Nature outlook epilepsia by Javier Ortega

OUTLOOK

EPILEPSY

10 July 2014 / Vol 511 / Issue No 7508

OUTLOOK EPILEPSY

Produced with support of an independent medical education grant from Sunovion Pharmaceuticals Inc.

The quest to calm the storm

Cover art: Nik Spencer

Editorial Herb Brody, Mike May, Michelle Grayson, Kathryn Miller, Nick Haines Art & Design Mohamed Ashour, Alisdair Macdonald, Andrea Duffy Production Donald McDonald, Susan Gray, Ian Pope, Christopher Clough Sponsorship Will Piper, Yvette Smith, Samantha Morley Marketing Steven Hurst, Hannah Phipps Project Manager Anastasia Panoutsou Art Director Kelly Buckheit Krause Publisher Richard Hughes Magazine Editor Rosie Mestel Editor-in-Chief Philip Campbell

pilepsy has been documented for thousands of years and can affect anyone at any age. There are at least a dozen types of epilepsy — the exact number depends on who is being asked — that can start in and spread to different brain regions, creating a range of seizure types. The World Health Organization conservatively estimates that 50 million people worldwide have epilepsy; yet, despite its prevalence, the condition attracts relatively little research funding (page S2). Part of the reason for the dearth of treatments is the long history of social stigma and fear that once surrounded people with the condition (page S10). Perhaps the most complex piece of the epilepsy puzzle is the fact that we still don’t understand the brain itself; simply knowing some of the roles of neurotransmitters and ion channels does not explain why some people develop epilepsy (page S4). Studies have helped us understand enough of epilepsy’s neurobiology to use surgery as a treatment, which is why neurologist Samuel Wiebe proposes that this tool is used more widely (page S7). Neuroscience and genetics have exposed crucial pieces of the epilepsy process, but studies have not determined the network of genes that drive seizures (page S8). Until recently even drug-makers tackled epilepsy by trial and error, but now researchers are using new targets and drug development strategies to help create more effective medicines (page S12). A high-fat, low-carbohydrate diet can help reduce seizure frequency in young children (page S14), and in the future, sensors that can be worn to predict an oncoming seizure could have clinical and research applications (page S16). This Outlook was produced with the support of an independent medical education grant from Sunovion Pharmaceuticals Inc. As always, Nature Publishing Group retains sole responsibility for all editorial content. Mike May Contributing Editor

Nature Outlooks are sponsored supplements that aim to stimulate interest and debate around a subject of interest to the sponsor, while satisfying the editorial values of Nature and our readers’ expectations. The boundaries of sponsor involvement are clearly delineated in the Nature Outlook Editorial guidelines available at go.nature.com/e4dwzw CITING THE OUTLOOK Cite as a supplement to Nature, for example, Nature Vol. XXX, No. XXXX Suppl., Sxx–Sxx (2014). VISIT THE OUTLOOK ONLINE The Nature Outlook Epilepsy supplement can be found at http://www.nature.com/nature/outlook/epilepsy It features all newly commissioned content as well as a selection of relevant previously published material.

CONTENTS S2 EPIDEMIOLOGY

The complexities of epilepsy Charting a century of research

S4 NEUROBIOLOGY

Unrestrained excitement Understanding the mechanisms behind seizures

S7 PERSPECTIVE

The surgical solution Samuel Wiebe argues the case for surgery as an epilepsy treatment

S8 GENETICS

Complex expressions Possible genes involved in epilepsy

S10 SOCIOLOGY

Shedding the shame The social stigma of epilepsy

S12 DRUG DEVELOPMENT

Illuminated targets The quest for new treatments

S14 FOOD SCIENCE

Fat chance Inhibiting seizures with a high-fat diet

S16 TECHNOLOGY

Dressed to detect Wearable epilepsy sensors could help to save lives

COLLECTION S18 Mutations of DEPDC5 cause

autosomal dominant focal epilepsies S. Ishida et al.

S22 GABA progenitors grafted into the

adult epileptic brain control seizures and abnormal behavior R. F. Hunt et al.

All featured articles will be freely available for 6 months. SUBSCRIPTIONS AND CUSTOMER SERVICES For UK/Europe (excluding Japan): Nature Publishing Group, Subscriptions, Brunel Road, Basingstoke, Hants, RG21 6XS, UK. Tel: +44 (0) 1256 329242. Subscriptions and customer services for Americas – including Canada, Latin America and the Caribbean: Nature Publishing Group, 75 Varick St, 9th floor, New York, NY 10013-1917, USA. Tel: +1 866 363 7860 (US/Canada) or +1 212 726 9223 (outside US/Canada). Japan/China/Korea: Nature Publishing Group — Asia-Pacific, Chiyoda Building 5-6th Floor, 2-37 Ichigaya Tamachi, Shinjuku-ku, Tokyo, 162-0843, Japan. Tel: +81 3 3267 8751. CUSTOMER SERVICES Feedback@nature.com Copyright © 2014 Nature Publishing Group

S28 Brain mitochondrial metabolic

dysfunction and glutamate level reduction in the pilocarpine model of temporal lobe epilepsy in mice O. B. Smeland et al.

S36 De novo mutations in epileptic

encephalopathies Epi4K Consortium & Epilepsy Phenome/ Genome Project

S41 The pathology of magnetic-

resonance-imaging-negative epilepsy Z. I. Wang et al.

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OUTLOOK EPILEPSY

THE COMPLEXITIES OF EPILEPSY

An estimated 50 million people worldwide have epilepsy. But research funding is low, treatment can fail and the mechanisms of the disease are a mystery. By Neil Savage. ARCHITECTURE OF EPILEPSY

FRONTAL LOBE EPILEPSY

Epilepsy is one of the most common neurological disorders and is characterized by uncontrolled firing of the brain’s neurons. There are more than a dozen types of epilepsy but the main ones are described below; a person can have more than one type. Precisely what happens in the brain during an epileptic seizure and the combination of brain areas involved have experts disagreeing on how to categorize the many forms of the disease. See page S4.

GENERALIZED EPILEPSY

Affects a specific brain region Seizures originating in the frontal lobe may develop into partial or generalized epilepsy. The frontal lobe brain tissues are associated with motor function and cognition. Epilepsy arising here may induce temporary alterations in personality.

Affects most or all of the brain

Typically congenital and occurs simultaneously in both sides of the brain. The most widely recognized form is tonic–clonic, which involves a fall to the floor, jerky convulsions and unconsciousness. Absence seizures are another form of generalized epilepsy — these involve transient loss of consciousness, which may last for only a few seconds.

60%

of cases of epilepsy arise from unknown causes1.

PARTIAL EPILEPSY

TEMPORAL-LOBE EPILEPSY

Affects one part of the brain

Affects a specific brain region

Usually limited to a specific region in one area of the brain. This form of epilepsy is often the result of an accident or neurological disease. Manifestations — such as hallucinations, twitching, smelling things or uncontrolled limb movements — can differ considerably.

1 2 3 4 5 6

The temporal lobes are associated with the brain’s language and auditory centres, as well as memory and emotion. This form of epilepsy varies in intensity and often arises within the hippocampus and amygdala — two structures that are deep in the brain’s centre.

Occipital lobe Parietal lobe Frontal lobe Temporal lobe Hypothalamus Amygdala

YOUNG AND OLD DANGERS

GEOGRAPHICAL VARIATION

In developed countries, epilepsy is more common in children and the elderly2.

Worldwide prevalence of lifetime epilepsy and active epilepsy3.

In children, epilepsy is primarily congenital.

20 Epilepsy becomes more common in over-65s as people have strokes or develop chronic conditions such as tumours or Alzheimer’s disease.

Rate per 100,000

250 200

Estimated prevalence (per 1,000 people)

300

150 100 50

Age

100

The higher figures for epilepsy in developing countries are thought to be due to factors that include poor management of parasitic infections, untreated childhood epilepsy and problems during childbirth.

Developed countries Developing countries (urban) Developing countries (rural)

Lifetime epilepsy

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Active epilepsy

Lifetime epilepsy: A person has had at least one seizure during his or her life. Active epilepsy: A person has had more than one seizure in the past five years or is currently using epilepsy medication.

EPILEPSY OUTLOOK

SURGICAL GAINS

DRUGS AT WORK

Temporal lobe epilepsy is the kind most likely to be resistant to drug treatment. Fortunately, this form of epilepsy responds well to surgery. In most people suitable for surgical treatment, surgery to one side of the brain is sufficient to control seizures but sometimes the surgeon will need to operate on both sides of the brain.

Epilepsy becomes more common as people grow older (see ‘Young and old dangers’) but effective antiepilepsy drugs are available for patients over the age of 55 (ref. 5). See page S12.

Phenytoin

1939

Carbamazepine

1974

Lamotrigine has few side effects and is effective at alleviating seizures in different types of epilepsy.

Sodium valproate 1978 How effective is surgery? A study published in 2012 involving 38 patients reported that 11 of the 15 patients with drug-resistant mesial temporal lobe epilepsy who received surgery to alleviate seizures had two seizure-free years. None of the 23 patients who hadn’t been recommended for surgery and continued with drug-only treatment had a seizure-free year4.

Gabapentin

1994

Lamotrigine

1994

Topiramate

1997

Levetiracetam

1999

Oxcarbazepine

2000

Zonisamide

2000 0

US Food and Drug Administration approval

Percentage of epilepsy patients age 55+ who experience a reduction in seizures

PSYCHIATRIC CONDITIONS In general, people with epilepsy have more chance of developing psychiatric disorders, particularly depression, but having a psychiatric condition also raises the likelihood of developing epilepsy6. People without epilepsy

People with epilepsy

Depression When studies were analysed to investigate possible links between epilepsy and psychiatric conditions, the figures varied. For example, one study found that 11% of people with epilepsy had depression, yet another study found that 80% of people with epilepsy had depression.*

Attention deficit hyperactivity disorder

Anxiety disorders Anterior temporal lobe

Panic disorder

Preparation for an epilepsy operation

Psychosis

Data from neuroimaging techniques are used to map the brain to precisely identify regions that give rise to epileptic activity. During surgery, the aim is to remove affected tissue without damaging functionally important regions. See page S7.

Percentage of people diagnosed with a psychiatric condition *The data used to compile the bars was extracted from studies that looked diagnosed psychiatric conditions in the general population and in people with epilepsy. The studies analysed were published between 1970 and 2002.

UNBALANCED ATTENTION US National Institutes of Health spending on epilepsy in 2010 lagged behind less common neurological conditions. A variety of factors, from historical issues at health agencies to social stigma, may explain this discrepancy7. See page S10.

Epilepsy is six times more prevalent than Parkinson’s disease yet receives almost the same amount of funding.

Amyotrophic lateral sclerosis Multiple sclerosis Epilepsy Parkinson’s disease Stroke Alzheimer’s disease 600

500

400

300

200

100

Research funding (US$ millions)

Prevalence (per 100,000 population)

References: 1. The WHO Epilepsy Fact Sheet No. 999.; 2. Thurman, D. J. See, go.nature.com/2spiwk; 3. Ngugi, A. K. et al; Epilepsia 51, 883–890 (2010).; 4. Engel, J. Jr. et al. J. Am. Med. Assoc. 307, 922–930 (2012).; 5. Arif, H. et al. Arch. Neurol. 67, 408–415 (2010).; 6. LaFrance, W. C. Jr., Kanner, A. M. & Hermann, B. Int. Rev. Neurobiol. 83, 347–383 (2008).; 7. Meador, K. J. et al. Neurology 77, 1305–1307 (2011).

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that have been described to date are quite divergent.” Reports of epileptic seizures date back thousands of years, but scientists are still grappling with the fundamental nature of the events that take place in the epileptic brain. Research continually reveals added complexity, and the blanket term ‘epilepsy’ has largely become anachronistic — a clinical descriptor that has limited value.

THE LIMITS OF CONTROL

A scan showing heightened activity on the right side of the brain (bright orange) during an epileptic seizure.

NE UROB IO LO GY

Unrestrained excitement Epilepsy arises from natural mechanisms in the brain that go awry. Researchers are trying to unravel its complexities. BY MICHAEL EISENSTEIN

“S

aying ‘epilepsy’ is like saying ‘sneezing’,” says Douglas Coulter, director of the Epilepsy Research Laboratory at the University of Pennsylvania in Philadelphia. “It’s a series of disorders with a common output — seizures — but even there, you have different kinds of seizures.” During a seizure, the brain’s neurons are activated in synchronized, high-frequency

patterns across broad populations, starting largely without warning and ending just as abruptly. Seizures share a common feature: a breakdown in the mechanisms that normally constrain neuronal activation, or firing. Indeed, findings from one type of epilepsy can potentially inform research on other types, but it remains unclear how deep or superficial those commonalities actually are. “My view is that there are going to be common pathways,” says Coulter, “but many of the mechanisms

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At the core of epilepsy is the delicate interplay between two types of brain cell: excitatory neurons and inhibitory interneurons. Excitatory neurons release the neurotransmitter glutamate, which binds to a receptor on other neurons and promotes firing (see ‘Electric ups and downs’). Inhibitory interneurons release γ-aminobutyric acid (GABA), which binds a receptor on excitatory neurons that restrains firing. Neurotransmitters typically act across synapses — the spaces between the neurons that form a neuronal circuit. However, some neurons also have receptors outside the synapse that can detect any GABA floating about, and these act as an additional failsafe when synaptic inhibition is inadequate. Both GABA and glutamate work by modulating the amounts of positively and negatively charged ions within neurons. Normally, neurons are negatively polarized relative to their surroundings. The binding of glutamate to its receptor triggers the opening of specialized protein-based pores in the membrane known as ion channels, which allows positively charged calcium and sodium ions to flood into the responding cell. This reduces the polarization of the cell and promotes neuronal firing. GABA signalling, on the other hand, opens other channels that allow negatively charged chloride ions to enter a cell — increasing the polarization and inhibiting firing. It’s therefore no wonder, says neurologist Matthew Walker of University College London (UCL) that “for epilepsies in which a mutation in a gene has been identified, the majority of the mutations affect channels and receptors”. For example, the SCN1A gene encodes a channel that aids excitation of a cell by allowing positively charged sodium ions to enter it. This channel is predominantly active in inhibitory interneurons; mutations that impair its function can contribute to a paediatric epileptic disorder known as Dravet syndrome as well as to certain partial epilepsies because of its effects on the release of GABA. Fortunately, because the brain has many safeguards, even profound defects in channel and receptor function rarely establish a permanent epileptic state. Nevertheless, defects NATURE.COM mean that under cer- To read how gene tain conditions the ‘dam’ therapy could help that keeps uncontrolled treat epilepsy, see: firing at bay breaks. go.nature.com/q8mqqw

CENTRE JEAN PERRIN, ISM/SPL

OUTLOOK EPILEPSY

SOVEREIGN, ISM/SPL

EPILEPSY OUTLOOK “Compensatory mechanisms usually work very well until you push the system too far, and then a seizure occurs,” explains Walker. The features of various types of seizure emerge from the ordinary mechanisms of brain function. “The machinery that makes seizures happen is the same machinery that allows us to think or move,” says Massimo Avoli, a neurologist at the Montreal Neurological Institute and Hospital in Canada. “It’s only the balance between inhibition and excitation that is not right.” Indeed, many epilepsies resemble a perverse imitation of normal activity for a given brain structure — and these lead to some of the distinctions between the pathology and activity associated with different epileptic disorders. For example, a structure deep in the brain called the hippocampus plays a key role in learning and memory. It receives incoming data from the entorhinal cortex, which relays perceptual information to a class of excitatory neurons — granule cells — in a part of the hippocampus called the dentate gyrus. However, granule cells don’t get excited easily: they are influenced by a network of inhibitory interneurons and only a tiny proportion of inflowing signals register in the hippocampus. This process of ‘dentate gating’ is thought to be important for processes such as pattern separation, which helps the brain distinguish between relatively similar stimuli. But dentate gating seems to break down in temporal-lobe epilepsies affecting the hippocampus, resulting in unrestrained, synchronized firing of granule cells. The onset of such seizures may begin with the perception of ‘auras’, characterized by unusual emotional states or a sense of déjà vu, followed by a period of confusion and memory loss. Most temporallobe epilepsies arise from physical trauma, The brain either from a direct patterns injury to the brain associated or through damage with absence arising from a stroke seizures mirror or tumour; accordthose observed ing to Coulter, this leads to a large loss of in sleep. interneurons as well as some loss of GABA receptors on the granule cells. Once the restrictions on excitatory signalling are lost, other disruptions may follow. “We’re developing a ‘domino theory’ of epilepsy, where a transient failure of dentate function may disrupt downstream regulatory functions and give you a secondary failure of downstream circuits,” says Coulter. The mechanism underlying seizures known as absence epilepsies is rather different. Absence seizures can emanate from a single site in the brain, but then give rise to a distinctive ‘spike wave’ electroencephalogram (EEG) pattern that is synchronized across multiple regions on both sides of the brain. This process is driven by the interplay between

In this epileptic seizure, parts of the brain show erratic activity on an electroencephalogram (bottom traces).

the brain’s outer layer, the cerebral cortex, and an inner structure called the thalamus. In contrast to many of the focal epilepsies, it is the inhibitory response of interneurons that fuels absence seizures. According to neurologist John Huguenard of Stanford School of Medicine in California, incoming signals from the cortex trigger a massive wave of GABA-driven inhibition of the excitatory neurons of the thalamus, deep in the brain. However, the inhibited excitatory neurons subsequently undergo a ‘rebound’ response — and react with a synchronized burst of activity. That activates cells that drive another wave of inhibition. The thalamus is involved in wakefulness and awareness, and the hallmark symptom of the absence seizure is a loss of consciousness. Intriguingly, the brain patterns associated with absence seizures — coordinated cycles of thalamic and cortical activity — closely mirror those observed in sleep, particularly during ‘spindle’ EEG signatures that represent the brain’s efforts to keep the sleeper unconscious, but on a far grander scale.

NETWORK NEWS

For all this knowledge, homing in on the faulty wiring involved in epilepsy remains difficult, confounding efforts to achieve lasting relief through surgery to remove the areas responsible. The success rate for patients with surgically treatable focal epilepsy is initially high, with around 80% becoming seizure-free postsurgery, and many experts endorse this form of treatment (see page S7). “But when you look 5, 10 or 20 years [post-surgery], it starts to drop to about 50% seizure-free,” says Walker. Two electrophysiology researchers, Andrew Trevelyan of Newcastle University, UK, and Catherine Schevon of Columbia University Medical Center in New York, have revealed a

potential reason why: conventional EEG methods can encounter difficulties in accurately pinpointing the brain regions responsible for focal epilepsies. “As the seizure wave-front propagates, you end up with recruited territories that seem to involve every neuron in the network,” says Trevelyan. But this in turn triggers a massive wave of inhibitory activity among the interneurons that surround this recruited zone. After identifying this phenomenon in rodent brain slices, Trevelyan and Schevon observed this same surrounding zone of inhibition, which they term the ‘ictal penumbra’, in humans by performing EEG using arrays of tiny electrodes implanted in the brains of epileptic patients1. EEG readings from electrodes placed on the scalp will detect strong synaptic activity within the seizure zone and in the ictal penumbra, even though most of those neurons are inhibited and not participating in the seizure. Failure to accurately pinpoint the brain regions involved in a person’s seizures can lead to the misidentification of the epileptic focus and increase the likelihood of failed surgery. Electrophysiology insights could guide more sophisticated monitoring of cortical epilepsies and possibly other focal epilepsies as well.

ON AND OFF SWITCHES

The discovery of light-responsive proteins that can directly switch neurons on or off could transform efforts to tease apart and modify the function of brain circuits in epilepsy. In ‘optogenetics’ experiments, researchers genetically modify specific subsets of neurons in animals to express these proteins and observe the extent to which different manipulations promote or prevent seizures. For example, Walker and UCL colleagues including Stephanie Schorge and Dimitri Kullmann reprogrammed neurons to express halorhodopsin, 1 0 J U LY 2 0 1 4 | V O L 5 1 1 | N AT U R E | S 5

OUTLOOK EPILEPSY a light-triggered ‘off ’ switch2. They found that even limited restraint of neuronal firing in a region of the motor cortex markedly reduced the number of seizure events in a rat model of cortical epilepsy. Walker notes that only a few neurons in a small area were turned off in the experiment. “This shows that treating epilepsy might not be about cutting out large areas of the brain,” he says. “Modifying the right areas might be enough to stabilize the network.” Similarly, a study3 by Huguenard’s team used halorhodopsin to show that forced inactivation of thalamocortical neurons can essentially halt seizures in rats with stroke-induced cortical epilepsy. This result was striking because these neurons were situated far from the injury site, in a region typically involved with generalized absence seizures. “It was thought that the primary reorganization is among regions adjacent to the cortical stroke,” says Huguenard. “We were surprised to see such a strong thalamic involvement.” Coulter sees such findings as compelling evidence that epilepsy neuroscientists need to cast a wider net. “These optogenetics studies suggest a very distributed network,” he says.

FROM SUPPORTING ROLE TO STAR

The nervous system is made up of two types of cells: neurons, which transmit nerve impulses, and glial cells, which play a supporting role. Glial cells perform essential functions such as providing a myelin sheath around the neurons to enable fast transmission of nerve signals and helping to maintain the correct ion concentration. Most epilepsy research to date has focused on the role of neurons. However, the brain contains at least as many glial cells. The past two decades of research have revealed surprising ways in which these once-underappreciated cells may contribute to both the onset and progression of epilepsy. Increased proliferation and activation of glial cells is a well-established hallmark of epilepsy. Among the glial subtypes, astrocytes are known to contribute to the epileptic state due to erosion of their role in maintaining the chemical environment of the brain. For example, elevated potassium levels render neurons hyperexcitable, and numerous studies have found impaired potassium control by astrocytes in the epileptic brain. Astrocytes also help to clean up neurotransmitter molecules in the aftermath of neuronal activity, and disruptions in the absorption and recycling of glutamate and GABA by astrocytes can similarly lead to inappropriate neuronal sensitization or inhibition in certain contexts. More recent findings suggest that astrocytes are not merely custodians, but can themselves secrete and respond to neurotransmitters. “We know that if you stimulate astrocytes from a human biopsy, these astrocytes exhibit calcium signalling and can also release glutamate,” says glia researcher Giorgio Carmignoto of the University of Padova, Italy. This glutamate can in

E L EC T R I C U P S A N D D OW N S In a healthy brain, excitatory and inhibitory neuron dynamics are tightly balanced in a controlled way. In epilepsy, the mechanisms underlying this balance go awry, causing overly-excited neurons to fire uncontrollably.

EXCITATION

When a neuron becomes excited: At excitatory synapses, the neurotransmitter glutamate is released. Glutamate crosses the synaptic cleft, binding to glutamate receptors at the postsynapse, initiating depolarization. Na+ ions enter the neuron, driving it to threshold and subsequent firing of an action potential, or nerve signal. In epilepsy, neurons are often very excitable, close to threshold and fire action potentials more readily. Positive ions (coloured red)

Axon

Excitatory neuron

Glutamate (yellow)

–+ – + – – –+ +–+ + – +–+ +–+ + – +–+ –+ – + – –+ –

Synaptic cleft

As the action potential travels down the axon, the inside transiently becomes positive.

Postsynapse

INHIBITION

When a neuron becomes inhibited: At inhibitory synapses, the neurotransmitter γ-aminobutyric acid (GABA) is released. GABA crosses the synaptic cleft, binding to GABA receptors at the postsynapse, initiating hyperpolarization. Cl– ions enter the neuron, driving it further from the action potential threshold, decreasing the probability that the neuron will fire. Increasing inhibition, in some cases, can assist in reducing the chance of unregulated seizure activity.

Inhibitory neuron

–+ – + – – –+ + – ––+ –+ –– +– – –+ –+ ––+ –+ – – +–– + – –+ – + – –+ –

GABA (green)

More negative charge inside than during excitation inhibits neuronal firing.

Negative ions (coloured brown)

turn contribute to the excitation of adjacent neurons, and Carmignoto describes the formation of ‘tripartite synapses’ in which astrocytes actively participate in conversations once thought to occur exclusively between neurons. However, activated astrocytes can also help to reduce seizure intensity: they contribute to the production of adenosine, a signalling molecule that can counter the effects of glutamate. In short, adenosine turns down the neural signals that glutamate turns up, and that could reduce seizure activity, explains Carmignoto. Huguenard has shown that astrocytes may also contribute to seizure control within the

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thalamus by producing endozepines4, which are naturally occurring molecules that resemble the sedative benzodiazepine — better known as Valium. “Astrocytes might act as sensors for seizure activity or even pre-seizure activity, and respond by enhancing the release of endozepines, thereby suppressing activity in the reticular nucleus,” he says. The injuries that trigger epilepsy are often associated with an inflammatory response in the brain, and mounting evidence suggests that astrocytes and other glial cell types are central to this process. They secrete signalling factors that normally contribute to damage control and injury repair, but they can also create a feedback loop that promotes epileptic activity. “Pathological electrical activity per se is enough to activate the glial cells,” says neuropharmacologist Annamaria Vezzani of the Mario Negri Institute for Pharmacological Research in Milan, Italy. Once activated, they secrete molecules such as interleukin-1β and these initiate a signalling cascade in neurons that renders them more sensitive to glutamate-induced excitation — and therefore, seizure activity. “So on the one hand you have this neuronal effect, and on the other you have a persistence of the inflammatory milieu because these neurons are activating the glia continuously,” says Vezzani. The inflammatory response also seems to disrupt the blood–brain barrier, the tight cellular seal that limits entry of materials from the bloodstream to the brain. There is evidence that penetration of this compromised barrier by molecules such as the protein albumin can exacerbate both neuronal hyperexcitability and inflammation. What remains unclear is the extent and the timing of these various astrocyte-mediated processes, and how they trigger or suppress epilepsy in humans. The evidence, which has mostly been obtained from either isolated brain slices or animal models, is intriguing but is not conclusive enough to form a robust disease narrative. “Any time you have an increase in excitability in a neuronal network, this, for sure, will involve astrocytes,” says Carmignoto. “But what comes first — the neuronal defect or the astrocyte defect — is the issue.” For now, there is not enough evidence to map the natural history of epilepsy. Better disease models and more human data are needed before these individual findings can be linked into a satisfying narrative. “Understanding epilepsy,” says Carmignoto, “means understanding how the brain works. It is as complex as that.” ■ Michael Eisenstein is a freelance journalist based in Philadelphia, Pennsylvania. 1. 2. 3. 4.

Schevon, C. A. et al. Nature Commun. 3, 1060 (2012). Wykes, R. C. et al. Sci. Transl. Med. 4, 161ra152 (2012). Paz, J. T. et al. Nature Neurosci. 16, 64–70 (2013). Christian, C. A. & Huguenard, J. R. Proc. Natl Acad. Sci. USA 110, 20278–20283 (2013).

EPILEPSY OUTLOOK

PERSPECTIVE The surgical solution

Not enough doctors and patients opt for surgery to treat epilepsy, despite clinical evidence of the benefits, says Samuel Wiebe.

andra was 15 when she started having weekly seizures that altered her awareness and behaviour; she also started having generalized convulsions about once a year. Over the years, she has tried numerous antiepileptic drugs in various combinations. For eight years while she was in her twenties Sandra had no seizures but as she got older, new drug treatments have typically only controlled her seizures for a few months before her seizures returned with the same intensity. The drugs made her drowsy and slowed her thinking, and the seizures caused injuries and embarrassment. Sandra’s education was affected and, together with the fact that she could not find gainful employment, she became depressed and socially isolated. Finally, at the age of 54, Sandra was referred to a comprehensive epilepsy programme and was diagnosed with left-temporal-lobe epilepsy. She had brain surgery to remove part of that lobe. Now, three years later, she has no more seizures and is an advocate for early epilepsy surgery. For many types of epilepsy, brain surgery has been shown to be safe and superior to anti epileptic drugs in all published controlled studies of drug-resistant epilepsy1. Among patients with specific types of focal epilepsy (seizures that start in one specific area of the brain, as opposed to multiple or bilateral brain regions), about 65% of surgically treated patients stopped having seizures, compared with 8% of those treated with antiepileptic drugs alone2. For every two patients given surgery, one will become seizure free. The same ratio applies for surgery performed early in the disease3, and for the number of patients achieving clinically important improvements in quality of life4. By comparison, carotid surgery to prevent stroke is considered to be hugely effective but needs to treat eight to ten patients for one to benefit. Epilepsy surgery helps to prevent death from accidents, seizure-related events, suicide and sudden unexpected death in epilepsy, and also extends a patient’s years of healthy life. Evidence-based clinical practice guidelines stipulate that patients with focal epilepsy should be referred for surgical evaluation straight away, but this generally happens only after two or three decades, or not at all. Moreover, the rate of epilepsy surgery remained unchanged despite the publication in 2001 of a randomized controlled trial demonstrating the benefits of surgery5, and the 2003 publication of evidence-based guidelines that encourage surgery6.

of risks and benefits. Physicians need to explain to patients that in centres with experienced surgeons using modern imaging and surgical techniques, epilepsy surgery has a low complication rate of only 3–5%, and almost no mortality. Epilepsy surgery is safe. The knowledge and attitudes of patients play a major role in the decision to explore epilepsy surgery, and some people with epilepsy come up with many reasons to avoid it. Race and socioeconomic standing also affect the decision. In the United States, for example, AfricanAmericans, Hispanic adults and other ethnic groups or those without private insurance are less likely to consider epilepsy surgery. The knowledge and attitudes of clinicians are equally important. International surveys show that neurologists may lack sufficient knowledge about the benefits and safety of epilepsy surgery. As well as conveying clearly and convincingly the benefits and safety of epilepsy surgery, clinicians need to be aware of the value of being completely free of seizures, and of the serious and lifethreatening consequences of poorly controlled seizures. Health-care experts also need to understand that patients have a very low probability of controlling their seizures with additional medications if they fail with two appropriately chosen and adequately used antiepileptic drugs — the definition of drug-resistant epilepsy. A group of colleagues and I have created a user-friendly Internet-based tool to help clinicians identify patients who should be referred for surgical evaluation7. Finally, the health-care system plays a central role in providing access to specialized epilepsy centres during pre-surgical evaluation, surgery and post-operative care. Clinicians often point to limited access to these resources as one of the main barriers to epilepsy surgery. But patients need a patient-centred, well-informed clinical environment that addresses their individual concerns as they navigate the decisionmaking process. Neurologists and the health-care system must create that environment. My colleagues and I need to do a better job of informing health care policy-makers and resource allocators about the high socioeconomic burden of uncontrolled epilepsy. Everyone working in health care needs to help spread awareness that epilepsy surgery is safe and cost-effective. Epilepsy patients around the world stand to gain great benefits if we succeed. ■

EPILEPSY SURGERY HELPS TO

PREVENT DEATH

AND ALSO HELPS EXTEND A PATIENT’S YEARS OF

HEALTHY LIFE.

WHY NOT SURGERY?

So why is this highly effective, potentially life-changing treatment used so infrequently? The clinical condition of drug-resistant epilepsy often follows a complex course marked by periods of remission, as in Sandra’s case, complicating the decision to opt for surgery. Another factor is the hope that a new drug or combination of drugs will be able to control seizures. In addition, brain surgery is a major intervention. Surgically removing part of the brain — the seat of our intelligence, emotions and sense of self — is a sobering prospect and demands meticulous evaluation

Samuel Wiebe is professor of clinical neurological sciences at the University of Calgary, Canada. Schmidt, D. & Stavem, K. Epilepsia 50, 1301–1309 (2009). Engel, J. et al. J. Am. Med. Assoc. 307, 922–930 (2012). Wiebe, S. & Jette, N. Nature Rev. Neurol. 8, 669–677 (2012). Fiest, K. M., Sajobi, T. T. & Wiebe, S. Epilepsia http://dx.doi.org/10.1111/epi.12625 (2014). 5. Wiebe, S. et al. N. Engl. J. Med. 345, 311–318 (2001). 6. Engel, J. Jr et al. Neurology 60, 538–547 (2003). 7. Jette, N. et al. Neurology 79, 1084–1093 (2012). 1. 2. 3. 4.

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RUBEN SALAZAR JR

OUTLOOK EPILEPSY

When doctors couldn’t explain to Tracy Dixon-Salazar why her daughter had developed epilepsy she decided to find out for herself.

G E NE T I CS

Complex expressions Epilepsy is one of the most common neurological disorders to affect the human brain. Many genetic aspects of the disease have been identified, but mechanisms remains elusive. BY CHARVY NARAIN

ome kinds of epilepsy are rooted in physical trauma — a brain injury at birth, perhaps. Others seem to show up like bolts from the blue, with no clear event to explain them. Yet one thing is clear: many cases of idiopathic epilepsy — epilepsy without an obvious physical cause — run in families, implicating heredity in their genesis. Indeed, studies1 suggest that genetic variations in ion channels on the surface of neurons — electrically excitable cells in the nervous system — might lie at the heart of many cases of idiopathic epilepsy, and presumably cause the firing of these cells to get out of control. But there is still much that scientists do not know about the genetics of idiopathic epilepsy. Currently, a gene variant can only be associated with 10–40% of patients, according to Holger

Lerche, who researches the genetics of neurological disorders at the Centre for Integrative Neuroscience in Tübingen, Germany. “But actually, almost all idiopathic epilepsy is likely to be genetic, so this figure should be closer to 80–100%,” he says. “The problem is that we haven’t identified all disease-associated genes just yet — nor how they interact.” Adding to the complexity of the puzzle are the facts that two-thirds of healthy individuals carry a gene variant associated with epilepsy2, that many genes pinpointed by genetic analyses are also implicated in other disorders, and that epilepsy often co-occurs with other diseases — 30% of children with autism also have epilepsy, for example. This makes it hard to connect a given genetic variant in a patient to one specific disease. Epilepsy is a complex genetic disorder involving interplay between many genes, often in unexpected ways.

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When Tracy Dixon-Salazar’s two-year-old daughter Savannah had her first seizure she thought that her child was choking. “When the paramedics told us that Savannah’s symptoms sounded like a seizure, I didn’t know what that was,” she says. By the time she was three, Savannah had epileptic seizures every day, and by the age of five she was having hundreds. Her physical and mental development regressed dramatically, and she needed round-the-clock care. “Throughout it all,” Dixon-Salazar says, “I really wanted to know why. Nobody could give us an explanation for how a child could go from being a healthy two-year-old to being completely taken over by epilepsy.” Dixon-Salazar’s hunt for an explanation took her from being a stay-at-home mother, who had left full-time education after high school, to getting a PhD in neurobiology from the University of California, San Diego.

EPILEPSY OUTLOOK Along the way, “I fell in love with genetics,” she says. As part of her postdoctoral work, she sequenced Savannah’s exome — the part of the genome that encodes proteins — and finally found something approaching an explanation, hidden within an ion channel.

RUBEN SALAZAR JR

CHASING CHANNELS

As the name suggests, ion channels are conduits; they sit on the largely impenetrable surface of a neuron and selectively let in ions — charged particles that trigger a cascade of events that lead to the neuron producing a burst of electricity, called an action potential. Different ion channels let in different kinds of ions, and mutations in the genes that carry instructions for making these channels have been correlated with epilepsy. These faulty channels then let in too many or too few ions, disturbing the way that the action potential is generated and how it travels down the neuron. Inheriting these faulty-channel genes leads to abnormalities in brain-cell firing. Although Savannah Dixon-Salazar had no family history of the disease, an analysis of her genome turned up 25 ion-channel variants that mostly — based on the channels they affected, and how — would probably cause too many calcium ions to be let into the cell. And so, working with Savannah’s doctors, her parents decided to try treating her with verapamil, a drug approved by the US Food and Drug Administration for treating heart arrhythmia, not epilepsy, and which disrupts the functioning of an ion channel that lets in calcium. “The effects were startling and immediate,” says Tracy Dixon-Salazar. “Within 30 days, Savannah’s seizures reduced from 300 a month to around 50, and currently average around 20 to 25 a month. They now happen only at night, so she is much less likely to hurt herself.” She adds that her daughter’s intellectual development has come along greatly, and “she has gone from struggling to speak a word to speaking 10- to 15-word sentences easily”. Dixon-Salazar acknowledges that these results are anecdotal and that verapamil is unlikely to be a general epilepsy treatment. But it could help some. And there is a lesson there, says Ivan Soltesz, a neurobiologist and epilepsy researcher at the University of California, Irvine. “These results highlight the fact that even if you don’t know exactly what is wrong, and the exact pathway involved, genetic analysis can still help with treatment,” he says.

INTRICATE INTERACTIONS

DNA variants affecting the calcium ion channel seemed to lead to Savannah’s epilepsy. Lerche’s work has implicated a different ion channel, which he does not want to describe before publishing his research. His team has found that when two variations of the same channel gene — one known to occur in the normal population and one novel variant found only in an epilepsy patient — came together, the channel’s

function changed. Individually, the mutations did not alter the channel’s function. “This suggests that the patient’s epileptic seizures are due to the occurrence of both variants occurring simultaneously,” Lerche says. Sometimes, however, adding epilepsyrelated gene variants together does the opposite of cause disease — it dampens it. In a 2007 paper3, a group led by epilepsy researcher Jeffrey Noebels of the Baylor College of Medi-

healthy people and people suffering from idiopathic epilepsy — and found that nearly 67% of the healthy group had mutations in at least one gene variant known to be linked to a familial form of epilepsy.2 What’s more, they found no gene variants that turned up only in the people with epilepsy. One of the healthy people in their study even had seven mutations in genes associated with epilepsy — just two less than the nine mutations detected in the most extreme epilepsy patient in the group. Having many gene mutations, it seems, is not a predictor of whether someone will be affected by the condition.

MODELLING MECHANISMS

Savannah (left) has around 20 seizures a month.

cine in Houston, Texas, expressed two different epilepsy-associated ion-channel gene variants in the same mouse. What they got were animals with no, or reduced, epilepsy symptoms. The mutations had opposite effects on how likely a neuron is to fire an action potential. Disruption of the Kcna1 gene, which encodes a particular class of potassium ion channels, normally leads to large increases in neuronal electrical excitability and subsequent epilepsy; on the flip side, malfunctions in the calcium ion channel encoded by the Cacna1a gene “Savannah result in reduced has gone from neurotransmitter struggling to release and absence speak a word to speaking ten- seizures (when the affected individuals word sentences ‘blank out’). When easily.” expressed together, the two genes seemed to compensate for each other, reducing the serious seizures and death that the Kcna1 mutants experience and masking the absence epilepsy of animals with Cacna1a mutations. Noebels’ studies also show that gene variants associated with epilepsy are common in the general population — and that the cause of the disorder is far less simple than the total number one has. In a study published in 2013, his group compared ion-channel genes between

Some researchers think that bioinformatics analyses — using computer simulations to look at the intricate interplay between epilepsyassociated genes — might reveal the complex genetic communication that determines who gets the disease and who doesn’t. “The aim is to build a cellular map of epilepsy, including as many known epilepsy-associated genes as possible,” Lerche says. “We can then use simulations to track how interactions between genes are happening.” For example, ion-channel expert Steven Petrou at the Florey Institute of Neuroscience and Mental Health in Parkville, Australia, used computational modelling to study the effect of sodium-channel mutations in a theoretical network of neurons mimicking epilepsy4. The results suggest that ion channel mutations may be more severe in their effects in a brain that is already abnormal. Epilepsy may initially be triggered by an external event such as a head injury or stroke — or, in a double whammy, ion-channel mutations may trigger the disease and once it is established, have an even greater effect in the altered brain than they did to begin with. It is a point not missed by Dixon-Salazar. “Savannah seized for 16 years before we found a drug that would make an impact on her seizures,” she says. “The brain she had before the seizures is totally different from the one that she had afterwards. Perhaps if we had given the drug earlier, she might now be entirely seizure-free.” Noebels hopes that efforts to build computer simulations of the entire mammalian brain will help researchers to understand the complex network of interactions in the abnormal brain. “It takes a village to cause epilepsy,” he says — myriad cellular factors must come together to result in disease. Eventually, the conversations between the villagers might be best tracked inside a computer. ■ Charvy Narain is a senior editor at Nature Neuroscience. 1. Lerche, H. et al. J. Physiol. 591, 753–764 (2013). 2. Klassen, T. et al. Cell 145, 1036–1048 (2011). 3. Glasscock, E. et al. Nature Neurosci. 10, 1554–1558 (2007). 4. Thomas, E. A. et al. Epilepsia 51, 136–145 (2009). 1 0 J U LY 2 0 1 4 | V O L 5 1 1 | N AT U R E | S 9

Medical Journal1, neurologist Rajendra Kale wrote: “The history of epilepsy can be summarised as 4,000 years of ignorance, superstition, and stigma followed by 100 years of knowledge, superstition, and stigma.” Over the past century, researchers have made huge gains in the scientific understanding of epilepsy, thanks largely to technologies that allow for a deeper view of the brain’s activity, such as the electroencephalogram (EEG) and magnetic resonance imaging (MRI). Much of the stigma that people with epilepsy endure stems from the alarming nature of the most common type of seizure. These generalized tonic–clonic seizures begin with a loss of consciousness before the convulsions begin. Additional symptoms can include screaming, loss of bladder or bowel control and, on regaining consciousness, confusion and amnesia. There is another reason for epilepsy’s poor reputation. “Part of the mythology around epilepsy has been because it’s episodic. That’s what led, centuries ago, to the idea that someone was possessed: all of a sudden someone who looks perfectly fine had behaviour that was abnormal,” says Gregory Bergey, director of the epilepsy centre at Johns Hopkins University in Baltimore, Maryland. “As we move into the twenty-first century, I’d like to think that this mythology about being possessed has been dispelled. But there are still misconceptions.”

BREAKING DOWN BARRIERS

In centuries past, a priest would cast out the demons that were thought to cause epilepsy.

S OCIOLO GY

Shedding the shame Plagued by a history of fear and stigma, epilepsy has languished when it comes to research funding. B Y L A U R E N G R AV I T Z

hroughout history, in almost every culture, epilepsy has been viewed as something to be feared, avoided and concealed. In what is thought to be the earliest written description of the condition, dating from around 1050 bc, the Babylonians referred to it as miqtu, or ‘the falling disease’, and attributed it to ghosts and demons. The ancient Greeks called it ‘the sacred disease’ and believed that it resulted from divine

intervention. Epilepsy even makes appearances in the Bible, when Jesus heals a boy who suffers from seizures by casting out a ‘demon’. By 400 bc, Greek physician Hippocrates concluded that seizures are hereditary and originate in the brain, yet this view failed to become widely accepted for hundreds of years (see ‘Epilepsy’s past’). Today, at least in the developed world, the shame and suspicion surrounding epilepsy have eased, but they are far from a distant memory. In an oft-cited editorial in the British

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With misconceptions come fear and stigmatization. And the greater the stigma, the poorer the outcome: in people with epilepsy, feelings of shame have been strongly associated with inadequate seizure control, as well as with increased depression, anxiety and isolation. Although prejudice is a known problem in almost every country, it may be greatest in developing nations, where religious and spiritual beliefs often trump medical understanding of the condition. “In Asia and Africa, families in low-income settings misinterpret what a seizure is, so you have an interpretation problem from the get-go,” says Gretchen Birbeck, a neurologist and public-health researcher at the University of Rochester Medical Center in New York. “If someone develops a severe cough that doesn’t go away, they recognize they need antibiotics or even a tuberculosis test. In that same family, if someone says something nonsensical, has a seizure and falls to the floor, they tend to think there’s a possession or that the person’s been cursed. They don’t think there’s a medical problem.” Misconceptions are not limited to family members. In Nigeria, for instance, at least 16% of health-care workers believe epilepsy is a mental-health disorder rather than a medical one. What’s more, 6% of Nigeria’s healthcare workers believe it is contagious2. With these types of mistakes, “patients aren’t going to get the right treatment”, says Nathalie Jette, a neurologist at the University of Calgary in

INTERFOTO/ALAMY

OUTLOOK EPILEPSY

SHEILA TERRY/SPL

EPILEPSY OUTLOOK Alberta, Canada, who is currently chairing an International League Against Epilepsy task force aimed at assessing stigma in epilepsy. Incorrect diagnoses are one of the more obvious obstacles to appropriate care, but they are not the only one. Birbeck, who studies epilepsy and other neurological disorders in developing countries, says that even when health-care providers do recognize seizures as a medical problem, family members are often loath to seek treatment. “It casts a pall on the family: if the community realizes that someone in the family has epilepsy, the siblings won’t be able to find someone to marry,” she says. “So do you take someone to get care or do you hide them at home?” Even in the developed world, through most of the twentieth century epilepsy remained an affliction that people believed was best kept out of sight. “In civil societies, including the United States, it was felt you could catch epilepsy just by looking at someone having a seizure. So people were sent off to epileptic colonies,” says Steven Schachter, a neurologist at Harvard Medical School in Boston, Massachusetts, and past president of the American Epilepsy Society. The last of these colonies closed only about 50 years ago. Yet the practice may have had some benefit. “The cultural tendency and movement to isolate people with epilepsy may have had a silver lining,” Schachter says. “It provided the opportunity to conduct research and move the field forward.”

FUNDING GAP

For the most part, however, epilepsy’s history of stigma and superstition has done more to slow research than to further it. The disease suffers from a woeful research-funding gap. “Relative to the burden and cost-effectiveness of treatability, epilepsy is incredibly neglected,” Birbeck says. In the United States, 1% of the population has epilepsy at any given time, and 2–4% of the population will have a seizure disorder at some point during their life, making epilepsy the third most common neurological disease, after stroke and Alzheimer’s disease. Yet of the six most prevalent neurological conditions, epilepsy ranks fifth in funding from the US National Institutes of Health (NIH) — that level, which equalled about 40% of the funding for stroke in 2011, is decreasing every year3. In low-income countries, the economic disparity is even more striking. There, the dearth of resources dedicated to treating the disease can be traced to an accident of medical evolution, Birbeck says. When the World Health Organization (WHO) was first established in 1948, it classified all neurological disorders, including epilepsy, as psychiatric disorders. As technologies such as brain scans and EEGs emerged, neurology and psychiatry began to split into separate disciplines. Yet although epilepsy was identified as a physical

and potentially treatable problem in the brain, funding structures at the WHO and other global ministries of health were never rearranged to reflect that new understanding, Birbeck notes. “Global health is modelled off the WHO structure, which has no neurologic section. So, in developing countries, there are psychiatrists but no neurologists,” she says. In the developed world, the misunderstandings associated with epilepsy can also be blamed for a shortage of advocacy; the stigma of the disease has often prevented people who have the disorder and their family members from coming forward to talk about their experiences. This lack of advocacy is directly related to the lack of funding. “If you look across the board at diseases and NIH funding, you’re not going to find too many in which there is huge success and great breakthroughs unless there’s an advocacy group behind it and a lot of push,” says Susan Axelrod, one of the founders of Citizens United for Research in Epilepsy (CURE), an advocacy organization in Chicago, Illinois, that funded about US$3.5 million of epilepsy research last year. Despite the fact that patients with epilepsy outnumber patients with Parkinson’s disease by about six to one, Parkinson’s disease receives much more funding, says Axelrod. For example, the Michael J. Fox Foundation for Parkinson’s Research provides about US$50 million in research funding each year. Axelrod and others in the field say that they have met public figures who have some form of epilepsy, or who have family members with the disease, but have not gone public because of the negative images associated with it. The early onset of the disorder means that few people have the chance to become powerful advocates. It is a difficult cycle. Stigma begets lack of advocacy, which begets lack of funding. And researchers are unlikely to choose a field in which little or no grant money is available unless they have a deeply personal reason for doing so. But it is a cycle that many are working to break. CURE, for instance, has partnered with the Howard Hughes Medical Institute to sponsor medical students’ internships in epilepsy research laboratories. Also, a growing collection of molecular targets promise enhanced medications in the future (see page S12) and even watch-like devices could help (see page S16). “We’ve made some strides,” Axelrod says. “I’m not fatalistic. Given how few private resources there are for this disease — and how few spokespeople — I think we’re making progress.” ■ Lauren Gravitz is a freelance writer and editor based in Los Angeles, California. 1. Kale, R. Br. Med. J. 315, 2–3 (1997). 2. Ekenze, O. S. & Ndukuba, A. C. Epilepsy Behav. 26, 87–90 (2013). 3. Meador, K. J., French, J., Loring, D. W. & Pennell, P. B. Neurology 77, 1305–1307 (2011).

EPILEPSY’S PAST

A brutal cure for epilepsy in the Middle Ages

c. 400 b c Ancient Greek physician Hippocrates advises treatment of epilepsy with diet and drugs. 400 –1400 People attribute epilepsy to demonic possession. Physicians treat epilepsy by boring holes in the skull.

c. 1800 Castration or circumcision sometimes used to treat epilepsy. 1886 English surgeon Victor Horsley performs the first epilepsy neurosurgery. 1938 Canadian neurosurgeon Kenneth McKenzie performs the first hemispherectomy for epilepsy, removing half the patient’s brain. 1940 US neurosurgeons William van Wagenen and Andrew Akelaitis perform the first corpus callostomy, severing the connection between the brain halves. 1990 Lamotrigine is proved effective against epilepsy with few side effects. 2001 Canadian neurologist Samuel Wiebe publishes clinical trial results showing the benefits of surgery. 2014 Rosalind Picard and her colleagues at the Massachusetts Institute of Technology develop a wrist-worn device that detects seizures. 1 0 J U LY 2 0 1 4 | V O L 5 1 1 | N AT U R E | S 1 1

NIK SPENCER

OUTLOOK EPILEPSY

DRUG DEVELO PMENT

Illuminated targets The development of effective antiepilepsy drugs is moving on from trial-and-error approaches to sophisticated molecular solutions. B Y M E G A N C U L LY

or most of the twentieth century, the development of medications to treat epilepsy relied on trial and error. “The drugs were taken through development and introduced on to the market before any molecular target or targets in the brain were identified,” says Michael Rogawski, a neurologist at the University of California, Davis, adding that we still don’t know the molecular target for some agents. In the 1960s, for example, researchers in France noted that every drug they tested reduced seizures in animals. The reason, they discovered, was that they had dissolved their compounds in valproic acid, a common practice back then. It was the solvent — not the candidate drugs — that was responsible for the anticonvulsive effects. They’d accidentally uncovered the potential of a drug now

known as valproate1. Within a year, valproate was approved and is now the most widely prescribed antiepileptic drug in the world. Despite such successes, there is a growing realization that the old approaches are not enough. Existing medications control seizures in about 70% of people with epilepsy, but for those 30% with drug-resistant seizures, treatments remain scarce. To move forward, pharmaceutical companies and other researchers are looking to change tack. Some are shifting away from the traditional rodent model so they can ramp up their ability to screen many compounds. Others are exploring new treatments aimed at specific molecular targets.

FISH FOR SUCCESS

The traditional way of testing for antiepilepsy drugs involves the generation of epilepsy-like convulsions in rats and mice by administering electrical stimuli or chemicals such as

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pentylenetetrazol. A drug developer administers compounds to find ones that protect the animals from the seizures, and these then move on to human clinical trials. Nearly all of the 25 or so marketed antiepileptic drugs were identified this way, says Rogawski. To test a wider range of targeted treatments, some researchers are turning to animals that are easier and cheaper to keep, and quicker to breed, than rodents — such as fish. Scott Baraban, a researcher at the University of California, San Francisco, has been investigating Dravet syndrome, a rare and severe form of epilepsy that affects children. It is one of the most drug-resistant types of epilepsy2. Around 70–80% of patients with NATURE.COM Dravet syndrome carry a To read how mutation in a gene called chemogenetics can SCN1A, which plays stop seizures, see: a fundamental role in go.nature.com/muqfvt activating neurons; the

EPILEPSY OUTLOOK mutation seems to turn them on too much and thereby causes seizures. Baraban used a strain of zebrafish with a mutation in the SCN1A gene — such fish have seizure-like convulsions. He then screened for drugs that could prevent the seizures, testing more than 300 compounds from a ‘repurposing’ library — one containing drugs that are known to be safe for human use but for whatever reason weren’t effective enough to be used today. He found that a long-forgotten antihistamine called clemizole inhibited seizures in his fish3. Precisely how clemizole prevents seizures is unclear, but it probably has nothing to do with histamine, the immunemodulating molecule it is known to affect. In the same way that aspirin interacts with distinct molecules in the body and so can be used for both pain relief and to reduce inflammation, clemizole possibly interacts with both histamine (or molecules controlling its release) and some element governing nerve firing — the ion channels that regulate a nerve’s excitability, perhaps, or receptors that control neurotransmitter release. The ability to breed so many zebrafish — imagine an aquarium of many, many fish versus a few rodents in a cage — allows researchers to screen numerous drugs in a short period. “We’ve screened over 800 drugs in about two years,” says Baraban. He plans to generate mutant zebrafish for all 12 genes associated with severe forms of childhood epilepsy and use them to identify new drugs.

MOLECULAR MEDICINES

Another approach to drug development is to work out the molecular causes of seizures, then aim drugs at the targets. Researchers now have a set of promising molecules of this type, many of them identified through hereditary forms of the disorder, says Mike Ehlers, chief scientific officer for neuroscience at Pfizer in New York City. For example, pregabalin (marketed by Pfizer as Lyrica) was approved by the US Food and Drug Administration (FDA) in 2004 for nerve pain and later for seizures, and it targets a component of calcium channels, which lets calcium ions in and out of nerves and plays a role in some forms of epilepsy4. For a noteworthy example of developing a molecular epilepsy medicine around a known target, Ehlers points to perampanel, a drug manufactured by Tokyo-based Eisai and marketed as Fycompa, which was approved by the FDA in 2012. In the 1990s, Eisai was looking for drugs that target the AMPA receptor, a protein present on the membranes of neurons. When the neurotransmitter glutamate binds to the AMPA receptor, the neurons become excited and drive seizures in some cases. Problems with glutamate and the AMPA receptor are implicated in several neurological diseases, including epilepsy5 — and the Eisai researchers reasoned that inhibiting the AMPA receptor could be used to treat epilepsy.

NEW TREATMENTS TRICKLING IN

Trials that are actively recruiting participants are an indication of progress in developing new medication. In epilepsy research, there are currently only five trials testing entirely new compounds. Compound

Type of epilepsy

Phase

Target

Company

SAGE-547

Adults with super-refractory status epilepticus

I/II

GABAA*

Sage Therapeutics

PRX-00023

Localization-related epilepsy

Serotonin receptors

US National Institute of Neurological Disorders and Stroke

YKP3089

Partial onset seizures

Unknown

SK Life Science

Ganaxolone

Partial onset seizures

GABAA

Marinus Pharmaceuticals

USL261

Seizure clusters

III

GABAA

Upsher-Smith Laboratories

*GABA: γ-aminobutyric acid

Some other researchers ran into trouble getting the drugs to the intended target; one drug they tested couldn’t cross the blood–brain barrier. “Eisai, from the start, had strict criteria: they wanted a potent, orally active molecule with the right properMany of the ties” including reaching and binding to the recepmajor drug tor, says Kate Carpenter, companies medical affairs manager no longer have epilepsy at Eisai. It took more than programmes. 12 years to move a developmental compound into an approved product. Perampanel is currently approved as an add-on treatment for patients with partial-onset seizures (seizures that affect only one hemisphere of the brain). Researchers see the potential for other drugs aimed at receptors related to epilepsy. Studies have shown that a neurotransmitter called γ-aminobutyric acid (GABA) can inhibit neurons that tend to get overexcited during an epileptic seizure (see page S4). So it might be possible to design a drug that could produce this inhibition by raising the availability of GABA, as valproate does through unknown means. Or a drug might directly activate GABA receptors, with similar effects. Rogawski and his colleagues are working on neuroactive steroids, which target a class of GABA receptors known as GABAA receptors. Specific mutations that make this receptor insensitive can trigger epilepsy. Conversely, a drug that turns on the GABAA receptor could potentially be used to inhibit epileptic seizures. Researchers are also attempting to develop therapies through studying the mode of action of existing antiepileptic medications. In 1999, the Belgian pharmaceutical firm UCB, in Brussels, received approval from the FDA for a drug called levetiracetam as a treatment for epilepsy. Levetiracetam binds to a protein called synaptic vesicle glycoprotein 2A (SV2A), which is found in a wide range of neuronal vesicles — spheres that contain neurotransmitters. The drug seems to inhibit the release of neurotransmitters that contribute to uncontrolled activity of the central nervous system in epilepsy6, but it has the

drawback of side effects including dizziness, drowsiness and infections such as the common cold. UCB scientists started to look for alternative compounds that bind to SV2A and found brivaracetam7, which resembles levetiracetam in structure but binds more strongly to SV2A. It is currently in phase III trials. Higher affinity for its target should allow brivaracetam to be effective at lower doses, meaning fewer side effects8.

LIGHT AHEAD

Despite advances in identifying molecular targets for drugs, the number of improved or new antiepilepsy medications has been slight. Consequently, many of the major pharmaceutical companies — with the notable exceptions of UCB, Eisai and Pfizer — no longer have epilepsy programmes. That leaves the bulk of the discovery and development work to academics, small biotech firms and speciality pharmaceutical companies. The result is a limited number of players in the field and some of them, such as academics, are unable to finance clinical trials, which explains the low number of trials recruiting patients to test epilepsy treatments (see ‘New treatments trickling in’). Schmidt is optimistic that future research will lead to the development of drugs that will reach specific molecular targets and with fewer unwanted side effects. If we could understand how and why epilepsy develops in the first place, it might even be possible to prevent the condition in people at high risk, such as those who have had severe head trauma or stroke. ■ Megan Cully is a freelance writer based in London, UK. 1. Meunier, H. et al. Therapie 18, 435 (1963). 2 Chiron, C. & Olivier, O. Epilepsia 52, Supp. S2, 72–75 (2011). 3. Baraban, S. C., Dinday, M. T. & Hortopan, G. A. Nature Commun. 4, 2410 (2013). 4. Davies, A. et al. Trends Pharmacol. Sci. 28, 220–228 (2007). 5. Rogawski, M. Epilepsy Curr. 11, 56–63 (2011). 6. Lynch, B. A. et al. Proc. Natl Acad. Sci. USA 101, 9861–9866 (2004). 7. Mula, M. Expert Rev. Neurother. 14, 361–365 (2014). 8. Van Paesschen, W. V. et al. Epilespsia 54, 89–97 (2013). 1 0 J U LY 2 0 1 4 | V O L 5 1 1 | N AT U R E | S 1 3

FARLAP/ALAMY

OUTLOOK EPILEPSY

High-fat foods, such as cream and butter, are part of the ketogenic diet that can help reduce seizure frequency and intensity in children with epilepsy.

FOOD SCIENCE

Fat chance For children with epilepsy whose condition is resistant to medication, a high-fat, low-carbohydrate diet may help bring their seizures under control. BY RACHEL BRAZIL

y nephew, Elijah, had his first seizure when he was 18 months old. Initially, he experienced myoclonic seizures, which are brief muscle contractions that made his muscles stiffen, his arms lift up and his head jerk back. He then developed atonic seizures, in which his muscle lost tone — his muscles would go limp and he would drop to the ground. Elijah was diagnosed with Lennox–Gastaut syndrome, a difficult-to-treat epilepsy that causes multiple daily seizures and severe cognitive impairment. Over the following 12 months, Elijah’s doctors treated him with several antiepilepsy drugs to reduce or stop his seizures. Some of the prescribed medication provided shortlived relief, but there were side effects that included bloating and drowsiness. By the time he was two-and-a-half, Elijah was experiencing more than 50 seizures a day, including generalized tonic–clonic seizures in which the muscles tense and contract and cause convulsions. Falls during his atonic seizures resulted in head injuries, so he started to wear a helmet. His cognitive development stopped. He wasn’t speaking or making any attempts to communicate.

At this point, Elijah’s neurologist told my sister, Elijah’s mother, about the ketogenic diet — low in carbohydrate and high in fat — that may help reduce or stop seizures. My sister was sceptical. A diet that would stop seizures seemed unlikely. Many neurologists were once unwilling to consider the ketogenic diet as a treatment for epilepsy because only anecdotal results were available, but trials conducted in the past decade are prompting a rethink (see ‘How fats help epilepsy’).

SEIZURE CONTROL

The concept of using food to help treat disease is not new. Ancient Greek texts contain references to dietary therapies for epilepsy, stemming from the observation that starvation stops seizures. Centuries later, in the 1920s and 1930s, doctors commonly prescribed the ketogenic diet for epilepsy in children. During fasting, and in people with diabetes, the liver metabolizes fatty acids into ketone bodies called β-hydroxybutyrate, acetoacetic acid and acetone that are used as an energy source when glucose levels are low. No one knows exactly why, but some evidence suggests that ketone bodies might protect against seizures1. A low-carbohydrate, high-fat diet creates the state of ketosis — the raised level of ketone

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bodies, from which the diet gets its name. The ketogenic diet fell out of favour from 1938, following the availability of a drug called phenytoin that controls the brain’s electrical activity and helps to reduce the frequency of seizures. Still, about 30% of epilepsies do not respond to pharmaceuticals, which prompted the search for alternative treatments. Russell Wilder, a metabolic-disease expert at the Mayo Clinic in Rochester, Minnesota, devised the classic ketogenic diet in 1921. It consists of a weight ratio of 3:1 or 4:1 of fat to a combination of protein and carbohydrate. This means that about 90% of daily calories come from fats, compared with the less than 35% recommended by US Department of Health and Human Services. The ratio is achieved by cutting out grains and adding cream and butter to meals. A ketogenic diet may cause short-term side effects such as constipation and nausea. Longer-term side effects include slowed growth in children and increased risks of bone fractures and kidney stones. For my sister, the turning point came after Elijah’s fourth failed drug. He started the diet in hospital and, under a nutritionist’s supervision, was seizure free within six weeks. Elijah’s story is not unique. Some children

MELANIE BRAZIL

EPILEPSY OUTLOOK who continue to have seizures in spite of treatment with antiepileptic medication experience an improvement on a ketogenic diet. Paediatric neurologist Eric Kossoff of Johns Hopkins Hospital in Baltimore, Maryland, is a leading proponent of the diet and says that of patients who do not respond to an antiepileptic drug, 30% will respond to the next drug they try and 50% will respond to the diet. In the past decade, the short-term success of the diet has been confirmed in four randomized controlled trials2, the largest of which enrolled 145 children at London’s Great Ormond Street Hospital, and was led by childhood-epilepsy specialist Helen Cross. “About 40% got a more than 50% reduction in seizures,” says Cross, and 10% became completely seizure free. Other beneficial effects of a ketogenic diet include statistically significant improvements in attention, social function and sleep patterns3.

DIET DEVELOPMENT

The problem with a ketogenic diet is its unpalatability — such as butter in almost every meal but no bread — which is perhaps why it is used mostly for young children rather than adults. Cross says that when adults try the diet they tend to feel “persistently hungry” because eating a high ratio of fat to carbohydrate and protein leaves many unsatisfied even though they’ve consumed their required daily calories. Fortunately, there are three alternative diets. In the 1960s, researchers discovered that medium-chain triglycerides (MCTs) — found in coconut oil — provide greater ketogenic effects than normal dietary fats, which are mainly long-chain triglycerides. The MCT diet, created by the late University of Chicago neurologist Peter Huttenlocher, is restrictive but incorporates more carbohydrates and protein because MCTs are absorbed more easily by the body than long-chain triglycerides. Trials4 have found the MCT diet to be as effective as the 4:1 fat-to-carbohydrate ratio in the classic ketogenic diet. Kossoff, for his part, designed the modified Atkins diet (MAD) in 2003. He says that the idea for the diet arose from observing similar results in people who relaxed the restrictions of the ketogenic diet5. In common with the Atkins weight-loss diet, MAD does not involve calorie counting, but limits carbohydrates and encourages fat consumption. In 2005, the low-glycaemic index treatment (LGIT) came from observations that patients on a ketogenic diet had extremely stable glucose levels6. In addition to high fat, the LGIT includes only carbohydrates with a glycaemic index lower than 50, which means that these foods do not tend to increase blood glucose levels. The diet offers more variety — permitted low-glycaemic-index foods include whole grains, green vegetables and berries. Despite the success of the diets, the mechanism remains largely a mystery. There is little correlation between seizure control and

Elijah enjoying whipped cream with blueberries.

blood ketone body levels. What does change are the metabolic pathways used by some cells, including neurons in the brain. The processes regulating metabolism occur in mitochondria — the organelles inside cells where energy is converted from dietary fuel. This energy conversion process might link diet to reducing epileptic events. Researchers at two institutions in Boston, Massachusetts, have studied why changing the cell metabolism reduces seizures: cell biologist

H OW FATS H E L P E P I L E P SY Epigenetics of eating A ketogenic diet, which is high in fatty foods such as avocados and low in carbohydrates and sugars, can reduce seizures in children. A paper published last year10 offers some clues on the way this diet exerts its effect. The researchers looked for genetic changes between rats induced to have epilepsy that were fed a normal diet and those fed a ketogenic diet. They found that the ketogenic diet changes the genetic pathways and could alter the expression of genes responsible for epilepsy. The mechanism is still not clear, but the team noticed that there were differences in the DNA between the two groups of rats. The rats fed a normal diet had a higher amount of methylation — the addition of a CH3 group — in their DNA compared with the animals fed the ketogenic diet. The team suggests that these changes in methylation are linked to deactivation of the genes.

Nika Danial at the Dana-Farber Cancer Institute and neurobiologist Gary Yellen at Harvard Medical School. Yellen became interested in understanding the diet through his wife, Elizabeth Thiele, a paediatric neurologist at Massachusetts General Hospital and developer of the LGIT diet. Yellen and Danial’s work has identified a protein that switches a cell’s fuel glucose to ketone bodies and in so doing opens a type of potassium ion channel in neurons that can dampen electrical activity7. “Some of the types of cells in the brain where these channels are found are well known as seizure gates that regulate whether a little bit of local excessive electrical activity gets spread to the whole brain and becomes a seizure,” Yellen explains. The success of the MCT diet suggests another pathway to seizure-protection. Neurologist Matthew Walker at University College London and molecular biologist Robin Williams at Royal Holloway, University of London, identified a number of MCTs that provide enhanced seizure control. One example is decanoic acid8. Simon Heales, a clinical chemist at University College London, showed that decanoic acid increases mitochondrial numbers in brain cells 9. The mitochondria produce ATP, which helps transmit signals along the neurons, and its increased production could provide better control of potassium channels related to the seizure gates that Yellen mentions. There is no agreement on how a ketogenic diet can help control epileptic seizures. It’s likely that there isn’t a single mechanism involved, and, says Cross, it may work in a different way in different children. After four years on a ketogenic diet, Elijah has fewer seizures, but he gets hungry and is unable to take part in celebrations that involve food. And he still has severe cognitive impairments and needs assistance with daily tasks such as dressing and feeding. But he is happy, has an increased attention span and is starting to talk. As Hippocrates, the Ancient Greek father of medicine, said: “Let food be thy medicine and medicine be thy food.” ■ Rachel Brazil is a freelance science writer based in London, UK. 1. McNally, M. A. & Hartman, A. L. J. Neurochem. 121, 28–35 (2012). 2. Levy, R. G., Cooper, P. N., Giri, P. & Pulman, J. Cochrane Database Syst. Rev. CD001903 (2012). 3. Hallböök, T., Ji, S., Maudsley, S. & Martin, B. Epilepsy Res. 100, 304–309 (2012). 4. Kossoff, E. H. et al. Epilepsia 50, 304–317 (2009). 5. Kossoff, E. H., Krauss, G. L., McGrogan, J. R. & Freeman, J. M. Neurology 61, 1789–1791 (2003). 6. Muzykewicz, D. A. et al. Epilepsia 50, 1118–1126 (2009). 7. Giménez-Cassina, A. et al. Neuron 74, 719–730 (2012). 8. Chang, P. et al. Neuropharmacology 69, 105–114 (2013). 9. Hughes, S. D. et al. J. Neurochem. 129, 426–433 (2014). 10. Kobow, K. et al. Acta Neuropath. 126, 741–756 (2013).

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Portable devices could help the wearer prepare for a seizure by taking rescue medication or lying down.

T ECH NO LO GY

Dressed to detect Wearable devices that monitor seizures promise improvements in epilepsy treatments and research. BY ELIE DOLGIN

t looks like a new-age fashion accessory, but the black, chunky bracelet on Rosalind Picard’s wrist is actually the latest technology for monitoring seizures. Similar to wearable devices for tracking fitness, this experimental wristband comes packed with sensors that measure heart rate, skin temperature and movement patterns. But unlike other fitness monitors, Picard’s biometric bracelet also gauges changes in electrodermal activity, or skin conductance — an indicator of the abnormalities in the

nervous system that are triggered during many epileptic seizures. Picard, an electrical engineer at the Massachusetts Institute of Technology (MIT) Media Lab in Cambridge, developed the idea for her ‘Embrace’ device with her former PhD student, Ming-Zher Poh. The researchers initially created a prototype bracelet called Q Sensor that tracked only electrodermal activity NATURE.COM and movement. Two How mathematical years ago, they showed models can predict that this device could seizures: accurately detect 94% go.nature.com/m8sfh9

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of large convulsive seizures experienced by children with epilepsy1. What’s more, the Q Sensor produced few incorrect signals — less than one false alarm per day on average — and most of these were triggered by forceful, rhythmic motion, such as shaking dice or vigorously playing with a Nintendo Wii. About one-third of people with epilepsy continue to experience seizures despite an increasing number of available drug treatments and considerable progress in surgery (see page S12 and page S7). A portable device that warns of an impending attack could help people prepare for a seizure by lying down, say, or taking a rescue medication. Existing devices can only record epileptic events that are already occurring — a major limitation for now. Researchers therefore hope to find measurable biomarkers that would warn the wearer of a seizure before it strikes. Nonetheless, even a device that falls short of that goal could dramatically alleviate the burden of disease. It could provide real-time information on how well a medication is working, or it could help people determine whether they need to seek medical attention. In one of Picard and Poh’s studies, for example, they showed2 that surges in electro-dermal activity detected by their device correlated with a measure of brain activity thought to be linked to the risk of sudden unexpected death in epilepsy, a mysterious complication of the disease that is the most common cause of epilepsy-related deaths. “This autonomic information tells you something that turns out to be really important in terms of what’s going on inside the brain,” says Picard. “That was a surprise to us, but it’s a pretty cool surprise, and that is where we think the potential is: for alerting people with epilepsy to something that is life-threatening.” So far, tests of the Q Sensor prototype have taken place in hospital. Picard now hopes that the second-generation Embrace device can be used to detect seizures in the home. To achieve this, she has joined forces with Empatica, a company based in Milan, Italy, that already sells a tool for mobile stress monitoring. According to Matteo Lai, Empatica’s chief executive, clinical trials involving Embrace are planned for early 2015.

SENSING SEIZURES

Most commercially available systems for 24-hour seizure monitoring currently rely on motion detection. One such system is manufactured by Smart Monitor, based in San Jose, California, which sells a device called the SmartWatch that uses three-dimensional accelerometers to detect the excessive and repetitive shaking movements that occur during a large seizure. Within seconds, the wristwatch issues alerts by text message or phone call to designated family members, who can then summon help in case of serious injury or loss of consciousness.

ICTALCARE

OUTLOOK EPILEPSY

ICTALCARE

EPILEPSY OUTLOOK SmartWatch and other movement-based detectors have a sensitivity of around 90% for identifying generalized tonic–clonic seizures — big, whole-body convulsions — compared with video electroencephalography (EEG), a diagnostic technique that uses video equipment and electrodes on the scalp to record brain waves and behaviour at the same time. Video EEG is the gold standard but is only available in a hospital setting. Some portable EEG systems have been developed for everyday use, but they are uncomfortable and unsightly — most people with epilepsy say they would not wear scalp electrodes in public to obtain seizure warnings, nor do they want implantable alternatives. To increase the sensitivity while providing a device that is comfortable and stigma-free, some researchers are investigating physiological metrics beyond movement patterns. One such trait is electrodermal activity. Another is electromyography, the electrical activity produced by muscles. Brain Sentinel, a start-up company in San Antonio, Texas, is developing a prototype device that is about the size of a bar of soap and can be worn around the upper arm to detect the electromyography patterns typical of generalized tonic–clonic seizures. Like the SmartWatch, Brain Sentinel’s sensor can alert caregivers that a seizure is occurring. At the 2013 American Epilepsy Society’s annual meeting in Washington DC, researchers from the South Texas Comprehensive Epilepsy Center in San Antonio reported that the Brain Sentinel device detected 95% of generalized tonic–clonic seizures. The device had been worn by 33 participants, each of whom wore the sensor for an average of two days, and only one false alarm was reported. A larger clinical trial, involving at least 100 participants “We’re on at 11 medical centres the edge across the United States, of a huge is ongoing. advance Compared with detecin epilepsy tors that rely on movement patterns, “the much science.” lower false-positive rate [of the electromyography-based device] is definitely an advantage”, says Michael Girouard, president of Brain Sentinel. “A high number of false detections can lead to alarm fatigue,” he explains, as people start ignoring the warnings or stop wearing the device. But with the Brain Sentinel detector, “when the system’s alert goes off, you’re pretty certain somebody’s having a seizure”. IctalCare, based in Hørsholm, Denmark, already sells an electromyography-based device, although it is only available in Denmark. According to Isa Conradsen, the company’s clinical research manager, another benefit of using electromyography is that it can detect changes during the tonic phase of a generalized tonic–clonic seizure, when the muscles initially stiffen and people often lose

+7732 µV

–7379 µV

+573 µV

–734 µV

Surface EMG trace (centre) on a bicep showing five minutes of a seizure and ‘normal’ activity with enlargements of (top) 60 seconds of seizure and (bottom) 60 seconds of ‘normal’ activity.

consciousness, whereas accelerometers generally have to wait until the clonic phase, when the muscles begin to spasm and jerk. “Looking at surface electromyography,” Conradsen says, “you can get the alarm much earlier.” There’s more to epilepsy than just generalized tonic–clonic seizures, however. “The problem is that people may die of seizures when there are no convulsions,” says John Duncan, a neurologist at University College London and clinical director of the National Hospital for Neurology and Neurosurgery in London. In these cases, measuring electrodermal activity could prove particularly helpful. In one study2 using the Q Sensor, Picard and Poh, working with a team that included paediatric neurologist Tobias Loddenkemper of Boston Children’s Hospital in Massachusetts, found that skin conductance rose significantly in 86% of complex partial seizures, a type of epileptic attack in which people often stare blankly into space but do not exhibit large convulsions. “The clinical presentation of seizures can vary,” says Loddenkemper, who is now running a larger trial involving the same prototype device. “You need the right sensor for the right epilepsy type.” Other researchers are working on devices that monitor different physiological changes that occur during seizures. At the Holst Centre in Eindhoven, the Netherlands, for example, scientists are developing a wearable electrocardiogram detector to track different kinds of seizure based on variations in heart rhythm. And at RTI International, a nonprofit organization based in Research Triangle Park, North Carolina, researchers are developing a thin harness that straps around a child’s chest and

incorporates sensors that measure respiratory function, heart rate and body orientation to detect all generalized seizures and some types of partial seizure. Eventually, all these signals will probably be combined into a single device. Although writing the algorithm for such a multimodal system might prove tricky, as Jacqueline French, a neurologist at New York University’s Comprehensive Epilepsy Center, points out. “The more things you measure that you know change in some people’s seizures, the more you’re likely to see a characteristic pattern for every person.”

BETTER TRIALS

Wearable seizure monitors are mostly being developed with the patient in mind. But when they have been clinically validated, these platforms should also prove useful for the biomedical research community. “It could change the way we do epilepsy trials,” says Loddenkemper. Epilepsy trials today that involve drugs, diets or other treatment interventions typically ask participants at home to keep track of their own seizure experiences in a notebook or electronic diary. But this method depends on people accurately recognizing and documenting their seizures, which is a problem because patients tend to be unaware of about half of all seizures recorded during video-EEG monitoring. By taking direct physiological measurements instead, wearable sensors could dramatically improve diagnostic accuracy in such studies. “We would get a more objective evaluation of the seizure frequency,” says Sándor Beniczky, a neurophysiologist at the Danish Epilepsy Centre in Dianalund. To test this idea, Brain Sentinel, Empatica, Smart Monitor and others are now running or planning trials designed, at least in part, to compare the accuracy of their devices with the self-reporting of seizures by patients. Standalone systems for detecting seizures could become obsolete if multinationals such as Apple and Samsung were to roll out smart watches with clinical-grade capabilities such as electrodermal activity or electromyography. At that point, says Lunal Khuon, a biomedical engineer at Villanova University in Pennsylvania, “there will be less hardware development and more software development to use the sensors that are already available”. “We’re on the edge of a huge advance in epilepsy science with better recording of seizures,” says French. “It’s fundamental that we understand the symptoms before initiating treatment — and it’s something that we’re not very good at.” ■ Elie Dolgin is senior news editor at Nature Medicine in Cambridge, Massachusetts. 1. Poh, M.-Z. et al. Epilepsia 53, e93–e97 (2012). 2. Poh, M.-Z. et al. Neurology 78, 1868–1876 (2012). 1 0 J U LY 2 0 1 4 | V O L 5 1 1 | N AT U R E | S 1 7

ORIGINAL ARTICLE

Brain mitochondrial metabolic dysfunction and glutamate level reduction in the pilocarpine model of temporal lobe epilepsy in mice Olav B Smeland1, Mussie G Hadera1, Tanya S McDonald2, Ursula Sonnewald1 and Karin Borges2 Although certain metabolic characteristics such as interictal glucose hypometabolism are well established for temporal lobe epilepsy (TLE), its pathogenesis still remains unclear. Here, we performed a comprehensive study of brain metabolism in a mouse model of TLE, induced by pilocarpine–status epilepticus (SE). To investigate glucose metabolism, we injected mice 3.5–4 weeks after SE with [1,2-13C]glucose before microwave ﬁxation of the head. Using 1H and 13C nuclear magnetic resonance spectroscopy, gas chromatography—mass spectrometry and high-pressure liquid chromatography, we quantiﬁed metabolites and 13C labeling in extracts of cortex and hippocampal formation (HF). Hippocampal levels of glutamate, glutathione and alanine were decreased in pilocarpine–SE mice compared with controls. Moreover, the contents of N-acetyl aspartate, succinate and reduced nicotinamide adenine dinucleotide (phosphate) NAD(P)H were decreased in HF indicating impairment of mitochondrial function. In addition, the reduction in 13C enrichment of hippocampal citrate and malate suggests decreased tricarboxylic acid (TCA) cycle turnover in this region. In cortex, we found reduced 13C labeling of glutamate, glutamine and aspartate via the pyruvate carboxylation and pyruvate dehydrogenation pathways, suggesting slower turnover of these amino acids and/or the TCA cycle. In conclusion, mitochondrial metabolic dysfunction and altered amino-acid metabolism is found in both cortex and HF in this epilepsy model. Journal of Cerebral Blood Flow & Metabolism (2013) 33, 1090–1097; doi:10.1038/jcbfm.2013.54; published online 24 April 2013 Keywords:

C isotope; glutamate; mitochondria; neurometabolism; NMR spectroscopy; temporal lobe epilepsy

INTRODUCTION Temporal lobe epilepsy (TLE) is one of the most common forms of human epilepsy and is associated with a high level of drug resistance among patients. The mechanisms underlying the pathogenesis of TLE still remain unclear, although increasing evidence points to a disturbance in amino-acid neurotransmitter homeostasis and energy metabolism, as well as neuronal injury. Metabolic characteristics of human TLE include interictal glucose hypometabolism and a decrease in the levels of the neuronal marker N-acetyl aspartate (NAA) in the epileptogenic region.1,2 Increased levels of extracellular glutamate in epileptogenic hippocampi have been reported before and during seizures3 and interictally.4 Moreover, it has been suggested that the uptake of glutamate from the extracellular space by astrocytes is slower in the epileptic brain as the expression of glutamine synthetase, the glial enzyme that converts glutamate to glutamine, was decreased in the epileptogenic hippocampi from patients with TLE.5,6 Changes in brain metabolism in rat models of TLE resemble those reported in human TLE such as interictal glucose hypometabolism demonstrated in lithium-pilocarpine rats,7 as well as alterations in NAA and glutamate reported in post-status epilepticus (SE) models induced by kainic acid and lithiumpilocarpine.8–10 There are, however, few comprehensive studies on brain metabolism in mouse models of TLE, although this should be of interest owing to advantages of using mice in epilepsy research such as a wider range of opportunities for genetic manipulation

and potentially shorter experiment duration with reduced expenses. In the present study, we aimed to investigate glucose, aminoacid, and energy metabolism in a well-established mouse model of TLE, specifically 3.5–4 weeks after SE was induced by pilocarpine. Injection of the muscarinic agonist pilocarpine leads to SE with the subsequent appearance of spontaneous recurrent seizures, which have been characterized in many laboratories by electroencephalography11–13 and behaviorally in most mouse strains.14,15 Histopathological alterations in this model include neuronal loss, mossy fiber sprouting, and hippocampal sclerosis, thus reproducing characteristics of human TLE.14,15 We utilized 1H nuclear magnetic resonance (NMR) spectroscopy and highpressure liquid chromatography (HPLC) to obtain detailed maps of the metabolite content in cerebral cortex and hippocampal formation (HF) in pilocarpine–SE mice. To be able to determine glucose metabolism, we injected animals with [1,2-13C]glucose 15 minutes before microwave fixation of the head, and evaluated brain extracts using 13C NMR spectroscopy and gas chromatography–mass spectrometry (GC–MS).

MATERIALS AND METHODS Animals For experiments, 7–8-week-old male CD1 mice (Animal Resources Center, Canningvale, Western Australia, Australia) were used. All mice were housed in individual cages under a 12-hour light–dark cycle. The animals were

1 Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway and 2Department of Pharmacology, School of Biomedical Sciences, The University of Queensland, St Lucia, Queensland, Australia. Correspondence: Dr K Borges, Department of Pharmacology, School of Biomedical Sciences, The University of Queensland, Skerman Building 65, St Lucia, Queensland 4072, Australia. E-mail: k.borges@uq.edu.au Received 29 January 2013; revised 14 March 2013; accepted 19 March 2013; published online 24 April 2013

Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1091 adapted to these conditions for at least 1 week before being used in the experiments. Food (SF11-027 standard diet, Specialty Feeds, Glen Forrest, Western Australia, Australia) and water were available ad libitum. All experiments were approved by the University of Queensland’s Animal Ethics Committee and followed the guidelines of the Queensland Animal Care and Protection Act 2001. All efforts were made to minimize the suffering and the number of animals. This work is written according to the ARRIVE guidelines (http://www.nc3rs.org/ARRIVE).

Pilocarpine–SE Model To minimize peripheral side effects, 35 CD1 mice, weighing 25–40 g, were injected with methylscopalamine (2 mg/kg intraperitoneally in 0.9% NaCl; Sigma Aldrich, St Louis, MO, USA) 15–30 minutes before pilocarpine (Sigma Aldrich) injections. A single dose of pilocarpine was administered (330– 345 mg/kg subcutaneously in 0.9% saline). Twenty-three pilocarpineinjected mice (66%) experienced behavioral SE as deﬁned by continuous seizure activity consisting mainly of whole-body continuous clonic seizures, while nine mice died and three showed no SE. Ninety minutes after pilocarpine administration all mice were injected with pentobarbital (22.5 mg/kg intraperitoneally in 0.9% NaCl; Provet, Northgate, Queensland, Australia) followed by 1 mL 4% dextrose in 0.18% saline (subcutaneous). After SE, mice were monitored twice daily. Weight and appearance were recorded, along with any observed spontaneous or handling-induced seizures. All mice were hand-fed moistened cookies and injected with 5% dextrose in lactate Ringer’s solution twice a day for about 3 days and thereafter when needed. No systematic observations were done to detect spontaneous seizures in mice, but 21 mice with SE were observed to have handling induced seizures and altered behavior, including lack of nest building and all mice had lost 10–20% of weight after SE. Two pilocarpine– SE mice died suddenly overnight in their home cages at 10 and 21 days, respectively. Autopsies did not reveal causes of death and therefore sudden unexplained death in epilepsy or severe seizures are likely. Ten of these mice were randomly selected for this study. When video-electroencephalography monitored, all male CD1 mice subjected to our pilocarpine–SE model developed spontaneous recurrent seizures and/or interictal spikes in another laboratory at our university,13 similar to a previous report in the same mouse strain.12 Eleven control mice received methylscopalamine and pentobarbital only and 0.9% saline instead of pilocarpine.

[1,2-13C]glucose Injections and Tissue Extraction At 3.5–4 weeks after SE, 10 pilocarpine–SE mice and 11 control mice were injected in random order with [1,2-13C]glucose (0.3 mol/L intraperitoneal 543 mg/kg; 99% 13C; Cambridge Isotope Laboratories, Woburn, MA, USA). At 15 minutes after glucose injection, the mice were subjected to microwave fixation of their heads at 5 kW for 0.80–0.86 seconds, instantaneously inactivating brain metabolic reactions (Model MMW-05, Muromachi, Tokyo, Japan). The time interval of 15 minutes between microwave fixation and 13C glucose injection ensures substantial 13C label incorporation in brain metabolites without washout (pilot experiments, results not shown). After microwave fixation, mice were decapitated, trunk blood was collected, and cerebral cortices and HF were dissected and stored at 80 1C till extraction. The HF included the dentate gyrus, hippocampus proper, subiculum, but not entorhinal cortex. The blood samples were centrifuged at 1,000 g for 5 minutes and the serum was later analyzed for total amounts of glucose using the glucose oxidase method (Sigma Aldrich), which revealed similar concentrations of blood glucose in the two groups (n ¼ 9 pilocarpine–SE mice 14.80±0.58 mmol/L; 8 control mice 16.88±0.97 mmol/L; P ¼ 0.11). The tissue samples were masked and subjected to a water/methanol– chloroform extraction method as previously described.16 L-2-aminobutyric acid (a-ABA) (Sigma Aldrich) was added as an internal standard for HPLC analysis and samples were then homogenized in 200 mL of methanol using a Vibra Cell sonicator (Model VCX 750, Sonics and Materials, Newtown, CT, USA). After extraction, samples were lyophilized and all subsequent analyses were performed by investigators masked to the treatment.

enrichment with 13C in glucose, alanine, and lactate in both brain regions was determined using 1H NMR spectroscopy. 1

H and

C NMR Spectroscopy

Lyophilized samples were dissolved in 120 mL of D2O (99.9%; Cambridge Isotope Laboratories) containing 0.10% ethylene glycol (Merck, Darmstadt, Germany) and 0.29 g/L 2,2,3.3-d(4)-3-(trimethylsilyl)propionic acid sodium salt (98%; Alfa Aesar, Karlsruhe, Germany) as internal standards for quantification. Samples were transferred to SampleJet tubes (3.0 103.5 mm2) for insertion into the SampleJet autosampler (Bruker BioSpin GmbH, Rheinstetten, Germany). All samples were analyzed using a QCI CryoProbe 600 MHz ultrashielded Plus magnet (Bruker BioSpin GmbH). 1 H and 13C spectra were recorded at 20 1C. 1H NMR spectra were acquired with the following parameters: pulse angle of 901, acquisition time of 2.66 seconds, and relaxation delay of 10 seconds. The number of scans was 256. Proton-decoupled 13C NMR spectra were acquired with the following parameters: pulse angle of 301, acquisition time of 1.65 seconds, and a relaxation delay of 0.5 seconds, 30 kHz spectral width with 98 K data points. The number of scans needed to obtain appropriate signal to noise ratios were between 20,000–40,000 (adjusted for sample weight). Relevant peaks in the spectra were identified and then integrated using TopSpin 3.0 software (Bruker BioSpin GmbH). The total amounts and 13C labeling of metabolites were calculated from the integrals of the peak areas using internal standards ethylene glycol in 13C spectra, and 2,2,3.3d(4)-3-(trimethylsilyl)propionic acid sodium salt in 1H spectra. Integrals from 1H spectra were corrected for number of protons constituting the peak. Integrals from 13C spectra were corrected for nuclear Overhauser enhancement and relaxation effects relative to the internal standard, and were corrected for the 1.1% natural abundance of 13C using the data obtained from 1H NMR spectroscopy or HPLC. When the metabolite was double-labeled, 13C natural abundance was calculated as 1.1% 1.1% of total metabolite amount. All concentrations were corrected for possible tissue loss during the extraction procedure using a factor derived from the known amount of a-ABA added to the tissue and the actual amount of the final sample quantified by HPLC.

HPLC To determine the total amounts of amino acids, the samples were analyzed using a Hewlett Packard 1100 System (Agilent Technologies, Santa Clara, CA, USA) with ﬂuorescence detection, after derivatization with o-phthaldialdehyde. The components were separated with a ZORBAX SB-C18 (4.6 150 mm2, 3.5 mm) column from Agilent using 50 mM sodium phosphate buffer (pH 5.9) with 2.5% tetrahydrofurane and methanol (98.75%) with tetrahydrofurane (1.25%) as eluents. Compounds were quantiﬁed by comparison with a standard curve derived from a standard solution of metabolites run repeatedly with 15 sample intervals, and were corrected for possible tissue loss during the extraction procedure using aABA as an internal standard.

GC–MS Aliquots of the samples were dissolved in 0.05 mol/L HCl, followed by lyophilization. Organic acids and amino acids were extracted into an organic phase of ethanol and benzene, dried under air, and reconstituted in N,N-dimethylformamide (Sigma Aldrich) before derivatization with N-Methyl-N-(t-butyldimethylsilyl)triﬂuoroacetamide in 1% t-butyldimethylchlorosilane (both Regis Technologies, Morton Grove, IL, USA). Compounds were analyzed with an Agilent 6890 N gas chromatograph linked to an Agilent 5975B mass spectrometer with an electron ionization source. Results for metabolites were corrected for natural abundance of 13C using standard solutions that were acquired concurrently with the samples.

Percentage

C Enrichment

We calculated the percentage 13C enrichment of lactate with [2,3-13C]lactate and alanine with [2,3-13C]alanine according to the following equation: % Enrichment ¼

Metabolite Quantiﬁcation We quantiﬁed amounts of metabolites in cerebral cortex and HF using HPLC and 1H NMR spectroscopy, amounts of 13C in cortical metabolites using 13C NMR spectroscopy and percentage 13C enrichment in HF with GC–MS, owing to the small amount of hippocampal tissue. The percentage & 2013 ISCBFM

Amount of 13 C labeling 13 C natural abundance x100 Total amount of compound

Notice that the percentage enrichment value actually represents percentage ‘excess enrichment’, as natural abundance is corrected for. However, in this paper, we refer to the value as percentage enrichment in accordance with the previous literature. This also applies to the GC–MS results. Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1092 13 C enrichment with [1,2-13C]glucose was calculated using a different formula, as we were unable to quantify 13C labeling of glucose in 1H spectra. Glucose in water is present in two forms a-glucose and b-glucose. The protons bound to the a-C-1 carbon atom of glucose give rise to a multiplet at 5.22 p.p.m. when bound to 12C and two multiplets when bound to 13C with a splitting of B170 Hz centered around 5.22 p.p.m. in 1H NMR spectra. These peaks are termed here 1H–12C a-glucose and 1H–13C aglucose. We calculated percentage 13C enrichment of [1,2-13C]glucose using the peaks of 1H–12C a-glucose and 1H–13C a-glucose according to the following equation:

H213 C a-glucose x100 1 H212 C a-glucose þ 1 H 13 C a-glucose

% Enrichment ¼

Notice that the formula does not include correction for natural abundance. Natural abundance of glucose cannot be reliably calculated as the level of brain glucose before administration of [1,2-13C]glucose to the animals is unknown. Calculating natural abundance based on measured total glucose amount (1.1% 1.1% (amount of 12C glucose þ 13C glucose)) will overestimate natural abundance, whereas calculating natural abundance based on 12C glucose concentration (1.1% 1.1% amount of 12C glucose) will underestimate 13C natural abundance. Therefore, we have refrained from correcting percentage enrichment of [1,2-13C]glucose with natural abundance in this paper.

Interpretation of [1,2-13C]glucose

A typical C NMR spectrum of a tissue extract from the cerebral cortex of a pilocarpine–SE mouse, injected with [1,2-13C]glucose 3.5–4 weeks after SE, is shown in Figure 1. Singlets denote monolabeled metabolites whereas doublets denote double-labeled metabolites. It should be noted that the peaks of creatine, taurine, and NAA represent natural abundance of 13C. To interpret the 13C incorporation results, it is necessary to analyze the metabolism of [1,2-13C]glucose (Figure 2). Via glycolysis, [1,2-13C]glucose is metabolized to [2,3-13C]pyruvate, which can be converted to [2,3-13C]alanine, [2,3-13C]lactate, or enter the tricarboxylic acid (TCA) cycle via pyruvate dehydrogenase (PDH) as [1,2-13C]acetyl-CoA. Metabolism of [1,2-13C]acetylCoA in the TCA cycle gives rise to [4,5-13C]a-ketoglutarate, which is a precursor for [4,5-13C]glutamate. Thereafter, [4,5-13C]glutamate may be converted to [4,5-13C]glutamine by the exclusively glial enzyme glutamine synthetase17 or to [1,2-13C]GABA in g-aminobutyric acid (GABA)ergic neurons. In astrocytes, [2,3-13C]pyruvate can also be converted to [2,3-13C]oxaloacetate via pyruvate carboxylase (PC),18 which can lead

7 5

Data Analysis Statistics were performed using the two-tailed unpaired Student’s t-test with Po0.05 regarded as signiﬁcant. Data are represented as mean±s.e.m. We chose to use 10 and 11 animals in each group based on previous experience on variations of metabolite levels in epilepsy models. Owing to experimental errors, the number of samples for each group varied between analytical methods.

RESULTS To assess the effects of SE induced by pilocarpine on brain energy metabolism and amino-acid neurotransmitter homeostasis in mice, concentrations of metabolites and incorporation of 13C label into metabolites were analyzed in extracts of cortex and HF using 1H and 13C NMR spectroscopy, HPLC, and GC–MS.

C-labeling Patterns from Metabolism of

to the formation of [2,3-13C]a-ketoglutarate and eventually [2,3-13C]glutamate, [2,3-13C]glutamine, and [3,4-13C]GABA. If [2,3-13C]aketoglutarate and [4,5-13C]a-ketoglutarate is further metabolized in the TCA cycle, labeled oxaloacetate will be formed, which can be transaminated to [1,2-13C]aspartate or [3,4-13C]aspartate. Further cycling of labeled metabolites gives rise to different labeling patterns in amino acids, which are not discussed in this paper.

ppm

Figure 1. Typical C nuclear magnetic resonance spectrum of a cerebral cortex extract from a mouse subjected to pilocarpine– status epilepticus (SE) and injected with [1,2-13C]glucose 3.5–4 weeks later. Monolabeled metabolites give rise to singlets whereas double-labeled metabolites give rise to two peaks on either side of the singlet. It should be noted that the peaks of creatine, taurine, and N-acetyl aspartate represent natural abundance of 13C. Peak assignment: 1: [2-13C]creatine; 2: [3-13C]aspartate and [3,4-13C]aspartate; 3: [2-13C]taurine; 4: [2-13C]GABA and [1,2-13C]GABA; 5: [4-13C]glutamate and [4,5-13C]glutamate; 6: [4-13C]glutamine and [4,5-13C]glutamine; 7: [3-13C]glutamate and [2,3-13C]glutamate; 8: [3-13C]glutamine and [2,3-13C]glutamine; 9: [3-13C]GABA and [3,4-13C]GABA; 10: [6-13C]N-acetyl aspartate; 11: [3-13C]lactate, and [2,3-13C]lactate. Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

Metabolism of [1,2-13C]glucose In this study, we injected mice with [1,2-13C]glucose to obtain information about the pentose phosphate pathway (PPP) and distinguish metabolism of 13C-labeled pyruvate via PC from that of PDH activity. Injection of [1,2-13C]glucose led to labeling of many metabolites as shown in a typical 13C-NMR spectrum from the cerebral cortex of a pilocarpine–SE mouse (Figure 1). The labeling patterns of metabolites labeled from [1,2-13C]glucose via [2,3-13C]pyruvate are depicted in Figure 2 (see Materials and Methods for details). Table 1 shows the total amounts and percentage 13C enrichment with [1,2-13C]glucose, [2,3-13C]lactate, and [2,3-13C]alanine, which were quantified using 1H-NMR spectroscopy, except for the amount of alanine, which was measured using HPLC. Pilocarpine– SE mice received less [1,2-13C]glucose, as their body weight was significantly lower compared with controls, 33.92±1.42 g vs. 38.60±1.25 g (P ¼ 0.024, n ¼ 10 pilocarpine–SE, n ¼ 11 control mice), respectively. This could lead to decreased enrichment of blood glucose with [1,2-13C]glucose in the pilocarpine–SE mice. However, the fact that 13C enrichment of glucose, lactate, and alanine was similar in both brain regions indicates that 13C enrichment of glucose was similar between the two groups in the blood. The only significant difference in metabolite data between the two groups was in alanine in the HF, which was decreased in pilocarpine–SE mice by 30% (P ¼ 0.001). Pentose phosphate pathway activity was below our detection limit in any metabolite in the brain regions analyzed. Content and 13C Labeling of Glutamate, Glutamine, GABA, and Aspartate We measured total amounts of glutamate, glutamine, GABA, and aspartate in extracts of cortex and HF using HPLC (Figure 3). Hippocampal glutamate was decreased by 26% in pilocarpine–SE mice (P ¼ 0.009), whereas other metabolite amounts were not significantly altered. Next, we determined 13C labeling of amino acids in cortex using 13 C NMR spectroscopy (Figure 4), which revealed that the content of [4,5-13C]glutamate and [4,5-13C]glutamine, both labeled via PDH, was decreased by 38% (P ¼ 0.010) and 48% (P ¼ 0.008), respectively, in pilocarpine–SE mice compared with control. The same was found for [2,3-13C]glutamate and [2,3-13C]glutamine, labeling derived from PC, which was decreased by 50% (P ¼ 0.036) and 45% (P ¼ 0.004), respectively. However, labeling of [1,2-13C]GABA, derived from PDH activity, was not significantly & 2013 ISCBFM

Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1093

Figure 2. Schematic representation of isotopomers derived from [1,2-13C]glucose. Only the first turn of the tricarboxylic acid (TCA) cycle is illustrated. Black circles indicate 13C labeling. 13C labeling from pyruvate carboxylase (PC) is indicated by hatched circles. [1,2-13C]aspartate and [3,4-13C]aspartate is labeled from pyruvate dehydrogenase (PDH) and PC.

Table 1.

Glucose metabolism in brain extracts of hippocampal formation and cortex from control and pilocarpine–SE mice

mmol/g

Glucose % [1,2-13C]Glucose Lactate % [2,3-13C]Lactate Alanine % [2,3-13C]Alanine

Cortex

Hippocampal formation

Control

Pilocarpine–SE

Control

Pilocarpine–SE

n¼6

n¼9

n ¼ 10

n¼8

1.69±0.21 23.08±2.59 3.16±0.25 4.97±0.74 1.15±0.11 7.18±1.79

2.03±0.48 23.07±3.52 7.33±1.75 5.35±0.89 0.88±0.07 6.20±0.62

3.11±0.33 37.15±3.86 3.99±0.94 5.89±0.72 0.99±0.05 11.80±1.22

2.37±0.27 30.44±4.39 5.48±1.26 6.33±0.62 0.70±0.06* 8.63±1.60

SE, status epilepticus. Amounts and 13C-enrichment were quantified using 1H-nuclear magnetic resonance spectroscopy, except for alanine, which was determined by high-pressure liquid chromatography. *Po0.05, statistically significantly different from control group, analyzed using the Student’s t-test. For cortex, the control group included 8 mice, and for hippocampal formation, the control group had 11 mice and the pilocarpine–SE group had 9. Data represent mean±s.e.m.

altered, whereas that of [3,4-13C]GABA, labeled via PC, was not measurable. Finally, the sum of [1,2-13C]aspartate and [3,4-13C]aspartate labeled both from PC and PDH was signiﬁcantly decreased in pilocarpine–SE mice by 43% (P ¼ 0.013). Owing to the small size of the HF in mice, the distribution of 13 C-labeled mass isotopomers was assessed using GC–MS instead of 13C NMR spectroscopy (Figure 5). We found that the percentage enrichment with M þ 2 of the TCA cycle intermediate citrate was decreased by 28% (P ¼ 0.015) in pilocarpine–SE mice. In another TCA cycle intermediate, malate, the percentage enrichment was decreased both in M þ 1 and M þ 2 by 40% (P ¼ 0.008) and 26% (P ¼ 0.020), respectively. Moreover, percentage enrichment with M þ 1 and M þ 2 in GABA was decreased by 36% (P ¼ 0.007) and 30% (P ¼ 0.003), respectively, and percentage enrichment with M þ 1 and M þ 2 aspartate was decreased by 32% (P ¼ 0.029) and 22% (P ¼ 0.049), respectively, in pilocarpine–SE mice. Percentage & 2013 ISCBFM

enrichment of mass isotopomers of glutamate and glutamine was not significantly affected in HF. Measurements of Various Metabolites Using HPLC and 1H NMR spectroscopy, we obtained the concentrations of various metabolites in cortex and HF (Table 2). In cortex, the content of the osmolyte myo-inositol was increased by 39% (P ¼ 0.030) in pilocarpine–SE mice compared with control, but was not significantly altered in the HF. The concentration of the essential amino-acid threonine was increased by 24% (P ¼ 0.028) in cortex and 20% (P ¼ 0.030) in HF. In the HF, the level of glutathione was significantly decreased by 18% (P ¼ 0.003), but was not significantly altered in cortex. Moreover, we found that the concentrations of NAA, reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H), and succinate were Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1094

Cortex

% 13C enrichment Hippocampal Formation

% 13C enrichment

mol/g tissue

6 *

4 *

* *

0 Citr Citr Mal Mal Glu Glu Gln Gln GAB GAB Asp Asp M+1 M+2 M+1 M+2 M+1 M+2 M+1 M+2 M+1 M+2 M+1 M+2

0 Glutamate

B 20

GABA

Aspartate

Hippocampal Formation

15 mol/g tissue

Glutamine

0 Glutamate

Glutamine

GABA

Aspartate

Figure 3. Amounts of amino acids glutamate, glutamine, gaminobutyric acid (GABA), and aspartate in brain extracts of (A) cortex and (B) hippocampal formation (HF) from control (black bars) and pilocarpine–status epilepticus (SE) mice (white bars). Data represent mean±s.e.m. of 8 control and 9 pilocarpine–SE mice for cortex, and 11 control and 9 pilocarpine–SE mice for HF, with the exception of glutamate for which the control group included only 10 mice. *Po0.05 statistically significantly different from control group. 13C-labeling Cortex

nmol/ g tissue

1000 800 600

cortex. We could not detect any statistically significant difference in amounts of the energy state-related parameters AMP, ADP, ATP, creatine, phosphocreatine, and the ratio of phosphocreatine to ATP (phosphocreatine/ATP) in either brain region. This was also the case for metabolites glycine, NAD(P) þ , and taurine. DISCUSSION The metabolic profile of pilocarpine–SE mice is discussed here, and compared with findings from rat models of chronic TLE and human TLE. The video electroencephalography data from Kharatishvili and colleagues13 using the CD1 mouse pilocarpine model developed in the Borges laboratory provide clear evidence that CD1 mice after 1.5 hours of pilocarpine-induced SE develop epilepsy. While our techniques do not allow localization of the metabolic changes to subregions or different cell types, we confirmed that mitochondrial metabolic dysfunction especially in the HF is a common hallmark of epilepsy as was previously shown in human tissue and rat models.19,20

400 200 0

Figure 5. The percentage of the total concentration of metabolites labeled with 13C in one (M þ 1) or two (M þ 2) carbon atoms of the molecule in extracts of hippocampal formation from control (black bars) and pilocarpine–status epilepticus (SE) mice (white bars) detected by gas chromatography–mass spectrometry. Mice were injected with [1,2-13C]glucose 15 minutes before microwave fixation of the head. Abbreviations are standard for amino acids and Citr, citrate; Mal, malate; GAB, g-aminobutyric acid. Data represent mean±s.e.m. of 7 control and 10 pilocarpine–SE mice. *Po0.05, statistically significantly different from control group.

* *

[4,5-13C] [2,3-13C] [4,5-13C] [2,3-13C] Glutamate Glutamate Glutamine Glutamine

[1,2-13C] [1,2+3,4-13C] GABA Aspartate

Figure 4. 13C labeling of amino acids derived from [1,2-13C]glucose in brain extract of cortex from control (black bars) and pilocarpine– status epilepticus (SE) mice (white bars). Mice were injected with [1,2-13C]glucose 15 minutes before microwave fixation of the head. [1,2 þ 3.4-13C]aspartate, sum of [1,2-13C]aspartate and [3,4-13C]aspartate labeled from both pyruvate carboxylase and pyruvate dehydrogenase. The control group included 4–6 mice and the pilocarpine–SE group 5–9 mice. Data quantified using 13C nuclear magnetic resonance spectroscopy. *Po0.05, statistically significantly different from control group. GABA, g-aminobutyric acid.

decreased by 27% (P ¼ 0.001), 19% (P ¼ 0.050), and 18% (P ¼ 0.049), respectively, in the HF in pilocarpine–SE mice compared with control, but were not signiﬁcantly altered in Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

Glucose Metabolism The major substrate for energy and amino-acid production in the adult mammalian brain is glucose. Changes in glucose content in the brain can be used to evaluate metabolism, where increased glucose levels imply hypometabolism.21 In the present study, however, no difference was detected in glucose content or 13C enrichment, although glucose hypometabolism was demonstrated in the continuous phase of lithium-pilocarpine rats7,9 and mice subjected to pentylenetetrazole kindling 30 minutes after ﬁnal pentylenetetrazole injection.22 Similarly, the majority of TLE patients display reduced uptake of [18F]ﬂuorodeoxyglucose in the epileptogenic region using positron emission tomography, an indicator of reduced glucose metabolism.1,23 Interestingly, neuronal loss does not appear to correlate with the decrease in glucose consumption,7,23 suggesting that interictal hypometabolism is affected more by dysfunctional mitochondrial oxidative and/or glycolytic energy metabolism than cell loss in epileptic tissue. After phosphorylation, glucose can be metabolized to glycogen in astrocytes, and to pyruvate in both astrocytes and neurons via glycolysis and a smaller extent the PPP. Using [1,2-13C]glucose, it is possible to distinguish between pyruvate production from & 2013 ISCBFM

Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1095 Table 2.

Amounts (mmol/g tissue) of metabolites in brain extracts of hippocampal formation and cortex from control and pilocarpine–SE mice

mmol/g

Glutathione Glycine Taurine Threonine AMP ADP ATP Creatine Myo-inositol NAA NAD(P) þ NAD(P)H Phosphocreatine PCr/ATP ratio Succinate

Cortex

Hippocampal formation

Control

Pilocarpine–SE

Control

Pilocarpine–SE

n ¼ 6–8

n ¼ 8–9

n ¼ 10–11

n ¼ 7–9

2.90±0.28 2.44±0.19 13.11±1.07 0.46±0.03 0.54±0.09 1.32±0.12 2.29±0.17 6.07±0.51 7.27±0.55 9.35±0.85 0.33±0.04 0.11±0.01 3.26±0.28 1.42±0.05 0.39±0.07

2.45±0.15 2.04±0.20 12.12±0.75 0.58±0.03* 0.60±0.11 1.39±0.13 2.04±0.17 7.35±0.74 10.12±0.87* 8.49±0.46 0.37±0.02 0.09±0.01 2.38±0.52 1.08±0.21 0.52±0.06

2.33 þ 0.08 2.07±0.08 9.79±0.45 0.51±0.02 0.35±0.03 1.47±0.11 1.79±0.10 6.26±0.48 9.02±0.36 7.50±0.33 0.31±0.03 0.08±0.01 3.98±0.87 1.72±0.36 0.64±0.03

1.90±0.10* 2.21±0.13 10.01±0.53 0.61±0.04* 0.31±0.04 1.36±0.08 1.69±0.09 6.19±0.71 10.93±1.23 5.49±0.34* 0.26±0.02 0.07±0.01* 2.32±0.20 1.32±0.13 0.52±0.04*

NAA, N-acetylaspartate; NAD(P), nicotinamide adenine dinucleotide and nicotinamide adenine dinucleotide (phosphate); PCr/ATP ratio, ratio of phosphocreatine to ATP; SE, status epilepticus. SE was induced in 7–8-week-old mice by pilocarpine injection. After 3.5–4 weeks, mice were subjected to microwave fixation of the head. Metabolites glutathione, glycine, taurine, and threonine were quantified using high-pressure liquid chromatography, whereas the other metabolites were quantified using 1 H-nuclear magnetic resonance spectroscopy. Data represent mean±s.e.m., *Po0.05.

glycolysis, reflected by [2,3-13C]pyruvate levels, and the PPP, revealed by levels of [3-13C]pyruvate and [1,3-13C]pyruvate. Pyruvate can be converted to lactate, alanine, oxaloacetate, or acetyl-CoA. In cortex, 13C enrichment and total amounts of lactate and alanine were unaltered in the continuous phase of epilepsy pointing to normal glycolysis, whereas in the HF total levels of lactate and 13C enrichment of lactate and alanine were not significantly different, indicating that there are no major changes in glycolysis and lactate formation. 13C enrichment of lactate and alanine via the PPP was negligible in both brain areas. However, in the HF total amounts of alanine and glutamate were decreased, which suggests reduced levels of either pyruvate and/or aketoglutarate and/or reduced activity of transaminases, such as glutamic pyruvic transaminase. The changes in glutamate levels are discussed in the next paragraph. Amino-acid and Neurotransmitter Metabolism The carbon skeleton of pyruvate may enter the TCA cycle via PC or after decarboxylation via PDH. The important neurotransmitter amino acids glutamate and aspartate are formed from TCA cycle intermediates a-ketoglutarate and oxaloacetate, respectively, and GABA is synthesized from glutamate, linking neurotransmitter metabolism with glucose metabolism in the brain. We found no differences in the contents of these amino acids in either brain region of chronic epileptic mice, except for a reduction of glutamate in the HF. Thus, pilocarpine–SE mice displayed the same profile for these amino acids as mice kindled with pentylenetetrazole,22 whereas in the forebrain of another mouse strain 5 weeks after pilocarpine–SE, there was a decreased GABA content.24 Similarly, studies on rat models of chronic epilepsy have shown reductions in the content of aspartate as well as glutamate.8,9 The reduction of glutamate content in the HF might reflect neuronal loss in this region, a histopathological hallmark of human TLE.25 Also, loss of hippocampal pyramidal cells has been demonstrated for this pilocarpine mouse model in most mice at several time points from 3 to 31 days after SE.15 However, a decrease in glutamate content did not correlate with neuronal loss in the hippocampus of patients with TLE.26 Reduction in glutamate levels is affected more by impaired cell & 2013 ISCBFM

metabolism, such as altered substrate transport, decreased activity of the TCA cycle, and/or various mitochondrial enzymes, than cell loss.27 A considerable number of studies have shown that the cycling of glutamate to glutamine between neurons and astrocytes may be slower in hippocampal tissue of TLE patients and animal models of epilepsy. Most brain glutamate is located within cells, but increased extracellular glutamate is reported in connection with seizures3,4,10,28 and the expression of glutamine synthetase is decreased in the epileptogenic HF of human TLE.5,6 We could not detect any difference in the total glutamine content in the HF despite the reduction in glutamate, in line with previous reports on kainate and lithium-pilocarpine rat models of TLE and the pentylenetetrazole-kindling model in mice.8,9,22 Similarly, a recent study of pilocarpine–SE rats revealed no quantitative changes in the number and volume of astrocytes expressing GS but there was a redistribution of the enzyme from distal to proximal astrocyte processes within the hippocampus.29 Analyzing metabolites using GC–MS revealed a decrease in 13C enrichment of the TCA cycle intermediates citrate and malate in the HF suggesting decreased TCA cycle turnover in this region, which also can explain the reduction in total levels of succinate and glutamate. Furthermore, this study revealed a decrease in the 13 C enrichment of GABA and aspartate, which was not the case for glutamate and glutamine. In cortex, the level of 13C labeling in glutamate and glutamine from both PC and PDH pathways was equally decreased in pilocarpine–SE mice compared with control. Furthermore, the sum of [1,2-13C]aspartate þ [3,4-13C]aspartate, labeled both from PC and PDH, was decreased too. These results imply reduced metabolism in astrocytes as PC is an astrocytic-speciﬁc enzyme30 and brain glutamine is formed in astrocytes only.17 However, neurons appear to metabolize B70% of acetyl-CoA from glucose in the brain31,32 and most glutamate is present in neurons.33 Therefore, altered neuronal metabolism of glutamate, glutamine, and aspartate in the cortex of pilocarpine–SE mice cannot be ruled out. While reduced 13C labeling reﬂects reduced use of glucose for the synthesis of these amino acids, the total amounts of glutamate, glutamine, and aspartate were not decreased to the same degree. Thus, it follows that there is either decreased uptake and/or reduced degradation of these Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1096 amino acids (or their precursors). In conclusion, the findings indicate reduced turnover of cortical glutamate, glutamine, and aspartate as well as reduced TCA cycling in the continuous phase of pilocarpine–SE mice, which was not evident for the GABAergic compartment. Other Metabolites Similar to glutamate content, that of NAA was decreased in the HF. N-acetyl aspartate is primarily synthesized in neuronal mitochondria34 and the content of this metabolite is commonly found to be decreased in the epileptic region of humans with TLE and rat models of chronic epilepsy.8,9,35 Several studies have failed to show any significant relationship between content of NAA and cell death in patients with TLE suggesting that NAA loss reflects metabolic dysfunction rather than neuronal loss.19,26,36,37 Therefore, decreases in NAA content further support our findings of reduced neuronal metabolism. Moreover, alterations of NAD(P)H transients during neuronal activation, a measure of dysfunctional oxidative and/or glycolytic energy metabolism, was revealed by fluorescence recording of hippocampal slices of human tissue from TLE patients.20 In line with this, we found decreased hippocampal contents of the reducing nucleotides NAD(P)H and the TCA cycle intermediate succinate in pilocarpine– SE mice indicating impairment of mitochondrial function. No significant differences in high-energy metabolites such as phosphocreatine and ATP and the ratio of phosphocreatine/ATP were found, similar to various other animal studies,9,22 although reduction of these metabolite levels have been reported in human TLE.38 The content of glutathione was decreased in the HF of pilocarpine–SE mice, similar to results from the lithiumpilocarpine rat model,9 which may suggest decreased capacity for cytosolic oxidative reduction in this region. As glutathione is a tripeptide composed of glutamate, cysteine, and glycine, the reduction in hippocampal glutamate content may be a direct cause for the decrease of glutathione, although the availability of cysteine is usually rate limiting. Moreover, a reduction in astrocytic glutamate might impair the uptake of cystine into astrocytes as import of cystine is obligatory linked to the release of glutamate via the cystine/glutamate antiporter. However, it was recently shown that the role of this transport system was not critical for the synthesis of glutathione in the mouse hippocampus in vivo.39 The increase of cortical myo-inositol in pilocarpine–SE mice was similar to that found in pentylenetetrazole-kindled mice.22 It suggests astroglial expansion, as myo-inositol is primarily localized in astrocytes40 and GFAP immunostaining is also stronger in these mice.15

CONCLUSION We characterized the metabolic profile of mice in the continuous phase of epilepsy, 3.5–4 weeks after SE was induced by pilocarpine. Altogether the metabolic alterations partly resemble those reported for human TLE and rat models of chronic epilepsy, such as glutamate content reduction and mitochondrial metabolic dysfunction in the HF. Moreover, the application of 13C NMR spectroscopy, HPLC, and GC–MS revealed decreased turnover of important metabolites within and derived from TCA cycle intermediates, specifically glutamate, glutamine, and aspartate in the cerebral cortex, and citrate, succinate, malate, GABA, and aspartate in the HF. These findings are consistent with impaired function of the TCA cycle in both the cerebral cortex and the HF in mice with spontaneous recurrent seizures. Targeting these impaired mitochondrial functions appears to be promising for the treatment of drug-resistant epilepsy. Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

DISCLOSURE/CONFLICT OF INTEREST The authors declare no conﬂict of interest.

ACKNOWLEDGEMENTS The authors thank Nicola K Thomas for help with the animals and Nina Berggaard and Tesfaye Tefera for their help with the GC–MS analyses. Karin Borges is grateful for funding by the Australian National Health and Research Council (Grants 63145 and 1044407).

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Altered brain metabolism in mouse model of epilepsy OB Smeland et al

1097 22 Smeland OB, Meisingset TW, Sonnewald U. Dietary supplementation with acetyl-lcarnitine in seizure treatment of pentylenetetrazole kindled mice. Neurochem Int 2012; 61: 444–454. 23 O’Brien TJ, Newton MR, Cook MJ, Berlangieri SU, Kilpatrick C, Morris K et al. Hippocampal atrophy is not a major determinant of regional hypometabolism in temporal lobe epilepsy. Epilepsia 1997; 38: 74–80. 24 Willis S, Stoll J, Sweetman L, Borges K. Anticonvulsant effects of a triheptanoin diet in two mouse chronic seizure models. Neurobiol Dis 2010; 40: 565–572. 25 de Lanerolle NC, Lee TS. New facets of the neuropathology and molecular proﬁle of human temporal lobe epilepsy. Epilepsy Behav 2005; 7: 190–203. 26 Petroff OA, Errante LD, Rothman DL, Kim JH, Spencer DD. Neuronal and glial metabolite content of the epileptogenic human hippocampus. Ann Neurol 2002; 52: 635–642. 27 Borges K, Sonnewald U. Triheptanoin--a medium chain triglyceride with odd chain fatty acids: a new anaplerotic anticonvulsant treatment? Epilepsy Res 2012; 100: 239–244. 28 Wilson CL, Maidment NT, Shomer MH, Behnke EJ, Ackerson L, Fried I et al. Comparison of seizure related amino acid release in human epileptic hippocampus versus a chronic, kainate rat model of hippocampal epilepsy. Epilepsy Res 1996; 26: 245–254. 29 Papageorgiou IE, Gabriel S, Fetani AF, Kann O, Heinemann U. Redistribution of astrocytic glutamine synthetase in the hippocampus of chronic epileptic rats. Glia 2011; 59: 1706–1718. 30 Yu AC, Drejer J, Hertz L, Schousboe A. Pyruvate carboxylase activity in primary cultures of astrocytes and neurons. J Neurochem 1983; 41: 1484–1487. 31 Hassel B, Sonnewald U, Fonnum F. Glial-neuronal interactions as studied by cerebral metabolism of [2-13C]acetate and [1-13C]glucose: an ex vivo 13C NMR spectroscopic study. J Neurochem 1995; 64: 2773–2782.

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32 Qu H, Haberg A, Haraldseth O, Unsgard G, Sonnewald U. (13)C MR spectroscopy study of lactate as substrate for rat brain. Dev Neurosci 2000; 22: 429–436. 33 Ottersen OP, Zhang N, Walberg F. Metabolic compartmentation of glutamate and glutamine: morphological evidence obtained by quantitative immunocytochemistry in rat cerebellum. Neuroscience 1992; 46: 519–534. 34 Urenjak J, Williams SR, Gadian DG, Noble M. Speciﬁc expression of N-acetylaspartate in neurons, oligodendrocyte-type-2 astrocyte progenitors, and immature oligodendrocytes in vitro. J Neurochem 1992; 59: 55–61. 35 Cendes F, Andermann F, Preul MC, Arnold DL. Lateralization of temporal lobe epilepsy based on regional metabolic abnormalities in proton magnetic resonance spectroscopic images. Ann Neurol 1994; 35: 211–216. 36 Kuzniecky R, Palmer C, Hugg J, Martin R, Sawrie S, Morawetz R et al. Magnetic resonance spectroscopic imaging in temporal lobe epilepsy: neuronal dysfunction or cell loss? Arch Neurol 2001; 58: 2048–2053. 37 Cohen-Gadol AA, Pan JW, Kim JH, Spencer DD, Hetherington HH. Mesial temporal lobe epilepsy: a proton magnetic resonance spectroscopy study and a histopathological analysis. J Neurosurg 2004; 101: 613–620. 38 Pan JW, Kim JH, Cohen-Gadol A, Pan C, Spencer DD, Hetherington HP. Regional energetic dysfunction in hippocampal epilepsy. Acta Neurol Scand 2005; 111: 218–224. 39 De Bundel D, Schallier A, Loyens E, Fernando R, Miyashita H, Van Liefferinge J et al. Loss of system x(c)- does not induce oxidative stress but decreases extracellular glutamate in hippocampus and inﬂuences spatial working memory and limbic seizure susceptibility. J Neurosci 2011; 31: 5792–5803. 40 Brand A, Richter-Landsberg C, Leibfritz D. Multinuclear NMR studies on the energy metabolism of glial and neuronal cells. Dev Neurosci 1993; 15: 289–298.

Journal of Cerebral Blood Flow & Metabolism (2013), 1090 – 1097

The pathology of magnetic-resonanceimaging-negative epilepsy Z Irene Wang1, Andreas V Alexopoulos1, Stephen E Jones2, Zeenat Jaisani3, Imad M Najm1 and Richard A Prayson4 1Cleveland

Clinic Epilepsy Center, Cleveland, OH, USA; 2Mellen Imaging Center, Cleveland Clinic, Cleveland, OH, USA; 3Sanford USD Medical Center, Sioux Falls, SD, USA and 4Anatomic Pathology, Cleveland Clinic Foundation, Cleveland, OH, USA

Patients with magnetic-resonance-imaging (MRI)-negative (or ‘nonlesional’) pharmacoresistant focal epilepsy are the most challenging group undergoing presurgical evaluation. Few large-scale studies have systematically reviewed the pathological substrates underlying MRI-negative epilepsies. In the current study, histopathological specimens were retrospectively reviewed from MRI-negative epilepsy patients (n ¼ 95, mean age ¼ 30 years, 50% female subjects). Focal cortical dysplasia cases were classified according to the International League Against Epilepsy (ILAE) and Palmini et al classifications. The most common pathologies found in this MRI-negative cohort included: focal cortical dysplasia (n ¼ 43, 45%), gliosis (n ¼ 21, 22%), hamartia þ gliosis (n ¼ 12, 13%), and hippocampal sclerosis (n ¼ 9, 9%). The majority of focal cortical dysplasia were ILAE type I (n ¼ 37) or Palmini type I (n ¼ 39). Seven patients had no identifiable pathological abnormalities. The existence of positive pathology was not significantly associated with age or temporal/extratemporal resection. Follow-up data post surgery was available in 90 patients; 63 (70%) and 57 (63%) attained seizure freedom at 6 and 12 months, respectively. The finding of positive pathology was significantly associated with seizure-free outcome at 6 months (P ¼ 0.035), but not at 12 months. In subgroup analysis, the focal cortical dysplasia group was not significantly correlated with seizure-free outcome, as compared with the negative-pathology groups at either 6 or 12 months. Of note, the finding of hippocampal sclerosis had a significant positive correlation with seizurefree outcome when compared with the negative-pathology group (P ¼ 0.009 and 0.004 for 6- and 12-month outcome, respectively). Absence of a significant histopathology in the resected surgical specimen did not preclude seizure freedom. In conclusion, our study highlights the heterogeneity of epileptic pathologies in MRInegative epilepsies, with focal cortical dysplasia being the most common finding. The existence of positive pathology in surgical specimen may be a good indication for short-term good seizure outcome. There is a small subset of cases in which no pathological abnormalities are identified. Modern Pathology (2013) 26, 1051–1058; doi:10.1038/modpathol.2013.52; published online 5 April 2013 Keywords: epilepsy; focal cortical dysplasia; gliosis; hippocampal sclerosis; MRI; MRI-negative epilepsy;

pharmacoresistant focal epilepsy

Patients with magnetic-resonance-imaging (MRI)negative (or ‘nonlesional’) pharmacoresistant focal epilepsy constitute the most challenging group undergoing presurgical evaluation.1–3 The overall prevalence of nonlesional epilepsy in all surgical studies is B26%.4 At present, surgical management of MRInegative pharmacoresistant focal epilepsy patients relies heavily on invasive intracranial electroencephalography, which is based on complimentary review of Correspondence: Dr RA Prayson, MD Anatomic Pathology, Cleveland Clinic foundation, 9500 Euclid Avenue, Desk L25, Cleveland, OH 44195, USA. E-mail: praysor@ccf.org Received 10 January 2013; accepted 11 January 2013; published online 5 April 2013 www.modernpathology.org

other noninvasive modalities including positron emission tomography, ictal single-photon emission computed tomography, and magnetoencephalography when available.5–8 Despite substantial efforts, the lack of a lesion on MRI has consistently been shown to be one of the predictors for surgical failure.9,10 Therefore, MRI-negative patients are usually considered unfavorable surgical candidates4 and are often denied epilepsy surgery. Yet, surgical resection can be effective in well-selected patients with no visible MRI abnormality. In order to improve surgical outcome of MRI-negative patients, it is important to understand the pathologies that these patients may demonstrate on examining their surgically resected tissues. The pathologic substrates underlying pharmacoresistant focal epilepsy are well established and most

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commonly include hippocampal sclerosis, focal cortical dysplasia, tumors, and remote ischemic events/ infarcts.11,12 Studies specifically on the surgical pathology of MRI-negative patients, however, are limited to small-scale experiences of individual centers,13–16 or cases buried in larger series containing both MRI-positive and -negative patients.17,18 Moreover, with the advance in MRI technology over the last decade and the establishment of more uniform epilepsy MRI protocols, the definition of ‘MRInegative’ cases in recent studies may not be equivalent to earlier ones. The purpose of this study is to systematically review one institution’s recent experience with the pathological substrates underlying strictly defined MRI-negative epilepsies.

Materials and methods After approval from Institutional Review Board, the Cleveland Clinic Epilepsy Center’s surgical database was searched for patients with chronic epilepsy who underwent a surgical resection from 2002 to 2011. During this period, all patients underwent high-resolution 1.5- or 3-Tesla preoperative MRI studies using a standard epilepsy protocol. From this group, we selected patients with strictly defined negative MRI based on two criteria: (1) all MRI scans were evaluated prospectively by dedicated epilepsy neuroradiologists for possible epileptogenic abnormalities during the presurgical evaluation process and showed no lesions and (2) MRI scans were evaluated again by epileptologists, neurosurgeons, and dedicated epilepsy neuroradiologists after re-review of images during the patient management conference, taking into account the results of comprehensive noninvasive testing, and were still judged to be negative. Patients with MRIs that were initially interpreted as normal were excluded if a probable or questionable lesion was

identified during re-review of the study in the patient management conference. Patients were excluded if they had poor MRI image quality, for example, motion artifacts hampering image interpretation. Patients with prior surgeries were excluded. Available microscopic slides from surgical resections were reviewed in all cases (mean ¼ 7, range ¼ 1–20). In 40 cases, all the resected tissues were submitted and reviewed microscopically; a subtotal sampling of resected tissue was done in the remaining 55 cases. Focal cortical dysplasia was classified according to both the International League Against Epilepsy (ILAE) classification19 as well as Palmini et al20 classification; classification criteria are described in Table 1. Hippocampal sclerosis was defined by a characteristic loss of neurons and gliosis in the hippocampus, preferentially involving the dentate, CA4, CA3, and CA1 regions.21 Hamartias were defined as collections of small neurons marked by scant cytoplasm and pericellular clearing.22 Nodular heterotopia is marked by the presence of disordered gray matter tissue in the white matter. Positive pathology is defined by the finding of focal cortical dysplasia, heterotopia, hippocampal sclerosis, other hippocampal abnormalities, and dual osseous metaplasia. Negative pathology is defined by the finding of gliosis only, gliosis with hamartia, or no microscopic abnormality identified. Based on location of surgical site, resections were classified as frontal, parieto-occipital, neocortical temporal, standard temporal lobectomies with removal of mesial temporal structures, and multilobar resections. We analyzed the outcome at 6 and 12 months. Outcome was classified into two groups: completely seizure-free (Engel’s class Ia) and not seizure-free (Engel’s class Ib–IV).23 Statistical significance was assessed using the Fisher’s exact test, with significance defined as a probability (P) value of r0.05.

Table 1 Classification of focal cortical dysplasia for the current study using ILAE classification19 and a variation of Palmini et al20 classification FCD type

Criteria

ILAE ILAE ILAE ILAE ILAE ILAE ILAE ILAE ILAE

Isolated lesions presenting as radial dyslamination of neocortex Isolated lesions presenting as tangential dyslamination of neocortex Isolated lesions presenting as both radial and tangential dyslamination Isolated lesion characterized by cortical dyslamination and dysmorphic neurons without balloon cells Isolated lesion characterized by cortical dyslamination and dysmorphic neurons with balloon cells Occurs in combination with hippocampal sclerosis Occurs with epilepsy-associated tumors Adjacent to vascular malformations In association with epileptogenic lesions acquired in early life (ie, traumatic injury, ischemic injury, or encephalitis)

Ia Ib Ic IIa IIb IIIa IIIb IIIc IIId

Palmini IA Palmini IB Palmini IIA Palmini IIB

Isolated architectural abnormalities (dyslamination, accompanied or not by other abnormalities of mild malformation of cortical development, or malformation of cortical development) Architectural abnormalities, plus giant or immature, but not dysmorphic, neurons Architectural abnormalities with dysmorphic neurons but without balloon cells Architectural abnormalities with dysmorphic neurons and balloon cells

Abbreviation: ILAE, International League Against Epilepsy. Modern Pathology (2013) 26, 1051–1058

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Table 2 Summary of pathological findings Pathology

n (%)

Focal cortical dysplasia ILAE Ib ILAE Ic ILAE IIb ILAE IIIa

9 (9) 28 (30) 4 (4) 2 (2)

Palmini Palmini Palmini Palmini Palmini Total

IA IA þ hippocampal sclerosis IA þ Nodular heterotopia IB IIB

Gliosis only Hamartia þ gliosis Hippocampal sclerosis only No pathology identified Dual osseous metaplasia Hippocampal neuronal loss Granular cell dispersion in hippocampus Total

26 (27) 2 (2) 2 (2) 9 (9) 4 (4) 43 (45) 21 (22) 12 (13) 9 (9) 7 (7) 1 (1) 1 (1) 1 (1) 95

Abbreviation: ILAE, International League Against Epilepsy.

Results Patient Demographics

A total of 95 patients (median/mean age ¼ 29/30 years, range 4–64 years; 50% female subjects) fulfilled the selection criteria. Histological slides were available in all patients. Surgery included 21 frontal resections, 6 parieto-occipital resections, 34 neocortical temporal resections, 32 standard temporal lobectomies with removal of mesial structures, and 2 multilobar resections. Left-sided resections were performed in 49 (52%) patients. Pathological Findings

Table 2 summarizes the pathological findings observed in this MRI-negative cohort. The most commonly identified pathology was focal cortical dysplasia (n ¼ 43, including 2 coexisting with hippocampal sclerosis and 2 with nodular heterotopia). A majority of cortical dysplasias were ILAE type I (n ¼ 37), with the majority being Ic (n ¼ 28); using Palmini classification, the majority were type I as well (n ¼ 39), with type IA being most common (n ¼ 30). Examples of ILAE type Ic (Palmini type IA) and Ib (Palmini type IB) are shown in Figures 1 and 2, respectively. Two patients had nodular heterotopia in addition to focal cortical dysplasia (Figure 3). Nine patients had hippocampal sclerosis alone (Figure 4). Twenty-one patients only had gliosis, and an additional 12 patients showed gliosis accompanied by hamartia (Figure 5). In seven patients, no microscopic abnormality was identified.

Figure 1 Low-magnification view of the cortex showing a linear arrangement of neurons in central layers 2 and 3, consistent with ILAE type Ic focal cortical dysplasia (Palmini et al20 type IA). (Hematoxylin and eosin staining; original magnification 100.)

Overall, 12/19 (63%) children (17 years or younger) had positive pathology, compared with 43/76 (57%) adults. No difference in positive pathology was noted between these two age groups (P ¼ 0.8). Twenty-one of the 29 (72%) extratemporal lobe epilepsy patients had positive pathology compared with 34/66 (52%) of patients with temporal lobe epilepsy. The finding of positive pathology was not significantly associated with temporal/extratemporal lobe epilepsy groups (P ¼ 0.07). Seventeen of the 55 (31%) subtotally submitted specimens had negative pathology; 23/40 (58%) of totally submitted specimens had negative pathology.

Correlation With Outcome

Follow-up data were available in 90 patients. Outcome data grouped by pathology are shown in Table 3. At 6 months’ follow-up, 63 (ie, 70% of the entire cohort) attained seizure freedom (Engel class Ia). Overall, 42 of the 53 (79%) patients with positive pathology, and 21 of the 37 (57%) patients with negative pathology were seizure-free. The finding of positive pathology was significantly associated with seizure-free outcome (P ¼ 0.035). We further performed subgroup analysis. Although focal cortical dysplasia constituted the largest group of seizure-free patients (30/63, 48%), there was no significant correlation between the existence of focal cortical dysplasia in surgical specimen and seizurefree outcome, as compared with the negativepathology group (P ¼ 0.16) or gliosis alone (P ¼ 0.09). Of note, the finding of hippocampal sclerosis (including nine hippocampal sclerosis only, and two hippocampal sclerosis þ focal cortical dysplasia) had a significant positive correlation with seizure-free outcome when compared with the negative-pathology group (P ¼ 0.009). The ILAE Ib group trended towards being positively associated Modern Pathology (2013) 26, 1051–1058

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Figure 2 Intermediate magnification view of the cortex showing an absence of a well-formed cortical layer 2 and neuronal cytomegaly, consistent with ILAE type Ib focal cortical dysplasia (Palmini et al20 type IB). (Hematoxylin and eosin staining; original magnification 200.)

Figure 4 Low magnification appearance of hippocampal sclerosis marked by permanent neuronal loss and gliosis (upper right) in the CA1 region. (Hematoxylin and eosin staining; original magnification 50.)

Figure 3 Low magnification view of multiple periventricular nodular heterotopia, which were associated with an overlying focal cortical dysplasia. (Hematoxylin and eosin staining; original magnification 50.)

Figure 5 Intermediate magnification view showing clustered collections of small neurons (hamartia) and gliosis. (Hematoxylin and eosin staining; original magnification 200.)

with seizure-free outcome when compared with the gliosis only plus no-identifiable-pathology group (P ¼ 0.06), but did not reach statistical significance. In the group where no pathology was identified, four out of the seven patients were seizure-free. At 12-month follow-up, 57 (63%) were completely seizure-free (Engel class Ia outcome). Overall, 37 of the 53 (70%) patients with positive pathology, and 20 of the 37 (54%) patients with negative pathology were seizure-free. Different from the 6-month follow-up data, the finding of positive pathology was not significantly associated with seizure-free outcome 12 months after surgical resection (P ¼ 0.18). Other data trends are similar to the 6-month-outcome data. Patients with focal cortical dysplasia were still more likely to attain seizure-free

outcome (27/57, 47%), but there was no significant correlation between the existence of focal cortical dysplasia in surgical specimen and seizure-free outcome, as compared with the negative-pathology group (P ¼ 0.35) or gliosis alone (P ¼ 0.27). The finding of hippocampal sclerosis still had a significant positive correlation with seizure-free outcome at 12 months when compared with the negative-pathology group (P ¼ 0.004). The ILAE Ib group trended toward being positively associated with seizure-free outcome when compared with the Ic group (P ¼ 0.056) and the gliosis plus no-identifiable-pathology group (P ¼ 0.06), but did not reach statistical significance for either. Four out of the seven patients with no-identifiable pathology remained seizure-free at 12 months.

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Table 3 Relationship between pathology findings and surgical outcome in 90 patients at 6- and 12-month follow-up Outcome at 6 months

Outcome at 12 months

Pathology Engel’s Engel’s Engel’s Engel’s class Ia class Ib–IV class Ia class Ib–IV Focal cortical dysplasia ILAE Ib ILAE Ic ILAE IIb ILAE IIIa

8 16 4 2

1 10 0 0

8 13 4 2

1 13 0 0

Palmini IA Palmini IA þ nodular heterotopia Palmini IA þ hippocampal sclerosis Palmini IB Palmini IIB

16 2

9 0

13 2

12 0

6 4

2 0

6 4

2 0

Gliosis only Hamartia þ gliosis Hippocampal sclerosis only No pathology identified Dual osseous metaplasia Hippocampal neuronal loss Granular cell dispersion in hippocampus

10 7 9

10 3 0

10 6 8

10 4 1

4 1

3 0

4 0

3 1

Total ¼ 90

Abbreviation: ILAE, International League Against Epilepsy.

Discussion We present the pathologic results of a large singlecenter series of 95 patients with strictly defined MRI-negative focal epilepsy who underwent epilepsy surgery. Consistent with previous studies, our data show that focal cortical dysplasia is the most common pathological substrate of surgically treated nonlesional epilepsy. In addition, our results show that the presence of positive pathology is significantly associated with early seizure-free outcome. There was no significant correlation between the existence of focal cortical dysplasia in surgical specimens and seizure-free outcome, as compared with the negative-pathology groups in either 6- or 12 months’ outcome data. Of note, the finding of hippocampal sclerosis had a significant positive correlation with seizure-free outcome, when compared with the negative-pathology group. Absence of a significant histopathology in the resected surgical specimen did not preclude seizure freedom. Limitations of the previous literature examining pathological substrates of nonlesional epilepsy include: small number of patients, variable definitions of ‘nonlesional’, and variable approaches to pathological diagnosis. Pathological findings are typically reported in small-scale studies from individual

centers,13–16 or buried in larger series containing a full spectrum of patients among which only a small number was MRI-negative.17,18 A few attempts at meta-analysis have been performed to better understand surgical outcome and factors such as pathology, surgery type, and seizure semiology in MRI-negative patients. Ansari et al24 reported 95 pediatric extratemporal nonlesional epilepsy patients from 17 studies, and classified surgical pathology into three categories: cortical dysplasia, gliosis, and others (neuronal loss, encephalitis, polymicrogyria, ulegyria, chronic inflammation, and normal). Their analysis demonstrated that a positive histopathological finding has a favorable association with postoperative outcome: a majority of patients in the Engel class I outcome group harbored cortical dysplasia. In a parallel study, Ansari et al25 reported on 131 adult patients with extratemporal nonlesional epilepsy and found that none of the variables, including surgical pathology, had any significant association with outcome in the adult group. This study also found focal cortical dysplasia to be the most common substrate in patients with seizure-free outcome. Both metaanalysis studies defined ‘nonlesional’ epilepsies based on pathological substrates, whereas only mass-like lesions such as tumors, vascular lesions, multiple sclerosis, and heterotopias were considered ‘lesional’, and focal cortical dysplasia was considered ‘nonlesional’. From a practical, presurgical evaluation point of view, however, MRI findings are generally used to define a case as ‘nonlesional’. In our study, we only included patients with negative MRI based on consensus review of high-resolution MRI studies during a multidisciplinary patient management conference, in addition to an independent neuroradiology interpretation. This approach ensured the inclusion of a highly selected group of patients with negative MRI findings who underwent surgical resection of identified epileptic foci, followed by a blinded neuropathological examination of the resected specimens. The high incidence of various focal cortical dysplasia types in the current study supports that the most common epileptic pathological correlate not visualized by MRI was indeed focal cortical dysplasia. These results are concordant with previous reports that showed that cortical dysplasia was identified in up to one-third of tissue specimens, following resective epilepsy surgery in both MRI-positive and -negative cases.24–27 Among the focal cortical dysplasia subtypes, our data also show that focal cortical dysplasia type I (by either classification) is the most common substrate of MRI-negative epilepsy. There were only four cases of balloon cell cortical dysplasia. The higher prevalence of type I lesions than type II further illustrates the challenging nature of presurgical identification and mapping of this pathology, and highlights the need for more sensitive and accurate Modern Pathology (2013) 26, 1051–1058

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presurgical studies. Focal cortical dysplasia type I lesions have highly idiosyncratic presentations and are usually more diffuse than type II lesions, making them the most challenging ones to be detected by structural imaging methodology.28–30 In addition to the accurate definition, delineation of the boundaries of type I focal cortical dysplasia is also difficult, as the microscopically dysplastic lesion may extend well beyond the margins defined by the MRI-visible abnormality (in MRIpositive cases),30–32 even with the use of highresolution dedicated epilepsy MRI protocols and review of the images by expert neuroradiologists.26,32 Our finding of MRI-negative patients with hippocampal sclerosis is also consistent with previous literature that up to 30% of patients with hippocampal sclerosis may have normal findings on conventional MRI.33 Surgical outcome of MRI-negative patients can be hard to determine due to heterogeneity of patient populations, surgical techniques, follow-up time, and outcome definition in the literature. A recent meta-analysis showed only 34–45% long-term seizure-free rate, whereas MRI-positive (or ‘lesional’) surgical candidates may have a two times higher probability of attaining seizure freedom.4 Our MRInegative cohort (comprised of temporal and extratemporal cases) had seizure-free rate of 59% at 12 months, this percentage is consistent with other studies from our center and can be anticipated to drop as follow-up durations increase.10,34,35 Overall, we found that positive pathology in surgical specimen positively associated with seizure-free outcome at 6 months, but not at 12 months. This finding is consistent with the hypothesis that immediate postoperative seizure recurrence may indicate a mislocalization and/or incomplete resection of the active epileptic focus, whereas long-term recurrence may be attributed to other factors such as the natural history of the disease and the postsurgical development of secondary epileptogenesis.36 Subgroup analysis revealed that focal cortical dysplasia did not positively correlate with seizure-free outcome, as the cortical dysplasia type I pathology (majority of the group) is generally more widespread, and often involves eloquent cortex in extratemporal cases, making it less amenable to resection. On the other hand, MRInegative patients with hippocampal sclerosis appeared to have a better chance for seizure-free outcome, as these lesions are relatively more circumscribed, and temporal lobectomy with complete removal of the epileptic and histopathologically abnormal mesial structures is usually an effective approach. In a subset of patients in the current study, no pathologic substrate was identified. One possible explanation is a presurgical mislocalization. In a recent study from our center,37 patients with multiple surgeries were examined in terms of their pathology: three of the 13 patients had no pathology Modern Pathology (2013) 26, 1051–1058

on the first surgery, but focal cortical dysplasia was pathologically identified on the second surgery. Similarly, false localization could explain the pathological findings in patients with gliosis or noidentifiable pathology who were not seizure-free in this study. It is even more intriguing to speculate on the four patients who became seizure-free, but had no-identifiable pathology. Notably, with three of these four patients, resected tissue was totally submitted and examined. A number of possible explanations may include: evolving pathology due to neural plasticity and ongoing development of cortex38,39 (given we could only sample surgically at one point of time), alterations at a neurotransmitter and/or neuromodulator level, mitochondrial level,40 genetics level,41,42 or neurogenesis level.43,44 One limitation of our study is the subtotal sampling of some specimens, which potentially could result in an underestimation of the epileptic pathologies. Another limitation is that we evaluated the relationship between pathology and outcome without the full consideration of the location and extent of resection. Patients who showed nonspecific gliosis or no-identifiable pathology may have focal cortical dysplasia pathology in an unresected lobe of the brain. In conclusion, our study highlights the heterogeneity of epileptic pathologies in MRI-negative epilepsies, with focal cortical dysplasia being the most common finding. The existence of positive pathology in surgical specimen may be a good indication for short-term good seizure outcome, but does not necessarily predict long-term seizure freedom. The subset of patients without any pathological findings is intriguing, and may indicate limitations of microscopic histopathological examination of resected human epileptic tissue, mislocalization/ inadequate resection, or incomplete histopathological sampling of the resected specimens. Advanced imaging and neurophysiological modalities, invasive or noninvasive, are called for to adequately delineate the anatomical, functional, and epileptic extent of these lesions.

Acknowledgements Financial support of this project is provided by the Cleveland Clinic Epilepsy Center.

Disclosure/conflict of interest Andreas V Alexopoulos serves on the editorial board of Epileptic Disorders, and has received research support from UCB, Pfizer Inc, and from the American Epilepsy Society. Imad M Najm is on the Speakers’ Bureau of UCB Inc and receives research funding from the US Department of Defense. The remaining authors declare no conflict of interest.

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19 Blu¨mcke I, Thom M, Aronica E, et al. The clinicopathologic spectrum of focal cortical dysplasias: a consensus classification proposed by an ad hoc Task Force of the ILAE Diagnostic Methods Commission. Epilepsia 2011;52:158–174. 20 Palmini A, Najm I, Avanzini G, et al. Terminology and classification of the cortical dysplasias. Neurology 2004;62:S2–S8. 21 Blu¨mcke I, Pauli E, Clusmann H, et al. A new clinicopathological classification system for mesial temporal sclerosis. Acta Neuropathol 2007;113:235–244. 22 Prayson RA. Diagnostic challenges in the evaluation of chronic epilepsy-related surgical neuropathology. Am J Surg Pathol 2010;34:e1–13. 23 Engel JJ, Van NP, Rasmussen TB, et al. Outcome with respect to epileptic seizures. In: Engel JJ (ed). Surgical Treatment of the Epilepsies. Raven Press: New York, NY, USA, 1993. 24 Ansari SF, Maher CO, Tubbs RS, et al. Surgery for extratemporal nonlesional epilepsy in children: a meta-analysis. Childs Nerv Syst 2010;26:945–951. 25 Ansari SF, Tubbs RS, Terry CL, et al. Surgery for extratemporal nonlesional epilepsy in adults: an outcome meta-analysis. Acta Neurochir (Wien) 2010;152: 1299–1305. 26 Widdess-Walsh P, Kellinghaus C, Jeha L, et al. Electroclinical and imaging characteristics of focal cortical dysplasia: correlation with pathological subtypes. Epilepsy Res 2005;67:25–33. 27 Wyllie E, Comair YG, Kotagal P, et al. Seizure outcome after epilepsy surgery in children and adolescents. Ann Neurol 1998;44:740–748. 28 Krsek P, Maton B, Korman B, et al. Different features of histopathological subtypes of pediatric focal cortical dysplasia. Ann Neurol 2008;63:758–769. 29 Krsek P, Pieper T, Karlmeier A, et al. Different presurgical characteristics and seizure outcomes in children with focal cortical dysplasia type I or II. Epilepsia 2009;50:125–137. 30 Widdess-Walsh P, Diehl B, Najm I. Neuroimaging of focal cortical dysplasia. J Neuroimaging 2006;16: 185–196. 31 Rosenow F, Luders H. Presurgical evaluation of epilepsy. Brain 2001;124:1683–1700. 32 Najm IM, Ying Z, Babb T, et al. Epileptogenicity correlated with increased N-methyl-D-aspartate receptor subunit NR2A/B in human focal cortical dysplasia. Epilepsia 2000;41:971–976. 33 Smith AP, Sani S, Kanner AM, et al. Medically intractable temporal lobe epilepsy in patients with normal MRI: surgical outcome in twenty-one consecutive patients. Seizure 2011;20:475–479. 34 Jeha LE, Morris HH, Burgess RC. Coexistence of focal and idiopathic generalized epilepsy in the same patient population. Seizure 2006;15:28–34. 35 Bulacio JC, Jehi L, Wong C, et al. Long-term seizure outcome after resective surgery in patients evaluated with intracranial electrodes. Epilepsia 2012;53:1722–1730. 36 Jehi L, Sarkis R, Bingaman W, et al. When is a postoperative seizure equivalent to ‘epilepsy recurrence’ after epilepsy surgery? Epilepsia 2010;51:994–1003. 37 Cruz VB, Prayson RA. Neuropathology in patients with multiple surgeries for medically intractable epilepsy. Ann Diagn Pathol 2012;16:447–453. 38 Leite JP, Neder L, Arisi GM, et al. Plasticity, synaptic strength, and epilepsy: what can we learn from ultrastructural data? Epilepsia 2005;46(Suppl 5):134–141. Modern Pathology (2013) 26, 1051–1058

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doi:10.1038/nature12439

De novo mutations in epileptic encephalopathies Epi4K Consortium* & Epilepsy Phenome/Genome Project*

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown1. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n 5 149) and Lennox–Gastaut syndrome (n 5 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the 4,000 genes that are the most intolerant to functional genetic variation in the human population (P 5 2.9 3 1023). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P 5 4.1 3 10210 and P 5 7.8 3 10212, respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P , 1028), as has been reported previously for autism spectrum disorders2. Genetics is believed to have an important role in many epilepsy syndromes; however, specific genes have been discovered in only a small proportion of cases. Genome-wide association studies for both focal and generalized epilepsies have revealed few significant associations, and rare copy number variants explain only a few per cent of cases3–6. An emerging paradigm in neuropsychiatric disorders is the major impact that de novo mutations have on disease risk7,8. We searched for de novo mutations associated with epileptic encephalopathies, a heterogeneous group of severe epilepsy disorders characterized by early onset of seizures with cognitive and behavioural features associated with ongoing epileptic activity. We focused on two ‘classical’ forms of epileptic encephalopathies: infantile spasms and Lennox– Gastaut syndrome, recognizing that some patients with infantile spasms progress to Lennox–Gastaut syndrome. Exome sequencing of 264 trios (Methods) identified 439 putative de novo mutations. Sanger sequencing confirmed 329 de novo mutations (Supplementary Table 2), and the remainder were either false positives, a result of B-cell immortalization, or in regions where the Sanger assays did not work (Supplementary Table 3). Across our 264 trios, we found nine genes with de novo single nucleotide variant (SNV) mutations in two or more probands (SCN1A, n 5 7; STXBP1, n 5 5; GABRB3, n 5 4; CDKL5, n 5 3; SCN8A, n 5 2; SCN2A, n 5 2; ALG13, n 5 2; DNM1, n 5 2; and HDAC4, n 5 2). Of these, SCN1A, STXBP1, SCN8A, SCN2A and CDKL5 are genes that have a previously established association with epileptic encephalopathy9–14. To assess whether the observations in the other genes implicate them as risk factors for epileptic encephalopathies, we determined the probability of seeing multiple mutations in the same gene given the sequencespecific mutation rate, size of the gene, and the number and gender of patients evaluated in this study (Methods). The number of observed de novo mutations in HDAC4 and DNM1 are not yet significantly greater than the null expectation. However, observing four unique de novo mutations in GABRB3 and two identical de novo mutations in ALG13

were found to be highly improbable (Table 1 and Fig. 1). We performed the same calculations on all of the genes with multiple de novo mutations observed in 610 control trios and found no genes with a significant excess of de novo mutations (Supplementary Table 4). Although mutations in GABRB3 have previously been reported in association with another type of epilepsy15, and in vivo mouse studies suggest that GABRB3 haploinsufficiency is one of the causes of epilepsy in Angelman’s syndrome16, our observations implicate it, for the first time, as a single-gene cause of epileptic encephalopathies and provide the strongest evidence to date for its association with any epilepsy. Likewise, ALG13, an X-linked gene encoding a subunit of the uridine diphosphate-N-acetylglucosamine transferase, was previously shown to carry a novel de novo mutation in a male patient with a severe congenital glycosylation disorder with microcephaly, seizures and early lethality17. Furthermore, the same ALG13 de novo mutation identified in this study was observed as a de novo mutation in an additional female patient with severe intellectual disability and seizures18. Each trio harboured on average 1.25 confirmed de novo mutations, with 181 probands harbouring at least one. Considering only de novo SNVs, each trio harboured on average 1.17 de novo mutations (Supplementary Fig. 1). Seventy-two per cent of the confirmed de novo SNV mutations were missense and 7.5% were putative loss-of-function (splice donor, splice acceptor, or stop-gain mutations). Compared to rates of these classes of mutations previously reported in controls (69.4% missense and 4.2% putative loss-of-function mutations)2,19,20, we observed a significant excess of loss-of-function mutations in patients with infantile spasms and Lennox–Gastaut syndrome (exact binomial P 5 0.01), consistent with data previously reported in autism spectrum disorder2,8,19,20. A framework was recently established for testing whether the distribution of de novo mutations in affected individuals differs from the general population8. Here, we extend the simulation-based approach of ref. 8 by developing a likelihood model that characterizes this effect and describes the distribution of de novo mutations among affected individuals in terms of the distribution in the general population, and a set of parameters describing the genetic architecture of the disease. These parameters include the proportion of the exome sequence that can carry disease-influencing mutations (g) and the relative risk (c) of the mutations (Supplementary Methods). Consistent with what was reported in autism spectrum disorder8, we found no significant deviation in the overall distribution of mutations from expected (c 5 1 and/or g 5 0). It is, however, now well established that some genes tolerate protein-disrupting mutations without apparent adverse phenotypic consequences, whereas others do not21. To take this into account, we used a simple scoring system that uses polymorphism data in the human population to assign a tolerance score to every considered gene (Methods). We then found that genes with a known association with epileptic encephalopathy rank among the most intolerant genes using this scheme (Supplementary Table 8). We therefore evaluated the distribution of de novo mutations within these 4,264 genes that are within the 25th percentile for intolerance and found a significant shift from the null distribution (P 5 2.9 3 1023). The maximum likelihood estimates of g (percentage of intolerant genes involved in epileptic encephalopathies) was 0.021 and c (relative risk) was 81, indicating that there are 90 genes among the intolerant genes

*A list of authors and affiliations appears at the end of the paper. 1 2 S E P T E M B E R 2 0 1 3 | VO L 5 0 1 | N AT U R E | 2 1 7

RESEARCH LETTER Table 1 | Probability of observing the reported number of de novo mutations by chance in genes recurrently mutated in this cohort Gene

Chromosome

Average effectively captured length (bp)

Weighted mutation rate

De novo mutation number

SCN1A STXBP1 GABRB3 CDKL5 ALG131 DNM1 HDAC4 SCN2A1 SCN8A

2 9 15 X X 9 2 2 12

6,063.70 1,917.51 1,206.86 2,798.38 475.05 2,323.37 2,649.82 5,831.21 5,814.48

1.61 3 1024 6.44 3 1025 3.78 3 1025 5.44 3 1025 1.03 3 1025 9.10 3 1025 1.16 3 1024 1.52 3 1024 1.64 3 1024

5{ 5 4 3 2 2 2 2 2

P value{

1.12 3 1029 1.16 3 10211 4.11 3 10210 4.90 3 1027 7.77 3 10212 2.84 3 1024 4.57 3 1024 1.14 3 1029 9.14 3 1024

*** *** *** ** ***

***

{ Adjusted a is equivalent to 0.05/18,091 5 2.76 3 1026 (*), 0.01/18,091 5 5.53 3 1027 (**) and 0.001/18,091 5 5.53 3 1028 (***). { Counts exclude three additional patients with an indel or splice site mutation as these are not accounted for in the mutability calculation. 1 Two de novo mutations occur at the same position. The probability of these special cases obtain P 5 7.77 3 10212 and P 5 1.14 3 1029 for ALG13 and SCN2A, respectively (Methods).

STXBP1 GABRB3

3 2

SCN1A 15

CDKL5 ALG13

DNM1 HDAC4

SCN8A SCN2A

1 0.00000

–log10(P value)

De novo mutation count within gene

that can confer risk of epileptic encephalopathies and that each mutation carries substantial risk. We also found that putatively damaging de novo variants in our cohort are significantly enriched in intolerant genes compared with control cohorts (Supplementary Methods). We next evaluated whether the de novo mutations were drawn preferentially from six gene sets (Methods and Supplementary Table 10), including ion channels22, genes known to cause monogenic disorders with seizures as a phenotypic feature23, genes carrying confirmed de novo mutations in patients with autism spectrum disorder2,8,19,20 and in patients with intellectual disability18,24, and FMRP-regulated genes. Taking into account the size of regions with adequate sequencing coverage to detect a de novo mutation (Methods), we found significant overrepresentation for all gene lists in our data (Supplementary Table 10), and no over-representation in controls2,19,20,24. To determine possible interconnectivity among the genes carrying a de novo mutation, we performed a protein–protein interaction analysis and identified a single network of 71 connected proteins (Fig. 2 and Supplementary Fig. 7). These 71 proteins include six encoded by OMIM reported epileptic encephalopathy genes (http://www.omim. org/) where we identified one or more de novo mutations among the epileptic encephalopathy patients in this study. Genes in this protein– protein network were also found to have a much greater probability of overlap with the autism spectrum disorder2,8,19,20 and severe intellectual disability disorder18,24 exome sequencing study genes, and with FMRPassociated genes, than genes not in this network (Supplementary Table 11). In support of a hypothesis that individual rare mutations in different genes may converge on biological pathways, we draw attention to six mutations that all affect subunits of the GABA (c-aminobutyric acid) ionotropic receptor (four in GABRB3, and one each in GABRA1 and

0 0.00005

0.00010

0.00015

0.00020

Effective gene mutation rate (sum of site-specific rates across length of gene)

Figure 1 | Heat map illustrating the probability of observing the specified number of de novo mutations in genes with the specified estimated mutation rate. The number of de novo mutations required to achieve significance is indicated by the solid red line. The superimposed dots reflect positions of all genes found to harbour multiple de novo mutations in our study. GABRB3, SCN1A, CDKL5 and STXBP1 have significantly more de novo mutations than expected. The positions indicated for ALG13 and SCN2A reflect only the fact that there are two mutations observed, not that there are two mutations affecting the same site (Methods).

GABRB1), and highlight two interactions: HNRNPU interacting with HNRNPH1, and NEDD4L (identified here) binding to TNK2, a gene previously implicated in epileptic encephalopathies25 (Fig. 2). Although the HNRNPU mutation observed here is a small insertion/deletion variant (indel) in a splice acceptor site, and therefore probably results in a modified protein, the HNRNPH1 de novo mutation is synonymous and thus of unknown functional significance (Supplementary Table 2). Notably, a minigene experiment indicates that this synonymous mutation induces skipping of exon 12 (Supplementary Methods). Evaluation of the clinical phenotypes among patients revealed significant genetic heterogeneity underlying infantile spasms and Lennox– Gastaut syndrome, and begins to provide information about the range of phenotypes associated with mutations in specific genes (Supplementary Table 13). We identified four genes—SCN8A, STXBP1, DNM1 and GABRB3—with de novo mutations in both patients with infantile spasms and patients with Lennox–Gastaut syndrome. Although infantile spasms may progress to Lennox–Gastaut syndrome, in three of these cases the patients with Lennox–Gastaut syndrome did not initially present with infantile spasms, indicating phenotypic heterogeneity associated with mutations in these genes yet supporting the notion of shared genetic susceptibility. Notably, in multiple patients we identified de novo mutations in genes previously implicated in other neurodevelopmental conditions, and in some cases with very distinctive clinical presentations (Supplementary Table 12). Most notably, we found a de novo mutation in MTOR, a gene recently found to harbour a causal variant in mosaic form in a case with hemimegalencephaly26. Our patient however showed no detectable structural brain malformation. Similarly, we found one patient with a de novo mutation in DCX and another with a de novo mutation in FLNA, previously associated with lissencephaly and periventricular nodular heterotopia, respectively27,28; neither patient had cortical malformations detected on magnetic resonance imaging. In addition to de novo variants, we also screened for highly penetrant genotypes by identifying variants that create newly homozygous, compound heterozygous, or hemizygous genotypes in the probands that are not seen in parents or controls (Supplementary Methods). No inherited variants showed significant evidence of association. Additional studies evaluating a larger number of epileptic encephalopathy patients will be required to establish the role of inherited variants in the disease risk associated with infantile spasms and Lennox–Gastaut syndrome. We have identified novel de novo mutations implicating at least two genes for epileptic encephalopathies, and also describe a genetic architecture that strongly suggests that we have identified additional causal mutations in genes intolerant to functional variation. Given that our sample size already shows many genes with recurrent mutations, it is clear that even modest increases in sample sizes will confirm many new genes now seen in only one of our trios. Our results also emphasize that it may be difficult to predict with confidence the responsible gene, even among known genes, based upon clinical presentation. This makes it clear that the future of genetic diagnostics in epileptic encephalopathies will need to focus on the genome as a whole as opposed to single genes or even gene panels. In particular, several of the genes with de novo mutations in our cohort have also been identified in patients with

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Figure 2 | A protein–protein interaction network of genes with de novo mutations found in infantile spasms and Lennox–Gastaut syndrome patients studied. The geometric shapes reflect differing protein roles, as defined by ingenuity pathway analysis (Ingenuity Systems): enzyme, rhombus; ion channel, vertical rectangle; kinase, inverted triangle; liganddependent nuclear receptor, horizontal rectangle; phosphatase, triangle; transcription regulator, horizontal oval; transmembrane receptor, vertical oval; transporter, trapezoid; and unknown, circle. Six of the genes found to harbour

de novo mutations in an infantile spasms or Lennox–Gastaut syndrome patient are known OMIM genes associated with epileptic encephalopathy (shaded circles). Five additional known OMIM genes associated with epileptic encephalopathy that were not found to be mutated in the 264 epileptic encephalopathy patients, but are involved in this network, are also shown (shaded circles with the gene underlined). The previously identified severe infantile epilepsy gene TNK2 is superimposed into this network (red circle).

intellectual disability or autism spectrum disorder. Finally, and perhaps most importantly, this work suggests a clear direction for both drug development and treatment personalization in the epileptic encephalopathies, as many of these mutations seem to converge on specific biological pathways.

inspection of alignment quality. Candidate de novo mutations were confirmed to be de novo mutations using Sanger sequencing. In all cases, primary DNA from the proband was used for the Sanger confirmation so that mutations appearing in the transformation process for the 40 trios sequenced from LCLs would be eliminated. To determine whether our list of de novo mutations was preferentially located in genes contained in the six gene lists we calculated the proportion of CCDS de novo mutation opportunity space for each list (Additional Methods). A binomial probability calculation was used to determine whether the de novo mutations in CCDS transcripts identified in this cohort of epileptic encephalopathy patients were selectively enriched within the coding sequence of genes within a particular gene list (Supplementary Table 10). Ingenuity Pathway Analysis (Ingenuity Systems) was used to assess the connectivity of proteins harbouring a de novo mutation.

METHODS SUMMARY All probands and family members were collected as part of the Epilepsy Phenome/ Genome Project (EPGP) cohort29 (Supplementary Table 1). Detailed inclusion and exclusion criteria are provided in Methods. Patient collection and sharing of specimens for research were approved by site-specific Institutional Review Boards. We sequenced the exome of each trio, from DNA derived from primary cells (n 5 224 trios) or from lymphoblastoid cell lines (LCLs) in one or more family members (n 5 40 trios), using the TruSeq Exome Enrichment kit (Illumina). We aligned samples and called variants using established algorithms (Methods) and identified candidate de novo variants at sites included in the exons or splice sites of the consensus coding sequence (CCDS) as those called in the affected child and absent in both parents, despite each parent having at least tenfold coverage at the site. Variants created by the de novo mutation also had to be absent in our internal controls (n 5 436), as well as the approximately 6,500 samples represented in the Exome Variant Server (http://evs.gs.washington.edu/EVS), and had to pass visual

Full Methods and any associated references are available in the online version of the paper. Received 3 March; accepted 9 July 2013. Published online 11 August 2013. 1.

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Supplementary Information is available in the online version of the paper. Acknowledgements We are grateful to the patients, their families, clinical research coordinators and referring physicians for participating in the Epilepsy Phenome/ Genome Project (EPGP) and providing the phenotype data and DNA samples used in this study. We thank the following professional and lay organizations for substantial assistance in publicizing EPGP and therefore enabling us to recruit participants effectively: AED Pregnancy Registry, American Epilepsy Society, Association of Child Neurology Nurses, California School Nurses Organization, Child Neurology Society, Citizens United for Research in Epilepsy, Dravet Syndrome Foundation, Epilepsy Alliance of Orange County, Epilepsy Foundation, Epilepsy Therapy Project, Finding a Cure for Epilepsy and Seizures, IDEA League, InfantileSpasms.com, Lennox-Gastaut Syndrome Foundation, PatientsLikeMe, People Against Childhood Epilepsy, PVNH Support & Awareness, and Seizures & Epilepsy Education. We thank the EPGP Administrative Core (C. Freyer, K. Schardein, R.N., M.S., R. Fahlstrom, M.P.H., S. Cristofaro, R.N., B.S.N. and K. McGovern), EPGP Bioinformatics Core (G. Nesbitt, K. McKenna, V. Mays), staff at the Coriell Institute – NINDS Genetics Repository (C. Tarn, A. Scutti), and members of the Duke Center for Human Genome Variation (B. Krueger, J. Bridgers, J. Keebler, H. Shin Kim, E. Campbell, K. Cronin, L. Hong and M. McCall) for their dedication and commitment to this work. We also thank S. Shinnar (Albert Einstein College of Medicine) and N. Risch (University of California, San Francisco) for valuable

input into the creation of EPGP and Epi4K, and R. Stewart, K. Gwinn and R. Corriveau from the National Institute of Neurological Disorders and Stroke for their careful oversight and guidance of both EPGP and Epi4K. This work was supported by grants from the National Institute of Neurological Disorders and Stroke (The Epilepsy Phenome/Genome Project NS053998; Epi4K Project 1—Epileptic Encephalopathies NS077364; Epi4K—Administrative Core NS077274; Epi4K—Sequencing, Biostatistics and Bioinformatics Core NS077303 and Epi4K—Phenotyping and Clinical Informatics Core NS077276); Finding a Cure for Epilepsy and Seizures; and the Richard Thalheimer Philanthropic Fund. We would like to acknowledge the following individuals and groups for their contribution of control samples: J. Hoover-Fong, N. Sobreira and D. Valle; The MURDOCK Study Community Registry and Biorepository (D. Murdock); S. Sisodiya; D. Attix; O. Chiba-Falek; V. Shashi; P. Lugar; W. Lowe; S. Palmer; D. Marchuk; Z. Farfel, D. Lancet, E. Pras; Q. Zhao; D. Daskalakis; R. Brown; E. Holtzman; R. Gbadegesin; M. Winn; S. Kerns; and H. Oster. The collection of control samples was funded in part by ARRA 1RC2NS070342, NIAID R56AI098588, the Ellison Medical Foundation New Scholar award AG-NS-0441-08, an award from SAID-Frederick, Inc. (M11-074), and with federal funds by the Center for HIV/AIDS Vaccine Immunology ("CHAVI") under a grant from the National Institute of Allergy and Infectious Diseases, National Institutes of Health (UO1AIO67854). Author contributions Initial design of EPGP: B.K.A., O.D., D.D., M.P.E., R.Kuz., D.H.L., R.O., E.H.S. and M.R.W. EPGP patient recruitment and phenotyping: B.A.-K., J.F.B., S.F.B., G.C., D.C., P.Cr., O.D., D.D., M.F., N.B.F., D.F., E.B.G., T.G., S.G., S.R.H., J.H., S.L.H., H.E.K., R.C.K., E.H.K., R.Kup., R.Kuz., D.H.L., S.M.M., P.V.M., E.J.N., J.M.Pao., J.M.Par., K.P., A.P., I.E.S., J.J.S., R.S., J.Si., M.C.S., L.L.T., A.V., E.P.G.V., G.K.V.A., J.L.W. and P.W.-W. Phenotype data analysis: B.A.-K., B.K.A., A.B., G.C., O.D., D.D., J.F., T.G., S.J., A.K., R.C.K., R.Kuz., D.H.L., R.O., J.M.Pao., A.P., I.E.S., R.A.S., E.H.S., J.J.S., J.Su., P.W.-W. and M.R.W. Initial design of Epi4K: S.F.B., P.Co., N.D., D.D., E.E.E., M.P.E., T.G., D.B.G., E.L.H., M.R.J., R.Kuz., D.H.L., A.G.M., H.C.M., T.J.O., R.O., A.P., I.E.S. and E.H.S. Epileptic encephalopathy phenotyping strategy: S.F.B., P.Co., D.D., R.Kuz., D.H.L., R.O., I.E.S. and E.H.S. Encephalopathy phenotyping: D.D., K.B.H., M.R.Z.M., H.C.M., A.P., I.E.S., E.H.S. and C.J.Y. Sequence data analysis and statistical interpretation: A.S.A., D.B.G., Y.Ha., E.L.H., S.E.N., S.P., E.K.R. and E.H.S. Functional evaluation of identified mutations: D.B.G., E.L.H., Y.Hi. and Y.-F.L. Writing of manuscript: A.S.A., S.F.B., D.D., D.B.G., Y.Ha., E.L.H., M.R.J., D.H.L., H.C.M., R.O., A.P., S.P., E.K.R., I.E.S. and E.H.S. Author Information Exome sequence data will be available in dbGAP (Epi4K: Gene Discovery in 4,000 Epilepsy Genomes). Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Correspondence and requests for materials should be addressed to Epi4K (epi4k@duke.edu).

Epi4K Consortium Andrew S. Allen1, Samuel F. Berkovic2, Patrick Cossette3, Norman Delanty4, Dennis Dlugos5, Evan E. Eichler6, Michael P. Epstein7, Tracy Glauser8, David B. Goldstein9, Yujun Han9, Erin L. Heinzen9, Yuki Hitomi9, Katherine B. Howell10, Michael R. Johnson11, Ruben Kuzniecky12, Daniel H. Lowenstein13, Yi-Fan Lu9, Maura R. Z. Madou13, Anthony G. Marson14, Heather C. Mefford15, Sahar Esmaeeli Nieh16, Terence J. O’Brien17, Ruth Ottman18, Slave´ Petrovski2,9,17, Annapurna Poduri19, Elizabeth K. Ruzzo9, Ingrid E. Scheffer20,21, Elliott H. Sherr22 & Christopher J. Yuskaitis23 Epilepsy Phenome/Genome Project Bassel Abou-Khalil24, Brian K. Alldredge25, Jocelyn F. Bautista26, Samuel F. Berkovic2, Alex Boro27, Gregory D. Cascino28, Damian Consalvo29, Patricia Crumrine30, Orrin Devinsky31, Dennis Dlugos5, Michael P. Epstein7, Miguel Fiol32, Nathan B. Fountain33, Jacqueline French12, Daniel Friedman12, Eric B. Geller34, Tracy Glauser8, Simon Glynn35, Sheryl R. Haut36, Jean Hayward37, Sandra L. Helmers38, Sucheta Joshi39, Andres Kanner40, Heidi E. Kirsch13,41, Robert C. Knowlton42, Eric H. Kossoff43, Rachel Kuperman44, Ruben Kuzniecky12, Daniel H. Lowenstein13, Shannon M. McGuire45, Paul V. Motika46, Edward J. Novotny47, Ruth Ottman18, Juliann M. Paolicchi24,48, Jack M. Parent49,50, Kristen Park51, Annapurna Poduri19, Ingrid E. Scheffer20,21, Rene´e A. Shellhaas52, Elliott H. Sherr22, Jerry J. Shih53, Rani Singh54, Joseph Sirven55, Michael C. Smith40, Joseph Sullivan13, Liu Lin Thio56, Anu Venkat5, Eileen P. G. Vining57, Gretchen K. Von Allmen58, Judith L. Weisenberg59, Peter Widdess-Walsh34 & Melodie R. Winawer60 1

Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, and Center for Human Genome Variation, Duke University Medical Center, Durham, North Carolina 27710, USA. 2Epilepsy Research Centre, Department of Medicine, University of Melbourne (Austin Health), Heidelberg, Victoria 3084, Australia. 3Centre of Excellence in Neuromics and CHUM Research Center, Universite´ de Montre´al, CHUM-Hoˆpital Notre-Dame Montre´al, Quebec H2L 4M1, Canada. 4Department of Neurology, Beaumont Hospital and Royal College of Surgeons, Dublin 9, Ireland. 5Department of Neurology and Pediatrics, The Children’s Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA. 6Department of Genome Sciences, University of Washington School of Medicine, Seattle, and Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA. 7 Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia 30322, USA. 8Division of Neurology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229, USA. 9Center for Human Genome Variation, Duke University School of Medicine, Durham, North Carolina 27708, USA. 10Department of Neurology,

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LETTER RESEARCH The Royal Children’s Hospital Melbourne , Parkville, 3052 Victoria, Australia. 11Centre for Clinical Translation Division of Brain Sciences, Imperial College London, London SW7 2AZ, UK. 12Comprehensive Epilepsy Center, Department of Neurology, NYU School of Medicine, New York, New York 10016, USA. 13Department of Neurology, University of California, San Francisco, San Francisco, California 94143, USA. 14Department of Molecular and Clinical Pharmacology, University of Liverpool, Clinical Sciences Centre, Lower Lane, Liverpool L9 7LJ, UK. 15Department of Pediatrics, Division of Genetic Medicine, University of Washington, Seattle, Washington 98115, USA. 16University of California, San Francisco, California 94143, USA. 17Departments of Medicine and Neurology, The Royal Melbourne Hospital, Parkville, Victoria 3146, Australia. 18 Departments of Epidemiology and Neurology, and the G. H. Sergievsky Center, Columbia University; and Division of Epidemiology, New York State Psychiatric Institute, New York, New York 10032, USA. 19Division of Epilepsy and Clinical Neurophysiology, Department of Neurology Boston Children’s Hospital, Boston, Massachusetts 02115, USA. 20Epilepsy Research Centre, Department of Medicine, University of Melbourne (Austin Health), Heidelberg, Victoria 3084, Australia. 21Florey Institute and Department of Pediatrics, Royal Children’s Hospital, University of Melbourne, Victoria 3052, Australia. 22 Departments of Neurology, Pediatrics and Institute of Human Genetics, University of California, San Francisco, San Francisco, California 94158, USA. 23Department of Neurology, Boston Children’s Hospital Harvard Medical School, Boston, Massachusetts 02115, USA. 24Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA. 25Department of Clinical Pharmacy, UCSF School of Pharmacy, Department of Neurology, UCSF School of Medicine, San Francisco, California 94143, USA. 26Department of Neurology, Cleveland Clinic Lerner College of Medicine & Epilepsy Center of the Cleveland Clinic Neurological Institute, Cleveland, Ohio 44195, USA. 27 Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York 10467, USA. 28Divison of Epilepsy, Mayo Clinic, Rochester, Minnesota 55905, USA. 29Epilepsy Center, Neurology Division, Ramos Mejı´a Hospital, Buenos Aires 1221, Argentina. 30Medical Epilepsy Program & EEG & Child Neurology, Children’s Hospital of Pittsburgh of UPMC, Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224, USA. 31NYU and Saint Barnabas Epilepsy Centers, NYU School of Medicine, New York, New York 10016, USA. 32Department of Neurology, Epilepsy Care Center, University of Minnesota Medical School, Minneapolis 55414, USA. 33FE Dreifuss Comprehensive Epilepsy Program, University of Virginia,

Charlottesville, Virginia 22908, USA. 34Division of Neurology, Saint Barnabas Medical Center, Livingston, New Jersey 07039, USA. 35Department of Neurology, Comprehensive Epilepsy Program, University of Michigan Health System, Ann Arbor, Michigan 48109, USA. 36Comprehensive Epilepsy Center, Montefiore Medical Center, Bronx, New York 10467, USA. 37The Kaiser Permanente Group, Oakland, California 94618, USA. 38 Neurology and Pediatrics, Emory University School of Medicine, Atlanta, Georgia 30322, USA. 39Pediatrics & Communicable Diseases, University of Michigan, Ann Arbor, Michigan 48109, USA. 40Department of Neurological Sciences, Rush Epilepsy Center, Rush University Medical Center, Chicago, Illinois 60612, USA. 41Department of Radiology, University of California, San Francisco, California 94143, USA. 42Neurology, University of Texas Medical School, Houston, Texas 77030, USA. 43Neurology and Pediatrics, Child Neurology, Pediatric Neurology Residency Program, Johns Hopkins Hospital, Baltimore, Maryland 21287, USA. 44Epilepsy Program, Children’s Hospital & Research Center Oakland, Oakland, California 94609, USA. 45Clinical Neurology, Children’s Hospital Epilepsy Center of New Orleans, New Orleans, Louisiana 70118, USA. 46Comprehensive Epilepsy Center, Oregon Health and Science University, Portland, Oregon 97239, USA. 47 Departments of Neurology and Pediatrics, University of Washington School of Medicine, Seattle Children’s Hospital, Seattle, Washington 98105, USA. 48Weill Cornell Medical Center, New York, New York 10065, USA. 49Department of Neurology and Neuroscience Graduate Program, University of Michigan Medical Center, Ann Arbor, Michigan 49108, USA. 50Ann Arbor Veterans Administration Healthcare System, Ann Arbor, Michigan 48105, USA. 51Departments of Neurology and Pediatrics, University of Colorado School of Medicine, Children’s Hospital Colorado, Denver, Colorado 80045, USA. 52University of Michigan, Pediatric Neurology, Ann Arbor, Michigan 48109, USA. 53Department of Neurology, Mayo Clinic, Jacksonville, Florida 32224, USA. 54Division of Pediatric Neurology, University of Michigan Health System, Ann Arbor, Michigan 48109, USA. 55 Department of Neurology, Mayo Clinic, Scottsdale, Arizona 85259, USA. 56Department of Neurology, Washington University School of Medicine, St Louis, Missouri 63110, USA. 57 Department of Neurology, Johns Hopkins Hospital, Baltimore, Maryland 21287, USA. 58 Division of Child & Adolescent Neurology, Departments of Pediatrics, University of Texas Medical School, Houston, Texas 77030, USA. 59Department of Neurology, Division of Pediatric Neurology, Washington University School of Medicine, St Louis, Missouri 63110, USA. 60Department of Neurology and the G.H. Sergievsky Center, Columbia University, New York, New York 10032, USA.

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RESEARCH LETTER METHODS Study subjects. Infantile spasms and Lennox–Gastaut syndrome patients evaluated in this study were collected through the Epilepsy Phenome/Genome Project (EPGP, http://www.epgp.org)29. Patients were enrolled across 23 clinical sites. Informed consent was obtained for all patients in accordance with the site-specific Institutional Review Boards. Phenotypic information has been centrally databased and DNA specimens stored at the Coriell Institute–NINDS Genetics Repository (Supplementary Table 1). Infantile spasms patients were required to have hypsarrhythmia or a hypsarrhythmia variant on EEG. Lennox–Gastaut syndrome patients were required to have EEG background slowing or disorganization for age and generalized spike and wave activity of any frequency or generalized paroxysmal fast activity (GPFA). Background slowing was defined as ,8 Hz posterior dominant rhythm in patients over 3 years of age, and ,5 Hz in patients over 2 years of age. EEGs with normal backgrounds were accepted if the generalized spike and wave activity was 2.5 Hz or less and/or if GPFA was present. All patients were required to have no evidence of moderate-to-severe developmental impairment or diagnosis of autistic disorder or pervasive developmental disorder before the onset of seizures. Severe developmental delay was defined by 50% or more delay in any area: motor, social, language, cognition, or activities of living; or global delay. Mild delay was defined as delay of less than 50% of expected milestones in one area, or less than 30% of milestones across more than one area. All patients had no confirmed genetic or metabolic diagnosis, and no history of congenital TORCH infection, premature birth (before 32 weeks gestation), neonatal hypoxicischaemic encephalopathy or neonatal seizures, meningitis/encephalitis, stroke, intracranial haemorrhage, significant head trauma, or evidence of acquired epilepsy. All infantile spasms and Lennox–Gastaut syndrome patients had an MRI or CT scan interpreted as normal, mild diffuse atrophy or focal cortical dysplasia. (Our case with the mutation in HNRNPU had had a reportedly normal MRI but on review of past records, a second more detailed MRI was found showing small regions of periventricular nodular heterotopia.) To participate, both biological parents had to have no past medical history of seizures (except febrile or metabolic/toxic seizures). A final diagnosis form was completed by the local site EPGP principal investigator based on all collected information. A subset of cases was reviewed independently by two members of the EPGP Data Review Core to ensure data quality and consistency. All EEGs were reviewed by a site investigator and an EEG core member to assess data quality and EEG inclusion criteria. EEGs accepted for inclusion were then reviewed and scored by two EEG core members for specific EEG phenotypic features. Disagreements were resolved by consensus conference among two or more EEG core members before the EEG data set was finalized. MRI scans were reviewed by local investigators and an MRI core member to exclude an acquired symptomatic lesion. Exome-sequenced unrelated controls (n 5 436) used to ascertain mutation frequencies were sequenced in the Center for Human Genome Variation as part of other genetic studies. Exome sequencing, alignment and variant calling. Exome sequencing was carried out within the Genomic Analysis Facility in the Center for Human Genome Variation (Duke University). Sequencing libraries were prepared from primary DNA extracted from leukocytes of parents and probands using the Illumina TruSeq library preparation kit following the manufacturer’s protocol. Illumina TruSeq Exome Enrichment kit was used to selectively amplify the coding regions of the genome according to the manufacturer’s protocol. Six individual barcoded samples (two complete trios) were sequenced in parallel across two lanes of an Illumina HiSeq 2000 sequencer. Alignment of the sequenced DNA fragments to Human Reference Genome (NCBI Build 37) was performed using the Burrows–Wheeler Alignment Tool (BWA) (version 0.5.10). The reference sequence we use is identical to the 1000 Genomes Phase II reference and it consists of chromosomes 1–22, X, Y, MT, unplaced and unlocalized contigs, the human herpesvirus 4 type 1 (NC_007605), and decoy sequences (hs37d5) derived from HuRef, Human Bac and Fosmid clones and NA12878. After alignments were produced for each individual separately using BWA, candidate de novo variants were jointly called with the GATK Unified Genotyper for all family members in a trio. Loci bearing putative de novo mutations were extracted from the variant call format files (VCFs) that met the following criteria: (1) the read depth in both parents should be greater than or equal to 10; (2) the depth of coverage in the child should be at least one-tenth of the sum of the coverage in both parents; (3) for de novo variants, less than 5% of the reads in either parent should carry the alternate allele; (4) at least 25% of the reads in the child should carry the alternate allele; (5) the normalized, phred-scaled likelihood (PL) scores for the offspring genotypes AA, AB and BB, where A is the reference allele and B is the alternate allele, should be .20, 0 and .0, respectively; (6) the PL scores for both parents should be 0, .20 and .20; (7) at least three variant alleles must be observed in the proband; and (8) the de novo variant had to be located in a CCDS exon targeted by the exome enrichment kit. PL scores are assigned such that the most likely genotype is given a score of 0, and the score for the other two genotypes

represent the likelihood that they are not the true genotypes. SnpEff (version 3.0a) was used to annotate the variants according to Ensembl (version 69) and consensus coding sequencing (CCDS release 9, GRCh37.p5) and limited analyses to exonic or splice site (2 bp flanking an exon) mutations. All candidate de novo mutations that were absent from population controls, including a set of 436 internally sequenced controls and the ,6,500 individuals whose single nucleotide variant data are reported in the Exome Variant Server, NHLBI Exome Sequencing Project (http:// evs.gs.washington.edu/EVS/; August 2012) were also visually inspected using Integrative Genomics Viewer (IGV). All candidate de novo mutations were confirmed with Sanger sequencing of the relevant proband and parents. For comparison, we also called de novo variants from probands and parents individually for a subset of trios. Using this individual calling approach we identified and confirmed an additional 46 de novo mutations. These were included in all the downstream de novo mutation analyses. Calculation of gene-specific mutation rate. Point mutation rates were scaled to per base pair, per generation, based on the human genome sequences matrix30 (provided by S. Sunyaev and P. Polak), and the known human average genome de novo mutation rate (1.2 3 1028)31. The mutation rate (M) of each gene was calculated by adding up point mutation rates in effectively captured CCDS regions in the offspring of trios, and then dividing by the total trio number (S 5 264). The P value was calculated as [1 2 Poisson cumulative distribution function (x 2 1, l)], where x is the observed de novo mutation number for the gene, and l is calculated as 2SM for genes on autosome or (2f 1 m)M for genes on chromosome X (f and m are the number of sequenced female and male probands, respectively). Genes on Y chromosome were not part of these analyses. Two de novo mutations in gene ALG13 are at the same position, likewise in gene SCN2A. We calculated the probability of this special case as [1 2 Poisson cumulative distribution function (1, (2f 1 m)r)], where r reflects the point mutation rate on that specific de novo mutation position. Further investigations indicated that it is unlikely for these de novo mutations, which occur at the same site across distinct probands, to have been caused by sequencing or mapping errors (Supplementary Methods). Calculation of mutation tolerance for HGNC genes. To assign quantitatively a mutation tolerance score to genes in the human genome (HGNC genes), we calculated an empirical penalty based on the presence of common functional variation using the aggregate sequence data available from the 6,503 samples reported in the Exome Variant Server, NHLBI Exome Sequencing Project (http://evs.gs.washington. edu/EVS/; accessed August 2012). We first filtered within the EVS database and eliminated from further consideration genes where the number of tenfold average covered bases was less than 70% of its total extent. In calculating a score, we focused on departures from the average common functional variant frequency spectrum, corrected for the total mutation burden in a gene. We construct this score as follows. Let Y be the total number of common, minor allele frequency .0.1%, missense and nonsense (including splice) variants and let X be total number of variants (including synonymous) observed within a gene. We regress Y on X and take the studentized residual as the score (S). Thus, the raw residual is divided by an estimate of its standard deviation and thus account for differences in variability that comes with differing mutational burdens. S measures the departure from the average number of common functional mutations found in genes with a similar amount of mutational burden. Thus, when S 5 0 the gene has the average number of common functional variants given its total mutational burden. Genes where S , 0 have less common functionals than average for their mutational burden and thus, would seem to be less tolerant of functional mutation, indicating the presence of weak purifying selection. We further investigated how different ‘intolerance’ thresholds of S captured known epileptic encephalopathy genes (Supplementary Table 8). Supplementary Fig. 6 illustrates how different percentiles of S lead to the classification of different proportions of the known epileptic encephalopathy genes as ‘intolerant’. Note that ARX is not in these analyses as this gene did not meet a 70% of gene coverage threshold. The dashed vertical line in Supplementary Fig. 6 illustrates the 25th percentile of S and shows that using this threshold results in 12 out of the 14 assessed known genes being considered ‘intolerant’. On the basis of this analysis, we used this 25th percentile threshold in classifying genes as intolerant in all subsequent analyses. Supplementary Table 9 lists the 25th percentile of most intolerant genes that had Sanger confirmed de novo mutations among the infantile spasms/Lennox–Gastaut syndrome probands. Defining the CCDS opportunity space for detecting de novo mutations. For each trio, we defined callable exonic bases that had the opportunity for identification of a coding de novo mutation, by restricting to bases where each of the three family members had at least tenfold coverage, obtained a multi-sampling (GATK) raw phred-scaled confidence score of $20 in the presence or absence of a variant, and were within the consensus coding sequence (CCDS release 9, GRCh37.p5) or within the two base pairs at each end of exons to allow for splice acceptor and donor variants. Using these three criteria, the average CCDS-defined de novo mutation opportunity space across 264 trios was found to be 28.84 6 0.92 Mb (range of 25.46–30.25 Mb).

LETTER RESEARCH To explore at the gene level, we similarly assessed the de novo calling opportunity within any given trio for every gene with a CCDS transcript. For genes with instances of non-overlapping CCDS transcripts, we merged the corresponding regions into a consensus summary of all CCDS-defined bases for that gene. Using these criteria, over 85% of the CCDS-defined exonic regions were sequenced to at least tenfold coverage across the three family members in over 90% of trios. All 264 trios covered at least 79% of the CCDS-defined regions under the CCDS opportunity space criteria.

Calculations of CCDS opportunity space for calling a de novo mutation, aside from the Y chromosome, were used in both the gene-list enrichment and architecture calculations. 30. 31.

Kryukov, G. V., Pennacchio, L. A. & Sunyaev, S. R. Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am. J. Hum. Genet. 80, 727–739 (2007). Kong, A. et al. Rate of de novo mutations and the importance of father’s age to disease risk. Nature 488, 471–475 (2012).

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Mutations of DEPDC5 cause autosomal dominant focal epilepsies

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Saeko Ishida1,2, Fabienne Picard3, Gabrielle Rudolf4,5, Eric Noé1,2, Guillaume Achaz2,6,7, Pierre Thomas8, Pierre Genton9,10, Emeline Mundwiller11, Markus Wolff12, Christian Marescaux4, Richard Miles1,2, Michel Baulac1,2,13, Edouard Hirsch4, Eric Leguern1,2,14 & Stéphanie Baulac1,2 The main familial focal epilepsies are autosomal dominant nocturnal frontal lobe epilepsy, familial temporal lobe epilepsy and familial focal epilepsy with variable foci. A frameshift mutation in the DEPDC5 gene (encoding DEP domain–containing protein 5) was identified in a family with focal epilepsy with variable foci by linkage analysis and exome sequencing. Subsequent pyrosequencing of DEPDC5 in a cohort of 15 additional families with focal epilepsies identified 4 nonsense mutations and 1 missense mutation. Our findings provided evidence of frequent (37%) loss-of- function mutations in DEPDC5 associated with a broad spectrum of focal epilepsies. The implication of a DEP (Dishevelled, Egl-10 and Pleckstrin) domain–containing protein that may be involved in membrane trafficking and/or G protein signaling opens new avenues for research. Epilepsy is a frequent neurological disorder characterized by spontaneous, recurrent seizures. Focal epileptic seizures are thought to originate within networks limited to one hemisphere. Several autosomal dominant, non-lesional focal epilepsies have been described as specific age-related and electroclinical syndromes: autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE; MIM 600513)1, familial temporal lobe epilepsy (FTLE; MIM 600512)2, including mesial and lateral forms (also termed autosomal dominant epilepsy with auditory features (ADEAF; MIM 604619)3, and familial focal epilepsy with variable foci (FFEVF; MIM 604364), characterized by focal seizures that are initiated in distinct cortical regions in different family members4. The only gene mutations currently identified are those linked to ADNFLE (CHRNA4, CHRNA2, CHRNB2 and KCNT1, encoding, respectively, the α4, α2 and β2 subunits of the neuronal nicotinic acetylcholine receptor and a potassium channel subunit)5,6 and to ADEAF (LGI1, encoding epitempin)7. Although no causal genes have

yet been identified for FFEVF, linkage to 22q12 has been reported in several families4,8–11. We have previously described the electroclinical characteristics of 19 families with autosomal dominant focal epilepsies, subdivided into ADNFLE, FTLE and FFEVF12. Two large multiplex French families (N and S) with diagnosed FFEVF were selected from this cohort for linkage analysis using a high-density genome-wide scan with 10,000 SNPs. Both families mapped to the FFEVF-associated locus on chromosome 22q12, with maximum logarithm of odds (LOD) scores of 2.08 (family N) and 1.81 (family S). Haplotype reconstruction confirmed the segregation of a disease haplotype in both families (Supplementary Figs. 1 and 2). We then sequenced the entire exome of subjects N-III:4 and N-III:6 and sought rare coding variants in the 22q12 candidate region. In both individuals, we found the same single-base deletion, c.1122delA, in exon 16 of the DEPDC5 gene (also known as KIAA0645; NM_001242896). This variant caused a frameshift, p.Leu374Phefs*30, introducing a premature stop codon 29 amino acids downstream. The c.1122delA variant fully segregated with the phenotype within the family (Fig. 1). We next sought DEPDC5 mutations in 15 additional probands from the families with autosomal dominant focal epilepsies (ADNFLE, n = 7; FTLE, n = 4; FFEVF, n = 4)12, including family S in which disease was linked to the 22q12 locus. Massively parallel pyrosequencing screening of all 43 exons and splice regions of DEPDC5 identified 4 further nonsense mutations (encoding p.Arg239* in family S, p.Arg328* in family L, p.Gln372* in family Q and p.Gln1523* in family B) and 1 missense mutation (p.Arg485Gln in family O) in 5 families (Fig. 2a, Table 1 and Supplementary Fig. 3). All mutations were shown to segregate with the phenotype within the families, except for the mutation encoding p.Gln1523* in family B, where additional family members were unavailable for analysis (Fig. 1). In family

1Institut

National de la Santé et de la Recherche Médicale (INSERM) U975, Institut du Cerveau et de la Moelle Epinière (ICM), Hôpital Pitié-Salpêtrière, Paris, France. 2Université Pierre et Marie Curie–Paris 6 (UPMC), Paris, France. 3Department of Neurology, University Hospitals of Geneva (HUG), Geneva, Switzerland. 4Neurology Department, Strasbourg University Hospital, Strasbourg, France. 5Strasbourg University (UDS), Strasbourg, France. 6Unité Mixte de Recherche (UMR) 7138, Centre National de la Recherche Scientifique (CNRS), Paris, France. 7UMR 7241, Collège de France, Paris, France. 8Service de Neurologie, Hôpital Pasteur, Nice, France. 9Centre Saint Paul, Henri Gastaut, Marseille, France. 10Mediterranean Institute of Neurobiology (INMED), Marseille, France. 11Genotyping/Sequencing Platform of ICM, Hôpital Pitié-Salpêtrière, Paris, France. 12Department of Pediatric Neurology, University Children’s Hospital, Tuebingen, Germany. 13Epilepsy Unit, Assistance Publique–Hôpitaux de Paris (AP-HP) Groupe Hospitalier Pitié-Salpêtrière, Paris, France. 14Département de Génétique et de Cytogénétique, AP-HP Groupe Hospitalier Pitié-Salpêtrière, Paris, France. Correspondence should be addressed to S.B. (stephanie.baulac@upmc.fr). Received 21 December 2012; accepted 7 March 2013; published online 31 March 2013; doi:10.1038/ng.2601

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letters Database of Genomic Variants. DEPDC5 mutations occurred significantly more often I 1 2 in our group of affected individuals (5/32; 2 1 +/+ m/+ P = 5 × 10−12, Fisher exact test). II II Four out of six mutations (encod2 3 7 1 6 5 4 8 1 2 m/+ +/+ +/+ +/+ m/+ ing p.Arg239*, p.Arg328*, p.Gln372* and +/+ m/+ p.Leu374Phefs*30 alterations) are predicted III III to result in degradation of the mutated tran1 2 3 4 9 5 6 10 7 8 1 2 +/+ +/+ m/+ m/+ +/+ m/+ +/+ m/+ m/+ script by the nonsense-mediated mRNA m/+ m/+ decay (NMD) system, whereas the nonsense IV Family Q: c.1114C>T mutation encoding p.Gln1523*, located in 1 2 3 4 5 6 7 +/+ m/+ m/+ +/+ m/+ I the last exon of the gene, is not likely to be 1 2 targeted by the NMD system. To confirm m/+ +/+ Family S: c.715C>T that the mutation encoding the p.Arg239* II I alteration leads to NMD, we treated cultured ? ? 1 4 2 3 5 1 2 lymphoblasts from three mutation carriers m/+ III (S-III:10, S-IV:7 and S-IV:9) and one spouse II 1 (S-III:11) with emetine, an NMD inhibi1 2 5 6 3 4 Family B: c.4567C>T tor. With sequencing of DEPDC5 cDNA 2 III 2 the mutation encoding p.Arg239* was only I 4 5 3 7 6 10 11 12 13 14 15 18 16 17 1 2 detected when NMD was inhibited (Fig. 2c), m/+ +/+ m/+ +/+ +/+ m/+ m/+ showing that this nonsense mutation speci II IV 3 2 1 4 fically leads to transcript degradation. 1 2 3 4 5 6 10 7 8 9 12 11 DEPDC5 haploinsufficiency is likely to be +/+ m/+ m/+ m/+ m/+ III the cause of disease in individuals carrying 1 2 3 4 V this mutation. 6 1 2 3 4 5 We identified mutations in one-third of IV m/+ m/+ m/+ m/+ 1 2 3 the families in our cohort (6/16, 37%), and, m/+ overall, 20 subjects with epilepsy carried a Family O: c.1454G>A Focal epilepsy DEPDC5 mutation. The age of disease onset ranged from 0 to 39 years (mean of 12.9 ± Generalized epilepsy I 10.9 (s.d.)). DEPDC5 mutations were not lim1 2 3 4 5 Lesional focal epilepsy ited to families with the FFEVF phenotype II Electrical seizure but were also found in a family with two indi1 2 3 5 4 6 7 8 9 10 11 12 viduals exhibiting a typical nocturnal fron+/+ Undefined epilepsy tal lobe epilepsy (family B)13 and two other m Mutated III families (L and O) with individuals with tem1 2 3 4 5 6 7 8 9 10 11 12 + Not mutated m/+ m/+ poral lobe seizures. A phenotype of FFEVF was attributed to family N because frontal Figure 1 Pedigrees of families with segregation of DEPDC5 mutations. Identified DEPDC5 seizures have been diagnosed in one fammutations included c.1122delA (p.Leu374Phefs*30) in family N, c.715C>T (p.Arg239*) ily member (N-IV:5), and frontal electrical in family S, c.982C>T (p.Arg328*) in family L, c.1114C>T (p.Gln372*) in family Q, c.1454G>A (p.Arg485Gln) in family O and c.4567C>T (p.Gln1523*) in family B. Individual N-IV:4 showed seizures were identified in another (N-IV:4), frontal spikes in electroencephalography (EEG) but no clinical seizure. A question mark whereas seizures in other family members indicates individuals born in the 1870s with doubtful epilepsy histories. Diagonal lines originate in the temporal lobe. Penetrance indicate deceased individuals. was incomplete in families N, S and O, in agreement with reports of low penetrance of O, the father (O-II:8) may have transmitted the mutation encod- 62% (ref. 14) or 50% (ref. 4) in families with FFEVF. Seven asymptoing p.Arg485Gln, as it was not inherited from the mother (O-II:7). matic obligate carriers (N-II:2, S-II:5, S-III:4, S-III:7, S-III:10, S-IV:5 The arginine at position 485 is a highly conserved amino acid (Fig. 2b). and O-II:8) and four asymptomatic at-risk individuals aged 8–42 years Different prediction software tools—MutationTaster, SIFT and (N-III:5, N-IV:7, S-IV:7 and S-V:2) carried the mutations. Our data PolyPhen-2—predicted that the arginine-to-glutamine alteration strongly support the causal role of DEPDC5 in a subset of our families at position 485 is disease causing, tolerated and possibly damaging, with focal epilepsies. However, the observed low penetrance and respectively. This p.Arg485Gln substitution was not detected in a variable expressivity (in age at onset and localization of seizure focus cohort of 450 controls of matched ancestry. None of the six DEPDC5 in various brain areas) suggest that other gene(s) or epigenetic and variants was present in dbSNP135 or the 1000 Genomes Project data- environmental factors modulate the phenotype. base or in the 6,503 exomes for which variants are currently listed in Because five out of the six mutations introduce a premature stop the National Heart, Lung, and Blood Institute (NHLBI) exome vari- mutation, loss of function of DEPDC5 presumably causes the epiant server (EVS) database. One nonsense mutation (1/11,813) and leptic phenotype. It will now be crucial to determine the function 1 frameshift mutation (1/11,775) have been identified in the 6,503 of the DEPDC5 gene product and examine how its loss causes epiexomes listed in the EVS database, and no copy number variations lepsy. DEPDC5 transcript was first identified in human brain cDNA disrupting the DEPDC5 coding sequence have been reported in the libraries15. This gene is strongly expressed at rather constant levels Family N: c.1122delA

Family L: c.982C>T

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553

letters

52 p. G ln 1

DUF3608 381

1,179 1,260

R R R R R R R R R A V

A A A A A A A A A Q H

Q Q Q Q Q Q Q Q Q S G

C C R R R R R R R T T

L L L L L L C S S C S

T A S A A A T I T S S

T T T T T T T T N L L

C C C C C C F F F Q Q

R R R R R R R R R R R

S S S S S S S A S V I

V V V V V V V V S V A

R R R R R R R R R R R

E E E E E E E E A T

–

1,603

Arg485

Homo sapiens Pan troglodytes Bos taurus Canis lupus Rattus norvegicus Mus musculus Gallus gallus Xenopus tropicalis Danio rerio Drosophila melanogaster Anopheles gambiae

+ S-IV:9 c.715C>T/+

DEP

100

Emetine

p.Arg239*

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p. Ar g2 p. 39 Ar * p. g32 G 8 p. ln3 * Le 7 u3 2* 74 p. P Ar g4 hef s* 85 3 G ln 0

DEPDC5 protein Amino acids 1

15 16

C >T

Exons

c. 45

DEPDC5 gene

c. 71

5C >T c. 98 c. 2C 11 > c. 14 T 11 C 22 >T de c. lA 14 54 G >A

+ R R R R Q Q R R K K

E E E D E E E E E K K

S S S S N N S R S T T

H H H H H H R Q V S S

S S S N N S T V S V V

R R R R R R R R R P P

K K K K K K K K K S S

S A S S A S S A S S A S S A S S A S S S S S S C S W G L E T L D G

S S S S S S S S S Y F

C C C C C C Y Y A A G

D D D D D D D D D Y T

S-III:11 +/+ –

Figure 2 DEPDC5 mutations. (a) Schematics of the exon-intron structure of the DEPDC5 gene with the position of mutations shown based on the human genomic sequence (NM_001242896) (top) and of the DEPDC5 protein with the positions of alterations indicated (bottom). DEPDC5 is a multidomain protein carrying an N-terminal domain of unknown function termed DUF3608 and a DEP domain at its C terminus. The p.Arg239*, p.Arg328*, p.Gln372* and p.Leu374Phefs*30 alterations are clustered in the DUF3608 domain. (b) Multiple-protein alignment showing conservation of the arginine residue at position 485 in the proteins encoded by the orthologs of DEPDC5 across species. (c) Sequence chromatograms of one affected (S-IV:9) and one unaffected (S-III:11) member of family S, showing the presence of a mutation encoding p.Arg239* in the DEPDC5 cDNA of lymphoblasts from S-IV:9 pretreated with emetine but not in untreated cells.

that DEPDC5 may be a G protein substrate. The DEPC5 ortholog gene product in yeast, Yjr138p (also known as SEA1), is part of an evolutionary conserved multiprotein SEA complex involved in membrane trafficking16. DEPDC5 may also be involved in oncological processes, as (i) it was reported to be deleted in two glioblastomas17 and (ii) an intronic SNP (rs1012068) in the DEPDC5 locus has been associated with hepatocellular carcinoma risk18. In conclusion, this work provides clear evidence that loss-of-function mutations in DEPDC5 are a major cause in a broad spectrum of autosomal dominant focal epilepsies. It shows that a single gene, DEPDC5, is a common genetic actor in epileptic syndromes with different brain localization and electroclinical expression, including ADNFLE, FTLE and FFEVF. Thus, seizure initiation sites may be dissociated from underlying genetic mechanisms, in striking contrast to previous data, which link LGI1 mutations with a seizure focus localized in the lateral temporal lobe and mutations in nicotinic acetylcholine subunit genes with a seizure focus localized in the frontal lobe. Understanding the relationship between loss of DEPDC5 function and the genesis of pathological neuronal synchronies in different epileptic networks and syndromes will provide new, clinically relevant insights and knowledge that may be useful in genetic counseling. With no known homology between the DEPDC5 protein and other proteins, new pathogenic mechanisms seem likely. DEPDC5 is the second gene after LGI1 found to be mutated in familial focal epilepsies not Allele encoding ion channel or transmitter receptor frequency Protein alteration (EVS) subunits. In addition to channelopathies, we p.Leu374Phefs*30 0% must consider alternative genetic pathways p.Arg239* 0% leading to epileptogenesis.

in both the developing and adult human brain (Human Brain Transcriptome), consistent with a role in epilepsy. We attempted to obtain clues from sequence analysis and database mining. The RefSeq collection reports five putative isoforms of DEPDC5 of 1,572, 559, 1,594, 1,603 and 1,503 amino acids in length for isoforms 1–5, respectively. One of the mutations (encoding p.Gln1523*) lies within an exon absent from isoform 2, suggesting that this isoform is not involved in pathology. Alignment with orthologs, using reciprocal best-BLASTP hits, and phylogeny showed that the DEPDC5 protein is highly conserved in metazoa and fungi (but absent from plants) (Supplementary Fig. 4), indicating a core role for this ancient eukaryotic factor. We note also that DEPDC5 and its orthologs occur as single gene copies, even within genomes known to be ancient polyploids, such as Dario rerio and Saccharomyces cerevisiae. This evidence, together with the dominance of epilepsy-causing mutations, suggests that gene dosage may be critical for normal brain function. Transmembrane prediction using hidden Markov model (TMHMM) analysis also showed that the DEPDC5 protein has no transmembrane domain and no homology with known ion channels. The presence of a DEP domain, a globular protein motif of about 80 amino acids found in many proteins involved in G protein signaling pathways, suggests

Table 1 Mutations identified in the DEPDC5 gene Family Phenotype

Genomic position (hg19)

Coding mutation (NM_001242896)

N S L Q O B

Chr. Chr. Chr. Chr. Chr. Chr.

c.1122delA c.715C>T c.982C>T c.1114C>T c.1454G>A c.4567C>T

554

FFEVF FFEVF FTLE FFEVF FTLE ADNFLE

22: 22: 22: 22: 22: 22:

g.32200188delA g.32188751C>T g.32198725C>T g.32200180C>T g.32210986G>A g.32302238C>T

Exon 16 12 15 16 21 43

p.Arg328* p.Gln372* p.Arg485Gln p.Gln1523*

0% 0% 0% 0%

URLs. 1000 Genomes Project, http:// www.1000genomes.org/; BLASTP, http://blast. ncbi.nlm.nih.gov/; Database of Genomic

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letters Variants, http://projects.tcag.ca/variation/; dbSNP, http:/www.ncbi. nlm.nih.gov/projects/SNP/; Human Brain Transcriptome, http:// hbatlas.org/; MERLIN, http://www.sph.umich.edu/csg/abecasis/ merlin/; MutationTaster, http://www.mutationtaster.org/; NHLBI Exome Variant Server, http://evs.gs.washington.edu/EVS/; Online Mendelian Inheritance in Man (OMIM), http://www.omim.org/; PolyPhen-2, http://genetics.bwh.harvard.edu/pph2/; RefSeq, http:// www.ncbi.nlm.nih.gov/refseq/rsg/; SIFT, http://sift.jcvi.org/; transmembrane prediction using hidden Markov model (TMHMM), http://www.cbs.dtu.dk/services/TMHMM/. Methods Methods and any associated references are available in the online version of the paper.

Acknowledgments We thank the genotyping and sequencing platform of ICM for technical assistance, the DNA and cell bank of ICM for DNA extraction and cell culture, P. Couarch for technical assistance, M. Gaussen for linkage analysis and C. Depienne for helpful discussions. S.I. received a grant from the French government. This study was supported by the program Investissements d’Avenir ANR-10-IAIHU-06. AUTHOR CONTRIBUTIONS S.I. performed experiments and analyzed data. F.P. performed phenotyping and collected clinical data. G.R. collected samples and extracted DNA. E.N. and E.M. participated in genetic experiments. G.A. carried out the bioinformatics analysis on DEPDC5 and statistical analysis. P.T., P.G., M.W., C.M. and E.H. performed phenotyping of families. R.M. and M.B. contributed to the writing of the manuscript. E.L. supervised the project and contributed to the writing of the manuscript. S.B. designed the study, supervised data analysis and wrote the manuscript. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. Reprints and permissions information is available online at http://www.nature.com/ reprints/index.html.

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Note: Supplementary information is available in the online version of the paper.

1. Scheffer, I.E. et al. Autosomal dominant nocturnal frontal lobe epilepsy. A distinctive clinical disorder. Brain 118, 61–73 (1995). 2. Berkovic, S.F. et al. Familial temporal lobe epilepsy: a common disorder identified in twins. Ann. Neurol. 40, 227–235 (1996). 3. Ottman, R. et al. Localization of a gene for partial epilepsy to chromosome 10q. Nat. Genet. 10, 56–60 (1995). 4. Klein, K.M. et al. Familial focal epilepsy with variable foci mapped to chromosome 22q12: expansion of the phenotypic spectrum. Epilepsia 53, e151–e155 (2012). 5. Baulac, S. & Baulac, M. Advances on the genetics of mendelian idiopathic epilepsies. Clin. Lab. Med. 30, 911–929 (2010). 6. Heron, S.E. et al. Missense mutations in the sodium-gated potassium channel gene KCNT1 cause severe autosomal dominant nocturnal frontal lobe epilepsy. Nat. Genet. 44, 1188–1190 (2012). 7. Kalachikov, S. et al. Mutations in LGI1 cause autosomal-dominant partial epilepsy with auditory features. Nat. Genet. 30, 335–341 (2002). 8. Berkovic, S.F. et al. Familial partial epilepsy with variable foci: clinical features and linkage to chromosome 22q12. Epilepsia 45, 1054–1060 (2004). 9. Callenbach, P.M. et al. Familial partial epilepsy with variable foci in a Dutch family: clinical characteristics and confirmation of linkage to chromosome 22q. Epilepsia 44, 1298–1305 (2003). 10. Morales-Corraliza, J. et al. Familial partial epilepsy with variable foci: a new family with suggestion of linkage to chromosome 22q12. Epilepsia 51, 1910–1914 (2010). 11. Xiong, L. et al. Mapping of a gene determining familial partial epilepsy with variable foci to chromosome 22q11-q12. Am. J. Hum. Genet. 65, 1698–1710 (1999). 12. Picard, F. et al. Dominant partial epilepsies. A clinical, electrophysiological and genetic study of 19 European families. Brain 123, 1247–1262 (2000). 13. Thomas, P., Picard, F., Hirsch, E., Chatel, M. & Marescaux, C. Autosomal dominant nocturnal frontal lobe epilepsy. Rev. Neurol. (Paris) 154, 228–235 (1998). 14. Scheffer, I.E. et al. Familial partial epilepsy with variable foci: a new partial epilepsy syndrome with suggestion of linkage to chromosome 2. Ann. Neurol. 44, 890–899 (1998). 15. Ishikawa, K. et al. Prediction of the coding sequences of unidentified human genes. X. The complete sequences of 100 new cDNA clones from brain which can code for large proteins in vitro. DNA Res. 5, 169–176 (1998). 16. Dokudovskaya, S. et al. A conserved coatomer-related complex containing Sec13 and Seh1 dynamically associates with the vacuole in Saccharomyces cerevisiae. Mol. Cell Proteomics 10, M110 006478 (2011). 17. Seng, T.J. et al. Complex chromosome 22 rearrangements in astrocytic tumors identified using microsatellite and chromosome 22 tile path array analysis. Genes Chromosom. Cancer 43, 181–193 (2005). 18. Miki, D. et al. Variation in the DEPDC5 locus is associated with progression to hepatocellular carcinoma in chronic hepatitis C virus carriers. Nat. Genet. 43, 797–800 (2011).

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read depth, and detects variants (SNPs and indels). Only positions included in the bait coordinates were conserved. Genetic variation was annotated with the IntegraGen in-house pipeline, consisting of gene annotation (using RefSeq), detection of known polymorphisms (using dbSNP135 and the 1000 Genomes Project database) and characterization of mutations as exonic, intronic, silent or nonsense.

Genotyping and linkage analysis. A genome-wide screen was performed on families N and S with Illumina 6K panel microarrays (Linkage-24 DNA Analysis BeadChip). LOD scores were calculated with MERLIN software assuming an autosomal dominant trait with 70% penetrance, a disease frequency of 0.0001 and 0% phenocopy. Haplotypes were reconstructed according to hg19 annotations.

Screening of a cohort by pyrosequencing. All 43 exons and intron-exon junctions of DEPDC5 (except exon 2, which was screened by Sanger sequencing) were analyzed by universal tailed amplicon sequencing (454 Sequencing Technology, Roche). This approach used the 454 GS Junior system and involved an initial PCR amplification with primer sets designed to amplify exons corresponding to the sequence under accession NM_001242896 (Supplementary Table 1), a second PCR aiming to incorporate multiplex identifier and 454 adaptors and, finally, an emulsion PCR step carried out according to the emPCR Amplification Method Manual (Roche).

Exome sequencing. Exome sequencing was carried out in subjects III-4 and III-6 of family N. Targeted exome sequencing, library preparation, capture and sequencing, and variant detection and annotation were performed by IntegraGen (Evry, France). Exons of genomic DNA samples were captured using Agilent in-solution enrichment methodology with a biotinylated oligonucleotide probe library, and paired-end 75-base massively parallel sequencing was carried out on an Illumina HiSeq2000. Sequence capture was performed according to the manufacturer’s instructions (Human All Exon kit V4+UTRs, 70 Mb, Agilent). Briefly, 3 µg of each genomic DNA sample was fragmented by sonication and purified to yield fragments of 150–200 bp in length. Pairedend adaptor oligonucleotides from Illumina were ligated on repaired A-tailed fragments, and fragments were purified and enriched by six PCR cycles. Purified libraries (500 ng) were hybridized to the SureSelect oligonucleotide probe capture library for 24 h. After hybridization, washing and elution, the eluted fraction was PCR amplified with 10 to 12 cycles, purified and quantified by qPCR to obtain sufficient DNA template for downstream applications. Each eluted enriched DNA sample was then sequenced on an Illumina HiSeq2000 as paired-end 75-base reads. Image analysis and base calling were performed using the Illumina Real-Time Analysis Pipeline version 1.14 with default parameters. Bioinformatics analysis. Bioinformatics analysis of sequencing data was based on the Illumina pipeline (CASAVA 1.8). CASAVA aligns reads to the human reference genome (hg19) with the alignment algorithm ELANDv2 (it performs multiseed and gapped alignments), calls SNPs on the basis of allele calls and

Validation of exome and pyrosequencing variants by Sanger sequencing. Mutations found through exome sequencing and pyrosequencing were validated by Sanger sequencing using the BigDye Terminator kit on an ABI Prism 3730 DNA Analyzer (Applied Biosystems). Segregation analysis of withinfamily variants was carried out using the same primers as for pyrosequencing (Supplementary Table 1). Mutation interpretation was assessed with Alamut version 2.2 (Interactive Biosoftware). The effects of amino-acid substitutions on protein function were predicted using MutationTaster, SIFT and PolyPhen-2. Cell culture and mRNA experiments. Lymphoblastic cells from three mutation carriers (S-III:10, S-IV:7 and S-IV:9) and one spouse (S-III:11) from family S were treated (or not) overnight with 10 mg/ml emetine to inhibit NMD. Total RNA was extracted with the Qiagen RNeasy Mini kit and reverse transcribed with the ThermoScript RT-PCR System (Invitrogen). DEPDC5 cDNA was amplified and sequenced using specific primers located in exons 12 and 15. Phylogenetic tree reconstruction. All amino-acid sequences encoded by orthologous genes were retrieved from NCBI and aligned using MUSCLE. Visual inspection of the alignment with SEAVIEW showed that homology was present across several regions of the protein. Protein alignment was trimmed to 454 homologous sites using GBLOCK. Tree reconstruction was performed by maximum likelihood using PhyML software with an LG matrix.

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Families and subjects. Sixteen unrelated families from western Europe with non-lesional focal epilepsies were studied12. Mutations in CHRNA4, CHRNB2 and LGI1 have been excluded in all families. Local ethics committee (CCPPRB of Pitié-Salpêtrière Hospital, Paris, 69-03, 25/9/2003) approved this study. Informed consent was obtained from all participants or their parents.

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a r t ic l e s

GABA progenitors grafted into the adult epileptic brain control seizures and abnormal behavior

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Robert F Hunt1,2, Kelly M Girskis1,2, John L Rubenstein3, Arturo Alvarez-Buylla2 & Scott C Baraban1,2 Impaired GABA-mediated neurotransmission has been implicated in many neurologic diseases, including epilepsy, intellectual disability and psychiatric disorders. We found that inhibitory neuron transplantation into the hippocampus of adult mice with confirmed epilepsy at the time of grafting markedly reduced the occurrence of electrographic seizures and restored behavioral deficits in spatial learning, hyperactivity and the aggressive response to handling. In the recipient brain, GABA progenitors migrated up to 1,500 mm from the injection site, expressed genes and proteins characteristic for interneurons, differentiated into functional inhibitory neurons and received excitatory synaptic input. In contrast with hippocampus, cell grafts into basolateral amygdala rescued the hyperactivity deficit, but did not alter seizure activity or other abnormal behaviors. Our results highlight a critical role for interneurons in epilepsy and suggest that interneuron cell transplantation is a powerful approach to halting seizures and rescuing accompanying deficits in severely epileptic mice. GABA-producing inhibitory interneurons are essential for regulating cortical excitability and coordinating appropriate behaviors. In hippocampus, interneuron dysfunction has been implicated in many forms of epilepsy1,2 and can disrupt learning and memory3 or social behaviors4. Current medications that systemically potentiate GABA-mediated inhibition can be effective at suppressing seizures, but prolonged drug treatment can have unwanted cognitive or neurobehavioral side effects and epilepsy remains refractory to medical treatment in nearly one-third of affected individuals 5. Recently, optogenetic techniques have been used to interrupt seizure activity in animal models of epilepsy6,7, supporting the general concept that focal inhibition of epileptic networks might have therapeutic application. Although promising, these approaches require expression of light-sensitive opsins, invasive light delivery interface and seizuredetection hardware. Transplantation and subsequent integration of new inhibitory neurons into neural circuits affected by epilepsy might be a therapeutic strategy for controlling seizures, or other cooccurring behaviors, as a one-time procedure without the need for regular neural modulation or online seizure prediction. The majority of cortical interneurons are born in the medial ganglionic eminence (MGE) of the embryonic ventral telencephalon8–11. When grafted into the neonatal brain, MGE progenitor cells migrate long distances and functionally integrate as inhibitory neurons 9,12–14. Previously, we found that early postnatal transplantation of GABA progenitor cells into neocortex, before seizure onset, reduced spontaneous electrographic seizure activity in mice with a congenital potassium channel mutation13. However, whether this approach would be successful in the more common and medically refractory types of epilepsy seen in adults has not been directly tested. The emergence of epilepsy in adulthood involves a wide range of modifications to brain

structure and function1,2, and it is not known whether the adult nervous system can support GABA progenitor cell migration, differentiation, integration or functional recovery of pre-existing deficits. On this basis, we first carefully characterized the development of MGE progenitors grafted into adult recipients. We then asked whether epileptic phenotypes could be improved by MGE cell grafts into the hippocampus or amygdala after epileptic seizures emerge (Supplementary Fig. 1). For this purpose, we selected a pilocarpine model of epilepsy that is characterized by robust, frequent spontaneous seizures acquired after a brain insult15–18, well-described behavioral abnormalities18 and poor responses to antiepileptic drugs19. These animals recapitulate several key features of human temporal lobe epilepsy, the most common type of epilepsy in adults1,2. RESULTS We obtained MGE progenitors from embryonic day 13.5 (E13.5) GFP+ donor mice20, in which the EGFP gene is driven by a CMV (cytomegalovirus) immediate early enhancer coupled to the chicken β-actin (ACTB) promoter, as described previously9,12–14, and injected 3 × 104 cells into the dorsal hippocampus of adult (postnatal day 60, P60) control recipients. The migration (Fig. 1a) and neurochemical expression (Fig. 1b) of grafted cells was examined 7 and 60 d after transplantation (DAT). By 7 DAT, GFP+ MGE cells had moved away from the injection and dispersed throughout hippocampal subfields (n = 3 mice; Supplementary Fig. 2). Many grafted cells were found along major fiber tracts and exhibited a bipolar, migratory morphology, whereas others started to extend multiple processes from the cell body. Survival rate at 7 DAT was 32.6 ± 2.3% (n = 3). By 60 DAT (n = 6 mice), these cells had migrated up to 1,500 µm from the injection site, and cell survival was 14.8 ± 1.3%. We did not detect a significant

1Epilepsy Research Laboratory, University of California, San Francisco, California, USA. 2Department of Neurological Surgery, University of California, San Francisco, California, USA. 3Department of Psychiatry, University of California, San Francisco, California, USA. Correspondence should be addressed to R.F.H. (robert.huntiii@ucsf.edu) or S.C.B. (scott.baraban@ucsf.edu).

Received 6 December 2012; accepted 26 March 2013; published online 5 May 2013; doi:10.1038/nn.3392

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Figure 1 Transplanted MGE cells migrate into the adult hippocampus and express markers of inhibitory neurons. (a) Distribution of transplanted E13.5 MGE cells expressing GFP 7 DAT (white bars, n = 3 mice) and 60 DAT (gray bars, n = 6 mice). (b) Quantification of marker expression in GFP-labeled cells (n = 3–6 mice per marker). CR, calretinin; GFAP, glial fibrillary acid protein; DCX, doublecortin; nNOS, neuronal nitric oxide synthase; NPY, neuropeptide Y; PV, parvalbumin; SST, somatostatin; VIP, vasoactive intestinal peptide. (c) Hippocampus of a pilocarpine-injected recipient mouse (60 DAT) labeled for NeuN (red) and transplanted GFP-labeled inhibitory neurons (green). Transplanted neurons dispersed after grafting into recipient mice despite extensive hippocampal cell loss resulting from pilocarpine injection. (d) At 60 DAT, GFP-labeled cells (green) coexpressed somatostatin, parvalbumin and neuronal nitric oxide synthase (all in red). Arrowheads, colabeled cells; error bars, s.e.m.; scale bars, 1,000 µm (c) and 67 µm (d).

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60 DAT, most GFP-labeled cells exhibited the morphological features of mature interneurons, with large, extensive processes and cell bodies positioned in regions normally occupied by endogenous inhibitory neurons (that is, polymorph and molecular layers). GFP-labeled cells expressed NeuN (92.2 ± 2.9%), GAD67 (63 ± 4.4%) and interneuron markers, with somatostatin (41.3 ± 2.8%), neuronal nitric oxide synthase (21.6 ± 1.2%) and parvalbumin (7.7 ± 0.8%)

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difference between the mean rostrocaudal distance of grafted MGE cells at 60 DAT and that at 7 DAT (P = 0.44, two-tailed t-test; Fig. 1a), suggesting that rostrocaudal migration is nearly complete by 7 DAT. At

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Figure 2 Transplanted MGE cells differentiate into functional inhibitory interneurons. (a–e) Example electrophysiological responses of five different transplanted MGE cells to the indicated square wave current pulses (bottom) from a holding potential near −70 mV. Recordings were obtained from slices 61–65 DAT. Depolarizing current pulses and corresponding responses are for near threshold (red), 2× threshold (blue) and near maximal firing (black). Right, RNA profiles obtained from single-cell RT-PCR analysis for each recorded cell. MW, molecular weight marker; CB, calbindin; CCK, cholecystokinin. (f) Positive control for the single-cell RT-PCR procedure using 1 ng of hippocampus RNA from a GFP+ mouse. (g) Summary plot for the occurrence of each marker in recorded GFP+ cells (n = 9 cells). RNA was obtained from regular-spiking (n = 3), fast-spiking (n = 2), burst-spiking (n = 3) and late-spiking (n = 1) interneurons. (h) Occurrence of each interneuron subtype recorded based on firing properties (n = 46 cells). (i,j) Mean EPSC frequency (i) and amplitude (j) according to interneuron subtype. Error bars represent s.e.m. Electrophysiological properties of grafted interneurons are summarized in Supplementary Table 2.

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Figure 3 Distribution of MGE-derived cells 60+ DAT into the adult epileptic hippocampus. (a–j) Serial sections (300 µm apart) through the entire hippocampus of a pilocarpine-treated recipient mouse labeled for transplanted MGE cells (green) and DAPI (blue). Arrowheads in d,g,h indicate injection sites. Scale bars, 100 µm (a–f) and 1,000 µm (g–j).

s ubtypes representing the majority of colabeled cells, as reported previously8–10. We also examined other GABAergic subtypes, including those expressing calretinin (6.4 ± 1.3%), neuropeptide Y (7.5 ± 1.1%), reelin (12.5 ± 1.5%) and vasoactive intestinal peptide (0%). None of the GFP+ MGE cells expressed CamKII (excitatory neurons) or doublecortin (immature neurons). A small percentage of cells around the injection site colabeled for olig2 (oligodendrocytes, 1.8%) or glial fibrillary acid protein (astrocytes, 1%) and failed to exhibit neuronal electrophysiological properties (Supplementary Fig. 3). We obtained similar results using adult epileptic mice as recipients, indicating that dispersion or marker expression of the transplanted cells were not affected in epileptic mice (Fig. 1c,d). Next, we examined the electrophysiological and molecular properties of GFP+ MGE neurons using visualized patch-clamp recordings in combination with post hoc single-cell reverse transcription (RT)-PCR. In acute hippocampal slices from transplanted mice (60–65 DAT), GFP+ MGE cells exhibited electrophysiological phenotypes and RNA expression profiles consistent with those of mature interneurons of a MGE lineage21 (Fig. 2 and Supplementary Table 1). Electrophysiological recordings from 46 cells revealed four main subtypes of interneurons: fast spiking (n = 12 cells, 26%), regular spiking nonpyramidal (n = 19 cells, 41%), late spiking (n = 4 cells, 9%) and burst spiking (n = 11 cells, 24%). All interneurons examined by single-cell RT-PCR (n = 9 interneurons) expressed Lhx6, a transcription factor expressed in MGE-derived interneurons, and other gene markers expressed in MGE-derived GABA neurons (Fig. 2a–g). None of the recorded cells contained RNA for the ionotropic serotonin receptor 5HT3A or vasoactive intestinal peptide, which are expressed in cortical interneurons from the caudal ganglionic eminence21. Voltage-clamp recordings confirmed the presence of spontaneous excitatory postsynaptic currents in all of the grafted interneurons (Fig. 2i,j and Supplementary Table 2), consistent with functional integration of these cells into the hippocampal network. Taken together, these findings indicate that the adult hippocampus is permissive for migration and functional integration of embryonic GABA progenitors and that these cells differentiate into mature interneurons. To test the effect of transplanted MGE cells on spontaneous seizures, we performed continuous video-electroencephalographic (video-EEG) monitoring in the pilocarpine model 18,19. After an acute episode of pilocarpine-induced status epilepticus, P51 adult mice were first video monitored for 9–20 d to document the emergence of at least one spontaneous seizure before random assignment into untreated, vehicle-injected or MGE cell–injected groups (Supplementary Fig. 1). After seizure confirmation, we made bilateral injections of MGE cells into hippocampus (four injections of 3 × 104 cells per hippocampi). This approach distributed newly generated inhibitory neurons throughout the adult hippocampus of epileptic recipients at 60+ DAT (Fig. 3). In a separate group of mice, we made bilateral injections into the basolateral amygdala (a single injection of 3 × 10 4 cells per hemisphere); dispersion and marker expression of MGE cell grafts into the amygdala were comparable to hippocampus (Fig. 4). We chose these brain regions because they exhibit substantial neuropathology1,2,15,22, including inhibitory neuron loss, and contribute to seizure generation in this model1,2,17. 694

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All of the untreated (n = 7 mice) or vehicle-injected (n = 7) epileptic mice displayed spontaneous electrographic seizures (Fig. 5a), consisting of high-frequency, high-voltage, rhythmic activity with clear onset and termination and prominent voltage spikes preceding ictal events (frequency = 2.36 ± 0.46 seizures per day, n = 14 mice). Electrographic seizures or high-voltage spiking were never observed in naive control mice that did not receive pilocarpine (n = 3 mice). Simultaneous video monitoring confirmed convulsive, Racine stage 3–5 seizure behaviors during electrographic events23 (Supplementary Movie 1). Epileptic mice that received injections of MGE cells into the hippocampus exhibited a 92% reduction in seizure frequency (frequency = 0.17 ± 0.09, n = 8 mice; Fig. 5b). In 50% of these mice, no electrographic seizures were observed during the entire video-EEG monitoring period (7–10 d). In contrast, transplantation into the basolateral amygdala had no effect on seizure frequency (frequency = 2.24 ± 0.46, n = 8 mice). The duration of electrographic events or behavioral severity was not different in MGE-grafted mice than in untreated or vehicle-injected epileptic mice (Supplementary Table 3). We next asked whether MGE cell transplantation affected mossy fiber sprouting into the inner molecular layer of the dentate gyrus, a wellcharacterized pathology in epilepsy patients and animal models1,2,15,24. To visualize mossy fibers, we stained for zinc transporter 3 (ZnT3), which is highly expressed in mossy fiber terminals25 (Supplementary Fig. 4), and assigned Timm scores from 0 (little to no sprouting) to 3 (robust sprouting), as previously described15. Robust mossy fiber sprouting was present in all vehicle-injected epileptic mice (Timm score = 2.85 ± 0.1, n = 4 mice) and at 60 DAT in mice that received MGE cell grafts into the hippocampus (Timm score = 2.75 ± 0.13, n = 4 mice), but not in controls (Timm score = 0, n = 4 mice). One-way ANOVA on ranks analysis revealed that Timm scores for mossy fiber sprouting were not significantly different between vehicle-injected epileptic mice and those that received MGE cell grafts (H = 8.045, Tukey’s post hoc, P > 0.05), but both groups had significantly greater Timm scores than controls (P < 0.05). This observation suggests that the marked decrease in seizures obtained with MGE cell transplantation was not a result of a reversal of abnormal mossy fiber sprouting in the dentate gyrus. VOLUME 16 | NUMBER 6 | JUNE 2013 nature NEUROSCIENCE

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the visible platform training (Supplementary Fig. 5), which can confound the interpretation of spatial learning deficits in the hidden platform task27,28. During the hidden platform test (Fig. 6i), epileptic mice that did not receive MGE cell grafts had significantly longer escape latencies than controls (P < 0.001), consistent with previous reports and impaired spatial learning18,27,28, although the possibility that noncognitive deficits might influence water maze performance in these mice cannot be excluded. This deficit was confirmed in a probe test 1 h after the final testing session (Fig. 6j–l). Although control mice spent significantly more time in the target quadrant (P < 0.001) and made numerous platform crossings, epileptic mice showed no preference for any quadrant (P = 0.4) and rarely crossed the platform location. MGE cell transplantation into hippocampus rescued these deficits in escape latencies, quadrant time and platform crossings to control levels. However, mice that received MGE cell grafts into

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Quality of life in epilepsy patients is often markedly affected by cognitive decline, and epilepsy can be accompanied by debilitating neurobehavioral comorbidities, including psychiatric disorders, anxiety or social problems26. Thus, we examined whether MGE cell transplantation could rescue any of the well-characterized behavioral phenotypes associated with the pilocarpine model18. A handling test revealed that epileptic mice had a marked increase in their reaction to handling. All of the epileptic mice displayed aggressive behaviors to touch, which were rare in controls. MGE cell transplantation into hippocampus rescued this abnormal behavior to control levels, but transplantation into amygdala had no effect (Fig. 6a and Supplementary Movie 2). During a 10-min open field test (locomotion), epileptic mice displayed hyperactivity and traveled significantly farther than controls (P < 0.01). This behavioral deficit was reversed by cell transplantation into the hippocampus or amygdala (Fig. 6b). In an accelerating rotarod assay (motor coordination), we did not observe a significant difference among treatment groups in either the r.p.m. reached (P = 0.31) or the amount of time spent on the rod (P = 0.38; Fig. 6c,d). In the elevated plus maze (general anxiety), we did not observe differences among treatment groups in either the number of open arm entries (P = 0.16) or the amount of time spent in the open arms (P = 0.12; Fig. 6e,f). In the forced swim test (despair), control mice developed a characteristic immobile posture when placed into a waterfilled cylinder from which they could not escape, but most epileptic mice continued to swim, trying to escape the cylinder throughout the test duration. MGE transplantation into the hippocampus or amygdala of epileptic mice did not alter this behavior (Fig. 6g). Finally, we asked whether MGE cell transplantation affected performance in a Morris water maze test, which requires the use of external visual cues to locate a hidden platform and escape the water. We first examined the mice’s ability to locate a visible platform (cued learning) and to then locate a hidden platform (acquisition). Next, we removed the hidden platform (probe trial) to measure the short-term retention of spatial memory. Nearly all of the mice showed improvement in the time to find the visible platform, demonstrating efficient cued learning (Fig. 6h); two mice in the ‘epilepsy’ group and one mouse that received MGE cell grafts into amygdala were excluded from further analysis because they showed a substantial deficit in

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Figure 5 Inhibitory neuron transplantation reduces seizure occurrence in epileptic mice. (a) Example EEG recording of a spontaneous seizure from an untreated epileptic mouse. Numbers indicate the regions of the seizure shown below at high resolution. (b) Bar plots show the mean spontaneous seizure frequency (seizures per d) for each group based on continuous EEG recordings (7–10 d). Bars represent mean ± s.e.m. The data points superimposed over the bar graph each represent an individual mouse from which recordings were obtained. *P < 0.01. MGE-HC, MGE transplantation into the hippocampus; MGE-AMG, MGE transplantation into the amygdala.

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Figure 6 Inhibitory neuron transplantation rescues behavioral comorbidities of epilepsy. (a) Epileptic mice showed an increase in aggressive behaviors to handling compared with naive controls. This was reversed by MGE cell transplantation into the hippocampus (MGE-HC), but not by transplantation into the amygdala (MGE-AMG). (b) In the open field test, mice traveled farther 2 weeks after pilocarpine injections when compared with naive controls and baseline measurements prior to pilocarpine injection. MGE cell transplantation into both the hippocampus and amygdala reversed this behavior to control levels by 60 DAT. (c,d) There was no difference between treatment groups in the amount of time spent on an accelerating rotarod (c) or the mean r.p.m. reached (d). (e,f) In the elevated plus maze, there was no difference between treatment groups in the amount of time spent in the open arm (e) or the number of open arm entries (f). (g) In the forced swim test, epileptic mice spent less time immobile than control mice, and MGE transplantation into the hippocampus or amygdala did not improve this behavior. (h) In a Morris water maze test, all mice showed a decrease in latency to escape the maze during repeated training trials in the visible platform test. (i) Epileptic mice showed a marked deficit in latency to escape the maze during the six repeated sessions of the hidden platform test. (j,k) During a probe trial following the final testing session, epileptic mice made fewer platform crossings (j) and did not show a preference for any quadrant (k). MGE cell transplantation into hippocampus, but not transplantation into amygdala, rescued deficits in escape latency (i) and probe trial performance (j,k) with control levels. (l) Example locomotion tracking plots showing the total path-length during session 1 (S1) and session 6 (S6) of the hidden platform task and the probe trial. Black circle indicates platform location. All data represent mean ± s.e.m. from 6–25 mice per treatment group. *P < 0.05 versus control, **P < 0.05 versus epilepsy, ***P < 0.001 versus other quadrants; n.s., not significant (P = 0.4 for epilepsy group and P = 0.11 for MGE-AMG group). All values and statistical analyses are provided in Supplementary Table 3. Probe

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amygdala did not show improvement in spatial learning and were indistinguishable from untreated epileptic mice. DISCUSSION We found that MGE progenitor cells grafted into the adult epileptic brain exerted a substantial therapeutic effect on seizures and abnormal behaviors commonly associated with epilepsy. The degree to which this procedure was successful in abrogating seizures in the pilocarpine model was notable given that neuropathology (for example, mossy fiber sprouting) as a result of pre-existing limbic epilepsy remained present in these mice and the reported difficulty of controlling spontaneous seizures using conventional antiepileptic treatments 19. Improved behavior after MGE cell grafting into epileptic mice could be relevant to other brain disorders that involve a disruption of inhibitory circuits in hippocampus, such as Alzheimer’s disease29 or autism4. Not surprisingly, these neurological disorders often involve increased seizure susceptibility as a co-morbidity. Interneuron-based cell transplantation might have an important clinical advantage over current therapeutic approaches in that cell grafts can be targeted to spatially restricted brain regions as a one-time procedure for seizure control. 696

In addition to the obvious benefits for promoting functional recovery, this approach might also be useful for limiting adverse behavioral side effects that can be associated with medications or for sparing areas of the epileptic brain normally targeted for surgical resection. Although our goal was not to examine the site of seizure initiation in this epilepsy model, we did find that interneuron cell grafts into the hippocampus, but not the amygdala, were critical for controlling epileptic activity. Despite the potentially widespread tissue damage associated with systemic pilocarpine administration1,2,12,19, these findings are consistent with reports that around 70% of electrographic seizure events involve the hippocampal formation in this model17. Our findings support a critical role for the loss of inhibitory neurons in epilepsy, a pathology that likely contributes to the reduced synaptic inhibition observed in the hippocampus of epileptic pilocarpine-treated rodents30–32. Enhancement of GABA-mediated synaptic inhibition that is associated with new MGE-derived interneurons12–14,33 further supports the concept that abnormal electrical activity is kept in check by a powerful interneuron-mediated ‘inhibitory restraint’ 34–36 and that this enhancement may be sufficient to prevent seizure initiation. Given that we assessed mice around 80–100 d after the induction of VOLUME 16 | NUMBER 6 | JUNE 2013 nature NEUROSCIENCE

a r t ic l e s status epilepticus, a time at which epilepsy is well established in this model, it also seems reasonable to conclude that GABA progenitor cell transplantation has long-term effects on seizures and behavior. A major challenge in the field has been to develop new approaches for controlling epilepsies that do not respond to current medications. Our results suggest that GABA progenitors are particularly promising candidates for cell therapy, as they can be broadly distributed in spatially restricted brain regions in adult behaving mice. This approach is based on the functional engraftment of new inhibitory interneurons into existing circuits and, in contrast with optogenetics-based6,7 or stimulation-based37 approaches, does not require a system for realtime seizure detection. Although production of a comparable and safe MGE-like human stem cell line will ultimately be necessary before translation to the clinic, our results are an encouraging step toward using inhibitory neurons for brain repair in adults with severe forms of epilepsy.

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Methods Methods and any associated references are available in the online version of the paper. Note: Supplementary information is available in the online version of the paper. Acknowledgments We thank M. Dinday and W. Hindle-Katel for assistance with pilocarpine injections, J. Sebe for tissue dissection training, G. Hortopan for advice on the single-cell RT-PCR procedure, R. Palmiter for the ZnT3 antibody, and S. Canchola for training on behavior assays. This work was supported by funding from US National Institutes of Health grants from the National Institute of Neurological Disorders and Stroke (RO1-NS071785 to S.C.B., J.L.R. and A.A.-B., and F32-NS077747 to R.F.H.), and a grant from the California Institute of Regenerative Medicine (#TR2-01749 to A.A.-B. and S.C.B.). AUTHOR CONTRIBUTIONS R.F.H. contributed to the concept, design, execution and analysis of all of the experiments, provided funding, and wrote the manuscript. K.M.G. contributed to the execution and analysis of the immunostaining and behavior experiments. J.L.R. and A.A.-B. contributed to the concept, provided funding and edited the manuscript. S.C.B. contributed to the concept and design of the experiments, analyzed the EEG data, provided funding, and wrote the manuscript. COMPETING FINANCIAL INTERESTS The authors declare competing financial interests: details are available in the online version of the paper. Reprints and permissions information is available online at http://www.nature.com/ reprints/index.html. 1. Lothman, E.W., Bertram, E.H. III & Stringer, J.L. Functional anatomy of hippocampal seizures. Prog. Neurobiol. 37, 1–82 (1991). 2. Noebels, J.L., Avoli, M., Rogawski, M.A., Olsen, R.W. & Delgado-Escueta, A.V. Jasper’s Basic Mechanisms of the Epilepsies, 4th edn. (National Center for Biotechnology, Bethesda, Maryland, 2012). 3. Andrews-Zwilling, Y. et al. Hilar GABAergic interneuron activity controls spatial learning and memory retrieval. PLoS ONE 7, e40555 (2012). 4. Han, S. et al. Autistic-like behavior in Scn1a+/− mice and rescue by enhanced GABA-mediated neurotransmission. Nature 489, 385–390 (2012). 5. Anonymous. Epilepsy Fact Sheet. World Health Organization 〈http://www.who.int/ mediacentre/factsheets/fs999/en/index.html〉 (October 2012). 6. Paz, J.T. et al. Closed-loop optogenetic control of thalamus as a tool for interrupting seizures after cortical injury. Nat. Neurosci. 16, 64–70 (2013). 7. Krook-Magnuson, E., Armstrong, C., Oijala, M. & Soltesz, I. On-demand optogenetic control of spontaneous seizures in temporal lobe epilepsy. Nat. Commun. 4, 1376 (2013).

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8. Lavdas, A.A., Grigoriou, M., Pachnis, V. & Parnavelas, J.G. The medial ganglionic eminence gives rise to a population of early neurons in the developing cerebral cortex. J. Neurosci. 19, 7881–7888 (1999). 9. Wichterle, H., Garcia-Verdugo, J.M., Herrera, D.G. & Alvarez-Buylla, A. Young neurons from medial ganglionic eminence disperse in adult and embryonic brain. Nat. Neurosci. 2, 461–466 (1999). 10. Xu, Q., Cobos, I., De La Cruz, E., Rubenstein, J.L. & Anderson, S.A. Origins of cortical interneuron subtypes. J. Neurosci. 24, 2612–2622 (2004). 11. Butt, S.J. et al. The temporal and spatial origins of cortical interneurons predict their physiological subtype. Neuron 48, 591–604 (2005). 12. Alvarez-Dolado, M. et al. Cortical inhibition modified by embryonic neural precursors grafted into the postnatal brain. J. Neurosci. 26, 7380–7389 (2006). 13. Baraban, S.C. et al. Reduction of seizures by transplantation of cortical GABAergic interneuron precursors into Kv1.1 mutant mice. Proc. Natl. Acad. Sci. USA 106, 15472–15477 (2009). 14. Southwell, D.G. et al. Intrinsically determined cell death of developing cortical interneurons. Nature 491, 109–113 (2012). 15. Shibley, H. & Smith, B.N. Pilocarpine-induced status epilepticus results in mossy fiber sprouting and spontaneous seizures in C57BL/6 and CD-1 mice. Epilepsy Res. 49, 109–120 (2002). 16. Goffin, K., Nissinen, J., Van Laere, K. & Pitkänen, A. Cyclicity of spontaneous recurrent seizures in pilocarpine model of temporal lobe epilepsy in rat. Exp. Neurol. 205, 501–505 (2007). 17. Bortel, A., Lévesque, M., Biagini, G., Gotman, J. & Avoli, M. Convulsive status epilepticus duration as determinant for epileptogenesis and interictal discharge generation in the rat limbic system. Neurobiol. Dis. 40, 478–489 (2010). 18. Gröticke, I., Hoffmann, K. & Löscher, W. Behavioral alterations in the pilocarpine model of temporal lobe epilepsy in mice. Exp. Neurol. 207, 329–349 (2007). 19. Löscher, W. Strategies for antiepileptogenesis: antiepileptic drugs versus novel approaches evaluated in post-status epilepticus models of temporal lobe epilepsy. in Jasper’s Basic Mechanisms of the Epilepsies, 4th edn. (eds. Noebels, J.L., Avoli, M., Rogawski, M.A., Olsen, R.W. & Delgado-Escueta, A.V.) (National Center for Biotechnology Information, Bethesda, Maryland, 2012). 20. Hadjantonakis, A., Gertenstein, M., Ikawa, M., Okabe, M. & Nagy, A. Generating green fluorescent mice by germline transmission of green fluorescent ES cells. Mech. Dev. 76, 79–90 (1998). 21. Tricoire, L. et al. A blueprint for the spatiotemporal origins of mouse hippocampal interneuron diversity. J. Neurosci. 31, 10948–10970 (2011). 22. Vignoli, T. et al. Consequences of pilocarpine-induced status epilepticus in immunodeficient mice. Brain Res. 1450, 125–137 (2012). 23. Racine, R.J. Modification of seizure activity by electrical stimulation. II. Motor seizure. Electroencephalogr. Clin. Neurophysiol. 32, 281–294 (1972). 24. Babb, T.L., Kupfer, W.R., Pretorius, J.K., Crandall, P.H. & Levesque, M.F. Synaptic reorganization by mossy fibers in human epileptic fascia dentata. Neuroscience 42, 351–363 (1991). 25. Palmiter, R.D., Cole, T.B., Quaife, C.J. & Findley, S.D. ZnT-3, a putative transporter of zinc into synaptic vesicles. Proc. Natl. Acad. Sci. USA 93, 14934–14939 (1996). 26. Hermann, B., Seidenberg, M. & Jones, J. The neurobehavioural comorbidities of epilepsy: can a natural history be developed. Lancet Neurol. 7, 151–160 (2008). 27. D’Hooge, R. & De Deyn, P.P. Applications of the Morris water maze in the study of learning and memory. Brain Res. Brain Res. Rev. 36, 60–90 (2001). 28. Palop, J.J. et al. Neuronal depletion of calcium-dependent proteins in the dentate gyrus is tightly linked to Alzheimer’s disease–related cognitive deficits. Proc. Natl. Acad. Sci. USA 100, 9572–9577 (2003). 29. Verret, L. et al. Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell 149, 708–721 (2012). 30. Hirsch, J.C. et al. Deficit of quantal release of GABA in experimental models of temporal lobe epilepsy. Nat. Neurosci. 2, 499–500 (1999). 31. Cossart, R. et al. Dendritic but not somatic GABAergic inhibition is decreased in experimental epilepsy. Nat. Neurosci. 4, 52–62 (2001). 32. Kobayashi, M. & Buckmaster, P.S. Reduced inhibition of dentate granule cells in a model of temporal lobe epilepsy. J. Neurosci. 23, 2440–2452 (2003). 33. Zipancic, I., Calcagnotto, M.E., Piquer-Gil, M., Mello, L.E. & Alvarez-Dolado, M. Transplant of GABAergic precursors restores hippocampal inhibitory function in a mouse model of seizure susceptibility. Cell Transplant. 19, 549–564 (2010). 34. Chagnac-Amitai, Y. & Connors, B.W. Horizontal spread of synchronized activity in neocortex and its control by GABA-mediated inhibition. J. Neurophysiol. 61, 747–758 (1989). 35. Trevelyan, A.J., Sussillo, D. & Yuste, R.M. Feedforward inhibition contributes to the control of the speed of epileptiform propagation. J. Neurosci. 27, 3383–3387 (2007). 36. Schevon, C.A. et al. Evidence of an inhibitory restraint of seizure activity in humans. Nat. Commun. 3, 1060 (2012). 37. Berényi, A., Belluscio, M., Mao, D. & Buzsaki, G. Closed-loop control of epilepsy by transcranial electrical stimulation. Science 337, 735–737 (2012).

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Animals. Mice were maintained in standard housing conditions on a 12-h light/dark cycle with food and water provided ad libitum. All protocols and procedures followed the guidelines of the Laboratory Animal Resource Center at the University of California, San Francisco. The young adult CD1 mice used for pilocarpine injections and breeding were purchased from Charles River Laboratories. Embryonic donor tissue was produced by crossing wild-type CD1 mice to homozygous GFP+ mice20. Pilocarpine injections (289 mg per kg of body weight) were performed in adult P51 male mice as described previously15. After recovering from acute status epilepticus, mice were housed singly and monitored for chronic spontaneous seizures between 9 and 20 d after pilocarpine administration by video recording. Mice only became candidates for transplantation after motor seizures of grade 3 or greater were detected, according to a modified Racine rating scale15,23. Mice that were not observed to have spontaneous seizures were killed around 25 d after pilocarpine injection. Tissue dissection and transplantation. Ventricular and subventricular layers of the MGE were harvested from E13.5 GFP+ embryos. The time point at which the sperm plug was detected was considered E0.5. Embryonic MGE explants were dissected in Leibovitz L-15 medium, mechanically dissociated by repeated pipetting in medium containing DNase I (100 µg ml−1) and concentrated by centrifugation (2 min at 1,000 g). Concentrated cell suspensions (~103 cells nl−1) were front loaded into bevelled glass micropipettes (40–50-µm tip diameter, Wiretol 5 µl, Drummond Scientific) and injected (3 × 104 cells per injection) into the hippocampus or amygdala of adult control or epileptic CD1 mice (P60–76). All injection coordinates were first verified in a series of preliminary dye and/or cell injection studies into control and epileptic mice (Supplementary Fig. 6). For hippocampal transplantations, injections were made into stratum radiatum of the CA3 subfield at the following stereotaxic coordinates: anterior-posterior (AP) 1.75 mm, medial-lateral (ML) 2.3 mm, dorsal-ventral (DV) 1.7 mm. A second group of injections were made at three sites along the length of the hippocampus: AP 3.25 mm, ML 3.0 mm and DV 3.65 mm, 2.9 mm and 2.0 mm. For amygdala transplantations, injections were made into the basolateral nuclei at AP 1.5 mm, ML 3.65 mm and DV 3.7 mm. Sham-operated controls were injected with an equal volume of vehicle at each site (that is, four sites per hemisphere for hippocampus, one site per hemisphere for amygdala). For migration studies, only a single injection was made into the right, dorsal CA3 region of the hippocampus. For behavior and EEG experiments, transplantations were only considered to be successful if the density and migration of GFP cells in the recipient brain were evenly distributed in both hemispheres and confirmed as ≥30,000 cells (hippocampus, range = 34,200 to 68,100) or ≥5,000 cells (amygdala, range = 5,800 to 8,600) per mouse and ≥600 µm from the injection site; these criteria were met in all mice. Cell viability (74.1 ± 1.7%) and concentration were quantified using 0.5 µl of the cell suspension mixed with 24.5 µl of L-15 medium and 25 µl of Trypan Blue (Sigma) as described previously38. Immunostaining. Mice were transcardially perfused with 4% paraformaldehyde (vol/vol) and free-floating vibratome sections (50 µm) were processed using standard immunostaining procedures12–14. Primary antibodies and dilutions are provided in Supplementary Table 4. For ZnT3 staining, we used a TSA Cyanine 3 System kit (PerkinElmer, NEL704A001KT) for signal amplification. For secondary antibodies (1:500, Invitrogen), we used Alexa 488–conjugated goat antibody to chicken IgG (cat. #A11039) and Alexa 594–conjugated goat antibody to mouse IgG (cat. #A11005), goat antibody to rabbit IgG (cat. #A11012), goat antibody to guinea pig IgG (cat. #A11076) and donkey antibody to goat IgG (cat. #A11058). Sections were then mounted on charged slides (Superfrost plus, Fisher Scientific) with Vectashield that contained DAPI. Images were obtained with a spinning disk confocal microscope (Nikon Yokogawa CSU-X1 Borealis). Epifluorescent images were obtained using a Nikon Eclipse microscope. Brightness and contrast were adjusted manually using Adobe Photoshop. Cell quantification. Transplanted GFP-labeled cells were directly counted in fluorescently labeled sections (50 µm) from recipient mice as described previously12–14. All transplanted cells that expressed GFP were counted in every sixth coronal section in all layers of the entire hippocampus or amygdala (that is, 300 µm apart) using a Nikon Eclipse microscope with a 40× objective.

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Electrophysiology. Coronal brain slices (300 µm thickness) were prepared from recipient mice 60–65 DAT. Slices were submerged in the recording chamber and continuously perfused with oxygenated artificial cerebrospinal fluid (32–34 °C) containing 124 mM NaCl, 3 mM KCl, 1.25 mM NaH2PO4-H2O, 2 mM MgSO47H2O, 26 mM NaHCO3, 10 mM dextrose and 2 mM CaCl2 (pH 7.2–7.4, 300– 305 mOsm kg−1). Whole-cell patch-clamp recordings from GFP-labeled cells were performed at 40× using an upright, fixed-stage microscope (Olympus BX50WI) equipped with infrared differential interference contrast and epifluorescence optics. Patch pipettes (3–5 MΩ) were filled with an internal solution containing 140 mM potassium gluconate, 1 mM NaCl, 5 mM EGTA, 10 mM HEPES, 1 mM MgCl2, 1 mM CaCl2, 3 mM KOH, 2 mM ATP and 0.2% biocytin (wt/vol), pH 7.21. Recordings were obtained with an Axopatch 1D amplifier, filtered at 5 kHz, and recorded to pClamp 10.2 software (Clampfit, Axon Instruments). Spontaneous EPSCs were examined at a holding potential of −70 mV. Series resistance was typically <15 MΩ and was monitored throughout the recordings. Data were only used for analysis if the series resistance remained <20 MΩ and changed by ≤20% during the recordings. Recordings were not corrected for a liquid junction potential. Resting membrane potentials were measured immediately after breakthrough by temporarily removing the voltage clamp and monitoring voltage. For current-clamp recordings, cells were held at −70 mV, and electrophysiological properties were measured in response to a series of long (1,000 ms) hyperpolarizing and depolarizing current-injections (10 pA steps, range = −80–1,000 pA). Data analysis was performed using pClamp 10.2 (Clampfit, Axon Instruments), MiniAnalysis 6.0 (Synaptosoft), Microsoft Excel and Sigmaplot 12.3 programs. A 2-min sample recording per cell was used for measuring EPSC characteristics. Events characterized by a typical fast rising phase and exponential decay phase were manually detected using MiniAnalysis. The threshold for event detection was currents with amplitudes greater than three times the root mean square noise level. Single-cell RT-PCR. At the end of the recording session (<15 min), we aspirated the cytoplasm of the cell into the recording pipette while maintaining a tight seal, similar to methods described previously21. The pipette was carefully removed and its contents (~6 µl) were expelled into a test tube containing 1.5 µl of nuclease free water and 1 µl of RNaseOUT (40 U µl−1) and stored at −80 °C. Samples were incubated with DNase I (Invitrogen) according to manufacturer instructions for complete removal of genomic DNA. Reverse transcription was then performed using 2 µl of 10× reverse transcription buffer, 1 µl of mixed 10mM deoxy NTPs, 4 µl of 25 mM MgCl2, 2 µl of 0.1 M DTT, 1 µl of random hexamer (50 ng µl−1) and 1 µl of SuperScript III reverse transcription (Invitrogen) in a final volume of 22 µl. Next, two consecutive rounds of PCR were performed using outer and nested primer pairs21,39 (Supplementary Table 1). All targets were first amplified simultaneously using 1 µl of each primer (20 pmol µl−1) and 40 µl of 2× GoTaq Green Master Mix in a final volume of 100 µl. Targets were amplified using 5 min of initial denaturation at 94 °C followed by 21 cycles of denaturing at 94 °C for 30 s, annealing at 60 °C for 30 s, elongation at 72 °C for 35 s and 7 min of final elongation at 72 °C. Next, individual targets were re-amplified separately for 20 cycles of PCR with the same thermal cycling conditions using 3 µl of the first PCR product as a template and nested primer sets. Products were assayed on a 1.5% agarose gel stained with ethidium bromide, using a 100-bp DNA ladder (Thermo Scientific) as a molecular weight marker. All primer sets were first verified on 1 ng of total RNA purified from GFP mouse hippocampus using the RT-PCR protocol described above (n = 2 samples; Fig. 2f and Supplementary Table 1). To rule out mRNA contamination from surrounding tissue, we placed patch pipettes into the slice without seal formation and, after the removal of the pipette, processed its content as described above (n = 3 samples). To rule out contamination of reaction materials, PCR was performed using nuclease-free water in place of a sample (n = 5 samples). No PCR product was obtained using these protocols. Video-EEG. EEG recordings were obtained using a time-locked video-EEG monitoring system (Pinnacle Technologies). Each mouse was anesthetized with ketamine and xylazine (10 and 1 mg per kg, intraperitoneal) so that there was no limb-withdrawal response to a noxious foot pinch. Sterile, stainless steel bone screw recording electrodes were placed epidurally through burr holes in the skull (one electrode on either side of the sagittal suture, approximately halfway between bregman and lambdoid sutures and ≈1 mm from the midline) using surface head-mount EEG hardware (Pinnacle Technologies). Electrodes were cemented

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in place with a fast-acting adhesive and dental acrylic. Two wires were laid on the shoulder muscles for electromyographic recording. Mice were allowed to recover for 3 d before experiments were initiated. Electrographic seizures were defined as high-frequency, high-voltage synchronized polyspike or paroxysmal sharp waves with amplitude more than twofold greater than background that lasted ≥15 s. Electrographic EEG seizures were analyzed by two investigators who were blinded to the treatment condition of the mice using SireniaScore software (Pinnacle) and confirmed by offline review of behavioral video recordings obtained at two different viewing angles. Behaviors were scored according to a modified Racine rating scale12,23. Experimental mice were monitored for 7–10 d (24 h d−1). Because electrographic seizure characteristics in untreated and vehicle-injected epileptic mice were comparable in frequency (2.8 ± 0.5 versus 1.9 ± 0.4 seizures per d, P = 0.3, two-tailed t test) and duration (54.4 ± 2.8 versus 56.0 ± 3.1 s, P = 0.8, two-tailed t test), the data from these groups were pooled. A total of 24 d of recording were analyzed for control mice (n = 3), 111 d for untreated or vehicle-treated epileptic mice (n = 14), 64 d for mice that received MGE cell grafts into the hippocampus (n = 8) and 65 d for mice that received MGE cell grafts into the amygdala (n = 8). Behavior. All behavioral testing was conducted during the light phase of the light/dark cycle under the guidance and supervision of the University of California at San Francisco Neurobehavioral Core for Rehabilitation Research facility. Pilocarpine-injected mice and age-matched controls were housed singly starting immediately after the induction of status epilepticus. Mice were tested in two separate groups. Group 1 was subjected to the open field test (before pilocarpine injections), open field test (14 d after pilocarpine injections), handling test around 60 DAT, open field test ~24 h after the handling test, rotarod immediately following the final open field session and then 2–3 d later, and EEG surgery and monitoring. Group 2 (60 DAT) was subjected to the elevated plus maze, Morris water maze and forced swim test. Mouse identities were coded, and all behaviors were performed and analyzed by two investigators who were blinded to the treatment condition of the animals. Open field test. Mice were placed in the center of a 40 × 40 × 38 cm SmartFrame open field arena (Kinder Scientific) for 10 min under standard overhead lighting conditions. Behavioral performance was recorded using a computer-operated tracking system (MotorMonitor, Kinder Scientific). Rotarod. Mice were placed on a rotarod apparatus (UGO-Basile, model 7650) that accelerated from 4 to 40 r.p.m. over 3.5 min and then maintained 40 r.p.m. for another 1.5 min. All mice were first acclimated to the rotarod immediately following the final open field testing session and then tested 2–3 d later. Performance was assessed by measuring the latency until the mouse fell completely off the rod or gripped the device and spun around without attempting to walk on the rod. Three trials were performed and both the r.p.m. reached and total time spent on the rod were averaged across the trials for each mouse. Handling test. Reaction to handling was assessed using a semiquantitative handling test described previously40. The test included four measures: nonstressful handling was performed by rubbing slowly along the back of the mouse in a petting motion in the direction of the grain of fur with a latex-gloved hand, and stressful handling was performed by rubbing vigorously against the grain of fur, pinching at the tail tip with a plastic-tipped hemostat and pinching at the tail base. Each task was performed for 15 s. Reaction to handling was scored for each task using a four-point rating scale in which 1 indicated initial struggle, but calmed within 15 s, 2 indicated struggle for more than 15 s, 3 indicated struggle for more than 15 s and exhibiting one or more defensive reactions (piloerection, flattening of the ears against the head, attempt to bite or back away from the experimenter), and 4 indicated struggled for more than 15 s and exhibited flight behavior (loud vocalization or wild running).

doi:10.1038/nn.3392

Elevated plus maze. The elevated plus maze apparatus (Kinder Scientific) was comprised of two open arms (38 × 2 cm) and two enclosed arms (38 × 2 × 15 cm), elevated 64 cm above the floor level. Mice were placed in the central platform always facing the same open arm. Test duration was 10 min under standard overhead lighting conditions. All data were collected using Ethovision software (Noldus Information Technology). Morris water maze. The Morris water maze task was conducted similar to the method described previously28,41. A white, circular pool (140 cm in diameter) was filled with water (22–24 °C) that was mixed with black, nontoxic paint to make it opaque, and a circular platform (15 cm in diameter) was submerged 1 cm beneath the surface of the water. The testing room was filled with a number of visual cues. Mice were first trained to locate a visible platform (days 1 and 2) and then a submerged hidden platform (days 3–5) in two daily sessions ~3.5 h apart. Each session consisted of three 60-s trials with an intertrial interval of 10–15 min. Mice were allowed to swim until they found the platform and, if they did not find the platform within 60 s, they were guided to it by the experimenter. During visible platform training, the platform was moved to a new, random location quadrant for each session, and mice were placed in a different starting location for each trial. Exclusion criteria for visible platform performance were defined as an average latency (mean of all trials in sessions 3 and 4) greater than the average escape latency plus two s.d. in naive controls28. During the hidden platform task, mice were placed in a different starting location for each trial, but the platform remained in the same location for each trial (in the center of the target quadrant). Time to reach the platform, path length and swim speed were recorded with a video tracking system (Noldus Information Technology). Because there were no substantial differences in average swim speeds between the treatment groups during the visible platform sessions (data not shown), the time required to locate the platform (escape latency) was used as the main mea sure for analysis. A probe trial was conducted 1 h after the final hidden platform testing session; the platform was removed, and mice were placed in the pool and allowed to swim for 60 s. Forced swim test. The mouse forced swim test was conducted similar to the method described previously42. Mice were placed individually into glass cylinders (height = 40 cm, diameter = 15 cm) containing 22 cm of water (22–23 °C) for 6 min. The total duration of immobility was recorded during the last 4 min of the 6-min testing period. A mouse was considered to be immobile when it floated in an upright position and made only minimal movements to keep its head above water. Trials were video recorded and scored offline by an investigator blinded to the experimental outcome of each animal. Statistical analysis. All analyses were performed with SigmaPlot 12.3 software and assessed for normality (Shapiro-Wilk) and variance. Data were compared by t test, one-way ANOVA for multiple comparisons, nonparametric one-way ANOVA on ranks or by two-way repeated-measures ANOVA. A Tukey’s post hoc test was performed when appropriate. Sample sizes for behaviors significantly affected by MGE treatment were determined based on power analysis, as indicated in Supplementary Table 3. Data are expressed as mean ± s.e. and significance was set at P < 0.05. 38. Marchenko, S. & Flanagan, L. Counting human neural stem cells. J. Vis. Exp. 7, 262 (2007). 39. Vucurovic, K. et al. Serotonin 3A receptor subtype as an early and protracted marker of cortical interneuron subpopulations. Cereb. Cortex 20, 2333–2347 (2010). 40. Mortazavi, F., Ericson, M., Story, D., Hulce, V.D. & Dunbar, G.L. Spatial learning deficits and emotional impairments in pentylenetetrazole-kindled rats. Epilepsy Behav. 7, 629–638 (2005). 41. Raber, J., Bongers, G., LeFevour, A., Buttini, M. & Mucke, L. Androgens protect against apilipoprotein E4-induced cognitive deficits. J. Neurosci. 22, 5204–5209 (2002). 42. Can, A. et al. The mouse forced swim test. J. Vis. Exp. 59, 3638 (2012).

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