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Dickie EW, Ameis SH, Boileau I, Diaconescu AO, Felsky D, Goldstein BI, Gonçalves V, Griffiths JD, Haltigan JD, Husain MO, Rubin-Kahana DS, Iftikhar M, Jani M, Lai MC, Lin HY, MacIntosh BJ, Wheeler AL, Vasdev N, Vieira E, Ahmadzadeh G, Heyland L, Mohan A, Ogunsanya F, Oliver LD, Zhu C, Wong JKY, Charlton C, Truong J, Yu L, Kelly R, Cleverley K, Courtney DB, Foussias G, Hawke LD, Hill S, Kozloff N, Polillo A, Rotenberg M, Quilty LC, Tempelaar W, Wang W, Nikolova YS, Voineskos AN. Neuroimaging and Biosample Collection in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:275-284. [PMID: 37979944 DOI: 10.1016/j.bpsc.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/11/2023] [Accepted: 10/17/2023] [Indexed: 11/20/2023]
Abstract
BACKGROUND The Toronto Adolescent and Youth (TAY) Cohort Study will characterize the neurobiological trajectories of psychosis spectrum symptoms, functioning, and suicidality (i.e., suicidal thoughts and behaviors) in youth seeking mental health care. Here, we present the neuroimaging and biosample component of the protocol. We also present feasibility and quality control metrics for the baseline sample collected thus far. METHODS The current study includes youths (ages 11-24 years) who were referred to child and youth mental health services within a large tertiary care center in Toronto, Ontario, Canada, with target recruitment of 1500 participants. Participants were offered the opportunity to provide any or all of the following: 1) 1-hour magnetic resonance imaging (MRI) scan (electroencephalography if ineligible for or declined MRI), 2) blood sample for genomic and proteomic data (or saliva if blood collection was declined or not feasible) and urine sample, and 3) heart rate recording to assess respiratory sinus arrhythmia. RESULTS Of the first 417 participants who consented to participate between May 4, 2021, and February 2, 2023, 412 agreed to participate in the imaging and biosample protocol. Of these, 334 completed imaging, 341 provided a biosample, 338 completed respiratory sinus arrhythmia, and 316 completed all 3. Following quality control, data usability was high (MRI: T1-weighted 99%, diffusion-weighted imaging 99%, arterial spin labeling 90%, resting-state functional MRI 95%, task functional MRI 90%; electroencephalography: 83%; respiratory sinus arrhythmia: 99%). CONCLUSIONS The high consent rates, good completion rates, and high data usability reported here demonstrate the feasibility of collecting and using brain imaging and biosamples in a large clinical cohort of youths seeking mental health care.
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Affiliation(s)
- Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Isabelle Boileau
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Andreea O Diaconescu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Daniel Felsky
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Benjamin I Goldstein
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Vanessa Gonçalves
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - John D Griffiths
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - John D Haltigan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Muhammad O Husain
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Dafna S Rubin-Kahana
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Myera Iftikhar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Melanie Jani
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; National Taiwan University Hospital and College of Medicine, Taiwan
| | - Hsiang-Yuan Lin
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Bradley J MacIntosh
- Sunnybrook Research Institute, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Oslo University Hospital, Oslo, Norway
| | - Anne L Wheeler
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Hospital for Sick Children, Neurosciences and Mental Health, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Neil Vasdev
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Erica Vieira
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ghazaleh Ahmadzadeh
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Lindsay Heyland
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Acadia University, Wolfville, Nova Scotia, Canada
| | - Akshay Mohan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Feyi Ogunsanya
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychology, Western University, London, Ontario, Canada
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Cherrie Zhu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Lunenfeld-Tanenbaum Research Institute at Sinai Health, Toronto, Ontario, Canada
| | - Jimmy K Y Wong
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Colleen Charlton
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Jennifer Truong
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Lujia Yu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Rachel Kelly
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Kristin Cleverley
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Darren B Courtney
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - George Foussias
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Lisa D Hawke
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Sean Hill
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Nicole Kozloff
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Alexia Polillo
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Martin Rotenberg
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Lena C Quilty
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Wanda Tempelaar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Wei Wang
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Yuliya S Nikolova
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
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Tio ES, Misztal MC, Felsky D. Evidence for the biopsychosocial model of suicide: a review of whole person modeling studies using machine learning. Front Psychiatry 2024; 14:1294666. [PMID: 38274429 PMCID: PMC10808719 DOI: 10.3389/fpsyt.2023.1294666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/21/2023] [Indexed: 01/27/2024] Open
Abstract
Background Traditional approaches to modeling suicide-related thoughts and behaviors focus on few data types from often-siloed disciplines. While psychosocial aspects of risk for these phenotypes are frequently studied, there is a lack of research assessing their impact in the context of biological factors, which are important in determining an individual's fulsome risk profile. To directly test this biopsychosocial model of suicide and identify the relative importance of predictive measures when considered together, a transdisciplinary, multivariate approach is needed. Here, we systematically review the emerging literature on large-scale studies using machine learning to integrate measures of psychological, social, and biological factors simultaneously in the study of suicide. Methods We conducted a systematic review of studies that used machine learning to model suicide-related outcomes in human populations including at least one predictor from each of biological, psychological, and sociological data domains. Electronic databases MEDLINE, EMBASE, PsychINFO, PubMed, and Web of Science were searched for reports published between August 2013 and August 30, 2023. We evaluated populations studied, features emerging most consistently as risk or resilience factors, methods used, and strength of evidence for or against the biopsychosocial model of suicide. Results Out of 518 full-text articles screened, we identified a total of 20 studies meeting our inclusion criteria, including eight studies conducted in general population samples and 12 in clinical populations. Common important features identified included depressive and anxious symptoms, comorbid psychiatric disorders, social behaviors, lifestyle factors such as exercise, alcohol intake, smoking exposure, and marital and vocational status, and biological factors such as hypothalamic-pituitary-thyroid axis activity markers, sleep-related measures, and selected genetic markers. A minority of studies conducted iterative modeling testing each data type for contribution to model performance, instead of reporting basic measures of relative feature importance. Conclusion Studies combining biopsychosocial measures to predict suicide-related phenotypes are beginning to proliferate. This literature provides some early empirical evidence for the biopsychosocial model of suicide, though it is marred by harmonization challenges. For future studies, more specific definitions of suicide-related outcomes, inclusion of a greater breadth of biological data, and more diversity in study populations will be needed.
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Affiliation(s)
- Earvin S. Tio
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Melissa C. Misztal
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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