-depressed behavior in rats: Behavioural Pharmacology, 25(2), 119–129. https://doi.org/10.1097/FBP.0000000000000023 13. Luongo, L., Maione, S., & Di Marzo, V. (2014). Endocannabinoids and neuropathic pain: focus on neuron-glia and endocannabinoid-neurotrophin interactions. European Journal of Neuroscience, 39(3), 401–408. https://doi.org/10.1111/ejn.12440 14. Malberg, J. E. (2004). Implications of adult hippocampal neurogenesis in antidepressant action. Journal of Psychiatry and Neuroscience, 29(3), 196–205. 15. McLaughlin, R. J., Hill, M. N., Morrish, A. C., & Gorzalka, B. B. (2007). Local enhancement of cannabinoid CB1 receptor signalling in the dorsal hippocampus elicits an antidepressantlike effect: Behavioural Pharmacology, 18(5–6), 431–438. https://doi.org/10.1097/ FBP.0b013e3282ee7b44

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16. Molina-Holgado, F., Rubio-Araiz, A., García-Ovejero, D., Williams, R. J., Moore, J. D., ArévaloMartín, Á., … Molina-Holgado, E. (2007). CB2 cannabinoid receptors promote mouse neural stem cell proliferation: CB2 receptors in neural stem/precursor cells. European Journal of Neuroscience, 25(3), 629–634. https://doi.org/10.1111/j.1460-9568.2007.05322.x 17. Nicholson, B., & Verma, S. (2004). Comorbidities in Chronic Neuropathic Pain. Pain Medicine, 5(suppl 1), S9–S27. https://doi.org/10.1111/j.1526-4637.2004.04019.x 18. Realini, N., Vigano’, D., Guidali, C., Zamberletti, E., Rubino, T., & Parolaro, D. (2011). Chronic URB597 treatment at adulthood reverted most depressive-like symptoms induced by adolescent exposure to THC in female rats. Neuropharmacology, 60(2–3), 235–243. https://doi. org/10.1016/j.neuropharm.2010.09.003 19. Saarto, T., & Wiffen, P. J. (2007). Antidepressants for neuropathic pain. Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD005454.pub2 20. Sairanen, M., Lucas, G., Ernfors, P., Castrén, M., & Castrén, E. (2005). Brain-Derived Neurotrophic Factor and Antidepressant Drugs Have Different But Coordinated Effects on Neuronal Turnover, Proliferation, and Survival in the Adult Dentate Gyrus. Journal of Neuroscience, 25(5), 1089– 1094. https://doi.org/10.1523/JNEUROSCI.3741-04.2005 21. Saxe, M. D., Battaglia, F., Wang, J.-W., Malleret, G., David, D. J., Monckton, J. E., … Drew, M. R. (2006). Ablation of hippocampal neurogenesis impairs contextual fear conditioning and synaptic plasticity in the dentate gyrus. Proceedings of the National Academy of Sciences, 103(46), 17501–17506. https://doi.org/10.1073/pnas.0607207103 22. Smaga, I., Jastrzębska, J., Zaniewska, M., Bystrowska, B., Gawliński, D., Faron-Górecka, A., … Filip, M. (2017). Changes in the Brain Endocannabinoid System in Rat Models of Depression. Neurotoxicity Research, 31(3), 421–435. https://doi.org/10.1007/s12640-017-9708-y 23. Tyrtyshnaia, A. A., Manzhulo, I. V., Sultanov, R. M., & Ermolenko, E. V. (2017). Adult hippocampal neurogenesis in neuropathic pain and alkyl glycerol ethers treatment. Acta Histochemica, 119(8), 812–821. https://doi.org/10.1016/j.acthis.2017.10.007 24. Vera, G., Cabezos, P. A., Martín, M. I., & Abalo, R. (2013). Characterization of cannabinoidinduced relief of neuropathic pain in a rat model of cisplatin-induced neuropathy. Pharmacology Biochemistry and Behavior, 105, 205–212. https://doi.org/10.1016/j.pbb.2013.02.008 25. Umathe, S. N., Manna, S. S. S., & Jain, N. S. (2011). Involvement of endocannabinoids in antidepressant and anti-compulsive effect of fluoxetine in mice. Behavioural Brain Research, 223(1), 125–134. https://doi.org/10.1016/j.bbr.2011.04.031 26. Zhou, D., Li, Y., Tian, T., Quan, W., Wang, L., Shao, Q., … Ma, Y.-M. (2017). Role of the endocannabinoid system in the formation and development of depression. Pharmazie, 72(8), 435–439. https://doi.org/10.1691/ph.2017.7474

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Targeting The Achilles Heel of Zika Virus Through Engineered Peptide Faizan Nadeem Zika virus (ZIKV) is a biologically transmitted virus between a vertebrate host and vector such as a mosquito. The virus is made up of three structural proteins, a lipid envelope and capped RNA. The virus is implicated in etiology of pathologies in the nervous system such as Guillain-Barre syndrome in adults and microcephaly in neonates. Currently there is no effective treatment or prevention of ZIKV other than avoidance of mosquito vectors. The research conducted by Jackman et. al (2018) addresses this lack of therapeutics options though lipid envelope antiviral disruption (LEAD) strategy. ZIKV and other like viruses contain a lipid envelope that is necessary for their structure and function. The authors were able to show that destabilization of this envelope would be effective to reduce viral infectivity. They engineered an alpha peptide capable of penetrating the blood brain barrier. The LEAD antiviral therapy peptide used (D)-amino acids. The peptide was then tested in cultures and mouse models to identify the target range of the peptide against virus mimicking liposomes and evaluate in vitro neutralization, in vivo therapeutic effects and brain delivery and injury protection. This allowed them to observe liposome destruction, inhibition of cell death, inhibition of viral replication and reduced neuroinflammation and neurodegeneration. Therefore, serving as evidence for a possible therapeutic through systematic control and inhibitory activity. Keywords: Zika virus, blood brain barrier, neurodegenerative, microcephaly, microgliosis, neuroprogenitor cells, microglial activation, cell death, therapy, peptide, neuroinflammation

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INTRODUCTION

Zika virus (ZIKV) is a biologically transmitted virus between a vertebrate host and vector such as a mosquito (Musso and Gubler 2016). First isolated from rhesus monkey in 1947, there were very few cases reported till 2007 in the South Pacific (Musso and Gubler 2016). The virus is made up of three structural proteins (capsid, membrane, and envelope), a lipid envelope and capped RNA (Olagnier et al. 2016). Introduction of Zika virus, like epidemics of other viruses, has led to rapid spread and public health consequences. Through bite of infected mosquito, human dermal fibroblast, epidermal keratinocytes and immature dendritic cells are permissive to the virus (Hamel et al. 2015). The virus can then induce apoptotic cell death to divert antiviral response to dying cells and therefore facilitate viral distribution (Hamel et al. 2015). The virus is implicated in etiology of pathologies in the nervous system such as Guillain-Barre syndrome in adults and microcephaly in neonates (White et al. 2016). In Guillain-Barre syndrome, there is a rapid onset of muscle weakness caused by damage in the peripheral nervous system (Yuki and Hartung 2012). The muscle weakness known as acute motor axonal neuropathy was due to demyelination, ischemia, inflammation and breakdown of the blood brain barrier (BBB) (Watrin et al. 2016). ZIKV infection in pregnant women has led to congenital abnormalities, reduced weight and fetal death. Microcephaly is most likely caused by increased cell death or failure of differentiation in neuronal cell death or progenitor cell growth(Miner et al. 2016). The placenta acts as a barrier against infection but the virus is able to pass though. Once in fetal circulation, ZIKV can directly infect neuronal progenitor cells (NPCs) and replicate within the cells, leading to attenuated expansion of NPC via apoptosis, cell-cycle dysregulation and induce immune response(Li et al. 2016). Along with NPC, there is microglial activation, astrogliosis and oligodendrocyte development disruption (Li et al. 2018). Currently there is no effective treatment or prevention of ZIKV other than avoidance of mosquito vectors. An effective therapeutic would need to target circulating virus particles to reduce spread and load, penetrate BBB and be applicable to other viruses. Therefore, the research conducted by Jackman et. al (2018) aims

to address this lack of therapeutics options though lipid envelope antiviral disruption (LEAD) strategy. ZIKV and other like viruses contain a lipid envelope that is necessary for their structure and function. The authors were able to show that destabilization of this envelope would be effective to reduce viral infectivity (Jackman et al. 2018). They engineered an alpha peptide capable of penetrating the blood brain barrier to target the lipid envelope. The LEAD antiviral therapy peptide used (D)-amino acids (AH-D) due to less susceptibility to protein degradation, increased stability and bioavailability. The peptide was then tested in cultures and mouse models to identify the target range of the peptide against virus mimicking liposomes and evaluate in vitro neutralization, in vivo therapeutic effects and brain delivery and injury protection (Jackman et al. 2018). This allowed them to observe liposome destruction, inhibition of cell death, inhibition of viral replication and reduced neuroinflammation and neurodegeneration(Jackman et al. 2018). Therefore, serving as evidence for a possible therapeutic through systematic control and inhibitory activity. RESULTS Surface Liposome

Jackman et. al (2018) used quartz crystal microbalance dissipation (QCM-D) to monitor real time mass and structural changes allowing them to show that the AH-D peptide was able to rupture liposomes quickly (Fig. 1) (Jackman et al. 2018). Time-lapsed fluorescence microscopy was also used to see decreased levels of surface fluorophore intensity of individual liposomes, indicating liposome rupture (Fig. 1) (Jackman et al. 2018). This result was observed at low concentrations of 50 nM of AH-D peptide and increasing concentrations (1000 nM) reduced the time scale needed to observe rupture whereas other antimicrobial peptides at higher concentrations were inactive (Fig. 1) (Jackman et al. 2018). This supports the notion that the engineered peptide exhibits potent and selective membrane disruption. This type of response was similarly seen in a trial by (Torcato et al. 2013)R-BP100 and RW-BP100, with activity against Gram-negative and Gram-positive

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bacteria”,”container-title”:”Biochimica et Biophysica Acta (BBA) in bacterial membrane. An antimicrobial peptide was engineered to target both gram negative and positive though disruption of the lipopolysaccharide layer, leading to inactivation (Torcato et al. 2013)R-BP100 and RW-BP100, with activity against Gram-negative and Grampositive bacteria”,”container-title”:”Biochimica et Biophysica Acta (BBA.

death (Fig 2A) and was non-toxic to uninfected cells, as assessed 48 hrs post infection (Jackman et al. 2018). It was also found that virus replication and other strains of ZIKV (HS-2015-BA-01) were inhibited by peptide treatment (Fig 2B) (Jackman et al. 2018). Overall the peptide was effective at preventing neuronal cell death and reducing viral loads. A

Figure 1: A. Time-lapsed fluorescence microscopy images of surface, fluorescently labeled liposomes. At t=0 min, 100 nM AH-D was added. B. The change in fluorescence intensity when treated with AH-D or other antimicrobial peptides at various concentrations. Decreased intensity is indicative of faster rupture time. (Figures derived from Jackman et al. (2018)). ZIKV-Induced Cell Death Jackman et. al (2018) used neuronal cell cultures from the cortex and striatum regions of C57BL/6 mice which were subjected to either mock or ZIKV infection while cell death was observed by LIVE/ DEAD staining. Using a specific strain (MR766) of African origin, they tested peptide ability to inhibit cell death. It was found that peptide concentrations as low as 10 nM was able to prevent neuronal cell

Figure 2: A. Cell viability of ZIKV MR766 infected cells at various concentrations of AH-D peptide B. Cell viability of ZIKV HS-2015-BA-01 infected cells at various concentrations of AH-D peptide (Each red dot indicates one culture) (Figures derived from Jackman et al. (2018)) Therapeutic Activity Jackman et. al (2018) intravenously inoculated 4x103 plaque forming units (p.f.u) of HS-2015BA-01 strain into adult 7-9 week old SV129 (A129/) mice. Treatment began three days post-infection with either AH-D peptide (25 mg/kg) or saline, twice a day for four days. All untreated mice died within 7 days, whereas 10/12 of peptide treated mice were protected (Jackman et al. 2018). Peptide was observed to protect against ZIKV induced weight loss, maintain intraocular pressure,

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decrease leukocyte and overall reduce viral load in the spleen, brain, serum and optic nerve (Jackman et al. 2018). By day 7, >3log10 reduction of viral load in the brain (Fig 3) resulting in decreased myeloperoxidase (MPO) activity, tumour necrosis factor-α, interleukin-1β, CCL5 and CXCL-1 chemokines (Jackman et al. 2018). Furthermore, treated mice were protected against cerebral damage, with reduced microglial activation in motor cortex and hippocampus (Fig 3) (Jackman et al. 2018). This indicates that peptide is able to cross the BBB for direct antiviral activity while inhibiting neuroinflammation and neurodegeneration. A

Figure 3: A. Decreased viral load observed in the brain 3-7 days post infection with treatment starting at day 3 (reach red dot is one mouse) B. Cerebral damage due to ZIKV and reduced neurodegeneration with AH-D peptide. (Figures derived from Jackman et al. (2018))

mortality and had no neurological symptoms(Yu et al. 2017). Therefore, supporting the results observed by Jackman et al. (2018). CONCLUSION/DISCUSSION

From this experiment, the authors were able to demonstrate that the engineered peptide served as a possible therapeutic to ZIKV. This is due to their observations that the peptide was able to specifically target ZIKV leading to neutralization via membrane disruption(Jackman et al. 2018). The peptide also served as a therapeutic by preventing cell death, reducing viral replication and viral load, and cross the BBB to prevent neuroinflammation and neurodegeneration(Jackman et al. 2018). Overall showing a combination of systemic control and inhibitory activity in organs, including the brain. Previous literature has been shown to target and alleviate symptoms of the virus, but direct ZIKV targeting therapies in the brain have not been identified or made available. The research conducted by Jackman et al. (2018) provides a possible mechanism for ZIKV targeting in patients post-infection and as a protective treatment preinfection as models showed specificity to ZIKV and non-toxicity to unaffected cells. The models used in this experiment serve as suitable representation. The Liposome model represents not only ZIKV but also other enveloped viruses such as Dengue and Chikungunya, therefore allowing therapeutic to be adaptable. This method has been used in previous research and has be shown to work through pore formation by peptide integrating into membranes, dissipating gradients and releasing cell content(Jackman et al. 2016). The induced cell cultures and therapeutic models are used because they mimic human features of the disease such as elevated levels of brain inflammatory markers, increased intraocular pressure and leukocytosis (Jackman et al. 2018) therefore displaying peptide ability to reduce mortality and symptoms. Engineering peptides is not a new idea and has been applied in previous literature on bacteria, as transport mechanisms and in other systems of the body. This research was able to advance beyond just controlling replication. Viruses can mutate, rendering the therapeutic inactive, therefore being able to target other factors like the membrane create a more robust treatment. The ability to

Similarly, both of these above results were seen in a trial by Yu et al. (2017). They derived a synthetic peptide (Z2) from ZIKV envelope and demonstrated that Z2 was able to cross the placental barrier and block vertical transmission in mice(Yu et al. 2017). Inhibition of viral replication was observed in a dosedepended manner, but larger doses (1.75±0.13 uM-3.69±0.27 uM) then those used by Jackman et al. (2018). They also found loss of infectivity of virions, reduced weight changes, reduced viral load, systematic specificity, protected against 108

distinguish between host and viral cell specificity is also an advancement as further host harm in infection situation would instigate viral survival and advance spread, which is one of the main evasion methods ZIKV employs. The authors are the first to evaluate such therapeutic across a scale of in vivo and in vitro more specifically targeting ZIKV in the brain rather than systemic symptoms.

non-enveloped viruses. Finally therapeutic activity of the peptide within the CNS showed protection from neuroinflammation and neurodengeration therefore demonstrating its ability to prevent apoptosis, cell cycle dysregulation and main structural stability of BBB, which have also been shown in previous literature such as (Yu et al. 2017). Since in Guillain-Barre syndrome, there damage in the peripheral nervous system (Yuki and Hartung 2012) and Microcephaly is due to failure in neuronal CRITICAL ANALYSIS cell or progenitor cells (Miner et al. 2016), theses would be important areas of application of the The authors of this paper identified a possible peptide along with other barriers such as placenta therapeutic to specifically target ZIKV in the brain, rather than previous treatment which was directed FUTURE DIRECTIONS towards symptoms such as fever and pain. This research displays the need for further experiments The optimal dosage and duration need to using engineered peptides to solidify the work be identified in clinical investigation and weather done by Jackman et al. (2018). The authors were able to compare this new D-amino acid peptide with oral or intravenous administration serves a more its enantiomer L-amino acid peptide to overcome efficient method. Since ZIKV can also be protected pharmacological challenges like specificity, improve by exosomes and travel through secretary stability and bioavailability. The LEAD strategy autophagy pathways to be secreted rather than was seen to be effective at direct targeting and degraded (Yuan, Zhang, and Li 2017), the authors membrane disruption, which was their intended could use QCM-D and fluorescence microscopy goal but could be further applied to other lipid to target exosome for membrane disruptions. instigators of ZIKV such as exosomes which can The results of this should be similar to liposomes serve as ZIKV shield (Yuan, Zhang, and Li 2017). as both are made from similar components. Since This type of similar strategy was implemented for ZIKV is able to cross through different barriers bacterial membranes by (Torcato et al. 2013) but such as placenta, it is important to determine if not for viruses. The peptide ability to distinguish the AH-D peptide is able to cross. This could be between virus and host by cell curvature and size done by randomly assigning ZIKV mice to either is a key advancement that could serve as a base treatment or control and injecting pregnant mice for targeting of other diseases, as peptides have with peptide or PBS and monitoring body weight, different surface topologies, which influences how post birth kidney, spleen, and brain of both mother a peptide molecule interacts with membranes and and pup to determine transmission, spread of virus lipid bilayer (Schmidt and Wong 2013). To test and peptide influence. Further this could also test peptide ability to prevent cell death, peptide was for Microcephaly by direct injecting ZIKV into fetal administered every 12 and 24 hrs but this could embryo head. If peptide is effective, a reduced be further tested by administering a higher dose viral load, maintained body weight, normal head over longer periods of time to test how long the size, no neuronal cell death and proper progenitor effect of the peptide is. Since the peptide was seen cell growth should be observed. Finally, to test for to be non-toxic at the concentrations applied, it Guillain-Barre syndrome, administration of peptide would also be beneficial to identify a concentration to PNS and muscles could be tested. Further at which host cells are destroyed. This is seen in testing needs to be conducted on bigger animals previous research such as Starr, He, and Wimley and human cell cultures. (2016) where weak affinity to host cells and large concentrations can lead to loss of activity of some peptides. The LEAD strategy was target specifically towards enveloped viruses so further research could be conducted to identify effects on 109

REFERENCES 1. Hamel, Rodolphe, Ophélie Dejarnac, Sineewanlaya Wichit, et al. (2015). Biology of Zika Virus Infection in Human Skin Cells. Journal of Virology 89(17): 8880–8896. 2. Jackman, Joshua A., Vivian V. Costa, Soohyun Park, et al. (2018). Therapeutic Treatment of Zika Virus Infection Using a Brain-Penetrating Antiviral Peptide. Nature Materials 17(11): 971–977. 3. Jackman, Joshua A., Haw Zan Goh, Vladimir P. Zhdanov, Wolfgang Knoll, and Nam-Joon Cho. (2016). Deciphering How Pore Formation Causes Strain-Induced Membrane Lysis of Lipid Vesicles. Journal of the American Chemical Society 138(4): 1406–1413. 4. Li, Cui, Qin Wang, Yisheng Jiang, et al. 5. (2018). Disruption of Glial Cell Development by Zika Virus Contributes to Severe Microcephalic Newborn Mice. Cell Discovery 4(1):43 6. Li, Cui, Dan Xu, Qing Ye, et al. (2016). Zika Virus Disrupts Neural Progenitor Development and Leads to Microcephaly in Mice. Cell Stem Cell 19(1): 120–126. 7. Miner, Jonathan J., Bin Cao, Jennifer Govero, et al. (2016). Zika Virus Infection during Pregnancy in Mice Causes Placental Damage and Fetal Demise. Cell 165(5): 1081–1091. 8. Musso, Didier, and Duane J. Gubler. (2016). Zika Virus. Clinical Microbiology Reviews 29(3): 487–524. 9. Olagnier, David, Michela Muscolini, Carolyn B. Coyne, Michael S. Diamond, and John Hiscott. (2016). Mechanisms of Zika Virus Infection and Neuropathogenesis. DNA and Cell Biology 35(8): 367–372. 10. Schmidt, Nathan W., and Gerard C. L. Wong. (2013). Antimicrobial Peptides and Induced Membrane Curvature: Geometry, Coordination Chemistry, and Molecular Engineering. Current Opinion in Solid State & Materials Science 17(4): 151–163. 11. Starr, Charles G., Jing He, and William C. Wimley. (2016). Host Cell Interactions Are a Significant Barrier to the Clinical Utility of Peptide Antibiotics. ACS Chemical Biology 11(12): 3391–3399. 12. Torcato, Inês M., Yen-Hua Huang, Henri G. Franquelim, et al. (2013). Design and Characterization of Novel Antimicrobial Peptides, R-BP100 and RW-BP100, with Activity against Gram-Negative and Gram-Positive Bacteria. Biochimica et Biophysica Acta (BBA) - Biomembranes 1828(3): 944–955. 13. Watrin, Louise, Frédéric Ghawché, Philippe Larre, et al. (2016). Guillain–Barré Syndrome (42 Cases) Occurring During a Zika Virus Outbreak in French Polynesia. Medicine 95(14):e2357 14. White, Martyn K., Hassen S. Wollebo, J. David Beckham, Kenneth L. Tyler, and Kamel Khalili. (2016). Zika Virus: An Emergent Neuropathological Agent. Annals of Neurology 80(4): 479–489. 15. Yu, Yufeng, Yong-Qiang Deng, Peng Zou, et al. (2017). A Peptide-Based Viral Inactivator Inhibits Zika Virus Infection in Pregnant Mice and Fetuses. Nature Communications 8: 15672. 16. Yuan, Shu, Zhong-Wei Zhang, and Zi-Lin Li. (2017). Trehalose May Decrease the Transmission of Zika Virus to the Fetus by Activating Degradative Autophagy. Frontiers in Cellular and Infection Microbiology 7, 402: doi: 10.3389/fcimb.2017.00402 17. Yuki, Nobuhiro, and Hans-Peter Hartung. (2012). Guillain–Barré Syndrome. New England Journal of Medicine. 366(24): 2294–2304.

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Comorbid Animal Model of Depression and Chronic Pain Shows Loss of Microglia and BDNF/CREB; Symptoms Reversed with Duloxetine Noshin Ullah The relationship between major depressive disorder (MDD) and chronic pain remains complicated as both conditions are often comorbid and occur frequently. MDD is often associated with episodes of intense sadness in addition to fatigue, anhedonia and changes in cognition. An estimated 30 million Americans alone, are believed to be living with this disorder, making it a prime candidate for research. Consequently, many patients suffering from depression are also inflicted by chronic pain. On the contrary, patients with chronic pain may develop depression. The neuropathology of these disorders remains unclear, though depression has been found to be correlated with changes in the hippocampus and hypothalamic pituitary access. Nonetheless, molecular aspects are still under scrutiny. Many neuronal factors, including brain derived neurotrophic factor (BDNF) are have been found at lower levels in patients with MDD. However, it is unknown whether patients comorbid with MDD and chronic pain would display similar levels of neurotrophic factors, or if additive effects would occur. Unfortunately models of comorbid subjects with MDD and chronic pain have not been heavily studied, leaving many questions unanswered in this field. A recent study conducted by Zhu and colleagues (2018) has focused on a comorbid animal model of MDD and chronic stress and used this to measure levels of multiple neurotrophic factors. The researchers induced depression and chronic pain in mice and compared phenotypes to mice who had induced forms of only depression or only chronic pain. They also measured levels of BDNF, cAMP response element-binding protein (CREB), density of microglial cells and activation of nuclear factor κB (NF-κB) in the medial prefrontal cortex (mPFC). The animals displayed comorbid behaviours and the results indicated a greater decrease in BDNF and density of microglia compared to animals with solely induced depression or chronic pain, dependent on upregulation of the activation of NF-κB. These findings suggest that comorbidity can be induced in animal models and be used to understand physiological features of MDD and chronic pain. The results indicated that there may be overlapping pathology between these disorders that practitioners should be aware of and further investigate for more targeted therapies. Keywords: major depressive disorder (MDD), chronic pain, comorbid, brain derived neurotrophic factor (BDNF), microglia, Nuclear factor κB (NF-κB), medial prefrontal cortex (mPFC)

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INTRODUCTION

The high incidence of depression, which is usually found to be comorbid with chronic pain makes it difficult to treat patients who may be suffering from multiple sources of distress (Walker, Kavelaars, Heijnen, & Dantzer, 2013). This leads to changes in cognition and often a the loss of interest or pleasure in daily activities (Phillips, 2017). As the pathology remains unclear, targeting specific neuronal circuits to elevate levels of neurotransmitters or neurotrophic factors is challenging. Comorbidities pose a problem, as overlapping circuitry may make disorders difficult to differentiate (Surah, Baranidharan, & Morley, 2014). A study conducted by Lin, Yen, Chen, & Chen, (2014) asked patients who were diagnosed with MDD to take a survey in order to rate their pain. A post hoc analysis revealed that depressed patients presented as having more intense pain than the general population. Those with MDD were found to have a lower quality of life (QoL) than those with only pain, but MDD and chronic pain were found to have additive effects. A similar study found that patients with MDD and chronic pain had lower quality of life scores than those with depression alone (Elliott, Renier, & Palcher, 2003). In lieu of this information, the pathology of the disorders seems to be of great relevance and a comorbid model may be able to help answer these questions.

the underpinnings of both MDD and chronic pain. Lastly, NF-ÎşB is also an important transcriptional regulator that is involved in learning and memory (Snow & Albensi, 2016). Thus, any deficits in the disorders may be explained by the levels of the product of this transcription factor. Though many potential pathological causes have been identified to explain the symptoms in patients exclusively suffering from one of the mentioned disorders, the pathology remains unclear for those comorbid with the disorders, thus further enhancing the need for a comorbid animal model. Treatment

Antidepressants are one of the treatment methods used to treat both depression and chronic pain. As previously mentioned, a potential target of these drugs may be BDNF (Figure 1), as levels seem to rise in patients taking antidepressants (Lee & Kim, 2010). One of these drugs is duloxetine, a selective serotonin reuptake inhibitor that is believed to aid in the treatment of depression and chronic pain (Zhu et al., 2018), thought the effects on comorbid patients remains unclear. However, recent evidence has pointed to low response rate to antidepressants for comorbid patients (Gerrits et al., 2012). Namgoong (2018) recently conducted a study to test the efficacy of duloxetine in neuropathic patients suffering from diabetes. Though the sample group may not be suffering Pathology of MDD and Chronic Pain from depression, the results are still informative. When compared to a placebo, there was a greater Many neurotrophic factors are thought to be reduction in pain and overall improvement in involved in the onset of depression and chronic quality of life in patients who had taken the drug. pain. BDNF is one such molecule that is important in the maintenance of synaptic integrity and neuroplasticity. It is regulated by CREB and binds to itâ&#x20AC;&#x2122;s receptor tropomyosin receptor kinase B (TrkB). The BDNF based hypothesis of depression is based on findings that suggest patients with MDD have lower serum levels of BDNF (Lee & Kim, 2010). Studies have also shown that administering BDNF to depressed patients has resulted in antidepressant-like effects (Sheng, Liu, Wang, Cui, & Zhang, 2017). BDNF is an important signaling factor for microglia, which are involved in inflammation responses in the brain, often due to injury or pain (Phillips, 2017). Thus, the density of microglia is also key in understanding 112

Figure 1. This chart maps the potential targets of antidepressants and displays pain and depression as being modulated by neural plasticity. Figure Adapted from Sheng, Liu, Wang, Cui, & Zhang, (2017) Neural Plasticity MAJOR RESULTS In their 2018 research study Zhu and colleagues attempted to address the unanswered questions and confirm molecular pathologies by inducing depression and chronic pain in a strain of mice and measuring levels of various of neuronal factors. Furthermore, they test the effects of an antidepressant on comorbid animals by using duloxetine to reverse the symptoms successfully. The authors randomly assigned rodents to a group. The conditions were; naïve; DSS (colitis induced by dextran sodium sulfate, analogous to chronic pain); stress (induced by chronic unpredictable stress; CUS) and the comorbidity group (both chronic pain and stress were induced). The results of this experiment indicated that comorbidity of chronic pain and depression could be induced in rodent models by administering DSS and chronic unexpected stress. The authors found that mice comorbid for both conditions showed greater depressive like behaviours compared to naïve mice, or subjects that were suffering from only one disorder (Figure 2). Those comorbid for depression and pain were found to have higher expression of NF-κB, and lower levels of BDNF, CREB and microglia in the mPFC (Figure 3). However, after being treated with the antidepressant duloxetine, symptoms of hyperalgesia and depression were shown to be alleviated (as shown in Figure 4). The findings suggest a pathology to depression and chronic pain which may have additive effects in comorbid subjects.

Figure 2. The results of various tests for depression; B] An open field test; comorbid animals had significantly lower in center frequencies compared to naïve mice. C] The forced swim test, indicated that comorbid mice has significantly longer durations of immobility compared to all other groups. D] Significantly higher durations of immobility in the tail suspension test for DSS+ Stress mice compared to other groups E] Anhedonia was significantly higher in comorbid mice compared to naïve mice. Figure Adapted from Zhu et. al (2018). Frontiers in Psychiatry Though there is a paucity of research on comorbid disorders, many studies have looked at depression and pain separately in order to identify phenotypes and pathology. In their paper on animal models for pain and psychiatric disorders (Leite-Almeida, Pinto-Ribeiro, & Almeida, 2015) discuss the various approaches used to measure depression phenotypes and pain. These methods include the Forced Swim test and Sucrose Preference test

Figure 3 Levels of neurotrophic factors (mRNA measured using qPCR). Used where lack of mobility and preference imply helplessness and anhedonia respectively, both models which were used in this experiment. Pain was tested using the von Frey test as suggested by the article. Figure Adapted from Zhu et. al (2018). Frontiers in Psychiatry

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Much research has been conducted on the molecular factors involved in depression and BDNF is one of the most prominent factors. In animals undergoing stressful periods and in patients with MDD lower levels of serum BDNF levels were found (Sheng et al., 2017). This was also found in post mortem results of deceased patients who had suffered from MDD (Villanueva, 2013). An analysis conducted on patients with MDD and control subjects revealed lower BDNF plasma levels in MDD patients as opposed to control subjects. Researchers also found that suicidal patients with MDD had significantly lower levels of plasma BDNF compared to non-suicidal patients (Lee, Kim, Park, & Kim, 2007). An increase in BDNF levels was found after antidepressant treatment using selective serotonin reuptake inhibitors (SSRIs) and selective noradrenaline reuptake inhibitors (SNRIs) increased BDNF levels (Lee & Kim, 2010). Due the downstream effects of BDNF, including the activation of CREB, it would be reasonable to expect decreases in the mRNA production of CREB, as supported by this study. On the contrary significantly higher levels of NF-κB were found in comorbid animals compare to all other groups (Figure 3). NF-κB is known to be well implicated in synaptic plasticity neuronal survival. However, due to pain and inflammation may lead to the production of many cytokines, which in turn leads to higher transcription of NFκB (Mattson, Culmsee, Yu, & Camandola, 2001). However, this mechanism remains unclear. Lastly, the detection of lower levels of microglia (through staining of IBa-1, a microglial marker; Figure 3) may explain depressive symptoms yet its relevance remains quite elusive.

to be significantly higher or lower than the other groups, it suggests that both disorders may have additive effects, or that one may dominate over the other. Furthermore, a study conducted by Yajimi et. al (2008) found a direct link between the presence of BDNF in the spinal cord and the development of pain. Mice with the gene for BDNF knocked out were found to be less responsive to tests for pain. If this were the case, increasing the levels of BDNF in depressed patients may be causing them pain. This suggests that BDNF has a role in not only MDD, but perhaps chronic pain as well. What makes this study unique, is that researchers measured phenotypical and molecular markers in a comorbid model. Though their research lines up with what is known in relation to levels of BDNF and CREB, there is still much controversy over the role of microglia in this process.

Figure 4; The administration of duloxetine results in the reversal of many symptoms of chronic pain (A]higher response frequency in the von Frey test; CONCLUSION/DISCUSSION B] CRD (colorectal distention) had higher response In conclusion the research conducted was not only scores) and depression (E] & F]). Figure Adapted able to model depression and chronic pain in an from Zhu et. al (2018). Frontiers in animal, but also found molecular hallmarks for the Psychiatry comorbidity. Essentially, the animal comorbid for depression and chronic pain displayed lowers levels CRITICAL ANALYSIS of BDNF/CREB and microglia and increased levels of NF-κB. However, observed behaviours atypical Though depression has not been completely of those suffering from chronic pain and depression localized in one area, the limbic system has been declined after administration of the antidepressant found to be quite involved (Pandya, Altinay, duloxetine. This implies that BDNF and microglia Malone, & Anand, 2012). This paper however, play central roles in the comorbidity of depression has only analyzed neurotrophic factors from the and pain. As many neurotrophic factors were found mPFC. It remains unclear if the same results would 114

be the same had they analyzed for example, the hippocampus which has actually been found to decrease in size in MDD patients (Otte et al., 2016). In addition to this, the role of microglia remains very unclear. The results simply reported that staining for microglia revealed fewer of them, though the processes were not studied in great detail. Interestingly, in models of pain, inflammation is usually associated with higher levels of microglia (Inoue & Tsuda, 2018). In this study however, while animals were suffering from an induced form of chronic pain, lower levels of microglia were reported. All the changes that were seen are also quite controversial. An earlier study conducted in mice, also induced forms of depression and pain, but found that comorbid models did not have exacerbated anxiety and pain, brining into question the additive effects that were observed in this experiment (Liu, Yang, Yu, & Zhang, 2015). In addition to this, Burke, Kerr, Moriarty, Finn, & Roche (2014) studied the effect of minocycline, a microglial inhibitor on models of depression and pain. The authors found that chronic (versus acute) application of the drug dissipated depressive behavior and prevented the onset of allodynia. This raises the question as to what role microglia have in the pathology of pain and depression. Zhu et. al (2018) found lower levels of microglia in comorbid animals, however, these animals were suffering from depression and pain. If inhibiting microglia alleviates depressive like behavior (Burke et al., 2014), then this contradicts the results found in Zhu et. alâ&#x20AC;&#x2122;s (2018) paper, re-enforcing the need to explore the role of microglia in mitigating depression and chronic pain. Furthermore, as with many animal studies, it is difficult to be able to generalize the results to human cases as there as often issues with face and predictive validity (LeiteAlmeida et al., 2015). Additionally, the model will never completely correspond to the disease in a human. Nonetheless, a model is key to bringing researchers closer to understanding a condition.

hippocampus and all other areas of the limbic system both post mortem and in vivo (possibly using positron emission tomography; Banati, 2003). This would provide a better understanding of the different areas of the brain that may or may not be more active in patients who have the disorders. It would be ideal to attempt the in vivo imaging in human patients who are comorbid and compare these patients to controls and those with only one disorder. Higher levels of activated glia could be observed in control patients or those taking antidepressants if microglia are affected by these disorders, as suggested by Zhu et. al (2018).

It would be ideal to test mice by reversing the order in which depression and pain are induced. In this study, mice were induced with chronic pain before being prone to CUS. This may model of pain induced depression, however, the reverse may also happen where patients experience depression before chronic pain. Similarly, both disorders may emerge at the same time. Depending on the mechanism results could look the same, or molecular changes could be observed. If one disorder is dominating over its comorbid partner, such as pain, this may lead to inflammation which in turn results in higher levels of microglia as opposed to the loss. Lastly, the mechanism by which this system operates in comorbid patients should be determined in order to target anti-depressant/inflammatory drugs. If using the BDNF or serotonergic hypothesis by inhibiting upstream and downstream components of the pathway and observing changes in phenotype or response level perhaps a mechanism can be determined. If inhibiting BDNF production results in an increase in depressive behavior or changes the signaling to the microglia, then it may be involved in both depression and pain.

Furthermore, different types of microglia, including the M1 and M2 phenotypes should be explored. The former is thought to be involved in inflammation and the latter in repair and protection (Tang & Le, 2016). Though there still remains controversy as to FUTURE DIRECTIONS whether these phenotypes exist (Ransohoff, 2016), It remains unclear if a specific part of the brain has perhaps their existence may explain the difference a greater influence/change leading to comorbidity. in microglia levels expressed. In addition to using This study focused on the changes in the mPFC, IBa-1 to stain for microglia, Cd11b and Arginase-1 however, it would be enticing to check levels (Jablonski et al., 2015;Peng, Geil Nickell, Chen, of proteins and neurotrophic factors in the McClain, & Nixon, 2017) can be used to potentially stain for M1 and M2 types in the conditions used 115

for this study.

Lastly, the role of exercise in modulating these neurotropic factors should also be assessed in comorbid patients. Physical has been found to increase serum BDNF levels in healthy adults and depressed individuals (Phillips, 2017). It would be more intriguing to observe any changes this may cause in the density of microglia and compare results to taking antidepressants alone. This would however, have to be performed in humans given that physical activity may be difficult to control in animals. Nonetheless, there is much work left to be done in this field and perhaps future research will provide more treatment options for patients with comorbid disorders.

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REFERENCES

1. Banati, R. B. (2003). Neuropathological imaging: in vivo detection of glial activation as a measure of disease and adaptive change in the brain. British Medical Bulletin, 65, 121–131. 2. Burke, N. N., Kerr, D. M., Moriarty, O., Finn, D. P., & Roche, M. (2014). Minocycline modulates neuropathic pain behaviour and cortical M1–M2 microglial gene expression in a rat model of depression. Brain, Behavior, and Immunity, 42, 147–156. https://doi.org/10.1016/j. bbi.2014.06.015 3. Elliott, T. E., Renier, C. M., & Palcher, J. A. (2003). Chronic pain, depression, and quality of life: correlations and predictive value of the SF-36. Pain Medicine (Malden, Mass.), 4(4), 331–339. 4. Gerrits, M. M. J. G., Vogelzangs, N., van Oppen, P., van Marwijk, H. W. J., van der Horst, H., & Penninx, B. W. J. H. (2012). Impact of pain on the course of depressive and anxiety disorders: Pain, 153(2), 429–436. https://doi.org/10.1016/j.pain.2011.11.001 5. Inoue, K., & Tsuda, M. (2018). Microglia in neuropathic pain: cellular and molecular mechanisms and therapeutic potential. Nature Reviews Neuroscience, 19(3), 138–152. https://doi. org/10.1038/nrn.2018.2 6. Jablonski, K. A., Amici, S. A., Webb, L. M., Ruiz-Rosado, J. de D., Popovich, P. G., PartidaSanchez, S., & Guerau-de-Arellano, M. (2015). Novel Markers to Delineate Murine M1 and M2 Macrophages. PLOS ONE, 10(12),. https://doi.org/10.1371/journal.pone.0145342 7. Lee, B.-H., Kim, H., Park, S.-H., & Kim, Y.-K. (2007). Decreased plasma BDNF level in depressive patients. Journal of Affective Disorders, 101(1), 239–244. https://doi.org/10.1016/j. jad.2006.11.005 8. Lee, B.-H., & Kim, Y.-K. (2010). The Roles of BDNF in the Pathophysiology of Major Depression and in Antidepressant Treatment. Psychiatry Investigation, 7(4), 231–235. https://doi.org/10.4306/ pi.2010.7.4.231 9. Leite-Almeida, H., Pinto-Ribeiro, F., & Almeida, A. (2015). Animal Models for the Study of Comorbid Pain and Psychiatric Disorders. Pain in Psychiatric Disorders, 30, 1–21. https://doi. org/10.1159/000435929 10. Lin, C.-H., Yen, Y.-C., Chen, M.-C., & Chen, C.-C. (2014). Depression and pain impair daily functioning and quality of life in patients with major depressive disorder. Journal of Affective Disorders, 166, 173–178. https://doi.org/10.1016/j.jad.2014.03.039 11. Liu, Y., Yang, L., Yu, J., & Zhang, Y.-Q. (2015). Persistent, comorbid pain and anxiety can be uncoupled in a mouse model. Physiology & Behavior, 151, 55–63. https://doi.org/10.1016/j. physbeh.2015.07.004 12. Mattson, M. P., Culmsee, C., Yu, Z., & Camandola, S. (2001). Roles of Nuclear Factor κB in Neuronal Survival and Plasticity. Journal of Neurochemistry, 74(2), 443–456. https://doi. org/10.1046/j.1471-4159.2000.740443.x 13. Namgoong, H. (2018.). Is duloxetine effective in reducing pain for patients with diabetic neuropathy?, 15. 14. Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., … Schatzberg, A. F. (2016). Major depressive disorder. Nature Reviews Disease Primers, 2, 16065. https://doi. org/10.1038/nrdp.2016.65 15. Pandya, M., Altinay, M., Malone, D. A., & Anand, A. (2012). Where in the Brain Is Depression? Current Psychiatry Reports, 14(6), 634–642. https://doi.org/10.1007/s11920-012-0322-7 16. Peng, H., Geil Nickell, C. R., Chen, K. Y., McClain, J. A., & Nixon, K. (2017). Increased expression of M1 and M2 phenotypic markers in isolated microglia after four-day binge alcohol exposure in male rats. Alcohol (Fayetteville, N.Y.), 62, 29–40. https://doi.org/10.1016/j.alcohol.2017.02.175 17. Phillips, C. (2017). Brain-Derived Neurotrophic Factor, Depression, and Physical Activity: Making the Neuroplastic Connection [Research article]. https://doi.org/10.1155/2017/7260130 18. Ransohoff, R. M. (2016). A polarizing question: do M1 and M2 microglia exist? Nature Neuroscience, 19(8), 987–991. https://doi.org/10.1038/nn.4338 19. Sheng, J., Liu, S., Wang, Y., Cui, R., & Zhang, X. (2017). The Link between Depression and Chronic Pain: Neural Mechanisms in the Brain. Neural Plasticity, 2017. https://doi.

117

org/10.1155/2017/9724371 20. Snow, W. M., & Albensi, B. C. (2016). Neuronal Gene Targets of NF-κB and Their Dysregulation in Alzheimer’s Disease. Frontiers in Molecular Neuroscience, 9. https://doi.org/10.3389/ fnmol.2016.00118 21. Surah, A., Baranidharan, G., & Morley, S. (2014). Chronic pain and depression. Continuing Education in Anaesthesia Critical Care & Pain, 14(2), 85–89. https://doi.org/10.1093/bjaceaccp/ mkt046 22. Tang, Y., & Le, W. (2016). Differential Roles of M1 and M2 Microglia in Neurodegenerative Diseases. Molecular Neurobiology, 53(2), 1181–1194. https://doi.org/10.1007/s12035-014-90705 23. Villanueva, R. (2013). Neurobiology of Major Depressive Disorder. Neural Plasticity, 2013, 1-7. https://doi.org/10.1155/2013/873278 24. Walker, A. K., Kavelaars, A., Heijnen, C. J., & Dantzer, R. (2013). Neuroinflammation and Comorbidity of Pain and Depression. Pharmacological Reviews, 66(1), 80–101. https://doi. org/10.1124/pr.113.008144 25. Yajima, Y., Narita, M., Usui, A., Kaneko, C., Miyatake, M., Narita, M., … Suzuki, T. (2005). Direct evidence for the involvement of brain-derived neurotrophic factor in the development of a neuropathic pain-like state in mice. Journal of Neurochemistry, 93(3), 584–594. https://doi. org/10.1111/j.1471-4159.2005.03045.x 26. Zhu, C., Xu, J., Lin, Y., Ju, P., Duan, D., Luo, Y., … Cui, D. (2018). Loss of Microglia and Impaired Brain-Neurotrophic Factor Signaling Pathway in a Comorbid Model of Chronic Pain and Depression. Frontiers in Psychiatry, 9(442),1-7. https://doi.org/10.3389/fpsyt.2018.00442

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Reducing the severity of neurodegenerative disorder symptoms with exercise: slowing down early onset Alzheimer’s disease Jessica Yu Many studies attempt to collect data to support the idea that exercise is a plausible, costeffective treatment to Alzheimer’s disease (AD). Correlations have been found in animal models in addition to humans. The levels of AD biomarkers, such as Pittsburgh compound (PIB), β-amyloid (Aβ) and phosphorylated tau, have shown to be significantly lower in older adults who are consistently active compared to those who exercise significantly less1. The mechanisms of how exercise may reduce symptoms of AD is still relatively unknown, as is the stimuli that cause neurodegeneration in AD. Recently, a paper by Do et al investigates the early metabolic changes that occur in early onset AD2. They examine the relationship exercise may have in regulating those changes detected in early onset AD in transgenic mice models. The study observed that mouse AD models, prior to the detection of Aβ plaques, exhibited significantly higher consumptions of food and oxygen. They observed a decrease in pro-opiomelanocortin (POMC) and Neuropeptide Y (NPY)-expressing neurons, an increase in inflammatory- and apoptotic-related genes. Short-term voluntary exercise was enough to reverse the gene expression levels of the latter genes. Longer periods of voluntary exercise, showed notable improvement in glucose metabolism and, reducing food intake in the mouse AD models. Do et al were able to provide support for the hypothesis that exercise may be able to reverse the effects of early onset AD as well as demonstrate that consistent exercise is key to early and maintained reversal of AD symptoms. Keywords: Alzheimer’s disease, voluntary exercise, glucose intolerance, inflammation, apoptosis, POMC-expressing neurons, NPY-expressing neurons.

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As the world population continues to age, a focus of research in neuroscience has shifted towards neurodegenerative diseases. One of the most common forms of dementia is Alzheimer’s disease (AD), which affects the central nervous system. Two hypothesized mechanisms of AD involve the accumulation of extracellular β-amyloid (Aβ) plaques and hyperphosphorylation of intracellular tau protein leading to neurofibrillary tangles3-4. Most often, one leads to another and both can be found simultaneously in the brain of an individual diagnosed with AD. Symptoms from other disorders may play a key role in triggering AD, most commonly abnormalities in glucose metabolism. A previous study has shown correlation between Type 2 diabetes mellitus, characterized by impaired glucose metabolism, with earlier onset of AD5. It was shown that disrupting normal glucose metabolism in animal models over-expressing human amyloid precursor protein (APP) promoted the accumulation of Aβ plaques and accelerated the progression of AD. A review strongly linked obesity with cognitive dysfunction6. Obesity is distinguished by excessive amounts of adipose tissue as well as metabolic abnormalities, frequently related to glucose intolerance. A strong association between higher adiposity and the risk of developing AD was demonstrated through various retrospective studies and animal studies. The mechanisms of impaired glucose metabolism increasing the risk of AD is still not very well understood. Numerous studies have shown long-term exercise improve behaviours such as executive function, learning and depression, in addition to improvements on a molecular scale resulting in a decrease in extracellular Aβ plaques 7-9. The mechanisms of exercise on AD are still not fully understood and there is little research done on the metabolic changes that occur during early stages of AD, as well as early introduction of consistent exercise as a therapeutic intervention. Furthermore, correlation of feeding and metabolic changes has been studied prior, but never at the neuronal level in the hypothalamus.

with AD – APP Swedish, MAPT P301L and PSEN1 M146V – and studied their metabolic status and hypothalamic neuronal structure with the treatment of different lengths of exercise over varying time intervals. Neurodegeneration in the arcuate nucleus (ARC), significant increase in consumption of food and oxygen, as well as significant decrease in NPY-expressing neurons were established. On the contrary, long-term voluntary exercise reduced apoptosis of neurons in the hypothalamus, and 6 weeks of exercise improved glucose metabolism. This study demonstrated that prior to build up of Aβ plaques and neurofibrillary tangles, significant changes in the metabolism also occur, indicating that AD may not only be a neurodegenerative disorder, but also a metabolic disorder. Major Results Abnormalities in energy metabolism The 3xtg-AD mice models consumed more food than the control mice in addition to consuming more oxygen, indicating that the transgenic mice had a higher metabolic rate than the control mice. Taking in consideration the changes in food and oxygen consumption there were significant differences indicating metabolic abnormalities. It should be noted that there was no difference in total weight, although lean mass was significantly lower in the transgenic-AD mice compared to their counterparts. 3xtg-AD mice had significant glucose intolerance as indicated by their plasma glucose levels compared to controls. This corroborates a previous hypothesis that AD induces diabetic-like symptoms during early onset5. Following 6 weeks of exercise training, the transgenic-AD models showed improvement in glucose metabolism with significantly reduced levels of plasma glucose. Gene expression and degenerative markers in the hypothalamus

3xtg-AD mice displayed a decrease AgRP (Agoutirelated peptide) and melanocortin 4 receptor (MC4R) mRNA expression in hypothalamic neurons of the ARC. This led to large increase in apoptosis of neurons in this area of brain. These results validate Do et al used triple transgenic AD (3xtg-AD), an existing hypothesis that stimulation of this circuit mice models, that had three mutations associated saw amelioration in AD symptoms10. Furthermore, 120

Do et al also observed that degenerative markers experienced a large increase in expression in hypothalamic neurons. Levels of tumour necrosis factor alpha (TNF-α) and interleukin-6 (IL-6) were significantly greater in transgenic mice than controls. Increase in inflammatory cytokines have been previously reported in other areas of the brain such as the hippocampus in induced animal models of AD11. These changes in gene expression suggest that there was inflammation and apoptosis occurring. Transgenic mice that had 4 weeks of voluntary exercise experienced a normalization of AgRP and MC4R mRNA expression, protection against apoptosis as well as reduced levels of TNF-α and IL-6.

Figure 1. Increase in POMC neurons after 8 weeks of voluntary exercise. 1A. Immunofluorescence of POMC neurons. 1B. Differences between control and 3xtg-AD and 3xtg-AD with exercise2.

Alteration of POMC- and NPY-expressing neurons At 12 weeks of age, there were no significant changes to POMC-expressing neurons. However, significant reduction of POMC neurons were displayed in 3xtg-AD mice compared to controls at 24 weeks old. At the same age, 3xtg-AD mice also had a significant decrease in NPY-expressing neurons. This corroborates with another study done on transgenic AD mice that displayed loss in POMC- and NPY-expressing neurons leading to obesity11. Following 8 weeks of voluntary exercise, the 3xtg-AD mice had an increase in POMCexpressing and levels were restored to relatively the same as the control as well as an increase in NPY-expressing neurons that even surpass the levels measured in the control.

Figure 2. Increase in NPY neurons after 8 weeks of voluntary exercise. 2A. Immunofluorescence of NPY neurons. 2B. Differences between control and 3xtgAD and 3xtg-AD with exercise2. Conclusions Signs of early onset AD occur before and lead to the hallmark symptoms such as accumulation of Aβ plaques and neurofibrillary tangles are reversible with consistent, long-term exercise. Abnormalities in energy metabolism, decrease mRNA expression of AgRP and MC4R in ARC and decrease in POMCand NPY-expressing neurons can be reversed with voluntary exercise, delaying the onset of distinctive and irreversible symptoms of AD2. Do et al outline that metabolic abnormalities occur prior to cognitive decline in 3xtg-AD mice models. They also note a decline in POMC- and NPYexpressing neurons in pre-pathological stages of AD. The study supports previous hypotheses of AD being a neurodegenerative disease affecting the cortex and hippocampus resulting in loss of memory and coordination. New findings provided by the data of this study demonstrates the role of exercise on the hypothalamus, in particular, on feeding-related neurons and the modulation of inflammation and apoptosis in 3xtg-AD mice

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implicating AD as potentially being a metabolic Further studies should focus on hormonal treatment disorder as well. to reverse the symptoms of pre-pathological AD in 3txg-AD mice. Administering NPY, AgRP or Traditionally, AD is thought to begin in the Îą-MSH, may allow the bypass of POMC- and NPYhippocampus, and spreads laterally12. The findings expressing neurons and stimulate a response in by Do et al provide new insight of pre-pathological the paraventricular nucleus causing a response symptoms and refute previous hypotheses by and affecting feeding and energy metabolism. If demonstrating that molecular and cellular level administrating feeding-regulating neurohormones changes can be detected outside the hippocampus, do not produce similar results as exercise in reducing most notably in the hypothalamus2. In addition, glucose intolerance and hypothalamic apoptosis in effects of exercise on the hypothalamus in early feeding-behaviour neurons; then we can conclude onset of AD had not been previously studied in that the contraction of muscles and the subsequent depth and results by Do et al reveal that 4 weeks release of myokines and adipokines, such as BDNF of voluntary exercise was sufficient to return 3xtg- are also required to reverse the abnormalities. AD mice back to normal, reversing the symptoms of pre-early onset AD. Critical Analysis The results and conclusions by Do et al corroborate with other literature in regard to the protective effects of exercise on the hypothalamus against AD13. Experiments that remain to be performed are how neurohormones that regulate feeding and metabolism are affected by AD and how exercise may possibly modulate them. Experiments on the effects of appetite-regulating neurohormones such as NPY, AgRP and Îą-MSH on the pre-pathological symptoms of AD should be performed. These neurohormones act on paraventricular nucleus to reduce food intake and increase energy expenditure14. The crucial role these neurohormones play in homeostasis may reveal further details about the mechanisms that induce the prepathological symptoms. An element of the paper that would require further studies would be the release of myokines and adipokines during exercise aiding to reverse glucose intolerance and reduce hypothalamic apoptosis of feeding behaviour neurons. It is known that there is a compensation mechanism in early stages of AD, where there is an increase in plasma BDNF, a myokine released by muscles when contracted15. BDNF continues to decrease throughout the course of the disorder, therefore exercise would force muscles to continue to release BDNF. This may potentially maintain levels of plasma BDNF and lead to the prevention of AD pathology. Future Directions 122

References 1. Liang KY, Mintun MA, Fagan AM, Goate AM, Bugg JM, Holtzman DM, Morris JC, Head D. Exercise and Alzheimer's disease biomarkers in cognitively normal older adults. Annals of Neurology. 2010;68(3). 2. Do K, Laing BT, Landry T, Bunner W, Mersaud N, Matsubara T, Li P, Yuan Y, Lu Q, Huang H. The effects of exercise on hypothalamic neurodegeneration of Alzheimer’s disease mouse model. Plos One. 2018;13(1). 3. Masters CL, Simms G, Weinman NA, Multhaup G, Mcdonald BL, Beyreuther K. Amyloid plaque core protein in Alzheimer disease and Down syndrome. Proceedings of the National Academy of Sciences. 1985;82(12):4245–4249. 4. Alonso ADC, Grundke-Iqbal I, Iqbal K. Alzheimers disease hyperphosphorylated tau sequesters normal tau into tangles of filaments and disassembles microtubules. Nature Medicine. 1996;2(7):783–787 5. Zhao W-Q, Townsend M. Insulin resistance and amyloidogenesis as common molecular foundation for type 2 diabetes and Alzheimers disease. Biochimica et Biophysica Acta (BBA) Molecular Basis of Disease. 2009;1792(5):482–496. 6. Naderali EK, Ratcliffe SH, Dale MC. Review: Obesity and Alzheimer’s Disease: A Link Between Body Weight and Cognitive Function in Old Age. American Journal of Alzheimers Disease & Other Dementias. 2009;24(6):445–449. 7. Yu F, Nelson NW, Savik K, Wyman JF, Dysken M, Bronas UG. Affecting Cognition and Quality of Life via Aerobic Exercise in Alzheimer’s Disease. Western Journal of Nursing Research. 2011;35(1):24–38.. 8. Cho JY, Hwang DY, Kang TS, Shin Dh, Hwang JH, Lim CH, Lee SH, Lim HJ, Min SH, Seo SJ, Song YS, Nam KT, Lee KS, Cho JS, Kim YK. Use of NSE/PS2m-transgenic mice in the study of the protective effect of exercise on Alzheimer's disease, J Sports Sci. 2003;21(11): 943-951. 9. Adlard PA. Voluntary Exercise Decreases Amyloid Load in a Transgenic Model of Alzheimers Disease. Journal of Neuroscience. 2005;25(17):4217–4221. 10. Shen Y, Tian M, Zheng Y, Gong F, Fu AK, Ip NY. Stimulation of the Hippocampal POMC/MC4R Circuit Alleviates Synaptic Plasticity Impairment in an Alzheimer’s Disease Model. Cell Reports. 2016;17(7):1819–1831. 11. Kohjima M, Sun Y, Chan L. Increased Food Intake Leads to Obesity and Insulin Resistance in the Tg2576 Alzheimer’s Disease Mouse Model. Endocrinology. 2010;151(4):1532–1540. 12. Li X-H, Li X-H, Zhang Y-Y, Wang M, Wang D. Atorvastatin attenuates the production of IL-1β, IL-6, and TNF-α in the hippocampus of an amyloid β1-42-induced rat model of Alzheimer’s disease. Clinical Interventions in Aging. 2013:103. doi:10.2147/cia.s40405. 13. Um H-S, Kang E-B, Koo J-H, Kim H-T, Jin-Lee, Kim E-J, Yang C-H, An G-Y, Cho I-H, Cho J-Y. Treadmill exercise represses neuronal cell death in an aged transgenic mouse model of Alzheimers disease. Neuroscience Research. 2011;69(2):161–173. 14. Abdalla MMI. Central and peripheral control of food intake. Endocrine Regulations. 2017;51(1):52–70. 15. Laske C, Stransky E, Leyhe T, Eschweiler GW, Wittorf A, Richartz E, Bartels M, Buchkremer G, Schott K. Stage-dependent BDNF serum concentrations in Alzheimer’s disease. J Neural Transm. 2006;113(9):1217-1224.

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How a small channel holds the key to understand epilepsy. Maria Jose Caceres Valdiviezo Type 2 K+/Cl- cotransporter channel (KCC2) is the major determinant of the low intracellular concentration of Cl- in mature neurons. Thus, it enables the hyperpolarizing inhibition following activation of type A GABA receptors. Antiepileptic drugs (AEDs) take advantage of the inhibitory capacity of GABAA receptors to reduce seizures. Yet, they are not very effective suggesting the presence of other factors that are intervening in GABAA receptors activity. Importantly, mutations of KCC2 have been associated with different types of epilepsy showing the importance to elucidate the regulatory mechanisms of this channel to develop more effective antiepileptic drugs (AEDs). However, little is known about the regulation of KCC2 except that phosphorylation of its C-terminal domain might play a role in its activity. S940 is considered to be important to provide stability to KCC2 and enhance its activity. For this reason, Silayeva et al. (2015) studied the role of S940 phosphorylation in epilepsy by creating knock-in mice to change this residue to alanine (S940A). They induced status epilepticus (SE) by injecting kainate acid and observed that the mutation increased the latency and lethality of SE. Even further, S940 mutants had a selective deficit during hyperexcitability induced by glutamate exposure. Their research provides an understanding of the epileptic pathology seen in people with KCC2 mutations and reduced S940 phosphorylation. And elucidates a potential therapy for epilepsy, increase phosphorylation of S940. Key words: Type 2 K-Cl cotransport (KCC2); epilepsy; serine 940 residue (S940); status epilepticus; SE; inhibition.

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Introduction

hyperpolarizing inhibition.

A balance between excitatory and inhibitory signaling is needed for the correct functioning of the brain. Epilepsy is understood as a disruption of this balance resulting in hyperexcitability and hypersynchronous activity of neurons (González et al., 2018; Kristopher T. Kahle et al., 2016; Snowball & Schorge, 2015; Wang, Wang, & Chen, 2018)encoded by SLC12A5, is required for the emergence and maintenance of GABAergic fast synaptic inhibition in organisms across evolution. These findings have suggested that KCC2 deficiency might play a role in the pathogenesis human epilepsy, but this has only recently been substantiated by two lines of genetic evidence. The first is the discovery of heterozygous missense polymorphisms in SLC12A5, causing decreased KCC2-dependent Cl− extrusion capacity, in an Australian family with inherited febrile seizures and in a French-Canadian cohort with severe genetic generalized epilepsy (GGE. Thus, identifying tools that help restore endogenous inhibition is important. Fast synaptic inhibition in the central nervous system (CNS) is mediated by GABAA and glycine receptors, ligand-gated anion channels permeable to Cl- (Kristopher T. Kahle & Delpire, 2015; Moore, Kelley, Brandon, Deeb, & Moss, 2017). Their hyperpolarizing activity is dependent on low intracellular chloride concentration [Cl-]i which is established by the K-Cl cotransporter (KCC2) (Kristopher T. Kahle & Delpire, 2015; Kristopher T. Kahle et al., 2016; Lee, Deeb, Walker, Davies, & Moss, 2011; Moore et al., 2017; Martin Puskarjov, Kahle, Ruusuvuori, & Kaila, 2014)our knowledge of the transporter’s regulatory mechanisms is incomplete. Recent studies suggest that the phosphorylation state of KCC2 at specific residues in its cytoplasmic COOH terminus, such as Ser940 and Thr906/Thr1007, encodes discrete levels of transporter activity that elicit graded changes in neuronal Cl− extrusion to modulate the strength of synaptic inhibition via Cl−-permeable GABAA receptors. In this review, we propose that the functional and physical coupling of KCC2 to Cl−-sensitive kinase(s. KCC2 is the principal Clextruder in mature neurons, coupling it with the K+ gradient. Therefore, KCC2 plays a vital role in

Even further, its activity is tightly coupled with NKCC1 activity, a Na+/K+/Cl- cotransporter responsible for inflow of Cl- into neurons (Gagnon & Delpire, 2010; Kristopher T. Kahle et al., 2013). Current antiepileptic drugs (AEDs) potentiate GABAA receptor activity (Deeb, Maguire, & Moss, 2012; Deeb, Nakamura, Frost, Davies, & Moss, 2013; Moore et al., 2017). However, they do not work in 30% of the cases and they are ineffective to treat neonatal seizures (Deeb et al., 2012; Martin Puskarjov et al., 2014; Wang et al., 2018). These patients have deficient expression or function of KCC2 resulting in a perturbed Cl- homeostasis that might affect the efficacy of AEDs (Deeb et al., 2013; Huberfeld et al., 2007). This is because GABAA receptor activity is dependent on the Clhomeostasis determined by KC22. Accordingly, reduction in the expression or function of KCC2 has been found to increase seizure susceptibility in animal models (Chen et al., 2017, p. 2). Furthermore, mutations in KCC2 described in human disease were not known until 2014 when Puskarjov et al. reported a KCC2-R952H variant present in a single Australian family with febrile seizures. This variant had reduced Cl- extrusion capacity and decreased surface expression (M. Puskarjov et al., 2014). In addition to R952H variant, Kahle et al. (2014) reported another nonsynonymous variant of KCC2, R1049C. R952H and R1049C were found to be strongly associated with idiopathic generalized epilepsies (IGE). Both KCC2 mutants presented decreased S940 phosphorylation suggesting a role of this residue in IGE pathology (K. T. Kahle et al., 2014). This implies a role of KCC2 in human epilepsy. Yet, the regulation of KCC2 activity is not completely understood. Several studies indicate that phosphorylation of residues in the C- terminal domain of KCC2 is key to regulate its activity and expression (Figure 1) (Kristopher T. Kahle et al., 2013; Moore et al., 2017).Thus, these mechanisms are potential therapeutic targets for epilepsy.

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Figure 2. EEG recording of wild-type and S940A mutants. The mutant mice died within 26 min following kainate injection. Figure Adapted from Figure 1. Phosphorylation sites that affect KCC2 Activity. Figure Silayeva et al. (2015). Proceedings of the National Adapted from Moore et al. (2017), Trends in Neurosciences. Academy of Sciences. 112(11):3523â&#x20AC;&#x201C;3528. 40(9):555â&#x20AC;&#x201C;571. Silayeva et al. (2015) studied the role of S940 phosphorylation of KCC2 by creating knockin mice in which this residue was changed to alanine (S940A). By using kainite acid to induce status epilepticus in wild-type and mutant mice, they found that S940A mutation increased the lethality and severity of SE (Silayeva et al., 2015). Their research suggests that the phosphorylation of S940 is critical to limit the development of epileptogenesis. And provides a new therapeutic alternative. Major Results

Effects of KCC2 during status epilepticus During the second part, the in vivo effects of the mutation following kainate injection were assessed. As mentioned above, this is a well-known model of epilepsy. The mice died within 26 min following the injection. As seen in Figure 1, the onset of SE remained the same compared to the wild-type mice. Yet, the severity of the seizure increased dramatically. Effects of Neuronal Hyperexcitability induced by glutamate

In Silayeva et al. (2015) research, knock in mice were Cultured neurons were exposed to glutamate to created changing S940 to alanine. This residue simulate the state of neuronal excitation during alteration was confirmed with DNA sequencing. SE. Glutamate induces activation of protein phosphatase 1 (PP1) mediated by NMDA receptor The first part of the study consisted in the causing dephosphorylation of S940 (Lee et al., characterization of the mutants. S940A mutation 2011). Importantly, previous research showed did not have an effect in the development and that the effects of glutamate are independent of behavior of mice as shown by the rotador task. NKCC1 (Lee et al., 2011). In addition, the expression of KCC2 and NKCC1 remained the same in both the wild-type and As observed in Fig. 3, wild-type and mutant mice mutant mice. This and the unchanged reverse presented comparable E depolarization values. GABA potential of GABA suggested that the basal activity However, the rate of recovery of S940A mutants of KCC2 was unaltered. The extrusion capacity of following glutamate removal was slower when KCC2 was measured by exposing the hippocampal compared to the wild-type mice. In addition, the neurons to furosemide and allow them to recover. recovery was blocked when the KCC2 inhibitor, Both wild-type and mutant neurons had similar VU0240551, was added suggesting that KCC2 rates of recovery. activity was responsible for the observed effects. Even further, when AP-5, an NMDA receptor antagonist, was added to the cultures, there was full recovery of the wild-type neurons. Yet, the rate of recovery remained unchanged for the mutant 126

neurons.

In this study, Silayeva et al. (2015) concluded that phosphorylation of S940 has a role in the latency of bursting epileptic activity. In contrast to previous literatures that reported the dephosphorylation of S940 and reduce KCC2 expression in animal models of epilepsy, Silayeva et al. (2015) showed that S940 phosphorylation is important in regulating KCC2 activity. Even further, their findings support the view that the activity of KCC2 is critical during epilepsy rather than its surface expression as S940A mutants blocked the KCC2 internalization induced by SE.

With respect to the effects following OKA exposure, they admitted that the observed reduced activity of S940A-KCC2 could have been the result of the phosphorylation of other residues, T906 and T1007. These two residues have been reported to be important in the regulation of KCC2 activity (Kristopher T. Kahle et al., 2013; Moore et al., 2017).

Figure 3. Wild-type hippocampal neurons showed faster rates of recovery after glutamate exposure and after addition of AP-5 compared to the S940A culture. Figure Adapted from Silayeva et al. (2015). Proceedings of the National Academy of Sciences. 112(11):3523â&#x20AC;&#x201C;3528. These results suggest that S940 phosphorylation is a limiting factor for NMDA receptor activity. More importantly, KCC2 of S940A mutants has a selective deficit during hyperexcitability. Okainic Acid becomes an inhibitor in S940A mutants. Okainic Acid (OKA) suppresses the effects of glutamate by inhibiting PP1 and thus, enhancing KCC2 activity. Surprisingly, OKA induced a positive shift of the reverse potential in S940A hippocampal neurons even before glutamate was added (Figure 3). This suggests that the function of OKA is mediated by S940 phosphorylation. Discussion/Conclusion

Yet, their work provides an alternative therapeutic target of epilepsy, inducing phosphorylation of S940. Critical Analysis

As mentioned before, their research offered an alternative pathway to regulate KCC2 activity via phosphorylation. Mutations that prevent phosphorylation of S940 in KCC2 could provide a reason of the non-efficiency of anti-epileptic drugs that enhance GABA receptors activity(K. T. Kahle et al., 2014; M. Puskarjov et al., 2014). The findings of mutations in KCC2 that decreases S940 phosphorylation reveals the importance and implications of this study; and the need of further research to clarify the regulation of KCC2 function. Future research could compare between the KCC2 and NKCC1 activities in S940A mutants. They concluded that the basal activity of KCC2 remained unchanged in S940A mutants by exposing the hippocampal neurons to furosemide and let the cultures recover. However, furosemide also inhibits NKCC1 and has been reported to have antiseizures effects in slice and in vivo (K. T. Kahle et al., 2014). Therefore, to correctly asses the basal functioning of KCC2, the cultured neurons could be exposed to

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VU0463271, a reversible selective KCC2 inhibitor (Delpire et al., 2012). Even further, the positive shift of EGABA following addition of OKA in S940A neurons could be the results of either two things: reduce activity of KCC2 or enhancement of NKCC1 (Chen et al., 2017, p. 2) . Previous studies have shown that PP1 inhibitors stimulate NKCC1 activity (Gagnon & Delpire, 2010). Thus, the use of bumetanide, a selective NKCC1 inhibitor, could be helpful to determine the effects of OKA in KCC2 activity.

stability to KCC2 and enhances its activity (Lee et al., 2007). Thus, by using anti-phosphoantibodies for T906 and T1007, it may be observed a reduction in phosphorylation of these residues in the mutant neurons compared to the wild-type. This might elucidate the effects of S940 mutations in the regulatory mechanisms of KCC2.

Even further, it might also clarify the mechanism of action of OKA. Because inhibition of PP1 might increase phosphorylation of these residues, Phosphorylation of the residues T906 and T1007 has the effects of OKA in S940A mutants might be shown to negatively regulate KCC2 (). Accordingly, mediated by these residues and not by S940. the use of other anti-phosphoantibodies that recognize other regulatory residues in KCC2 will be These results would clarify the effects of the absence helpful to determine OKA effects in this channel. of S940 phosphorylation in KCC2. And could And to confirm if OKA function is mediated by the allow researchers to devise alternative therapeutic residue S940. targets for epilepsy in which KCC2 is mutated and phosphorylation of this residue is reduced. Future Directions

Researchers could study the effects of S940A mutation in the phosphorylation of other residues that are known to regulate KCC2 activity.

Before this, to confirm that S940A mutants have normal basal functioning of KCC2, the reversible and specific KCC2 inhibitor, VU0463271, can be added to the culture neurons. As mentioned in the previous section, the effects of furosemide are contradictory. It may induce a positive shift of EGABA and also has antiseizures effects in slice and in vivo in animal models of epilepsy. Thus, the EGABA and the rate of recovery of S940A hippocampal neurons following VU0463271 exposure can be measured and compared to the wild-type neurons. If the values are similar, this would suggest that KCC2 basal activity is not affected by the mutation. It was previously mentioned that KCC2 activity is negatively regulated by T906 and T1007 phosphorylation. Therefore, future research could look into the effects of S940A mutations in the phosphorylation of these residues. Since the basal activity of KCC2 was normal, compensatory mechanisms may recover the basal activity of KCC2 as S940 phosphorylation provides 128

REFERENCES 1. Chen, L., Wan, L., Wu, Z., Ren, W., Huang, Y., Qian, B., & Wang, Y. (2017). KCC2 downregulation facilitates epileptic seizures. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-001967 2. Deeb, T. Z., Maguire, J., & Moss, S. J. (2012). Possible alterations in GABA A receptor signaling that underlie benzodiazepine-resistant seizures: GABAA Signaling and Refractory Seizures. Epilepsia, 53, 79–88. https://doi.org/10.1111/epi.12037 3. Deeb, T. Z., Nakamura, Y., Frost, G. D., Davies, P. A., & Moss, S. J. (2013). Disrupted Cl − homeostasis contributes to reductions in the inhibitory efficacy of diazepam during hyperexcited states. European Journal of Neuroscience, 38(3), 2453–2467. https://doi.org/10.1111/ejn.12241 4. Delpire, E., Baranczak, A., Waterson, A. G., Kim, K., Kett, N., Morrison, R. D., … Lindsley, C. W. (2012). Further optimization of the K-Cl cotransporter KCC2 antagonist ML077: Development of a highly selective and more potent in vitro probe. Bioorganic & Medicinal Chemistry Letters, 22(14), 4532–4535. https://doi.org/10.1016/j.bmcl.2012.05.126 5. Gagnon, K. B., & Delpire, E. (2010). Multiple Pathways for Protein Phosphatase 1 (PP1) Regulation of Na-K-2Cl Cotransporter (NKCC1) Function: THE N-TERMINAL TAIL OF THE Na-K-2Cl COTRANSPORTER SERVES AS A REGULATORY SCAFFOLD FOR Ste20-RELATED PROLINE/ALANINE-RICH KINASE (SPAK) AND PP1. Journal of Biological Chemistry, 285(19), 14115–14121. https://doi.org/10.1074/jbc.M110.112672 6. González, O. C., Shiri, Z., Krishnan, G. P., Myers, T. L., Williams, S., Avoli, M., & Bazhenov, M. (2018). Role of KCC2-dependent potassium efflux in 4-Aminopyridine-induced Epileptiform synchronization. Neurobiology of Disease, 109, 137–147. https://doi.org/10.1016/j. nbd.2017.10.011 7. Huberfeld, G., Wittner, L., Clemenceau, S., Baulac, M., Kaila, K., Miles, R., & Rivera, C. (2007). Perturbed Chloride Homeostasis and GABAergic Signaling in Human Temporal Lobe Epilepsy. Journal of Neuroscience, 27(37), 9866–9873. https://doi.org/10.1523/JNEUROSCI.2761-07.2007 8. Kahle, K. T., Merner, N. D., Friedel, P., Silayeva, L., Liang, B., Khanna, A., … Rouleau, G. A. (2014). Genetically encoded impairment of neuronal KCC2 cotransporter function in human idiopathic generalized epilepsy. EMBO Reports, 15(7), 766–774. https://doi.org/10.15252/embr.201438840 9. Kahle, Kristopher T., Deeb, T. Z., Puskarjov, M., Silayeva, L., Liang, B., Kaila, K., & Moss, S. J. (2013). Modulation of neuronal activity by phosphorylation of the K–Cl cotransporter KCC2. Trends in Neurosciences, 36(12), 726–737. https://doi.org/10.1016/j.tins.2013.08.006 10. Kahle, Kristopher T., & Delpire, E. (2015). Kinase-KCC2 coupling: Cl− rheostasis, disease susceptibility, therapeutic target. Journal of Neurophysiology, 115(1), 8–18. https://doi. org/10.1152/jn.00865.2015 11. Kahle, Kristopher T., Khanna, A. R., Duan, J., Staley, K. J., Delpire, E., & Poduri, A. (2016). The KCC2 Cotransporter and Human Epilepsy: Getting Excited About Inhibition. The Neuroscientist, 22(6), 555–562. https://doi.org/10.1177/1073858416645087 12. Lee, H. H. C., Deeb, T. Z., Walker, J. A., Davies, P. A., & Moss, S. J. (2011). NMDA receptor activity downregulates KCC2 resulting in depolarizing GABAA receptor–mediated currents. Nature Neuroscience, 14(6), 736–743. https://doi.org/10.1038/nn.2806 13. Lee, H. H. C., Walker, J. A., Williams, J. R., Goodier, R. J., Payne, J. A., & Moss, S. J. (2007). Direct Protein Kinase C-dependent Phosphorylation Regulates the Cell Surface Stability and Activity of the Potassium Chloride Cotransporter KCC2. Journal of Biological Chemistry, 282(41), 29777–29784. https://doi.org/10.1074/jbc.M705053200 14. Moore, Y. E., Kelley, M. R., Brandon, N. J., Deeb, T. Z., & Moss, S. J. (2017). Seizing Control of KCC2: A New Therapeutic Target for Epilepsy. Trends in Neurosciences, 40(9), 555–571. https:// doi.org/10.1016/j.tins.2017.06.008 15. Puskarjov, M., Seja, P., Heron, S. E., Williams, T. C., Ahmad, F., Iona, X., … Kaila, K. (2014). A variant of KCC2 from patients with febrile seizures impairs neuronal Cl- extrusion and dendritic spine formation. EMBO Reports. https://doi.org/10.1002/embr.201438749

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16. Puskarjov, Martin, Kahle, K. T., Ruusuvuori, E., & Kaila, K. (2014). Pharmacotherapeutic targeting of cation-chloride cotransporters in neonatal seizures. Epilepsia, 55(6), 806–818. https://doi. org/10.1111/epi.12620 17. Silayeva, L., Deeb, T. Z., Hines, R. M., Kelley, M. R., Munoz, M. B., Lee, H. H. C., … Moss, S. J. (2015). KCC2 activity is critical in limiting the onset and severity of status epilepticus. Proceedings of the National Academy of Sciences, 112(11), 3523–3528. https://doi.org/10.1073/ pnas.1415126112 18. Sivakumaran, S., Cardarelli, R. A., Maguire, J., Kelley, M. R., Silayeva, L., Morrow, D. H., … Deeb, T. Z. (2015). Selective Inhibition of KCC2 Leads to Hyperexcitability and Epileptiform Discharges in Hippocampal Slices and In Vivo. Journal of Neuroscience, 35(21), 8291–8296. https://doi. org/10.1523/JNEUROSCI.5205-14.2015 19. Snowball, A., & Schorge, S. (2015). Changing channels in pain and epilepsy: Exploiting ion channel gene therapy for disorders of neuronal hyperexcitability. FEBS Letters, 589(14), 1620– 1634. https://doi.org/10.1016/j.febslet.2015.05.004 20. Wang, Y., Wang, Y., & Chen, Z. (2018). Double-edged GABAergic synaptic transmission in seizures: The importance of chloride plasticity. Brain Research, 1701, 126–136. https://doi. org/10.1016/j.brainres.2018.09.008

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Toxoplasma gondii Preferentially Targets Neurons in the Central Nervous System Kate R. J. Friesen Toxoplasma gondii (T. gondii) (Nicolle & Manceaux) is an obligate single-celled parasite that is capable of chronically infecting and encysting in the brain of several mammalian species, including humans, resulting in a disease known as toxoplasmosis. Serious symptoms such as encephalitis and possible death, particularly in the immunocompromised and fetuses, are associated with this disease in humans. Approximately 1/3 of the world’s human population is chronically infected by this parasite and currently there are no prevention or treatment strategies available (other than attempting to avoid infection). Up to the time of the study being reviewed here (Cabral et al., 2016), most work with this parasite has been done in vitro using tissue culture. It has been demonstrated in vitro that T. gondii can infect nucleated cells including neurons and astrocytes. However, in vitro it also has been demonstrated that astrocytes can clear the parasite with interferon-γ (IFN-γ) stimulation, but neurons cannot. This finding along with some prior in vivo studies suggest that T. gondii is primarily associated with neurons in vivo. There is some discrepancy in the scientific literature between results of T. gondii research conducted under in vitro versus in vivo conditions, and it is unclear as to why the parasite-host cell interactions differed between these two environments. This paper addressed this question by using a novel mouse model capable of marking host cells that have had interactions with T. gondii. The study by Cabral et al. (2016) shows that in vivo, T. gondii preferentially targets neurons and this may be due to their physical size and characteristics. This result indicates that neurons interact with the parasite in establishing the chronic infection. Additionally, further elucidation of parasite-neuronal cell interactions may suggest possible targets where the parasite may be susceptible to pharmaceutical treatments. Key words: Toxoplasma gondii; toxoplasmosis; neurons; astrocytes; interferon-γ (IFN-γ); chronic infection; immunity-related GTPases (IRGs)

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Introduction

Toxoplasma gondii (T. gondii) (Nicolle & Manceaux) is an obligate single-celled protozoan parasite that localizes intracellularly in many warm-blooded animals such as mice, cats, and humans. (Carruthers & Suzuki, 2007; Gavrilescu & Denkers, 2001; Hill et al., 2005; McConkey et al., 2013). T. gondii infection is primarily acquired in humans through ingestion of undercooked meat and contaminated food or water containing T. gondii oocysts (Carruthers & Suzuki, 2007; Zhou et al., 2011). Additionally, this parasite is capable of crossing the placenta and infecting fetuses during pregnancy which may result in blindness and cognitive impairments in congenitally infected children (Nielsen et al., 2005; Zhou et al., 2011). T. gondii chronically infects over 1/3 of the world’s population (approximately two billion people) by encysting in neurons to form a latent infection that can persist for years. (Mendez & Koshy, 2017; Zhou et al., 2011). Additionally, T. gondii is the second most common cause of death attributed to foodborne illnesses (Furtado et al., 2011; Scallan et al., 2011). There currently are no prevention or treatment strategies available to kill cysts inside of human neurons (Halonen & Weiss, 2013; Wei et al., 2015). T. gondii infection is asymptomatic in the majority of immunocompetent people, however, in the immunosuppressed or immunodeficient such as AIDS patients and fetuses this parasite is capable of causing toxoplasmosis, and symptoms may include encephalitis and potential death (Halonen & Weiss, 2013; Lee & Lee, 2017; Sugden et al., 2016). T. gondii is also capable of causing extreme abnormal behavioural changes including infected mice losing their aversion towards cats, which ultimately facilitates completing the life cycle of the parasite (Gatkowska et al., 2012; Gulinello et al., 2010). Additionally, this parasite may cause abnormal behavioural changes in humans affecting the sexes differently including increased recklessness and jealousy in men and increased extroversion and romance/lovingness in women (Flegr, 2007).

Suzuki, 2007; Fischer et al., 1997; Halonen et al., 1996; Lüder et al., 1999; Mendez & Koshy, 2017) and it also has been demonstrated that astrocytes can clear the parasite with interferon-γ (IFN-γ) stimulation and IFN-γ-inducible, immunity-related GTPases (IRGs), but neurons cannot (Halonen et al., 1998; Halonen et al., 2000; Halonen et al., 2001; Schlüter et al., 2001; Suzuki et al., 1988; Suzuki et al., 1989). However, in vivo studies have demonstrated that T. gondii primarily infects neurons (Ferguson & Hutchison, 1987; Koshy et al., 2012; Melzer, 2010). Currently, it is unclear as to why parasite-host cell interactions differed between in vitro and in vivo conditions. Most research involving T. gondii to date has been done in vitro, however, the authors of this paper (Cabral et al., 2016) created a novel in vivo model to further elucidate the interaction between T. gondii and cells of the central nervous system (CNS). This model consisted of mice expressing green fluorescence protein (GFP) in a Cre-dependent fashion. These mice were injected with one of two strains of T. gondii that were modified to inject Cre-recombinase into host cells. Once a cell in a mouse has been infected with one of the two strains that inject Cre-recombinase into host cells, the infected cells express GFP in an irreversible manner. Cre-reporter mice were sacrificed at different time intervals and their brains were harvested and sectioned. A cocktail consisting of several anti-neuron antibodies was used to stain neurons, and anti-glial fibrillary acidic protein (GFAP) and anti-S100 were used to stain astrocytes. Confocal microscopy was used to determine co-localization between neuronal or astrocytic stain and GFP+ (infected cells).

The results of this paper (Cabral et al., 2016) showed that T. gondii is preferentially targeting neurons over astrocytes even with host cell IFN-γ depletion or infection with IRG resistant T. gondii. Furthermore, the authors also demonstrated that the lack of astrocytic infection in vivo is not due to IFN-γ stimulation and IRG-dependent cell necrosis. The results also showed that T. gondii cysts are found distant from the cell bodies in neuronal processes and that neuron cell morphology and physical size may be contributing to the parasites’ predilection for In vitro, it has been shown that T. gondii is capable infecting neurons over the smaller astrocytes or of infecting neurons and astrocytes (Carruthers & other CNS cells. These results indicate that further research is required to understand why and the 132

mechanism by which T. gondii is targeting neurons over astrocytes. Additionally, these findings suggest that understanding parasite-neuronal cell interaction is crucial to fully understanding the underlying biology and development of disease when it occurs. This interaction may be a target for developing prevention and treatment strategies against T. gondii infection.

Figure 1. Confocal microscopy results indicating relatively higher T. gondii infection rates in neurons as compared to astrocytes in mice. Figure from Cabral et al. (2016).

RESULTS

Since in vitro it has been demonstrated that astrocytes can clear T. gondii infections mediated by IRGs but neurons cannot, the authors wanted to investigate if the lack of observed GFP+ astrocytes was due to IFN-γ stimulated astrocytes being killed by cell necrosis after being infected. To accomplish this they used the methods outlined above and treated the mice with an anti-IFN-γ antibody. Mice treated with the anti-IFN-γ antibody showed a 10-fold increase in GFP+ cells as well as parasitic cysts in their brain sections. Additionally, 27 ± 7% of GFP+ cells were astrocytes in IFN-γ depleted mice compared to 1 ± 1% in control mice. IFN-γ depleted mice showed a decrease in neuronal infection with only 54 ± 4% of all GFP+ cells being neurons compared to 76 ± 8% in control mice. It is unclear why this decrease in the percentage of neurons infected occurred, and the authors did not address this question in their paper.

Neurons are the Primary Cell Type Infected with T. gondii in vivo Following the methods outlined above, this investigation (Cabral et al., 2016) showed that between 1.5 to 12 weeks post-infection (wpi), 85% of the GFP+ (infected) cells were neurons in mice infected with either of the two T. gondii strains. Additionally, at 1.5 wpi only 7 ± 4% of GFP+ cells were astrocytes in mice infected with the II-Cre T. gondii strain (Fig.1), and a similar result was recorded for the mice infected with the III-Cre T. gondii strain. Oligodendrocytes only accounted for less than 2% of GFP+ cells in mice infected with either strain. In summary, this experiment showed that neurons are the primary cell in the CNS that are either infected with T. gondii or its proteins, independent of the infecting T. gondii strain used. This finding is consistent with and confirms both previous and more recent literature by showing that T. gondii primarily infects neurons in vivo (Ferguson & Hutchison, 1987; Koshy et al., 2012; Melzer, 2010; Mendez & Koshy, 2017). Additionally, this finding is important because it suggests that neuron-T. gondii interaction should be further investigated in order to better understand the mechanisms of chronic infection and conditions of disease expression.

Blocking of IFN-γ Causes Greater Parasitic Infection

The authors (Cabral et al., 2016) proposed two reasons why there was an increase in GFP+ astrocytes associated with IFN-γ depletion. The first reason was that an increased parasitic burden allows for more frequent interaction between T. gondii and astrocytes, and the second reason was that blocking IRG-dependent cell death allows for detection of astrocytes that were killed before imaging in previous experiments (using wild type T. gondii with respect to IRG response). To determine which situation was occurring, the authors engineered IRG-resistant T. gondii because cells that are infected with this engineered parasite do not undergo IRG-dependent necrosis. A high percentage of all GFP+ cells were neurons (94 ± 1%) for mice infected with IRG-resistant T. gondii which was similar to the mice infected with T. gondii lacking this engineered characteristic. Additionally, approximately the same number of GFP+ astrocytes were observed in mice between the two different infecting strains (IRG resistant and non-engineered, normal IRG response strains), and

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astrocytes made up less than 10% of all GFP+ cells. If IRG-dependent cell death was responsible for the lack of observed GFP+ astrocytes, there should have been an increase in GFP+ astrocytes in mice infected with the IRG-resistant T. gondii compared with the T. gondii strain lacking this engineered trait. Since there was not a statistically significant difference between the number of GFP+ astrocytes in mice infected with the engineered (IRG-resistant) versus the non-engineered T. gondii, this indicates that IRG-dependent cell necrosis is not responsible for the lack of observed GFP+ astrocytes, and that increased parasitic burden is the reason why there are increased numbers of infected astrocytes with IFN-γ depletion. Furthermore, these results indicate that T. gondii is preferentially targeting neurons because even under IFN-γ depleted conditions, T. gondii infects approximately double the number of neurons versus astrocytes. This was a novel and unexpected finding that has yet to be confirmed and validated (Mendez & Koshy, 2017), however, Cekanaviciute et al. (2014) also demonstrated that there is no astrocyte necrosis during infection with T. gondii. It remains unclear as to why the parasite is only minimally infecting astrocytes in vivo, and further research is required in order to understand why T. gondii readily infects astrocytes in vitro but not in vivo. Further investigation of this question may reveal a specific signalling mechanism used by T. gondii in order to interact with neurons more frequently. T. gondii Cysts are Primarily Located in the Processes of Neurons The authors (Cabral et al., 2016) imaged individual neurons in situ to identify where T. gondii cysts were localizing in neurons. They demonstrated that T. gondii cysts primarily localize to neuronal processes rather than the cell bodies for both T. gondii strains (II-Cre and III-Cre) (Fig. 2). Additionally, they found that this parasite’s cysts localize a substantial distance from the cell body of the neuron and on average can be located 56 ± 9 μm from the cell body for mice infected with the II-Cre T. gondii strain and 75 ± 10 μm for mice infected with the III-Cre T. gondii strain. This result is consistent with previous literature (Koshy & Cabral, 2014) which

also reports that T. gondii cysts are primarily found in neuronal processes distant from the cell bodies. Furthermore, this result indicated that the large physical surface area of neurons compared to astrocytes may partially account for why neurons are primarily infected by T. gondii. Therefore, this parasite may have a predilection for neurons due to their physical morphology and size as compared to other cells in the CNS. These results suggest that neuron-T. gondii interaction is important and merits continued investigation with the ultimate goal being the development of treatment strategies and/or a pharmaceutical product.

Figure 2. Confocal microscopy results showing relatively higher number of T. gondii cysts located in neuronal processes for II-Cre and III-Cre T. gondii strains as compared to cell bodies of neurons in mice. Figure from Cabral et al. (2016). DISCUSSION & CONCLUSION The results of this paper (Cabral et al., 2016) showed that T. gondii is preferentially targeting neurons over astrocytes in mice and this remains true even under conditions of host cell IFN-γ depletion or infection with engineered IRG resistant T. gondii. Furthermore, the authors demonstrated that the lack of astrocytic infection in vivo is not due to IFN-γ stimulation or IRG-dependent cell necrosis but may be associated with the larger cell size of neurons as compared to astrocytes allowing for more frequent physical interactions with T. gondii and incidentally greater infection. This explanation is consistent with the authors’ finding showing that T. gondii cysts are primarily located in neuronal processes distant from the cell bodies indicating

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that T. gondii’s predilection for neurons is likely due to their relatively large surface area and extensive processes. These results are important because they may provide some basis for a novel explanation of why there is a difference in parasitehost cell interactions between in vitro and in vivo conditions (the relatively large three dimensional physical morphology of neurons in vivo may not be present or accurately represented in vitro). The finding that there was a general lack of astrocytic infection in vivo was unexpected by the authors, firstly because very few astrocytes were infected compared to neurons under a number of different treatments/conditions, whereas in vitro astrocytes are infected more than neurons (Carruthers & Suzuki, 2007; Fischer et al., 1997; Halonen et al., 1996; Lüder et al., 1999; Mendez & Koshy, 2017). Secondly, this finding was unexpected and novel because the lack of astrocytic infection in vivo could not be attributed to IFN-γ stimulation and IRG-dependent cell necrosis which astrocytes use as a main mechanism of clearing parasites in vitro (Halonen et al., 1998; Halonen et al., 2000; Halonen et al., 2001; Schlüter et al., 2001; Suzuki et al., 1988; Suzuki et al., 1989). This novel finding is important because the majority of research on T. gondii has been done in vitro using tissue culture. This novel result demonstrates that in vitro research does not reflect reality in this case and is a poor model for studying T. gondii-host interactions in living mammals, and therefore prior research results involving this parasite may be incorrect and possibly a number of past experiments should be repeated under in vivo conditions. The authors were unable to clearly and definitively explain why there is a difference between T. gondii-host cell interactions under in vitro versus in vivo conditions. Despite the lack of a clear explanation of this difference, the work reported in this paper provided additional insight into this question and advanced this field of research. Their results suggest that further research is required to understand the mechanisms underlying T. gondii targeting of neurons in preference to astrocytes in vivo, and these unknown mechanisms, once better understood, may be a possible target for prevention and treatment strategies for T. gondii infection.

CRITICAL ANALYSIS

The experiments described in this paper (Cabral et al., 2016) were generally of high caliber and provided additional information on T. gondii infection of mouse brain cells. The results reported in this paper indicate that T. gondii interaction with cells of the CNS differs under in vitro versus in vivo conditions, and the majority of the previous literature was based primarily on results obtained from in vitro studies. Additionally, there was a discrepancy between the findings reported in this paper of cysts being located distant from the nucleus of neurons versus what had been previously reported in the literature (McConkey et al., 2013). Immediate future research stemming from this paper (Cabral et al., 2016) should focus on repeating past research conducted under in vitro conditions with an in vivo model. Additionally, the authors performed the cyst localization experiment at one time interval only and this experiment should be repeated with a number of time intervals to determine if the cyst moves in the neuron over a period of time. Furthermore, under in vitro conditions astrocytes have been shown to apparently clear T. gondii infection through a number of different mechanisms (Degrandi et al., 2013; Martens et al., 2005), and these mechanisms should be further investigated under in vivo conditions to determine if they are responsible or partly responsible for the paucity of T. gondii infected astrocytes in vivo as noted by Cabral et al. (2016) in their study. FUTURE DIRECTIONS To expand on future experiments outlined in the critical analysis section above, the authors now proven, novel in vivo mouse model (Cabral et al., 2016) can be used to repeat many of past in vitro experiments. The outcomes of these experiments likely would be different based on the findings reported in the Cabral et al. (2016) paper that is being reviewed here. Additionally, further experiments investigating where the cysts localize and position in the neurons over time should be conducted using the same in vivo mouse model. The results of these

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experiments including a range of sampling at different time intervals would most likely show that the cyst is fairly stable in its position over the lifespan of the mouse and does not travel from the neuronal cell processes to the nucleus of host cells. Conversely, it cannot be ruled out that the cysts may be traveling to the nucleus after the cell is infected in order to modulate host cell responses through the activation or suppression of specific genes, and may be affecting dopamine levels in the brain which ultimately result in behavioural changes (Berenreiterovรก et al., 2011). Another area for future investigations would include how astrocytes are apparently clearing the T gondii infection through mechanisms other than IRG-dependent cell necrosis or killing of the parasite. These mechanisms by which astrocytes apparently clear T. gondii infection should be further investigated under in vivo conditions to determine if they are responsible for the lack of T. gondii infected astrocytes. In order to accomplish this, the researchers would have to create or use an in vivo mouse model with certain knockout genes for molecules in these mechanisms, or specific inhibitors. If the knockout models or inhibitors were non-specific, this experiment would be unsuccessful and further effort would have to be directed toward designing novel knockout models or in vivo models where it is possible to track these mechanisms. The authors were unable to clearly explain why there is a difference in T. gondii-host cell interactions between in vitro and in vivo conditions, specifically the paucity of infected astrocytes under in vivo conditions. To investigate these differences under in vitro and in vivo conditions, death of the infected astrocyte by other mechanisms must be ruled out using the experiment with knockout models (as suggested above). A broad area for further investigation in human hosts may include trying to develop vaccines against T. gondii similar to the current vaccine being developed for the malaria eradication initiative (malaria in humans also is caused by a parasite), partially funded by the Bill & Melinda Gates Foundation (Kite-Powell, 2018). In summary, this paper was a valuable contribution to advancing our knowledge of T. gondii biology and infection in vivo.

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REFERENCES 1. Berenreiterová, M., Flegr, J., Kuběna, A.A., Němec, P. (2011). The distribution of Toxoplasma gondii cysts in the brain of a mouse with latent toxoplasmosis: implications for the behavioral manipulation hypothesis. PLoS ONE 6(12), e28925. 2. Cabral, C.M., Tuladhar, S., Dietrich, H.K., Nguyen, E., MacDonald, W.R., Trivedi, T., et al. (2016). Neurons are the primary target cell for the brain-tropic intracellular parasite Toxoplasma gondii. PLoS Pathog, 12(2), e1005447. 3. Carruthers, V. B., Suzuki, Y. (2007). Effects of Toxoplasma gondii infection on the brain. Schizophrenia Bulletin, 33(3), 745-751. 4. Cekanaviciute, E., Dietrich, H.K., Axtell, R.C., Williams, A.M., Egusquiza, R., Wai, K.M., et al. (2014). Astrocytic TGF-β signaling limits inflammation and reduces neuronal damage during central nervous system Toxoplasma infection. J Immunol 193, 139-149. 5. Degrandi, D., Kravets, E., Konermann, C., Beuter-Gunia, C., Klümpers, V., Lahme, S., et al. (2013). Murine guanylate binding protein 2 (mGBP2) controls Toxoplasma gondii replication. Proc Natl Acad Sci USA, 110, 294-299. 6. Ferguson, D.J., Hutchison, W.M. (1987a). An ultrastructural study of the early development and tissue cyst formation of Toxoplasma gondii in the brains of mice. Parasitol Res, 73, 483-491. 7. Ferguson, D.J., Hutchison, W.M. (1987b). The host-parasite relationship of Toxoplasma gondii in the brains of chronically infected mice. Virchows Arch A Pathol Anat Histopathol, 411, 39-43. 8. Fischer, H.G., Nitzgen, B., Reichmann, G., Gross, U., Hadding, U. (1997). Host cells of Toxoplasma gondii encystation in infected primary culture from mouse brain. Parasitol Res, 83, 637-41. 9. Flegr, J. (2007). Effects of Toxoplasma on human behavior. Schizophrenia Bulletin, 33(3), 757760. 10. Furtado, J. M., Smith, J. R., Belfort, R., Gattey, D., Winthrop, K. L. (2011). Toxoplasmosis: a global threat. Journal of Global Infectious Diseases, 3(3), 281-284. 11. Gatkowska, J., Wieczorek, M., Dziadek, B., Dzitko, K., Dlugonska, H. (2012). Behavioral changes in mice caused by Toxoplasma gondii invasion of brain. Parasitol Res, 111(1), 53-58. 12. Gavrilescu, L.C., Denkers, E.Y. (2001). IFN-gamma overproduction and high level apoptosis are associated with high but not low virulence Toxoplasma gondii infection. J Immunol, 167, 902909. 13. Gulinello, M., Acquarone, M., Kim, J. H., Spray, D. C., Barbosa, H. S., Sellers, R., Tanowitz, H. B., Weiss, L. M. (2010). Acquired infection with Toxoplasma gondii in adult mice results in sensorimotor deficits but normal cognitive behavior despite widespread brain pathology. Microbes and Infection, 12(7), 528-537. 14. Halonen, S. K., Chiu, F., Weiss, L. M. (1998). Effect of cytokines on growth of Toxoplasma gondii in murine astrocytes. Infection and Immunity, 66(10), 4989-4993. 15. Halonen, S.K., Lyman, W.D., Chiu, F.C. (1996). Growth and development of Toxoplasma gondii in human neurons and astrocytes. J Neuropathol Exp Neurol, 55, 1150–1160. 16. Halonen, S. K., Taylor, G. A., Weiss, L. M. (2001). Gamma interferon-induced inhibition of Toxoplasma gondii in astrocytes is mediated by IGTP. Infection and Immunity, 69(9), 5573-5576. 17. Halonen, S. K., Weiss, L. M. (2000). Investigation into the mechanism of gamma interferonmediated inhibition of Toxoplasma gondii in murine astrocytes. Infection and Immunity, 68(6), 3426-3430. 18. Halonen, S. K., Weiss, L. M. (2013). Toxoplasmosis. Handbook of Clinical Neurology 114, 125145. 19. Hill, D., Chirukandoth, S., Dubey, J. (2005). Biology and epidemiology of Toxoplasma gondii in man and animals. Animal Health Research Reviews, 6(1), 41-61. 20. Kite-Powell, J. 2018. Gates Foundation funds research for new synthetic malaria vaccine. Forbes magazine online. https://www.forbes.com/sites/jenniferhicks/2018/01/19/gates-foundationfunds-research-for-new-synthetic-malaria-vaccine/#68111dd230c1,accessed November 29, 2018.

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21. Koshy, A.A., Cabral, C.M. (2014). 3-D imaging and analysis of neurons infected in vivo with Toxoplasma gondii. J. Vis. Exp, 94, 52237. 22. Koshy, A.A., Dietrich, H.K., Christian, D.A., Melehani, J.H., Shastri, A.J., Hunter, C.A., et al. (2012). Toxoplasma co-opts host cells it does not invade. PLoS Pathog, 8, e1002825. 23. Lee, S. B., Lee, T. G. (2017). Toxoplasmic encephalitis in patient with acquired immunodeficiency syndrome. Brain Tumor Research and Treatment, 5(1), 34-36. 24. Lüder, C.G.K., Giraldo-Velásquez, M., Sendtner, M., Gross, U. (1999). Toxoplasma gondii in primary rat CNS cells: differential contribution of neurons, astrocytes, and microglial cells for the intracerebral development and stage differentiation. Exp Parasitol, 93, 23-32. 25. Martens, S., Parvanova, I., Zerrahn, J., Griffiths, G., Schell, G., Reichmann, G., et al. (2005). Disruption of Toxoplasma gondii parasitophorous vacuoles by the mouse p47-resistance GTPases. PLoS Pathog, 1, e24. 26. McConkey, G. A., Martin, H. L., Bristow, G. C., Webster, J. P. (2013). Toxoplasma gondii infection and behaviour - location, location, location? Journal of Experimental Biology, 216(Pt 1), 113119. 27. Melzer, T.C., Cranston, H.J., Weiss, L.M., Halonen, S.K. (2010). Host cell preference of Toxoplasma gondii cysts in murine brain: a confocal study. J Neuroparasitology, 1. 28. Mendez, O. A., Koshy, A. A. (2017). Toxoplasma gondii: Entry, association, and physiological influence on the central nervous system. PLoS Pathog,13(7), e1006351. 29. Nielsen, H. V., Schmidt, D. R., Petersen, E. (2005). Diagnosis of congenital toxoplasmosis by two-dimensional immunoblot differentiation of mother and child immunoglobulin g profiles. Journal of Clinical Microbiology, 43(2), 711-715. 30. Scallan, E., Hoekstra, R. M., Angulo, F. J., Tauxe, R. V., Widdowson, M. A., Roy, S. L., Jones, J. L., Griffin, P. M. (2011). Foodborne illness acquired in the United States-major pathogens. Emerging Infectious Diseases, 17(1), 7-15. 31. Schlüter, D., Deckert, M., Hof, H., Frei, K. (2001). Toxoplasma gondii infection of neurons induces neuronal cytokine and chemokine production, but gamma interferon- and tumor necrosis factor-stimulated neurons fail to inhibit the invasion and growth of T. gondii. Infection and Immunity, 69(12), 7889-7893. 32. Sugden, K., Moffitt, T.E., Pinto, L., Poulton, R., Williams, B.S., Caspi, A. (2016). Is Toxoplasma gondii infection related to brain and behavior impairments in humans? Evidence from a population-representative birth cohort. PLoS ONE, 11(2), e0148435. 33. Suzuki, Y., Conley, F.K., Remington, J.S. (1989). Importance of endogenous IFN-gamma for prevention of toxoplasmic encephalitis in mice. J Immunol, 143, 2045-2050. 34. Suzuki, Y., Orellana, M.A., Schreiber, R.D., Remington, J.S. (1988). Interferon-gamma: the major mediator of resistance against Toxoplasma gondii. Science, 240, 516–518. 35. Wei, H.X., Wei, S.S., Lindsay, D.S., Peng, H.J. (2015). A systematic review and meta-analysis of the efficacy of anti-Toxoplasma gondii medicines in humans. PLoS ONE, 10(9), e0138204. 36. Zhou, P., Chen, Z., Li, H.L., Zheng, H., He, S., Lin, R.Q., Zhu, X.Q. (2011). Toxoplasma gondii infection in humans in China. Parasites & Vectors, 4(165).

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The integration of social influences in animal addiction models can contribute to novel treatment options for addiction Ria Patel Several animal models of addiction exist in the literature and have been monumentally helpful in determining the neurological pathways behind addiction. However, animal model translational to human addiction treatment is limited especially because most models fail to consider the impact of social influences on drug use. In a research study conducted by Venniro et al. the integration of the self-administration animal addiction model to a social parameter is used to elucidate the impact of societal influences on drug use. These researchers first found that the severity of drug addiction and abstinence from that drug to instead interact with a social partner is completely uncorrelated. They also found that compared to rats forced to abstain from methamphetamine use, rats that volitionally chose to interact with another rat and abstain from drug use had elevated FOS + protein kinase C-Î´ (PKCD) in neurons in the lateral central amygdala (CeL). It was speculated that these elevated levels contributed to protection against the incubation of methamphetamine addiction in rats that displayed volitional social abstinence. These results contribute to better treatment options for individuals struggling with drug addiction. Key words: drug addiction, animal model, methamphetamine, FOS, PKC- Î´ central amygdala

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Background and introduction

Addiction is described as a condition in which an individual develops compulsive drug seeking behavior, often at the expense of other activities and relationships in that individualâ&#x20AC;&#x2122;s life. (Koob, Caine, Parsons, Markou, & Weiss, 1997). Addiction is unique because it usually initiates through experimentation and morphs into a life-long dependence if left untreated. (Bell et al., 2016). Because this condition impacts a fair number of individuals, it doesnâ&#x20AC;&#x2122;t come as a surprise that addiction has been studied extensively in the literature for a number of years primarily using model systems to understand the circuitry and mechanisms behind this neurological behemoth (Kanarek, Dâ&#x20AC;&#x2122;Anci, Jurdak, & Mathes, 2009)(Robinson & Berridge, 2000) . One specific addiction model, the intravenous self-administration drug model, has been shown to correspond well to drugs used by humans with high abuse potential(Collins, Weeks, Cooper, Good, & Russell, 1983). Coupling this model with a choice model, in which an animal has the choice between self-administrating a drug or engaging in another more desired nondrug activity contributes to a better understanding of potential addiction treatments because choice plays a big part in human nature and the tendencies of an addicted individual (Wolffgramm, Galli, Thimm, & Heyne, 2000).

This is because for humans, societal factors, and not palatable food variables, play a monumental role in the consumption of drugs beginning from initial drug discovery, to continued use of the drug and treatment from the addiction (Hemminki, 1975). Consequently, despite robust research on addiction and addictive pathways, novel treatments are not as abundant as the research for addiction is(McGregor & Bowen, 2012).

A correlation between social influences and drug use was highlighted in a model in which addicted rats were exposed to stressful social environments and consequently increased drug use (Norman et al., 2015). However, the impact of a positive social experience on drug use had not been modelled yet and was the goal of the authors. To more closely model a human experience of drug addiction, Venniro et al., designed an experiment to observe drug self-administration when given a volitional nondrug social reward and a subject controlled operant choice (Venniro et al., 2018). They found that when given a choice, rats chose not to administer another dose of drug regardless of their addiction score and that volitional abstinence from drug use protected against methamphetamine incubation and relapse (Venniro et al., 2018). The authors correlated the prevention of a longer gestation period of methamphetamine with a subsequent increase of inhibitory neurons in the lateral central amygdala (CeL) expressing protein kinase C-Delta (PKCD) and FOS in mice exhibiting social choice abstinence and was absent from mice forced to abstain from the drug (Venniro et al., 2018).

Choice studies have been conducted on monkeys through preclinical drug vs food techniques in which subjects addicted to cocaine were presented with the choice to self-administer another dose of the drug or obtain a food reward (Banks & Negus, 2017). In this case, when presented with a nondrug Results reward, addicted monkeys more often took the reward rather than a dose of cocaine. Moreover, in Experiment 1: DSM-IV addicted rats abstain from a similar model using rats, when morphine addicted drug use when given a nondrug social alternative rats were presented with the choice of obtaining saccharine water or heroin, a significant number of rats abstained from drug administration and instead preferred the saccharine water (Ahmed, Lenoir, & Guillem, 2013). These studies emphasize the adverse relationship between a drug and a nondrug alternative when an addicted subject is given a choice between the two; however, they A D B C underline a lack of translation between animal addiction model treatment and that of humans. 140

Figure 1. Rats differing in addiction severity based on Diagnostic and Statistical Manual (IV)-based modelMale Sprague-Dawley rats were trained on methamphetamine self-administration for three 40-minute daily sessions with 15-minute breaks in between each training session. Training initiated with a red light illuminating the chamber in which the rat is present and insertion of a lever in the chamber. The rat had 60 seconds to press the lever upon which 0.1 mg/kg of methamphetamine was injected intravenously into the mouse. The number of lever presses made during this 15-minute break was recorded (figure 1a). A progressive-ratio test was conducted to determine motivation for methamphetamine in which experimenters increased the ratio of lever presses to drug administration in the sequence: 2,4,6,9,12,15,20,25,32,40, 50â&#x20AC;Ś (fig 1b). The number of instances a lever was pressed despite the fact that 50% of lever presses led to a foot shock (0.45mA) was recorded to see resistance to punishment (fig 2c). The addiction score distribution: high: z score >1; medium: z score 1 to -0.1; low: z score <-0.2 (fig 1d). Figure is obtained from Venniro et al. paper figure 2c (Venniro et al., 2018). Lever presses during a nondrug period, a progressive ratio test, and a punishment test were used as proxies for relapse testing on rats trained in methamphetamine self-administration and then using the z scores from these three tests, these rats were classified on the Diagnostic Statistical Manual (IV) (Linscott & van Os, 2010) (Fig. 1). Venniro et al. did this to ensure that the rats used in their study were clinically diagnosed with addiction or addictive tendencies.

Figure 2. DSM-IV score is irrespective of choosing social preference: Colors correlate to those in fig 1d. The same tests used in fig 1a-c are used here except lever presses (fig 2a) and number of rewards (fig 2b-c) are calculated instead of z-scores. Rats from each of the three groups were trained for social self- administration 40-minute sessions. This was done by first shining a yellow light in the chamber holding the rat for 10 seconds after which the social choice lever was inserted in the chamber. The rat in the chamber had 60 seconds to press the social choice lever before it retracted, and the light tuned off. After the lever was pressed, a distinct sound was emitted into the chamber and another rat (the social partner of the first rat) would enter the chamber for 120 seconds (fig 2d). The correlation between individual addiction scores and social rewards are shown in fig2e. Figure 2a-c is figure 2 d-f in Venniro et al. and fig 2d-e is figure 2 i-j in Venniro et al. (Venniro et al., 2018).

Venniro et al. found that the discrepancies in the addiction scores of the rats used in experiment 1 did not contribute to overall differences in the volitional choice of social interaction compared to self-administration of methamphetamine. This is emphasized in figure 2 by the significantly varied responses of the three levels of addiction to the relapse tests (fig 2a-c), but the lack of variation of these three groups during choice sessions. Fig 2e illustrates the lack of correlation between addiction score and choosing social interaction. Overall, even highly addicted rats choose social interaction over self-administration of drug. Experiment 2: Choosing socializing over self-administration of drug use prevents methamphetamine addiction incubation

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phenomenon. Vinnero et al. found that severity of addiction has no correlation to the volitional choice of socializing rather than receiving another dose of drug and that rats that voluntarily social abstention from self-administration of drugs had increased levels of FOS +PKCD expressed in CeL neurons (Venniro et al., 2018). This latter finding is important because the group elucidated that increased FOS +PKCD expression in inhibitory B neurons in the CeL region of the brains of rats that voluntarily abstained from methamphetamine was a protective measure that cut down the incubation time of drug addiction. This meant that these rats did not relapse back to drug use even after 15 days of abstinence. Venniro et al. proposed a mechanism for the protective pathway mentioned above in which social choice induced voluntary abstinence results in increased FOS and PKCD activity in inhibitory CeL neurons which then inhibit Figure 3. Social choice contributes to inhibition of methamphetthe activation of CeL somatostatin-positive or amine incubation and is correlated to an increase in FOS + PKCD in CeL neurons. A: Two groups of rats were used in this experiment: SOM+ neurons which are predicted to have been one that were given the choice to abstain from methamphetamine contributing to the incubation of drug addiction. dose and one that was forced to abstain. The relapse tests used in fig 1a and fig 2a were used in this experiment as a proxy for As mentioned in this paper, the role of the central meth addiction incubation. The rats were tested on the first day amygdala has previously been linked to studies on of abstinence and the 15th day of abstinence. This is figure 5d in Venniro et al. (Venniro et al., 2018) . B: the lateral central amygdala the appetite behaviors (Kim, Zhang, Muralidhar, (CeL) and the medial central amygdala (CeM) were lesioned in rats LeBlanc, & Tonegawa, 2017) and because of the from 4 categories: no test (served as the control and was taken from a rat at day 1 of abstinence); abstinence test day 1 (either forced strong link between appetite and drug addiction or voluntary); voluntary abstinence day 15; forced abstinence day (Davis & Carter, 2009), the pathway presented by 15. Immunohistochemistry after lesioning was conducted on these regions to yield the results above. This is figure 5h in Venniro et al. the Venniro et al. has some foundational integrity (Venniro et al., 2018). and is intriguing as it supports the argument that Experiment 2 showed firstly that voluntary social addiction to food can be similar to addiction to abstinence from methamphetamine use results drugs. in the prevention of drug addiction incubation as Moreover, the findings of this paper are significant seen in figure 3a in which the number of times rats because they first emphasize that severity of in the forced abstinence group press the lever on addiction is not a variable in the effectiveness of social day 15 is significantly greater than the number of interaction on abstinence from drug use in mice. lever presses on day 1 and that this difference is As a result, this study opens up a novel treatment absent for the rats voluntarily abstaining from sector for addictive individuals in the form of social drug use (fig 3a). Furthermore, when examining interactions which have not been given the most the brains of the rats in these two groups, CeL attention in general addiction treatment (Leshner, inhibitory neurons expressing FOS and PKCD was 1999). Additionally, with the finding that volitional significantly higher in the brains of rats voluntarily social abstinence is correlated with elevated FOS+ abstaining from drug use on day 15 than any of the PKCD levels in CeL neurons, an area of the brain is highlighted for further exploration and if pathways four other groups (fig 3b). associated with this region are mapped out, could again contribute to novel treatments for addictive Conclusion/Discussion behavior. Both these findings shed light to the fact that social influences should be considered as a This study was conducted to determine the vital variable in neuroscience research because it impact of social interaction on drug addiction and allows animal models to be more readily applied to used a self-administration model to describe this real life human situations. 142 A

Critical analysis

A major finding of the Venniro et al. paper was increased FOS+ PKCD expression in CeL neurons of rats choosing social interaction over drug use which consequently protects these rats from prolonged incubation of methamphetamine addiction. Another paper looking at the role of PKCD neurons in the central amygdala in relation to feeding behavior found that increased FOS+ PKCD expression was observed in cholecystokinin (CCK), lithium chloride, and lipopolysaccharide, three anorexigenic signals (Cai, Haubensak, Anthony, & Anderson, 2014). Like Vinnero et al.’s paper, the three signals above were found in the lateral region of the central amygdala and provide additional validity to the findings of Venniro et al. because if the argument that drug addiction and feeding signals are related is considered to be a valid one, signals of satiety, like CCK, and the repression of the incubation of a drug addiction, like the activity of inhibitory neurons in the CeL inhibiting SOM+ neurons as proposed by Venniro et al. should also be related. It would then make sense why these two repression mechanisms have the same elements activated: FOS+ PKCD. Additionally, because Vinnero et al.’s research is recent and has been published a handful of months ago and social influence has not been incorporated in many animal addiction models, there are limited papers to compare this one to and therefore discrepancies were not found. The methodology of Venniro et al. is overall quite extensive; however, in the case of classifying severity of addiction, it can be argued that had there been an intermediate classifcation between the “low” and “medium” group, the finding of the lack of correlation between the severity of addiction and choosing social interaction over drug administration would have held more validity. This is because addiction in humans is represented more from a spectrum rather than three distinct groups (Koob & Moal, 1997) and the data presented by this paper would have been more representative of human conditions had there been more than the three groups.

the researchers did train a group of rats to selfadminister heroin in one of their experiments. Because methamphetamine and heroin addiction have different neurological consequences especially in their relapse tendencies (Shaham, Shalev, Lu, de Wit, & Stewart, 2003), this paper could have benefitted from conducting experiment 2 described above on heroin addicted rats as well as methamphetamine addicted ones. If after the conduction of both these experiments, FOS+ PKCD was elevated in CeL neurons, a stronger case can be made for the role of these neurons in the inhibition of drug incubation. Future Directions

Although Venniro et al. designed their experiment to have a greater abstinence period than models using food as a nondrug alternative (Banks & Negus, 2017) (Ahmed et al., 2013) which typically use a 48h abstinence period, it can be argued that a 15 day abstinence period is not the best indicator for relapsing. In an experiment conducted on rats taught self-administration of cocaine, experimenters had abstinence periods of 30 days and then 90 days (Lu, Grimm, Shaham, & Hope, 2003). Lu et al. found a significantly high relapse test value in rats abstained from cocaine on day 90 than on day 30 or day 1. It can then be argued that although Venniro et al. found that volitional social abstinence after 1 day and after 15 days had insignificantly different relapse test values, that had this exact experiment been continued for a longer stretch of time, this consistency might have been absent. The proposal can be made that rats should not be lesioned after 15 days of volitional social abstinence or forced social abstinence and another relapse test be conducted on day 30 or even better, day 90.

Furthermore, because Venniro’s team emphasizes the finding of FOS + PCKD in rats engaged in volitional social abstinence, a future study could involve the overexpression of these two factors in neurons of the CeL in laboratory rats. These rats can then be trained for self-administration of drugs in the same procedures used by Venniro et al. for training and then a relapse lever pushing test can Moreover, although the majority of Venniro et be conducted against a control. Incorporating the al.’s data is on methamphetamine addiction, point made above, if after 15 days, 30 days, and 143

90 days, rats with an overexpression of FOS and PKCD in CeL neurons show consistent relapse test scores, there is even more evidence for why FOS and PKCD might be protective elements against drug incubation. On the other hand, a FOS + PKCD knock out model could be created after which relapse tests can be conducted. If rats with KO FOS +PKCD show lack of protection from drug incubation and their relapse tests scores mirror those seen in Venniro et al.â&#x20AC;&#x2122;s forced abstinence rats, the implicated importance of FOS + PKCD in addiction tendencies can be further elevated. One of the goals of researchers working on animal models is to heighten the translational capacity of animal model data to the human world and by having a 30 day or 90-day abstinence period, and genetic alterations to potential target factors like FOS and PKCD, greater strides can be made to increase this translational ability.

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References

1. Ahmed, S. H., Lenoir, M., & Guillem, K. (2013). Neurobiology of addiction versus drug use driven by lack of choice. Current Opinion in Neurobiology, 23(4), 581–587. https://doi.org/10.1016/j. conb.2013.01.028 2. Banks, M. L., & Negus, S. S. (2017). Insights from Preclinical Choice Models on Treating Drug Addiction. Trends in Pharmacological Sciences, 38(2), 181–194. https://doi.org/10.1016/j. tips.2016.11.002 3. Bell, R. L., Hauser, S., Rodd, Z. A., Liang, T., Sari, Y., McClintick, J., … Engleman, E. A. (2016). Chapter Seven - A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction. In Richard L. Bell & S. Rahman (Eds.), International Review of Neurobiology (Vol. 126, pp. 179–261). Academic Press. https://doi.org/10.1016/bs.irn.2016.02.017 4. Cai, H., Haubensak, W., Anthony, T., & Anderson, D. J. (2014). Central amygdala PKC-δ+ neurons mediate the influence of multiple anorexigenic signals. Nature Neuroscience, 17(9), 1240–1248. https://doi.org/10.1038/nn.3767 5. Collins, R. J., Weeks, J. R., Cooper, M. M., Good, P. I., & Russell, R. R. (1983). Prediction of abuse liability of drugs using IV self-administration by rats. Psychopharmacology, 82(1), 6–13. https:// doi.org/10.1007/BF00426372 6. Davis, C., & Carter, J. C. (2009). Compulsive overeating as an addiction disorder. A review of theory and evidence. Appetite, 53(1), 1–8. https://doi.org/10.1016/j.appet.2009.05.018 7. Hemminki, E. (1975). Review of literature on the factors affecting drug prescribing. Social Science & Medicine (1967), 9(2), 111–115. https://doi.org/10.1016/0037-7856(75)90103-1 8. Kanarek, R. B., D’Anci, K. E., Jurdak, N., & Mathes, W. F. (2009). Running and addiction: Precipitated withdrawal in a rat model of activity-based anorexia. Behavioral Neuroscience, 123(4), 905–912. https://doi.org/10.1037/a0015896 9. Kim, J., Zhang, X., Muralidhar, S., LeBlanc, S. A., & Tonegawa, S. (2017). Basolateral to Central Amygdala Neural Circuits for Appetitive Behaviors. Neuron, 93(6), 1464-1479.e5. https://doi. org/10.1016/j.neuron.2017.02.034 10. Koob, G. F., Caine, S. B., Parsons, L., Markou, A., & Weiss, F. (1997). Opponent Process Model and Psychostimulant Addiction. Pharmacology Biochemistry and Behavior, 57(3), 513–521. https://doi.org/10.1016/S0091-3057(96)00438-8 11. Koob, G. F., & Moal, M. L. (1997). Drug Abuse: Hedonic Homeostatic Dysregulation. Science, 278(5335), 52–58. https://doi.org/10.1126/science.278.5335.52 12. Leshner, A. I. (1999). Science-Based Views of Drug Addiction and Its Treatment. JAMA, 282(14), 1314–1316. https://doi.org/10.1001/jama.282.14.1314 13. Linscott, R. J., & van Os, J. (2010). Systematic Reviews of Categorical Versus Continuum Models in Psychosis: Evidence for Discontinuous Subpopulations Underlying a Psychometric Continuum. Implications for DSM-V, DSM-VI, and DSM-VII. Annual Review of Clinical Psychology, 6(1), 391– 419. https://doi.org/10.1146/annurev.clinpsy.032408.153506 14. Lu, L., Grimm, J. W., Shaham, Y., & Hope, B. T. (2003). Molecular neuroadaptations in the accumbens and ventral tegmental area during the first 90 days of forced abstinence from cocaine self-administration in rats. Journal of Neurochemistry, 85(6), 1604–1613. https://doi. org/10.1046/j.1471-4159.2003.01824.x 15. McGregor, I. S., & Bowen, M. T. (2012). Breaking the loop: Oxytocin as a potential treatment for drug addiction. Hormones and Behavior, 61(3), 331–339. https://doi.org/10.1016/j. yhbeh.2011.12.001 16. Norman, K. J., Seiden, J. A., Klickstein, J. A., Han, X., Hwa, L. S., DeBold, J. F., & Miczek, K. A. (2015). Social stress and escalated drug self-administration in mice I. Alcohol and corticosterone. Psychopharmacology, 232(6), 991–1001. https://doi.org/10.1007/s00213-014-3733-9 17. Robinson, T. E., & Berridge, K. C. (2000). The psychology and neurobiology of addiction: an incentive–sensitization view. Addiction, 95(8s2), 91–117. https://doi.org/10.1046/j.13600443.95.8s2.19.x 18. Shaham, Y., Shalev, U., Lu, L., de Wit, H., & Stewart, J. (2003). The reinstatement model of drug

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relapse: history, methodology and major findings. Psychopharmacology, 168(1), 3–20. https:// doi.org/10.1007/s00213-002-1224-x 19. Venniro, M., Zhang, M., Caprioli, D., Hoots, J. K., Golden, S. A., Heins, C., … Shaham, Y. (2018). Volitional social interaction prevents drug addiction in rat models. Nature Neuroscience, 21(11), 1520–1529. https://doi.org/10.1038/s41593-018-0246-6 20. Wolffgramm, J., Galli, G., Thimm, F., & Heyne, A. (2000). Animal models of addiction: models for therapeutic strategies? Journal of Neural Transmission, 107(6), 649–668. https://doi. org/10.1007/s007020070067

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Standard-Deviation Dependent Adaptive Prediction Error Coding in the Human Midbrain and Ventral Striatum Supports Learning Marlene Rong Reward-driven behaviour is an essential aspect of human behaviour and has evolutionarily beneficial value. Our notion of reward, and subsequent behaviour to gain additional rewards is based on our idea of the rewardâ&#x20AC;&#x2122;s expected value and probability of its occurrence. Reward prediction error (RPE) is generated when there are any discrepancies between what we expect as a reward outcome, and what we receive. Dopaminergic neurons, particularly in the midbrain, have been consistently implicated in processing reward and RPEs. However, the infinite range of values possible complicates representations of reward, and their fluctuation over time with varied probability distributions. In addition to this, the role adaptation to these broad distributions plays on human learning is not well understood. In their 2016 study, Diederen et al. find that prediction error coding in dopaminergic neurons is standard deviation-dependent in the substantia nigra/ventral tegmental area complex (SN/VTA), occurring over time. SD-dependent adaptations are also found in the ventral striatum. Most importantly, the study finds that adaptive prediction error coding is mirrored by behavioural adaptation, resulting in enhanced task performance and effective error-driven learning. The main result of Diederen et al. is an emphatic display of how our limited neural resources are best utilized, providing perspective on what situations are most informative in enhancing error-driven learning, and how our behaviour adapts, as a result, to guide informed decisions to receive additional rewards. Key words: reward prediction error; dopaminergic neurons; midbrain; standard deviation; substantia nigra/ventral tegmental area (SN/VTA); ventral striatum; adaptation

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BACKGROUND or INTRODUCTION

Reward, and behaviour to gain rewards, is an essential part of life rooted in one of the most basic forms of learning: error-driven reinforcement learning (Schultz, 2016). As Schultz (2016) explains, the evolutionary relevance of this is simple: when behaviour produces a better reward than expected, we will continue to enact the behaviour that produced that great reward. On the other hand, if the outcome is worse than predicted, we will adjust and avoid the behaviour in the future. This reward seeking behaviour is what drives reinforcement learning and decision-making. Our concept of reward, and subsequent choice behaviour, is based on our idea of the expected value of a reward. Based on probabilities of occurrence, the expected value (EV) is simply the weighted average of all possible reward magnitudes (Tobler, Fiorillo, & Schultz, 2005). Thus, humans, non-human primates, and rodents have been shown to constantly compare expected values with the reward itself (Schultz, 2016). A reward prediction error (RPE) is generated when there are discrepancies between what we expect as a reward outcome, and what we receive. RPEs are considered positive when the result exceeds our EV, and negative when the outcome is less than our EV. The crux of RPE-driven learning involves making mistakes—if there is no RPE, behaviour will not change and learning will not occur. In essence, because we desire the maximum reward possible, being able to take actions to improve our outcomes depends on our ability to adapt to environmental reward variability (Lee, Seo, & Jung, 2012; Tobler, Fiorillo, & Schultz, 2005). Our neurons constantly adjust—their signals are strengthened during winning actions and weakened during losing actions (Cohen & Ranganath, 2007; Schultz, 2016). As Bunzeck et al. (2010) note, this application also extends to novelty signals. Such mechanistic overlap is appropriate when we consider that novelty itself is driven by a desire to seek new rewards (Bunzeck et al., 2010).

been noted to fluctuate in relation to predicted reward magnitude in tandem with the probability with which such rewards are likely to occur (Lee et al., 2012). Most interestingly, Tobler et al. documented this in rodents, whose dopaminergic neurons were seen to code prediction error in such a manner, independent of the absolute reward magnitude difference when probability distributions were kept constant (2005). That is to say, these neurons responded similarly to reward with the same probability distributions, regardless of the absolute magnitude of the reward (Tobler et al., 2005). Kobayashi et al. were able to demonstrate this as well, where dopaminergic neurons in mouse orbitofrontal cortices showed adaptation to reward distribution (2010). In humans, dopaminergic neurons in the midbrain were noted to encode such reward prediction errors over a large range of reward values—such encoding also occurred independent of absolute differences. (Pedroni, Koeneke, Velickaite, & Jäncke, 2011). Finally, these dopamine neurons have been observed to be homogenous in nature, where their uniformity allows for the strongest prediction error signal possible (Eshel, Tian, Bukwich, & Uchida, 2016).

In mice, a vast majority of these neurons have been identified in the ventral tegmental area (VTA) via optogenetic methods (Eshel et al., 2016). Similarly, Chang et al. observed that optogenetic inhibition of the VTA mimics negative RPEs, highlighting a more causal link between these neurons and reward signalling (2016). Neurons in the ventral striatum have also been noted for their involvement in reward processing, but these effects are largely related to novelty (Guitart-Masip, Bunzeck, Stephan, Dolan, & Duzel, 2010). Collins et al. (2016) expanded upon these findings, observing prolonged dopamine signals in the nucleus accumbens in relation to novel violations in reward expectation. Overall, dopaminergic neuronal involvement in reward encoding is incredibly broad, where each neuron works in a similar manner to enhance the level of adaptation possible. Unfortunately, this makes it challenging to pinpoint the precise mechanisms by which adaptive coding occurs, and the role of efficient adaptation in learning (Diederen, Spencer, Vestergaard, Fletcher, & Schultz, 2016).

Dopaminergic neurons have been consistently implicated in involvement with processing reward The representation of reward in the brain is further and reward-predicting stimuli. Their activity has complicated by the infinite range of values possible 148

for rewards (Tobler et al., 2005). Moreover, these rewards are not constant and instead fluctuate over time with varied probability distributions (Diederen & Schultz, 2015). Due to our limited representational capacity in comparison to the infinite reward value possibilities, dopaminergic neurons, particularly in the substantia nigra/ventral tegmental area complex (SN/VTA), display adaptive coding in response to information about predictive reward value (Tobler et al., 2005). In a study conducted by Diederen and Schultz, it was suggested that reward prediction error scaling correlates with learning efficiency in humans (2015). That is, being able to utilize a prediction error seemed most important in contexts where rewards fluctuated less, and that this could potentially play a role in human learning (Diederen & Schultz, 2015). Ambiguity arises from the range of outputs possible in humans, the extent to which our SN/VTA neurons are able to achieve this prediction error coding, and their precise role in effective behavioural adaptation and learning. Through Diederen’s investigation (2016), prediction error coding in dopaminergic neurons was found to be standard deviation-dependent in the SN/VTA over time. Adaptations are also found in the ventral striatum, and are coded in an SD-dependent manner as well. This is in accordance with previous animal studies by Tobler et al. (2005), Kobayashi et al. (2010) and computational models by Preuschoff and Bossaerts (2007). Park et al. also noted that in humans, there is a reliance on the striatum and effective connectivity with other reward sensitive regions to achieve accurate representations of reward value (2012). Most importantly, the study finds that adaptive prediction error coding is mirrored by behavioural adaptation that results in enhanced task performance. Through their work, Diederen et al. (2016) determine that effective error-driven learning is dependent upon rapid acquisition of stable and accurate predictions based on the variability of reward. This is especially seen through individuals who have stronger task performance— in more efficient learners, dopaminergic neurons functioned at more optimal sensitivity and showed more robust utilization of such SD-dependent coding.

MAJOR RESULTS

In Diederen et al. (2016), participants were asked to perform a set of reward prediction tasks, which involves predicting their next reward based on previous rewards. Critically, the standard deviations of these rewards were varied from trial to trial. Participants received explicit cues about these SDs from which the expected value would be selected (i.e. rewards drawn from large pools or small pools of possible values). However, participants did not receive any explicit cue about the EV. As such, an RPE (either positive or negative) was generated each trial. Regions of interest (ROI) like the SN/VTA and ventral striatum were measured using fMRI to detect blood oxygen level dependent (BOLD) responses –this selection of ROIs was in reference to a wealth of literature pinpointing the midbrain as a centre for reinforcement learning and RPEs (Collins et al., 2016; Park et al., 2012; Tobler et al., 2005). Collectively, Diederen et al. (2016) found increasing SD-dependent adaptation in SN/VTA dopaminergic neurons. This was strongly correlated with heightened behavioural adaptation and improved task performance. Stable adaptation was also found in the ventral striatum, but to a lesser extent. Altogether, the authors’ results suggest that dopaminergic neurons in these ROIs engage in neural adaptation that facilitates effective learning in humans. SD-dependent adaptive coding occurs in the SN/ VTA and ventral striatum In their study, Diederen et al. address the existence of adaptive coding in the human midbrain (2016). The primary focus disentangles absolute coding versus standard deviation coding in these neurons. If absolute coding were to have been observed, prediction error coding slopes would have been the same regardless of standard deviation. However, this is not the case. Dopaminergic neuronal activity in the SN/VTA and ventral striatum is highly dependent on standard deviation. Such effects are most strongly felt with regards to smaller standard deviations.

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Figure 1. Activity slopes in the SN/VTA and ventral striatum decrease as standard deviation of reward variability increases, signalling adaptive coding. Note that the smallest SD (SD5) shows the steepest slope and therefore enhanced sensitivity. This is especially noticeable in the SN/VTA, and is consistent across positive and negative RPEs. Figure adapted from Diederen et al. (2016). Neuron, 90(5), 1127â&#x20AC;&#x201C;1138

Figure 2. Significant effects of SD changes on neuronal activity are observed in the SN/VTA and ventral striatum, particularly in small SD compared to larger SDs. Figure adapted from Diederen et al. (2016). Neuron, 90(5), 1127â&#x20AC;&#x201C;1138.

This is in line with the previous work of Tobler et al., which observed that dopamine neurons scale not based on the absolute value of the difference but based on probability instead (2005). The authors were able to determine that sensitivity is related to probability, where larger discrepancies led to less sensitive encoding and small discrepancies were more sensitive (Tobler et al., 2005). This same conclusion is noted in the results of Diederen et al., coinciding with their demonstration that RPEs of positive/negative coding were more finely tuned when SD was smaller, regardless of absolute outcome value. From this, it is affirmed that less variability results in higher sensitivity for both positive and negative RPEs, and that this is achieved through adaptive coding.

Several regions besides the SN/VTA have been reported to exhibit adaptation with regard to reward value. Namely, portions of the prefrontal cortex like the ventralmedial prefrontal cortex, and the orbitofrontal cortex have been implicated in tracking learned reward value and facilitating striatal prediction error encoding (Jocham, Klein, & Ullsperger, 2011; Lee, Seo, & Jung, 2012). However, none have reported these novel results, which pinpoint SD-dependent prediction error coding in the SN/VTA and ventral striatum. Diederen et al. find that SN/VTA neurons do not instantaneously enact RPE adaptive encoding, but instead do so over time (2016). This adaptation is also noted in the ventral striatum, but to a lesser extentâ&#x20AC;&#x201D; importantly, its adaptation is instantaneous and stable across trials.

These findings also agree with previous results that activity is highest when reward distributions change less frequently (Kobayashi et al., 2010; Lee et al., 2012). In essence, Diederen et al. data further reinforce that these neurons must focus on more probable rewards, and fine tune their

Adaptation in the SN/VTA occurs over time

SD-dependent coding in SN/VTA and ventral striatum supports behavioural adaptation and effective learning

Task performance is defined as the average number representations to reflect this at the expense of of errors across all trials. When considered with accuracy and stability, performance is able to signify less probable rewards (2016). learning (Diederen et al., 2016). In their study, Diederen et al. note that effective learning depends on the rapid acquisition of stable and accurate predictions based on the variability of reward in each standard deviation (2016). Individuals who have better task performance are found to be 150

more efficient learners— the higher the activity in the SN/VTA, the better the individual performed in comparison to participants with weaker adaptive activity in response to SD (Diederen et al., 2016). Dopaminergic neurons in more efficient learners are able to function at more optimal sensitivities, guided by standard deviation. It should be noted that these decreases in performance error were independent of working memory and instead were due to behavioural adaptation (Diederen et al., 2016).

90(5), 1127–1138.

The results of improved task performance can also be viewed as a quantification of degrees of adaptation with regards to the standard deviation of rewards variability. From the work of Diederen et al., SD-dependent neuronal adaptation supports behavioural adaptation and learning as a whole, achieved via the scaling of prediction errors to achieve optimal sensitivity (2016). Occurring mostly in the SN/VTA, and to a lesser extent in the ventral striatum, the study elucidates the degree to which this encoding is able to improve learning, which studies in the past have failed to investigate. CONCLUSIONS/DISCUSSION

It has been long understood that dopaminergic neurons encode a combination of the magnitude of reward and probability of their occurrence (Tobler, Fiorillo, & Schultz, 2005). However, the precise Figure 3. Trials were clustered into early (1-7), middle mechanism for encoding these adaptive changes (8-14) and late (15-21). While the ventral striatum’s in the human midbrain was not fully understood. In degree of adaptation remains stable throughout particular, the question of if such adaptation could trials, coding in the SN/VTA emerges over time positively affect learning was also unclear. Diederen and peaks during late trials. Figure adapted from et al. capture this mechanism of adaptive coding and its importance in adaptive human behaviour, Diederen et al. (2016). Neuron, 90(5), 1127–1138. effective task performance, and learning (2016). Their work acts as an important link between previous findings regarding dopaminergic activity in a broad range of regions in the for reward processing, and human learning (Diederen et al., 2016). Their findings further emphasize the role of the SN/VTA and ventral striatum in human representations of reward prediction errors (Diederen et al., 2016). In essence, the study captures what previous studies in the field have struggled to establish— that neurons do indeed adjust to standard deviation, and that efficiency in this coding translates to enhanced behavioural performance (Diederen et al., 2016). Figure 4. As neural adaptation increased overall, behavioural adaptation also increased, signifying the role of neural adaptation in both the SN/VTA and ventral striatum in learning. This was associated with decreases in performance error, calculated by |prediction - EV|, averaged across all trials and SD. Figure adapted from Diederen et al. (2016). Neuron,

For the first time, this study transforms our understanding of how adaptive coding in the SN/VTA influences human reward behaviour by demonstrating its dependence on standard deviation (Diederen et al., 2016). The authors’ work suggests that learning is more efficient when adaptive coding facilitates behavioural adaptation,

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and that this adaptive coding is based on the standard deviation of reward variability because of prediction errors (Diederen et al., 2016). Diederen et al. shed light on how our limited neural resources are best utilized, providing perspective on what situations are more informative in enhancing errordriven learning, and how our behaviour adapts as a result to guide informed decisions. CRITICAL ANALYSIS

Diederen et al. conclude that neural adaptation increases over time in the SN/VTA during reward prediction tasks, and that this guides behavioural adaptation and learning as a whole. As such, a major point of consideration is the role of time beyond what was tested, and the extent to which learning is preserved with respect to adaptive coding. The authors fail to express the extent to which this adaptation is maintained, both at the level of the SN/VTA and behaviourally. If behaviour and learning is maintained at longer time intervals, the question of whether adaptation in the SN/ VTA continues to increase arises and becomes an interesting point of concern. The range of standard deviations for reward variability is also lacking. While the authors’ work shows relatively strong SD-dependent adaptation, the full extent to which this occurs is limited by their incorporation of only three standard deviations within their study. It is briefly noted that early trials are most informative for neuronal adaptation (Diederen et al., 2016). However, the extent to which this occurs is unclear— when does this informative peak begin to plateau and is this observed equally between standard deviations? Moreover, the complexity of tasks must also be considered. It is difficult to see if these findings would generalize to a setting outside of simple generations of RPE. The extent of task difficulty may challenge the SD-dependent encoding of possible reward values, and diminish the effects observed in their study, as well as the informative nature of early trials.

option considers that the ventral striatum does not exclusively receive signals from the midbrain dopaminergic neurons. The authors’ ulterior explanation is attributed to fMRI sensitivity. However, Diederen et al. fail to acknowledge the role of the ventral striatum’s encoding of novel stimuli in relation to reward variability (GuitartMasip, Bunzeck, Stephan, Dolan, & Duzel, 2010). The task itself likely lost novelty over succeeding trials, which could have dampened or obscured detected neuronal adaptation. FUTURE DIRECTIONS

While the midbrain is an incredibly important structure in reward driven learning, other regions have also been noted to play a role in encoding RPEs—Diederen et al. also acknowledge this in their discussion (2016). Previous studies have identified many regions that Diederen et al. overlook, such as the orbitofrontal cortex (Kobayashi, Pinto de Carvalho, & Schultz, 2010). While Diederen et al. draw upon local maxima in multiple regions surrounding the SN/VTA (such as the thalamus) and in the frontal lobe, the BOLD responses are not high enough in resolution to be considered for full investigation in their present study (2016). However, some activity is detected. These may reflect assorted outputs and an overall distributed network of activity associated with RPEs. As such, because a fundamental aspect of their study delves into the links such neurons have with behavioural adaptation, these additional regions may be of interest for deeper investigation in the future (Diederen et al., 2016).

Burke et al. note that while neurons in the ventral striatum adapt like Diederen et al. observe, they still keep track of long-term goals through partial adaptive coding instead of full adaptive coding of outcomes (2016). Some levels of absolute coding were also noted, achieved via stepwise multivariate searchlight analysis that allowed the specific degree of increasing/decreasing activity with increasing value to be full evaluated (Burke et al., 2016). This is potentially linked to why the ventral Lastly, an interesting and important consideration striatum in Diederen et al. does not continue to see to make is the explanations of Diederen et al. scaling to the same degree as the SN/VTA. It may for the finding that the ventral striatum does also help combat the criticism regarding the role not change significantly over time (2016). One of time course on SD-dependent neuronal activity 152

preservation.

Although it is likely that the neural networks work in tandem to establish accurate and efficient representations of reward variability, it is important to disentangle the role of the ventral striatum in particular. As mentioned, it is important to acknowledge that the ventral striatum is found to mostly focus on novelty (Guitart-Masip et al., 2010). Chumbley et al. also supports the need for further exploration: signals of reward-related surprise outside of RPEs are linked to the ventral striatum, among other regions like the primary sensory cortex and amygdala (2014). As such, it may be of interest for researchers to continue exploring how the ventral striatum alone can guide behavioural adaptation, and if it employs the same stable SDdependency without the SN/VTA â&#x20AC;&#x201C;perhaps via transcranial magnetic stimulation. This dissociation may elucidate clearer mechanisms of the ventral striatumâ&#x20AC;&#x2122;s role in these learning processes. Finally, recent work highlights our ever-changing understanding of dopaminergic neurons, and the role of these prediction error neurons in modelbased acquisitions (Sharpe et al., 2017). These model-based acquisitions utilized by Sharpe et al. (2017) and explained by Lee et al. (2012), are reflective of more flexible adjustments of RPE coding neurons to complex stimuli that may be more relevant in everyday contexts. Diederen et al. do not investigate this in their 2016 study, disregarding the role of RPE encoding neuronal activity on other actions besides the exact, but limited, behaviour eliciting reward (2016). Sharpe et al. (2017) conclude that dopaminergic neuron prediction error coding also applies in non-reward settings. The authors and other researchers may consider this valuable in future work. Furthermore, it allows for a potential extension of the findings of Diederen et al. regarding SD-dependent RPE coding neurons and adaptive human learning (2016).

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REFERENCES 1. Burke, C. J., Baddeley, M., Tobler, P. N., & Schultz, W. (2016). Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses. Journal of Neuroscience, 36(39), 10016–10025. Bunzeck, N., Dayan, P., Dolan, R. J., & Duzel, E. (2010). A common mechanism for adaptive scaling of reward and novelty. Human Brain Mapping, 31(9), 1380–1394. https://doi.org/10.1002/hbm.20939 2. Burke, C. J., Baddeley, M., Tobler, P. N., & Schultz, W. (2016). Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses. Journal of Neuroscience, 36(39), 10016–10025. https://doi.org/10.1523/JNEUROSCI.0487-16.2016 3. Chang, C. Y., Esber, G. R., Marrero-Garcia, Y., Yau, H.-J., Bonci, A., & Schoenbaum, G. (2016). Brief optogenetic inhibition of dopamine neurons mimics endogenous negative reward prediction errors. Nature Neuroscience, 19(1), 111. https://doi.org/10.1038/nn.4191 4. Chumbley, J., Burke, C. J., Stephan, K. E., Friston, K. J., Tobler, P. N., & Fehr, E. (2014). Surprise Beyond Prediction Error. Human Brain Mapping, 35, 4805–4814. https://doi.org/10.1002/ hbm.22513 5. Cohen, M. X., & Ranganath, C. (2007). Reinforcement Learning Signals Predict Future Decisions. The Journal of Neuroscience, 27(2), 371–378. https://doi.org/10.1523/JNEUROSCI.4421-06.2007 6. Collins, A. L., Greenfield, V. Y., Bye, J. K., Linker, K. E., Wang, A. S., & Wassum, K. M. (2016). Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation. Scientific Reports, 6(October 2015), 1–15. https://doi.org/10.1038/srep20231 7. Diederen, K. M. J., & Schultz, W. (2015). Scaling prediction errors to reward variability benefits error-driven learning in humans. Journal of Neurophysiology, 114(3), 1628–1640. https://doi. org/10.1152/jn.00483.2015 8. Diederen, K., Spencer, T., Vestergaard, M. D. D., Fletcher, P. C. C., & Schultz, W. (2016). Adaptive Prediction Error Coding in the Human Midbrain and Striatum Facilitates Behavioral Adaptation and Learning Efficiency. Neuron, 90(5), 1127–1138. https://doi.org/10.1016/j.neuron.2016.04.019 9. Eshel, N., Tian, J., Bukwich, M., & Uchida, N. (2016). Dopamine neurons share common response function for reward prediction error. Nature Neuroscience. https://doi.org/10.1038/nn.4239 10. Guitart-Masip, M., Bunzeck, N., Stephan, K. E., Dolan, R. J., & Duzel, E. (2010). Contextual Novelty Changes Reward Representations in the Striatum. Journal of Neuroscience, 30(5), 1721–1726. https://doi.org/10.1523/JNEUROSCI.5331-09.2010 11. Jocham, G., Klein, T. A., & Ullsperger, M. (2011). Dopamine-Mediated Reinforcement Learning Signals in the Striatum and Ventromedial Prefrontal Cortex Underlie Value-Based Choices. Journal of Neuroscience, 31(5), 1606–1613. https://doi.org/10.1523/JNEUROSCI.3904-10.2011 12. Kobayashi, S., Pinto de Carvalho, O., & Schultz, W. (2010). Adaptation of Reward Sensitivity in Orbitofrontal Neurons. Journal of Neuroscience, 30(2), 534–544. https://doi.org/10.1523/ JNEUROSCI.4009-09.2010 13. Lee, D., Seo, H., & Jung, M. W. (2012). Neural Basis of Reinforcement Learning and Decision Making. Annual Review of Neuroscience, 35(1), 287–308. https://doi.org/10.1146/annurevneuro-062111-150512 14. Park, S. Q., Kahnt, T., Talmi, D., Rieskamp, J., Dolan, R. J., & Heekeren, H. R. (2012). Adaptive coding of reward prediction errors is gated by striatal coupling. Proceedings of the National Academy of Sciences, 109(11), 4285–4289. https://doi.org/10.1073/pnas.1119969109 15. Pedroni, A., Koeneke, S., Velickaite, A., & Jäncke, L. (2011). Differential magnitude coding of gains and omitted rewards in the ventral striatum. Brain Research, 1411, 76–86. https://doi. org/10.1016/j.brainres.2011.07.019 16. Preuschoff, K., & Bossaerts, P. (2007). Adding prediction risk to the theory of reward learning. Annals of the New York Academy of Sciences, 1104, 135–146. https://doi.org/10.1196/ annals.1390.005 17. Schultz, W. (2016). Dopamine reward prediction error coding. Dialogues in Clinical Neuroscience, 18(1), 23–32.

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18. Sharpe, M. J., Chang, C. Y., Liu, M. A., Batchelor, H. M., Mueller, L. E., Jones, J. L., … Schoenbaum, G. (2017). Dopamine transients are sufficient and necessary for acquisition of model-based associations. Nature Neuroscience, 20(5), 735–742. https://doi.org/10.1038/nn.4538 19. Tobler, P. N., Fiorillo, C. D., & Schultz, W. (2005). Adaptive Coding of Reward Value by Dopamine Neurons. https://doi.org/10.1126/science.1105370https://doi.org/10.1523/ JNEUROSCI.0487-16.2016 20. Chumbley, J., Burke, C. J., Stephan, K. E., Friston, K. J., Tobler, P. N., & Fehr, E. (2014). Surprise Beyond Prediction Error. Human Brain Mapping, 35, 4805–4814. https://doi.org/10.1002/ hbm.22513 21. Diederen, K., Spencer, T., Vestergaard, M. D. D., Fletcher, P. C. C., & Schultz, W. (2016). Adaptive Prediction Error Coding in the Human Midbrain and Striatum Facilitates Behavioral Adaptation and Learning Efficiency. Neuron, 90(5), 1127–1138. https://doi.org/10.1016/j.neuron.2016.04.019 22. Guitart-Masip, M., Bunzeck, N., Stephan, K. E., Dolan, R. J., & Duzel, E. (2010). Contextual Novelty Changes Reward Representations in the Striatum. Journal of Neuroscience, 30(5), 1721–1726. https://doi.org/10.1523/JNEUROSCI.5331-09.2010 23. Jocham, G., Klein, T. A., & Ullsperger, M. (2011). Dopamine-Mediated Reinforcement Learning Signals in the Striatum and Ventromedial Prefrontal Cortex Underlie Value-Based Choices. Journal of Neuroscience, 31(5), 1606–1613. https://doi.org/10.1523/JNEUROSCI.3904-10.2011 24. Kobayashi, S., Pinto de Carvalho, O., & Schultz, W. (2010). Adaptation of Reward Sensitivity in Orbitofrontal Neurons. Journal of Neuroscience, 30(2), 534–544. https://doi.org/10.1523/ JNEUROSCI.4009-09.2010 25. Lee, D., Seo, H., & Jung, M. W. (2012). Neural Basis of Reinforcement Learning and Decision Making. Annual Review of Neuroscience, 35(1), 287–308. https://doi.org/10.1146/annurevneuro-062111-150512 26. Sharpe, M. J., Chang, C. Y., Liu, M. A., Batchelor, H. M., Mueller, L. E., Jones, J. L., … Schoenbaum, G. (2017). Dopamine transients are sufficient and necessary for acquisition of model-based associations. Nature Neuroscience, 20(5), 735–742. https://doi.org/10.1038/nn.4538 27. Tobler, P. N., Fiorillo, C. D., & Schultz, W. (2005). Adaptive Coding of Reward Value by Dopamine Neurons. https://doi.org/10.1126/science.1105370

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More than just a sugar rush: The impact of fructose and diet-induced insulin resistance on the ability of the brain to recover after traumatic brain injury Katarina Savel As health trends in Western society move towards obesity, insulin resistance, metabolic syndrome, and type-2 diabetes, it is necessary to consider the effects of poor diet on brain health. In the study performed by Agrawal et al., â&#x20AC;&#x153;Dietary fructose aggravates the pathobiology of TBI by influencing energy homeostasis and plasticity,â&#x20AC;? the researchers examined the effect of dietary fructose and insulin resistance (IR) on the ability of mice to recover following traumatic brain injury (TBI)1. Sprague-Dawley mice were trained on the Barnes Maze Task for five days before having their escape times recorded. Half the mice were randomly assigned to consume a mixture of fructose and water (FRU cohort) while the other half was assigned to consume regular water (Con cohort). After 6 weeks of treatment, a glucose tolerance test was administered to both cohorts to establish insulin resistance in the FRU mice. At 7 weeks, half the mice from each of the FRU and Con cohorts were subjected to a fluid-percussion injury (FPI) as a model of TBI (FPI cohort), while the other half of the mice received sham injuries (Sham cohort). The four cohorts (Con/Sham, Con/FPI, FRU/Sham and FRU/FPI), were re-tested on the Barnes Maze Task, sacrificed immediately after, and had hippocampal brain tissue extracted for analyses. Fructose, IR, and TBI had a negative, additive effect on cognition, neuronal plasticity, energy regulation, mitochondrial function, and neuroinflammation. Future research should address the long-term impact of IR on TBI recovery and build upon the cellular mechanisms of the observed relationship. Key words: fructose, diet-induced insulin resistance (IR), Traumatic Brain Injury (TBI), plasticity, energy homeostasis, cognitive function.

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Introduction

Fructose is a simple sugar found in high quantities in sugar-sweetened beverages, high fructose corn syrup, honey, and fruit juices. It has been suggested as a central factor in the cognitive and neural abnormalities in individuals with Metabolic Syndrome, Type-2 Diabetes, and insulin resistance (IR)1. The impact of IR on chronic neurodegenerative disease has been widely studied. Alzheimer’s Disease has even been referred to as type-3 diabetes and diabetes of the brain2molecular, and biochemical abnormalities, including cell loss; abundant neurofibrillary tangles; dystrophic neurites; amyloid precursor protein, amyloid-β (APP-Aβ. Less is known about the impact of brain IR on brain injury. Diabetic patients have worse outcomes and higher mortality rates following traumatic brain injury (TBI) compared to non-diabetic patients, but the mechanisms of this observation are not yet understood3. IR is the diminished cellular response to insulin resulting in high blood glucose levels4recent reports on the location of insulin and its receptors in the brain have introduced new ways of considering this hormone responsible for several functions. The origin of insulin in the brain has been explained from peripheral or central sources, or both. Regardless of whether insulin is of peripheral origin or produced in the brain, this hormone may act through its own receptors present in the brain. The molecular events through which insulin functions in the brain are the same as those operating in the periphery. However, certain insulin actions are different in the central nervous system, such as hormone-induced glucose uptake due to a low insulin-sensitive GLUT-4 activity, and because of the predominant presence of GLUT-1 and GLUT3. In addition, insulin in the brain contributes to the control of nutrient homeostasis, reproduction, cognition, and memory, as well as to neurotrophic, neuromodulatory, and neuroprotective effects. Alterations of these functional activities may contribute to the manifestation of several clinical entities, such as central insulin resistance, type 2 diabetes mellitus (T2DM. In mice, fructose consumption causing IR impairs performance on novel object recognition tasks and spatial learning tasks5–7. In the hippocampus, fructose induced

IR reduces dendritic spine density, reduces neurogenesis, and impairs long-term potentiation at the Schaffer Collateral to CA1 synapses7,8. Fructose consumption decreases brain-derived neurotrophic factor (BDNF) production and interferes with the PI3 anti-apoptotic pathway, leading to neuronal death7,9. Fructose consumption increases inflammatory cytokine production including TNFα,and IL-68,10. It also increases lipid peroxidation as measured by 4HNE, a marker of oxidative stress5,8. Lastly, fructose impairs energy metabolism in the brain, reducing ATP production5. Markers of inflammation and energy dysfunction present in brain IR are paralleled in TBI. TBI impairs the brain’s ability to metabolize glucose causing an energy crisis1. As a result, mitochondria suffer from respiratory dysfunction leading to decreased ATP availability following injury, similar to what is observed in brain IR11,12which represents the direct mechanical damage, cannot be therapeutically influenced, target of the treatment is the limitation of the secondary damage (delayed non-mechanical damage. TBI also induces an inflammatory response in the brain. Microglia are activated by the release of molecules signaling neuronal distress13. Microglial activation promotes chemokine and cytokine production including IL-6 and TNFα, which peak shortly after injury13,14.

Agrawal et al. address the overlapping brain pathology present in diet-induced IR and TBI. IR was induced in mice by administering fructose infused water for 6 weeks and confirmed through a glucose tolerance test. TBI was modeled by fluid percussion injury (FPI). Mice received a craniotomy of the left parietal cortex that was then percussed with an injury device. Four cohorts of mice were analyzed and compared (n=7/group): (I) mice given normal water and a sham injury (Con/Sham), (II) mice given normal water and subjected to FPI (Con/ FPI), (III) mice given fructose infused water and a sham injury (FRU/Sham) and (IV) mice given fructose infused water and subjected to FPI (FRU/FPI). Mice were trained and tested on the Barnes Maze Task before treatment and re-tested after treatment. Following the second Barnes Maze Task mice were sacrificed and hippocampal tissue was extracted for analyses. Agrawal et al. demonstrated that dietary fructose consumption and diet-induced IR exacerbate TBI pathophysiology1. 157

MAJOR RESULTS

Figure 1: Comparison of maze latency times as an indication of memory retention and cognitive performance. FRU/FPI mice took significantly Metabolic Dysfunction longer to complete the Barnes Maze Task compared Fructose consumption reduced phosphorylation to the other cohorts. Figure Adapted from Agrawal of insulin receptors indicating impaired insulin et al. (2016). The Journal of Cerebral Blood Flow signaling and IR in FRU/FPI and FRU/Sham mice1. and Metabolism, 36(5) 941–953. These mice also had increased serum triglycerides1. The combination of IR and high serum triglycerides indicates the mice developed metabolic syndrome5. Cognitive Performance Fructose and FPI had an additive effect on escape time in the Barnes Maze Task. FRU/FPI mice took significantly longer to escape the maze compared to FRU/Sham and Con/FPI mice1. Fructose-induced IR exacerbated cognitive impairment occurring after injury, leading to decreased memory retention and longer escape times1. Figure 2: BDNF production expressed as a percent of Con/Sham levels. Fructose and FPI (FRU/FPI BDNF production and BDNF mediated plasticity cohort) reduced BDNF levels the most compared to fructose alone and FPI alone. Figure Adapted from Agrawal et al. (2016). The Journal of Cerebral Blood Fructose and FPI had an additive effect on BDNF Flow and Metabolism, 36(5) 941–953. production and BDNF mediated plasticity. FRU/ FPI mice had the greatest reduction in BDNF levels (Figure 2)1. FRU/FPI mice also had the greatest Energy Regulation reduction in TrkB phosphorylation, indicating decreased BDNF signalling1. Fructose and FPI Fructose and FPI impaired mitochondrial function Fructose and FPI caused the greatest reduction in SYP and GAP43 and energy regulation. independently reduced Cytochrome C oxidase expression, indicating decreased BDNF-mediated plasticity1. Fructose alone did not significantly (CO), an enzyme of the electron transport chain 1,11 reduce BDNF levels, but the additive effect seen involved in ATP production . CO activity was in FRU/FPI mice indicates that fructose induced IR also reduced in FRU/FPI mice, however no additive 1 predisposed the mice to greater BDNF reductions effect was observed (Figure 4) . following brain injury. All three treatment groups had significantly reduced PGC-1α levels, a transcriptional coactivator of mitochondrial biogenesis (Figure 5)1,15. Both fructose alone and fructose plus FPI reduced PGC1α levels more than FPI alone.

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Figure 4: A comparison of Cytochrome C Oxidase (CO) activity. CO activity was significantly reduced in all three treatment groups (FRU/Sham, Con/FPI and FRU/FPI). Figure Adapted from Agrawal et al. (2016). The Journal of Cerebral Blood Flow and Metabolism, 36(5) 941–953.

Figure 6: A comparison of 4HNE production expressed as a percentage of Con/Sham levels. Fructose and FPI significantly increased 4HNE levels, indicating oxidative stress and inflammation. Figure Adapted from Agrawal et al. (2016). The Journal of Cerebral Blood Flow and Metabolism, 36(5) 941–953.

DISCUSSION Agrawal et al.’s results demonstrate a strong and additive interaction between fructose induced IR and FPI pathology in mice. Agrawal et al. showed that fructose exacerbates the effects of FPI with respect to cognitive performance, BDNF levels, plasticity, energy regulation, and neuroinflammation. They also proposed a novel mechanism by which fructose, IR and TBI may interact to impact energy regulation, inflammation, protein expression, and cognition (Figure 7)1. More broadly, they concluded that diet is a predictor of resiliency after brain injury.

Figure 5: A comparison of PGC-1a levels expressed as a percentage of Con/Sham levels. Fructose alone reduced PGC-1a levels more than FPI alone. Figure Adapted from Agrawal et al. (2016). The Journal of Cerebral Blood Flow and Metabolism, 36(5) 941–953.

Neuroinflammation Fructose and FPI had an additive effect on 4HNE levels, a product of lipid peroxidation (Figure 6)1. Lipid peroxidation occurs when free radicals take electrons from a cell membrane, beginning a chain of inflammatory reactions that induce oxidative damage16. Fructose and FPI caused the greatest inflammatory response compared to fructose alone and FPI alone.

Agrawal et al. support their novel finding of the additive effect of fructose and FPI by also demonstrating the effects of fructose and FPI independent of one another. The FRU/Sham and Con/FPI cohorts show that Agrawal et al. successfully modelled brain IR and TBI. In the FRU/Sham mice, fructose induced insulin resistance, impaired cognition, dysregulated energy homeostasis, and caused inflammation. These results are supported by previous research demonstrating the effect of high fructose intake5–7,9,10,17. In Con/FPI mice, FPI alone reduced BDNF levels, impaired cognition, dysregulated energy, and caused inflammation. These results are also consistent with previous research demonstrating the effects of TBI11– 14,18 which represents the direct mechanical damage, cannot be therapeutically influenced, target of

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the treatment is the limitation of the secondary behavioural issues such as excessive aggression20. damage (delayed non-mechanical damage. Mice did not undergo any depression or anxiety tests, and no behavioural measures were taken Agrawal et al.’s results are clinically relevant beyond the Barnes Maze Task. considering the rising prevalence of obesity, Further research is needed to establish the type-2 diabetes, and metabolic syndrome1. The mechanism outlined in Figure 7. Agrawal et al. International Diabetes Federation estimated that provided a general framework of the mechanism, in 2017 there were 352 million people worldwide but each element of the interaction (insulin signaling, at risk of developing type-2 diabetes, of which IR is BDNF signaling, mitochondrial bioenergetics, a key factor19. Not only do these individuals have plasticity, cognition and inflammation) should be an increased risk of developing neurodegenerative independently studied. disease among other chronic diseases, but according to Agrawal et al.’s findings they also FUTURE RESEARCH DIRECTION have reduced capacity for resiliency and recovery after brain injury. Future research should focus on establishing the mechanism outlined in Figure 7 in both model organisms and humans. This can be achieved by repeated animal studies of IR and TBI interactions with a focus on different aspects of the proposed pathway. For example, a study looking solely at fructose, TBI, and inflammation. A detailed explanation of each aspect of the mechanism of interaction is necessary to gain a complete understanding of the impact of IR on TBI recovery and brain resiliency. In humans, researchers should perform post-mortem brain analyses of insulin resistant TBI patients similarly to how Agrawal et al. analyzed hippocampal tissue in mice. I expect that pathology in human brains will be similar to that Figure 7: A possible mechanism of interaction between in mouse brains given the comparable physiology. fructose, IR and TBI. Figure Adapted from Agrawal et al. (2016). The Journal of Cerebral Blood Flow and Metabolism, 36(5) 941–953.

CRITICAL ANALYSES One area in which Agrawal et al. did not provide any insight was the long-term effects of fructose on TBI pathology and prognosis. Mice were sacrificed one week after injury and did not undergo any rehabilitation. Had the researchers allowed a subset of mice to live to examine longitudinal effects, the results of this study would be more applicable in a clinical setting where the goal is long-term recovery. The researchers also neglected to discuss emotional and behavioural implications of IR and TBI. Following TBI many patients suffer from psychiatric disorders such as anxiety and depression, as well as

Cellular level studies should be accompanied by large scale epidemiological studies to determine whether identified markers are adequate predictors of patient outcomes. Longitudinal studies should follow insulin resistant TBI patients from injury to death, and should periodically measure markers such as glucose tolerance, insulin levels and C-Reactive protein (a marker of inflammation). Cognitive tests should also be performed. Together, physiological and cognitive measures can establish the patient’s resiliency and capacity for recovery. I expect that greater insulin resistance will directly associate with reduced recovery potential and mortality events due to the significant impact of IR on energy dysregulation in the brain. Upon death, patients’ brains should be analyzed as in the original study to determine the impact of IR and TBI on the markers of interest in humans.

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The long-term implications of IR on TBI should be experimentally determined through animal studies as well. This can be achieved through replication of the original study protocol, but with the addition of a recovery period. Following fructose and FPI administration, mice should be treated with current TBI-recovery protocols such as Hyperbaric Oxygen Therapy, non-invasive brain stimulation, and limb and organ function reconstruction20. Currently there are no first line pharmaceutical therapies available for TBI patients, so pharmaceutical intervention can be forgone in mice as well21. TBI patients often undergo emotional and behavioural therapy to combat psychiatric disorders such as depression and anxiety, as well as regulate feelings of aggression that precipitate following injury20. Emotional and behavioural therapy is not feasible in mice, so the researchers should instead ensure that mice are not exposed to stressful stimuli that might induce or worsen symptoms of psychiatric disorders. Depression prevalence in the mice can be determined through any number of depression models such as Forced-Swim Test, Tail Suspension Test, etc. During the recovery period mice should also be fed a healthy diet free of sugar and other foods that might augment IR and metabolic syndrome. After being given time to recover, mice can be tested on the Barnes Maze Task once again and sacrificed for tissue analyses as in the original study. I expect that given the time to recover, FRU/ FPI mice will exhibit improved cognition and will show reductions in brain pathophysiology as will FRU/Sham and Con/TBI mice. I expect that FRU/ FPI mice will show the least recovery compared to the other cohorts due to the additive impact of IR and TBI on the brain. Any early and unplanned mortality events should also be monitored to establish whether FRU/FPI mice are at greater risk for death. The goal in this line of research should be to establish treatment options for insulin resistant TBI patients. Considering the increasing rates of obesity, diabetes, metabolic syndrome and insulin resistance, researchers and clinicians must take the additional variable of poor metabolic health into consideration when establishing treatment plants for brain related injuries.

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REFERENCES

1. Agrawal, R. et al. Dietary fructose aggravates the pathobiology of traumatic brain injury by influencing energy homeostasis and plasticity. J. Cereb. Blood Flow Metab. 36, 941–953 (2016). 2. de la Monte, S. M. & Wands, J. R. Alzheimer’s Disease Is Type 3 Diabetes–Evidence Reviewed. J. Diabetes Sci. Technol. Online 2, 1101–1113 (2008). 3. Ley, E. J. et al. Diabetic Patients With Traumatic Brain Injury: Insulin Deficiency Is Associated With Increased Mortality. J. Trauma Acute Care Surg. 70, 1141 (2011). 4. Blázquez, E., Velázquez, E., Hurtado-Carneiro, V. & Ruiz-Albusac, J. M. Insulin in the Brain: Its Pathophysiological Implications for States Related with Central Insulin Resistance, Type 2 Diabetes and Alzheimer’s Disease. Front. Endocrinol. 5, (2014). 5. Agrawal, R. & Gomez-Pinilla, F. ‘Metabolic syndrome’ in the brain: deficiency in omega-3 fatty acid exacerbates dysfunctions in insulin receptor signalling and cognition. J. Physiol. 590, 2485– 2499 (2012). 6. Alegret, M. et al. Impairment of novel object recognition learning and brain insulin signaling in fructose-, but not glucose-drinking, female rats. Atherosclerosis 263, e268 (2017). 7. Stranahan, A. M. et al. Diet-induced insulin resistance impairs hippocampal synaptic plasticity and cognition in middle-aged rats. Hippocampus 18, 1085–1088 (2008). 8. van der Borght, K. et al. Reduced neurogenesis in the rat hippocampus following high fructose consumption. Regul. Pept. 167, 26–30 (2011). 9. Boucher, J., Kleinridders, A. & Kahn, C. R. Insulin Receptor Signaling in Normal and InsulinResistant States. Cold Spring Harb. Perspect. Biol. 6, (2014). 10. Djordjevic, A., Bursać, B., Veličković, N., Vasiljević, A. & Matić, G. The impact of different fructose loads on insulin sensitivity, inflammation, and PSA-NCAM-mediated plasticity in the hippocampus of fructose-fed male rats. Nutr. Neurosci. 18, 66–75 (2015). 11. Singh, I. N., Sullivan, P. G., Deng, Y., Mbye, L. H. & Hall, E. D. Time Course of Post-Traumatic Mitochondrial Oxidative Damage and Dysfunction in a Mouse Model of Focal Traumatic Brain Injury: Implications for Neuroprotective Therapy. J. Cereb. Blood Flow Metab. 26, 1407–1418 (2006). 12. Werner, C. & Engelhard, K. Pathophysiology of traumatic brain injury. Br. J. Anaesth. 99, 4–9 (2007). 13. Russo, M. V. & McGavern, D. B. Inflammatory neuroprotection following traumatic brain injury. Science 353, 783–785 (2016). 14. Corrigan, F., Mander, K. A., Leonard, A. V. & Vink, R. Neurogenic inflammation after traumatic brain injury and its potentiation of classical inflammation. J. Neuroinflammation 13, (2016). 15. Liang, H. & Ward, W. F. PGC-1alpha: a key regulator of energy metabolism. Adv. Physiol. Educ. 30, 145–151 (2006). 16. Mylonas, C. & Kouretas, D. Lipid peroxidation and tissue damage. Vivo Athens Greece 13, 295–309 (1999). 17. Jiménez-Maldonado, A., Ying, Z., Byun, H. R. & Gomez-Pinilla, F. Short-term fructose ingestion affects the brain independently from establishment of metabolic syndrome. Biochim. Biophys. Acta BBA - Mol. Basis Dis. 1864, 24–33 (2018). 18. Woodcock, T. & Morganti-Kossmann, C. The Role of Markers of Inflammation in Traumatic Brain Injury. Front. Neurol. 4, (2013). 19. International Diabetes Federation - Facts & figures. Available at: https://www.idf.org/ aboutdiabetes/what-is-diabetes/facts-figures.html. (Accessed: 22nd November 2018) 20. Dang, B., Chen, W., He, W. & Chen, G. Rehabilitation Treatment and Progress of Traumatic Brain Injury Dysfunction. Neural Plast. 2017, (2017). 21. Dougall, D., Poole, N. & Agrawal, N. Pharmacotherapy for chronic cognitive impairment in traumatic brain injury. Cochrane Database Syst. Rev. (2015). doi:10.1002/14651858.CD009221. pub2

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Designed by Maggie Chen Cover Image from Public Library of Science: Issue September 2012 Copyright ÂŠ 2019 Human Biology Program, University of Toronto, Toronto HMB300H1F

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