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Symptom dimensions of major depression in a large community-based cohort

Published online by Cambridge University Press:  19 May 2021

Michael Wainberg Open the ORCID record for Michael Wainberg [Opens in a new window] ,
Peter Zhukovsky ,
Sean L. Hill ,
Daniel Felsky ,
Aristotle Voineskos ,
Sidney Kennedy ,
Colin Hawco  and
Shreejoy J. Tripathy
Michael Wainberg*
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
Peter Zhukovsky
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
Sean L. Hill
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, Canada Institute of Medical Sciences, University of Toronto, Toronto, Canada Department of Physiology, University of Toronto, Toronto, Canada
Daniel Felsky
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, Canada Institute of Medical Sciences, University of Toronto, Toronto, Canada
Aristotle Voineskos
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, Canada Institute of Medical Sciences, University of Toronto, Toronto, Canada
Sidney Kennedy
Affiliation:
Department of Psychiatry, University of Toronto, Toronto, Canada Institute of Medical Sciences, University of Toronto, Toronto, Canada Krembil Research Institute, University Health Network, Toronto, Canada Li Ka Shing Knowledge Institute, Saint Michael's Hospital, Toronto, Canada
Colin Hawco
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, Canada Institute of Medical Sciences, University of Toronto, Toronto, Canada
Shreejoy J. Tripathy
Affiliation:
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, Canada Institute of Medical Sciences, University of Toronto, Toronto, Canada Department of Physiology, University of Toronto, Toronto, Canada
*
Author for correspondence: Shreejoy J. Tripathy, E-mail: shreejoy.tripathy@camh.ca
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Abstract

Background

Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community.

Methods

This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or ‘symptom dimensions’ via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records.

Results

Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations.

Conclusions

An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

Keywords

Major depressionsymptom dimensionscomorbiditypolygenic risk scoresUK Biobank

Information

Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 2 , January 2023 , pp. 438 - 445
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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