Open AccessMental health in the UK Biobank: A roadmap to self‐report measures and neuroimaging correlates
Author(s) -
Dutt Rosie K,
Han Kayla,
Easley Ty O,
Griffis Joseph C,
Zhang Wei,
Bijsterbosch Janine D
Publication year - 2022
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.25690
Subject(s) - biobank , mental health , neuroimaging , anxiety , univariate , multivariate statistics , psychology , medicine , population , clinical psychology , psychiatry , bioinformatics , biology , environmental health , computer science , machine learning
Abstract The UK Biobank (UKB) is a highly promising dataset for brain biomarker research into population mental health due to its unprecedented sample size and extensive phenotypic, imaging, and biological measurements. In this study, we aimed to provide a shared foundation for UKB neuroimaging research into mental health with a focus on anxiety and depression. We compared UKB self‐report measures and revealed important timing effects between scan acquisition and separate online acquisition of some mental health measures. To overcome these timing effects, we introduced and validated the Recent Depressive Symptoms (RDS‐4) score which we recommend for state‐dependent and longitudinal research in the UKB. We furthermore tested univariate and multivariate associations between brain imaging‐derived phenotypes (IDPs) and mental health. Our results showed a significant multivariate relationship between IDPs and mental health, which was replicable. Conversely, effect sizes for individual IDPs were small. Test–retest reliability of IDPs was stronger for measures of brain structure than for measures of brain function. Taken together, these results provide benchmarks and guidelines for future UKB research into brain biomarkers of mental health.