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Session #6: Clinical & Basic Science Myriam Beaulieu Karen Johal Rebecca Lim Caroline McCamus Ariel Qi
Fidan Sadig Tim Song Andrew Wilk Bernice Wong
Judge: Emily Schaeffer
#45 Myriam Beaulieu
Undergraduate Student, McGill University Supervisor: James Lim, Childhood Diseases Exploring Beta Integrin Subunits Pairing Preference to α6 Integrin Isoforms in Breast Cancer Cell Models
Abstract & Poster - https://bcchr.ca/posterday
Exploring Beta Integrin Subunits Pairing Preference to α6 Integrin Isoforms in Breast Cancer Cell Models Myriam Beaulieu | McGill University B. Sc. | Lim Research Team BC Children’s Hospital Research Institute, Vancouver, BC, Canada
Introduction • Integrins mediate cell adhesion and transmit mechanical and chemical signals to the cell interior • Integrins consist of an alpha and a beta subunit heterodimerized to form functional receptor • α6 can heterodimerize with either β1 or β4 • α6β1 and α6β4 can promote invasive phenotypes in various solid tumors1 • The cytoplasmic tail of α6 can be alternatively spliced into divergent isoforms (α6A and α6B)2 • Unknown whether the cytoplasmic tail sequence can determine recruitment of the β subunit
Results
Discussion #1
Figure 1. Confirmed presence of full length α4, and α4-α6 chimeric constructs in respective α6null clone-1 sub-line using antibodies recognizing specific α4 or α6 domains
#1
#2
To explore expression of total β1 and β4 integrins in MDA-MB231 α4-chimeric rescue cell lines
Method
• •
•
Able to confirm expressions of α4-integrin extracellular domain, α4tail and α6A-tail in MDA-MB-231 α4-chimeric rescue cell lines No significant changes in the total expressions β1 and β4 integrins in α4-α6 chimeric rescued sub-lines as compared to their parental α6null cell line Previously, Lim Lab unpublished data showed that β4 total expression is lost in α6null cells as compared to wildtype MDA-MB231 cells. Re-expressing full-length α6A, but not α6B isoform, restored β4 total expression, suggesting that β4 preferentially pairs with α6A cytoplasmic tail. Together with data obtained in α4-α6 chimeric rescued sub-lines, we showed that, while the extracellular domain of α6 is absolutely essential, α6A cytoplasmic tail preferentially determines β4 expression
Figure 3. Total β4 expression detected in WT and lost in null, reexpressing α6 with cytoplasmic tail A restored β4 expression
Objectives To confirm expressions of α4-integrin extracellular domain, α4tail and α6A-tail in MDA-MB-231 α4-chimeric rescue cell lines.
•
#2 Figure 2. β1 and β4 total expression are comparable in between sub-lines expressing α4-α6 chimeric constructs
Lim lab (unpublished data)
Conclusion • Successful transfection of MDA-MB-231 cell line with α4-α4/6-α6A/B construct • Additional data must be collected and analyzed with dot plot to confirm β1 and β4 expression in-between sub-lines
Acknowledgements BC Children’s Hospital Research Institute Summer Studentship Dr. C. James Lim Ling Li
(1) Stewart RL, O'Connor KL. Clinical significance of the integrin α6β4 in human malignancies. Lab Invest. 2015;95(9):976-86. (2) Zhou Z, Qu J, He L, Peng H, Chen P, Zhou Y. α6-Integrin alternative splicing: distinct cytoplasmic variants in stem cell fate specification and niche interaction. Stem Cell Research & Therapy. 2018;9(1):122.
#46 Karen Johal
Undergraduate Student, University of British Columbia Supervisor: Ali Eslami, Brain, Behaviour & Development Parent versus patient understanding of suicidal crisis: Is a difference in understanding a cause for concern?
Abstract & Poster - https://bcchr.ca/posterday
Parent vs. patient understanding of suicidal crisis: Is a difference in understanding a cause for concern? (1) Johal ,
(1) Surani ,
(1) Tomoum
Karen Simya Rawda , and Dr. Ali (1) BC Children’s Hospital Research Institute, Dept. of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
Background
Methods
Suicidality is a pressing concern among youth and has increased drastically over the years (3). Children and adolescents with suicidal ideations largely benefit from support, whether that be emotional or physical. Parents play a critical role among adolescents who engage in self harming behaviours (1). However, there are many barriers that prevent parents from being able to provide effective support. For instance, a discrepancy in their knowledge of their child’s crisis and its causes. Frequently, especially among minority ethnic groups, older individuals lack understanding and knowledge on mental health, such as what it is and how it impacts their child (2). Therefore, research evaluating parent and patient understanding can be valuable to improve treatment by enhancing support.
• We will perform a secondary analysis of a REDCap data registry which has been collecting information about patients admitted into the Child and Adolescent Psychiatry Emergency Unit (CAPE) for short term stabilization of a psychiatric crisis. • Admittance information on patient and family initial understandings of the causes for the crisis will be extracted, reviewed, and analyzed to obtain results.
(1) Eslami
Their findings indicated that significant efforts are needed to establish a mutual understanding between professionals, parents, and patients on terms such as ‘mental health’ or ’mental illness’ before involvement in child and adolescent mental health planning and development (2).
Implications • The results of this project can contribute to and allow adjustments in treatment plans to better support patients at risk of suicidality. • It can encourage efforts to provide counselling and/or education to patients and their families regarding ways to optimize treatment. • There is little research exploring influences of familial initial understanding and influences on treatment length; therefore, this research can encourage and open the door to exploring this topic further.
Expected Results We anticipate the outcome of our project to show that a lack of common understanding between the patient and their family on the cause of the crisis, will result in a longer stay under psychiatric care.
Previous Results
Future Directions Future studies should explore whether… • A mutual understanding regarding the cause of the suicidal crisis among the patient and their friends has any significant influence on the length of the patient’s treatment? • Parent vs. patient understanding can influence the severity or reoccurrence of the suicidal crisis?
References 1.
McLaughlin, J. A., Miller, P., & Warwick, H. (1996). Deliberate self-harm in adolescents: hopelessness, depression, problems and problem-solving. Journal of adolescence, 19(6), 523-532. https://doi.org/10.1006/jado.1996.0051
2.
Dogra, N., Vostanis, P., Abuateya, H., & Jewson, N. (2005). Understanding of mental health and mental illness by Gujarati young people and their parents. Diversity & Equality in Health and Social Care, 2(2), 91-97 https://www.primescholars.com/articles/understanding-ofmental-health-and-mental-illness-by-gujarati-young-peopleand-their-parents-94797.html
3.
Skinner, R., & McFaull, S. (2012). Suicide among children and adolescents in Canada: trends and sex differences, 1980– 2008. Cmaj, 184(9), 1029-1034. https://doi.org/10.1503/cmaj.111867
Figure A. Deaths by suicide (overall and by suffocation) among Figure B. Perceived parental understanding: percent of female Canadian children and adolescents. Rates were standardized per 100,000 population* using Canadian population in 1991. *Calculated using a 5-point central moving average. (3)
Objective To explore whether differences in initial understanding of the suicidal crisis between the patient and their family is associated with the length of the patient’s stay under psychiatric care.
adolescents reporting high understanding by mother ( father ( ) (1).
) and
They found that compared to a school-control group, the deliberate
self harm (DSH) group perceived that their parents understood them significantly less; however, compared to a clinical control group they reported less perceived parental understanding but not to a significant extent (1). Dogra et al., (2005) conducted a study to gain insight on the understanding of the terms ‘mental health’ and ‘mental illness’, among the sample of Gujrati Hindu people.
Acknowledgements • My work and this project is funded by Dr. Eslami’s lab
Rebecca Lim
#47
Medical Student, University of British Columbia Supervisor: Clare Beasley, Brain, Behaviour & Development Effect of clozapine on brain complement C5b9 protein levels
Abstract & Poster - https://bcchr.ca/posterday
Effects of Clozapine on Complement C5b9 Protein Levels in the Brain Rebecca Lim, Clare Beasley, Li Shao Department of Psychiatry, Faculty of Medicine, University of British Columbia, British Columbia Children’s Hospital Research Institute
BACKGROUND
FIGURES FIGURE 3. Tissue weights and litter size at gestational day 18.5
• Schizophrenia is a severe psychiatric disorder characterized by delusions and hallucinations • 1 in 100 Canadians and 21 million people worldwide are living with schizophrenia (WHO) • Second generation antipsychotics, such as clozapine, are first line for the treatment of schizophrenia
FIG. 1 Flowchart of complement cascade2
• Clozapine is more effective at treating schizophrenia than other medications but negatively affects health • We aren’t sure what causes these side effects but it may have to do with the immune system1
There are 3 ways that the complement cascade can be activated; the alternative, classical, and lectin pathways. The endpoint of all 3 pathways is the formation of C5b9, known as the membrane attack complex. C5b9 can disrupt cell membranes, which is useful in defending the body against invaders.
• Previous Beasley lab study showed that clozapine increased markers of immune activation in the blood of rats • C-reactive protein and complement C9 were increased in rats given clozapine compared to rats given saline • Does clozapine also increase immune activation in the brain? • Complement proteins play an important role in the immune system • Defends against bugs and responds to tissue damage via the membrane attack complex (aka C5b9) • Are there higher levels of the membrane attack complex in rat brains that were exposed to clozapine?
HYPOTHESIS Clozapine increases levels of the membrane attack complex (C5b9) in the brain, causing adverse effects.
METHODS • Rat brain tissue is from a previous study in the Beasley lab where rats were given clozapine, saline, or haloperidol (first-generation antipsychotic) • Western blot technique (method for measuring protein levels) was used to compare amounts of different complement proteins in rat brains exposed to clozapine, haloperidol and saline • Analysis will be conducted using Fuji image quantification system analysis software • Statistics will be conducted using SPSS10 software
SIGNIFICANCE AND FUTURE DIRECTIONS • Being able to predict a person’s risk of side effects • Potential therapies to use in conjunction with clozapine to reduce its side effects
REFERENCES 1. 2.
Woo JJ, et al. Molecular Psychiatry. 2020;25:114-130. Monie T. The Innate Immune System.
ACKNOWLEDGEMENTS
Caroline McCamus
#48
Medical Student, Royal College of Surgeons Ireland Supervisor: Mahmoud Pouladi, Childhood Diseases Leukodystrophy-linked mutant claudin-11 sensitizes cells to endoplasmic reticulum stress-induced death
Abstract & Poster - https://bcchr.ca/posterday
Leukodystrophy-linked mutant claudin-11 sensitizes cells to endoplasmic reticulum stress-induced death Caroline McCamus , Mikayla Poloz, Angeline Wu, Oguz Kaan Ozgoren, Costanza Ferrari Bardile, Sylvia Stockler, Mahmoud A. Pouladi Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, British Columbia Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
Experimental approach
Mutant claudin-11 sensitizes cells to stress-induced death: Serum starvation assay
The endoplasmic reticulum (ER) is the main site for intracellular calcium storage as well as protein synthesis and folding. ER stress-induced cell death is a cellular process that is triggered under a variety of conditions in response to disturbed protein folding in the ER.
• Serum starvation is a well-established assay of cellular stress, causing reduced viability and increased cell death through a number of mechanisms, including ER stress. • Serum starvation caused greater reduction in viability of mutant claudin-11 HEK293 cells
1.5
WT MT
ns
✱✱
1.0 0.5 0.0
W ith Se se ru ru m m W -fre ith e Se se ru ru m m -fr ee
Cell viability (normalized ATP levels)
Background
Mutant claudin-11 sensitizes cells to stress-induced death: Thapsigargin (TG) treatment • TG caused greater reduction in viability & increased cell death in mutant claudin-11 HEK293 cells
Stoploss mutations in CLDN11, the gene encoding the tight junction protein claudin-11, have recently been identified as a novel cause of PMD. How mutant (MT) claudin-11 causes PMD is unclear. In this project, we sought to test the hypothesis that the PMDlinked stoploss mutations in CLDN11 result in misfolding of its encoded protein, sensitizing to ER stress-induced cell death.
• The stoploss mutation is predicted to result in the addition of 39 amino acids to claudin-11 (A). • Consistent with this prediction, WB analysis showed an increase in the molecular weight of MT claudin-11 (B) and a decrease in its levels (C).
A
B Claudin-11
50 37 25 Predicted addition 20 of 39 amino acids 15 due to stoploss 10
WT
C
MT beta-actin Claudin-11
Claudin-11/β-actin (normalized to WT)
There are several diseases associated with ER-stress induced cell death, including Pelizaeus-Merzbacher disease (PMD), a rare, progressive, hypomyelinating condition associated with damage and degeneration of oligodendrocytes in the central nervous system. Patients with PMD show symptoms such as muscular trunk rigidity, spasticity of extremities, nystagmus and strabismus.
Stoploss mutation causes a shift in claudin-11’s molecular weight and decreases its protein levels
1.0
0.5
*** 0.0 WT MT
1.5
Cell death
G: P < 0.0001 D: P < 0.0001 GxD: P = 0.0006
1.0
**
0.5
***
***
0.0 0
0.5
1
3
6
Thapsigargin [µM]
Cytotoxicity - LDH assay (normalised to DMSO)
Results
Viability - ATP assay (normalised to DMSO)
Cell viability 2.0 1.5
G: P < 0.0006 D: P < 0.2000 GxD: P < 0.0295
**
**
WT MT
1.0 0.5 0.0 0
3
6
Thapsigargin [µM]
Conclusion
The stoploss mutation in CLDN11 altered the structure/stability of claudin11 and sensitized cells to ER stress-induced cell death. Overall our findings suggest that ER stress may contribute to CLDN11-induced leukodystrophy.
Acknowledgments
This research was funded by the grants to Dr. Mahmoud A Pouladi. I would like to thank the Pouladi lab for their support in this research.
Supported by the BC Children’s Hospital Foundation, the Rare Disease Discovery Hub (BCCHR), and the Canadian Rare Disease: Models & Mechanisms Network (RDMM).
pouladilab.org
Ariel Qi
#49
Recent Graduate, University of British Columbia Supervisor: Evelyn Stewart, Brain, Behaviour & Development COVID-19 Era Psychiatric Illness among Canadians: Exploring Intersectionality of Vulnerability Factors
Abstract & Poster - https://bcchr.ca/posterday
COVID-19 Era Psychiatric Illness among Canadians: Exploring Intersectionality of Vulnerability Factors Ariel (Ruo Chen) Qi
1,2,
John R. Best
1,2,
Anna MacLellan
1,2,
Boyee Lin
1,2,
Cynthia Lu
1,2,
Zainab Naqqash
1,2,
Hasina Samji
2,3,
S. Evelyn Stewart
1,2
1Department
of Psychiatry, University of British Columbia, Vancouver B.C. 2British Columbia Children’s Hospital Research Institute, Vancouver B.C. 3British
Introduction
Columbia Centre for Disease Control, Vancouver B.C.
Methods During the COVID-19 pandemic, Canadians faced unprecedented daily restrictions, social isolation and life challenges.
Personal Impacts of COVID-19 study (PICS) examined predictors for clinically relevant mental health (MH) outcomes following the first Canadian pandemic wave1. PICS identified poverty, limited education, LGBTQ2S+ status, and lifetime medical diagnoses as predictors for poor MH outcomes1.
“Intersectionality is a lens through which you can see where power comes and collides, where it interlocks and intersects. It’s not simply that there’s a race problem here, a gender problem here, and a class or LBGTQ problem there. Many times that framework erases what happens to people who are subject to all of these things.” ~ Dr. Kimberlé Crenshaw
Proposed Study Rationale: Given the complexities in MH determinants, there remains a need to investigate COVID-era clinically relevant MH outcomes among Canadians, through an intersectionality lens. Project Aims: 1. Examine pandemic-era MH outcomes of Canadians, in relation to 2-way identity intersections across ethnicity, gender, LGBTQ2S+ status, education level and poverty (household income below $75,000 and/or food insecurity)
2. Identify the intersecting identities most vulnerable to poor MH outcomes
Results
We analyzed baseline online survey data from 1559 Canadians (age range: 8 to 70+ y), obtained from targeted multi-source recruitment. MH outcome: presence or absence of probable depression, generalized anxiety disorder, obsessivecompulsive disorder and/or pandemic-era suicide attempt. Statistical Analyses: • Multivariable logistic regression models: MH outcome variable regressed on identity variables and covariates • Ten categorical variables created to encode for each of the identity intersections • Ten models constructed to separately examine each intersection • A significance threshold of p<0.005 was utilized to account for multiple testing
Discussion & Conclusion
Non-Poverty; LGBTQ
Our analyses reveal several intersectional identities which are significant predictors for poor MH outcome, including:
2.07 *
Non-Poverty; LGBTQ prefer not to answer
LGBTQ2S+ & Poverty
5.02 ***
Poverty; LGBTQ Poverty; LGBTQ prefer not to answer Poverty; Non-LGBTQ
LGBTQ2S+ & Limited Education
2.23 ***
Poverty & Limited Education
Figure 1. Risk for poor MH outcome across the Poverty-LGBTQ2S+ identity intersection. Odds Ratios in reference to Non-Poverty and Non-LGBTQ identity. Horizontal bars represent 99.5% confidence interval.
Statistical comparisons suggest no significant additive effect of the vulnerable identities on MH outcome
LGBTQ; ↑Education LGBTQ prefer not to answer; ↑Education LGBTQ prefer not to answer; Education prefer not to answer
Study Participants Ethnicity/Race White East/central Asian First Nations/Metis Multi Other South Asian Ethnicity/Race (binary) White Non-White Gender Male Female Other LGBTQ2S+ No
Future Directions 4.19 **
LGBTQ; ↓Education
Numbers (and Percentages) 1174 (75.3%) 72 (4.6%) 35 (2.2%) 120 (7.7%) 93 (6.0%) 65 (4.2%) 1174 (75.3%) 385 (24.7%) 286 (18.3%) 1228 (78.8%) 45 (2.9%) 1301 (83.5%)
Prefer not to answer
51 (3.3%)
Yes Education (parent/adult) Bachelors or more
207 (13.3%)
Less than Bachelors
562 (36.0%)
Prefer not to answer
15 (1.0%)
Poverty Non-Poverty Poverty
911 (58.4%) 648 (41.6%)
982 (63.0%)
Table 1. Participant characteristics breakdown based on ethnicity, gender, LGBTQ2S+, education and poverty status.
Non-LGBTQ; Education prefer not to answer
2. Explore mediators/explanatory factors for intersectional inequalities in MH outcome
LGBTQ prefer not to answer; ↓Education Non-LGBTQ; ↓Education
Figure 2. Risk for poor MH outcome across the Education-LGBTQ2S+ identity intersection. Odds Ratios in reference to Non-LGBTQ and high education identity. Horizontal bars represent 99.5% confidence interval.
There is still limited research on the intersectionality of MH determinants; and quantitative methods to assess intersectionality requires further standardization
References
Non-Poverty; ↓Education Non-Poverty; Education prefer not to answer Poverty; ↓Education
1. Assess how intersectional vulnerable identities fair over time with regards to MH outcome
3.39 ***
1. Stewart S.E., Best J.R., Selles R, Naqqash Z, Lin B, Lu C, Au A, Snell G, Westwell-Roper C, Vallani T, Ewing E, Dogra K, Doan Q, Samji H. Determinants of Clinically-Relevant Psychiatric Problems and Unmet Mental Health Support Needs among Canadians following the initial COVID-19 Wave: Baseline Results from a Cohort Online Survey Study. [Manuscript submitted for publication].
Poverty; Education prefer not to answer Poverty; ↑Education
2.07 ***
Figure 3. Risk for poor MH outcome across the Poverty-Education identity intersection. Odds Ratios in reference to Non-Poverty and high education identity. Horizontal bars represent 99.5% confidence interval. Significance levels: *, p<0.005; **, p<0.001; ***, p<0.0001
Acknowledgements
#50 Fidan Sadig
Undergraduate Student, University of British Columbia Supervisor: Wendy Robinson, Healthy Starts microRNA Expression In Healthy Human Placenta
Abstract & Poster - https://bcchr.ca/posterday
MicroRNA Expression in Healthy Human Placentas A Comparison Study Fidan Sadig
1, 2
, Nikita Telkar
1,2
2
, Maria Penaherrera , Wendy P. Robinson
2
1. University of British Columbia. 2. British Columbia Children’s Hospital Research Institute, Vancouver, BC, Canada
The placenta is a vital organ developed during pregnancy and its healthy functioning is essential to support the fetus A way to monitor the change of state of the fetus and the progress of pregnancy, is to check the levels of microRNAs (small molecules that modify gene regulation)
Differential Expression of 17 common microRNA by chromosome
Which are the microRNAs expressed during pregnancy, and what influences their change?
30 placentae at progressive gestational ages
+ 94 placentae from publicly available data Step 1: Data Exploration Step 2: Quality Control Step 3: Differential Analysis Step 4: Data Comparison
Contribution of Variables: Robinson
Robinson vs Public Data
Contribution of Variables: Public
Take home messages 17 microRNAs were found to be differentially expressed in the lab data and compared to the public data, and only one showed similar expression. . Both biological variables (Trimester) and technical (batch effect) ones can contribute to the variation.
Github
Blog
Tim Song
#51
Recent Graduate, Amherst College Supervisor: Evelyn Stewart, Brain, Behaviour & Development Improving health outcomes and access to care using digital pediatric mental health services during COVID-19: A systematic review Abstract & Poster - https://bcchr.ca/posterday
Improving health outcomes and access to care using digital pediatric mental health services during COVID-19: A systematic review Tim Song
1,2,3,
1Department
Anna MacLellan
1,2,3,
S. Evelyn Stewart
1,2,3
of Psychiatry, University of British Columbia, Vancouver, B.C.
2British
Columbia Children’s Hospital Research Institute, Vancouver, B.C. 3British Columbia Mental Health and Substance Use Services Research Institute, Vancouver, B.C.
Introduction
Methods
The COVID-19 pandemic has accelerated the implementation of digital mental health services, adapting to address elevated anxiety/stress levels and remove barriers to accessing care. Why children?
• 14% of Canadian children (approx. 1.1 million • Digital mental health services prevent children) suffer from psychiatric disorders, requiring transmission of infection and provides timely a multifaceted approach to mental health services treatment to the community members most in regardless of in-person pandemic restrictions.2 need, increasing access to care. • The global onset of one’s first mental disorder occurs before age 18 in almost half (48.4%) individuals; early intervention is important in improving health outcomes3.
Expected Outcomes Inclusion Criteria • Sample population includes patients ages below 18. • Intervention includes any clinical mental health service provided digitally/virtually. Platform examples
Why digital health?
• Perceived mental health of Canadian youth sharply • In health outcomes and satisfaction with care, declined during the COVID-19 pandemic compared digital healthcare services were comparable or to other age groups: over half (57%) of participants better than in-person services for general aged 15 to 17 reported worse mental health than pediatric care4 and mostly positive and beneficial prior to physical distancing measures.1 to patients of racial/ethnic minorities.5
• Despite quickly developing interventions, limited research on pediatric digital mental health service effectiveness and impact on barriers to accessing to care.
Results
• • • • •
Service examples
video-conferencing (Zoom) e-mails telephone contact phone and web applications virtual reality interventions
• • • • • •
diagnostic assessments psychotherapy training or coaching mental health monitoring behavioural interventions sharing of health-care resources
• Must contain at least one of three: 1. reported individual health outcomes (eg, physical or mental health) 2. reported health service outcomes (eg, readmission rates, barriers to implementation); 3. reported levels of access, barriers, or utilization of virtual mental health services • Published during COVID-19 pandemic (refined between March 2020 - current). • Published in a peer-reviewed journal. • Literature is written in English. Exclusion Criteria • Studies without data on children ages 0-18. • Non-clinical telehealth services • Literature that is not peer-reviewed (gray literature) • Opinion pieces, reviews, meta-analyses.
1. Effects of transferring to digital mental health services on children during COVID-19 2. Reported access barriers and facilitators to digital mental health services for children 3. Demographics impacted by digital mental health services 4. Digital health aspects more/less successful in improving mental health outcomes i.e. psychotherapy, initial assessment, medication management, interventions, etc. Authors/Study
Digital Health Sample population/ Intervention demographics
-
-
Outcome #3
Study findings (health outcomes) Outcome #1
Study findings Study findings (delivery (access to care outcomes) outcomes) Outcome #4 Outcome #2
• While digital pediatric mental healthcare likely broadly improves health outcomes and access to care, its impact may be limited in underserved communities (i.e. rural, low-income, or non-white children)6. • Currently in Title/Abstract screening stage (317 studies imported); continued eligibility and data collection for manuscript preparation by mid-September.
Future Directions 1. Implementation of digital mental health services with improvements/adjustments to specifically target reported barriers to care, particularly in vulnerable demographics. 2. Increase accessibility and effectiveness of digital mental health services post-pandemic. 3. Frameworks to risk-assess situations for which digital mental health services are appropriate.
Rationale: Given that childhood is a critical period for the development and treatment of mental health concerns, and that COVID-19 has disrupted this process, it is critical to identify vulnerable pediatric populations and reported access barriers via a robust systematic review to assess the feasibility of digital mental health interventions while keeping post-pandemic implementation in mind.
Electronic Search Databases
Search Term Categories 1 2 3
Aims To identify effectiveness of digital mental healthcare interventions on improving health outcomes and access to care in children during the COVID-19 pandemic. The following questions are to be addressed during this systematic review:
1. What has been the effect of transferring mental health services to digital platforms and interventions on children during COVID-19? …in particular mental illnesses, i.e. depression, anxiety, OCD?
4 Individually added 55 papers from references from relevant literature.
“telehealth”, “telemedicine”, “virtual”, “online”, “digital”, etc. “mental health”, “mental illness”, “mental disorder”, “anxiety”, “depression”, etc. “pediatric*”, “child*”, “adolescent”, “teen*”, “infant”, “youth”, “toddler”, “school-aged” "COVID-19" OR "COVID19" OR "SARS CoV-2" OR "SARS-Cov-2”, etc.
Title/Abstract Screening
Eligibility Screening • Full text review of papers to assess eligibility, according to inclusion and exclusion criteria.
reviewers; conflicts settled in discussion with third reviewer.
2. What are the reported access barriers and facilitators to digital mental health services for children?
References 1Canadian
Community Health Survey, 2019 (2021, March 4). Impacts on mental health. Government of Canada, Statistics Canada. https://www150.statcan.gc.ca/n1/pub/11-631-x/2020004/s3-eng.htm 2Waddell, C., Offord, D. R., Shepherd, C. A., Hua, J. M., & McEwan, K. (2002). Child psychiatric epidemiology and Canadian public policy-making: the state of the science and the art of the possible. Canadian journal of psychiatry. Revue canadienne de psychiatrie, 47(9), 825–832. https://doi.org/10.1177/070674370204700903 3Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., de Pablo, G. S., Il Shin, J., Kirkbride, J. B., Jones, P., Kim, J. H., Kim, J. Y., Carvalho, A. F., Seeman, M. V., Correll, C. U., & Fusar-Poli, P. (2022). Age at onset of mental disorders worldwide: Large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry, 27(1), 281–295. https://doi.org/10.1038/s41380-021-01161-7 4Shah, A. C., & Badawy, S. M. (2021). Telemedicine in Pediatrics: Systematic Review of Randomized Controlled Trials. JMIR pediatrics and parenting, 4(1), e22696. https://doi.org/10.2196/22696 5Truong, M., Yeganeh, L., Cook, O., Crawford, K., Wong, P., & Allen, J. (2022). Using telehealth consultations for healthcare provision to patients from non-Indigenous racial/ethnic minorities: a systematic review. Journal of the American Medical Informatics Association : JAMIA, 29(5), 970–982. https://doi.org/10.1093/jamia/ocac015 6Stewart S.E., Best J.R., Selles R, Naqqash Z, Lin B, Lu C, Au A, Snell G, Westwell-Roper C, Vallani T, Ewing E, Dogra K, Doan Q, Samji H. Determinants of Clinically-Relevant Psychiatric Problems and Unmet Mental Health Support Needs among Canadians following the initial COVID-19 Wave: Baseline Results from a Cohort Online Survey Study. [Manuscript submitted for publication].
Data Collection 3. Which demographics are most impacted by digital mental health services? 4. Which aspects of digital health services are more/less successful in improving mental health outcomes?
Basic study information
country of study, health setting, study aim, study design, sample size
Participant characteristics
demographics (i.e. gender, age, race/ethnicity/cultural background), socioeconomic status (family income), living environment (urban/suburban/rural), health condition(s), digital health intervention details
Study findings
physical and psychological health outcomes, reported access to healthcare, care delivery outcomes (satisfaction, implementation barriers and facilitators)
Acknowledgements
Andrew Wilk
#52
Undergraduate Student, University of Southern California Supervisor: Dan Goldowitz, Brain, Behaviour & Development The role of genetics in a choline intervention for fetal alcohol spectrum disorder (FASD) in a mouse model
Abstract & Poster - https://bcchr.ca/posterday
The role of genetics in a choline intervention for fetal alcohol spectrum disorder (FASD) in a mouse model Andrew Wilk1, Fannia Xu1, Cheryl Tan1, Samuel Mok1, Yasaman Hariri1, Jennifer Thomas2, Daniel Goldowitz1, Kristin Hamre3 1Centre
for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, Canada; 2Department of Psychology, San Diego State University, San Diego, CA; 3Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN
BACKGROUND Fetal ethanol exposure has numerous detrimental developmental effects, one being increased levels of apoptosis in the neural tube, which is believed to contribute to the development of Fetal Alcohol Spectrum Disorder (FASD)2.
RESULTS N=7 N=6
*
N=6
FASD symptoms vary greatly in their severity among individuals and can manifest neuropsychologically or as overt physical abnormalities7.
N=6
FASD is the most widespread preventable developmental disability globally, with an estimated prevalence between 1-5%1. There is currently no cure for the condition7.
N=6 N=7
The nutrient choline has been shown to ameliorate some of ethanol’s teratogenic effects3. Different mouse strains exhibit differential susceptibility to alcohol’s teratogenic effects during development4. C57BL/6(B) and DBA/2J(D) are two such strains and BXD recombinant inbred mice, derived from crossing the B and D strains, are a model panel of mice to study the genetics and epigenetics of alcohol-related disorders5.
Figure 2A. Effect of different doses of choline on cell death in the brainstem of BXD73 embryos, analyzed using one-way analysis of variance (ANOVA) (p = 0.701, F = 0.363). Y-axis represents the average density of apoptotic cells per mm2 in EtOHtreated groups minus the average density of apoptotic cells in MD-treated groups. Student’s t-test showed no significant differences between groups.
Figure 2B. Effect of different doses of choline on cell death in the forebrain of BXD73 embryos, analyzed using one-way ANOVA (p = 0.058, F = 3.374). Y-axis represents the average density of apoptotic cells per mm2 in EtOH-treated groups minus the average density of apoptotic cells in MD-treated groups. Student’s t-test showed a significant difference between the 0 mg/kg and 100 mg/kg groups (p = 0.041). *p < 0.05
OBJECTIVES 1. Determine if choline reduces ethanol-induced cell death in the neural tube of BXD mouse embryos. 2. Determine if choline is equally effective in different regions of the neural tube (brainstem and forebrain) and across various strains of BXD mice.
N=6
N=4
N=4
METHODS 1. Mating: Male and female mice of the same, high cell death strain are mated during a 4 hour period.
2. Treatment: Pregnant dams are treated at E9.0 with 5.8 g/kg of either ethanol (EtOH) or maltose-dextrin (MD) sugar control and 0, 100, or 250 mg/kg choline via gavage.
3. Isolation: Embryos are collected 7 hours after treatment, fixed in paraformaldehyde, and embedded in paraffin wax.
4. Sectioning & Mounting: Embedded embryos are sectioned at 8 μm and mounted onto glass slides.
5. TUNEL Staining: Slides are stained with TUNEL assays to distinguish apoptotic cells in the forebrain and brainstem (Figure 1).
6. Analysis: TUNEL+ cells are counted in each region of interest and divided by the total area of the region.
N=6
N=6 N=6
Figure 3A. Effect of different doses of choline on cell death in the brainstem of BXD2 embryos, analyzed using one-way ANOVA (p = 0.220, F = 1.704). Y-axis represents the average density of apoptotic cells in EtOH-treated groups minus the average density of apoptotic cells in MD-treated groups. Student’s t-test showed no significant differences between groups. N=6
Figure 3B. Effect of different doses of choline on cell death in the forebrain of BXD2 embryos, analyzed using one-way ANOVA (p = 0.230, F = 1.647). Y-axis represents the average density of apoptotic cells in EtOH-treated groups minus the average density of apoptotic cells in MD-treated groups. Student’s t-test showed no significant differences between groups.
*
N=6
*
N=6 N=6 N=6
N=6
Figure 4A. Effect of different doses of choline on cell death in the brainstem of BXD51 embryos, analyzed using one-way ANOVA (p = 0.018, F = 5.300). Y-axis represents the average density of apoptotic cells per mm2 in EtOH-treated groups minus the average density of apoptotic cells in MD-treated groups. Student’s ttest showed a significant difference between the 0 mg/kg and 100 mg/kg (p = 0.028) and between the 0 mg/kg and 250 mg/kg groups (p = 0.014). *p < 0.05
Figure 4B. Effect of different doses of choline on cell death in the forebrain of BXD51 embryos, analyzed using one-way ANOVA (p = 0.140, F = 2.244). Y-axis represents the average density of apoptotic cells in EtOH-treated groups minus the average density of apoptotic cells in MD-treated groups. Student’s t-test showed no significant differences between groups.
CONCLUSIONS + FUTURE DIRECTIONS Choline significantly reduced ethanol-induced cell death in the brainstem of BXD51 embryos and forebrain of BXD53 embryos.
ACKNOWLEDGEMENTS & REFERENCES The authors would like to thank Elizabeth Nguyen and Constance de Schaetzen for their assistance with tissue sectioning and mounting.
Its efficacy was not consistent in different neural tube regions nor across different strains of BXD embryos. This suggests that genetic differences may affect choline’s ability to reduce ethanol-induced cell death in the neural tube. Figure 1. Images of apoptotic (TUNEL+) cells in the forebrain (A) and brainstem (B) of embryos from high cell death BXD strains, imaged at 20x magnification. Panels C and D show the same sections at 40x magnification. TUNEL+ cells are brown and non-apoptotic cells are blue-green. Original images from Théberge et al. (2018).
Future research could investigate more BXD strains and attempt to elucidate candidate genes for the differential choline response through quantitative analysis.
NIH Grant R01AA023508 1May,
P. A., Chambers, C. D., Kalberg, W. O., Zellner, J., Feldman, H., Buckley, D., Kopald, D., Hasken, J. M., Xu, R., Honerkamp-Smith, G., Taras, H., Manning, M. A., Robinson, L. K., Adam, M. P., Abdul-Rahman, O., Vaux, K., Jewett, T., Elliott, A. J., Kable, J. A., . . . Hoyme, H. E. (2018). Prevalence of fetal alcohol spectrum disorders in 4 US communities. JAMA : The Journal of the American Medical Association, 319(5), 474-482. 2Sokol, R. J., Delaney-Black, V., & Nordstrom, B. (2003). Fetal alcohol spectrum disorder. Jama, 290(22), 2996-2999. 3Thomas, J. D., Abou, E. J., & Dominguez, H. D. (2009). Prenatal choline supplementation mitigates the adverse effects of prenatal alcohol exposure on development in rats. Neurotoxicology and Teratology, 31(5), 303-311. 4Théberge, E. T., Baker, J. A., Dubose, C., Boyle, J. K., Balce, K., Goldowitz, D., & Hamre, K. M. (2018). Genetic influences on the amount of cell death in the neural tube of BXD mice exposed to acute ethanol at mid-gestation. Alcoholism, Clinical and Experimental Research, 43(3), 439-452. 5Philip, V. M., Duvvuru, S., Gomero, B., Ansah, T. A., Blaha, C. D., Cook, M. N., Hamre, K. M., Lariviere, W. R., Matthews, D. B., Mittleman, G., Goldowitz, D., & Chesler, E. J. (2010). High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains. Genes, Brain and Behavior, 9(2), 129-159. 6Fischer, L. M., Da Costa, K. A., Galanko, J., Sha, W., Stephenson, B., Vick, J., & Zeisel, S. H. (2010). Choline intake and genetic polymorphisms influence choline metabolite concentrations in human breast milk and plasma. The American Journal of Clinical Nutrition, 92(2), 336-346. 7Wilhoit, L. F., Scott, D. A., & Simecka, B. A. (2017). Fetal Alcohol Spectrum Disorders: Characteristics, Complications, and Treatment. Community mental health journal, 53(6), 711–718.
Bernice Wong
#53
Undergraduate Student, University of British Columbia Supervisor: Bruce Vallance, Childhood Diseases Developing an ex vivo assay to examine composition and functional changes in individual gut microbiome from stool
Abstract & Poster - https://bcchr.ca/posterday
Developing an ex vivo assay to examine composition and functional changes in individual gut microbiome from stool Bernice Wong1, Christine McCulloch1, Catherine Chan1, Ho Pan Sham1, Roger Dyer2, David Levy-Booth3, Bruce Vallance1,4 1. Gut4Health Microbiome Profiling Core, British Columbia Children’s Hospital Research Institute, Vancouver, BC, Canada; 2. Analytical Core for Metabolomics and Nutrition, British Columbia Children’s Hospital Research Institute, Vancouver, BC, Canada; 3. University of British Columbia Sequencing and Bioinformatics Consortium, Vancouver, BC, Canada; 4. Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
Introduction • •
•
The gut microbiome and short-chain fatty acids (SCFAs), including acetic, butyric, and propionic acid, contribute to the host’s health.1,2,3 SCFAs are generated by the gut microbiota through bacterial fermentation of indigestible carbohydrates, such as inulin and starch, and oligosaccharides, which are found on mucin.2 There are limited methods that allow for the investigation of the individual gut microbiome and its functionality in a clinical setting.
Results A
B Figure 5. Reproducible SCFA concentration trends of C57BL/6 mice stool samples. Following the general setup of the
Figure 1. Bacterial fermentation in the gut produces short-chain fatty acids (SCFAs). Indigestible carbohydrates, including dietary fibres and resistant starch, as well as oligosaccharides can be used for SCFA production by bacteria found in the gut. The most abundant SCFAs produced includes acetic, butyric, and propionic acid.
Objective • To develop an ex vivo assay to allow for direct examination of different substrate’s influence on the gut microbiome and its functionality by pairing analysis of the microbiome composition and SCFA concentrations.
Methods
Figure 3. Detectable changes in the microbiome after a 24 hour incubation. 0%, 10%, and 25 % BHI were inoculated with human stool sample in replicates of three. Samples were collected before (0hr) and after (24hr) a 24 hour anaerobic incubation for microbiome analysis by 16S sequencing. (A) Principal coordination analysis (PCoA) plot shows apparent separate clustering of samples collected at 0hr and 24hr. (B) At the phylum level, expansion of Bacteroidetes and Proteobacteria were noted after the incubation period for all tested BHI percentages.
assay (Fig1.), C57BL/6 mice stool sample was inoculated into 10% BHI. Samples were spiked with PBS as a control or with inulin, starch, and mucin. Three technical replicates of each condition was performed and all samples were analyzed with GC-MS/MS for SCFA concentrations. Two separate runs of the same stool sample were performed.
Conclusion •
• •
This ex vivo assay is: • Sensitive to microbiome compositional changes • Able to differentiate between different individual gut microbiome functionality • Reproducible Limitations: With 24 hours of incubation, microbiome composition shifts This ex vivo assay has the potential of being utilized as a drug testing platform and method in determining influence of differing diets on individual gut microbiome and SCFA concentration for clinical use.
References 1. Nogal, A., Valdes, A. M., & Menni, C. (2021). The role of short-chain fatty acids in the interplay between gut microbiota and diet in cardio-metabolic health. Gut Microbes, 13(1), 124. https://doi.org/10.1080/19490976.2021.1897212 2. Silva, Y. P., Bernardi, A., & Frozza, R. L. (2020). The role of short-chain fatty acids from gut microbiota in gut-brain communication. Frontiers in Endocrinology (Lausanne), 11, 2525. https://doi.org/10.3389/fendo.2020.00025 3. Tsukuda, N., Yahagi, K., Hara, T., Watanabe, Y., Matsumoto, H., Mori, H., Higashi, K., Tsuji, H., Matsumoto, S., Kurokawa, K., & Matsuki, T. (2021). Key bacterial taxa and metabolic pathways affecting gut short-chain fatty acid profiles in early life. The ISME Journal, 15(9), 25742590. https://doi.org/10.1038/s41396-021-00937-7
Figure 2. An overview of the ex vivo assay setup. • Weighed human or C57BL/6 mice stool sample were inoculated into different concentrations of Brain Heart Infusion (BHI) broth, added with substrates. As a control, Phosphate-Buffered Saline (PBS) was added. • Baseline is collected while remainder of samples incubate 24 hour anaerobically, followed by sample collection. • Microbiome composition and SCFA concentrations are determined by 16S sequencing and gas chromatography-tandem mass spectrometry (GCMS/MS) respectively.
Figure 4. Different human donor stool samples yield varying SCFA concentrations. Following the general ex vivo assay setup (Fig.1), two different human donors were inoculated into 10% BHI that were either spiked with PBS as a control or with inulin, starch, and mucin. Three technical replicates of each conditions were performed. All samples were collected and run through GC-MS/MS for SCFA analysis.
Acknowledgments Dr. Bruce Vallance Dr. Ho Pan Sham Dr. Catherine Chan