Latent subtypes of manic and/or irritable episode symptoms in two population-based cohorts

Data availability: Data are available from UK Biobank and PROTECT subject to standard access procedures (www.ukbiobank.ac.uk, www.protectstudy.org.uk/).Supplementary material: To view supplementary material for this article, please visit https://doi.org/10.1192/bjp.2021.184.Erratum: This article was published with an error in Figure 1 Section b, which accidentally duplicated the percentage values of Figure 1 Section a. The correct version of the figure is attached below (Erratum.pdf). The publisher apologises for the error.Copyright © The Author(s), 2021. Background: Mood disorders are characterised by pronounced symptom heterogeneity, which presents a substantial challenge both to clinical practice and research. Identification of subgroups of individuals with homogeneous symptom profiles that cut across current diagnostic categories could provide insights in to the transdiagnostic relevance of individual symptoms, which current categorical diagnostic systems cannot impart. Aims: To identify groups of people with homogeneous clinical characteristics, using symptoms of manic and/or irritable mood, and explore differences between groups in diagnoses, functional outcomes and genetic liability. Method: We used latent class analysis on eight binary self-reported symptoms of manic and irritable mood in the UK Biobank and PROTECT studies, to investigate how individuals formed latent subgroups. We tested associations between the latent classes and diagnoses of psychiatric disorders, sociodemographic characteristics and polygenic risk scores. Results: Five latent classes were derived in UK Biobank (N = 42 183) and were replicated in the independent PROTECT cohort (N = 4445), including ‘minimally affected’, ‘inactive restless’, active restless’, ‘focused creative’ and ‘extensively affected’ individuals. These classes differed in disorder risk, polygenic risk score and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood largely comprised cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment. Conclusions: Findings suggest that data-driven investigations of psychopathological symptoms that include sub-diagnostic threshold conditions can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, toward a more dimensional classification of mood disorders.This research was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care South West Peninsula, the NIHR BioResource Centre Maudsley and the NIHR Exeter Clinical Research Facility. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care or King's College London. This work was funded in part by the University of Exeter through the MRC Proximity to Discovery: Industry Engagement Fund (External Collaboration, Innovation and Entrepreneurism: Translational Medicine in Exeter 2 (EXCITEME2) reference MC_PC_17189). Genotyping of the PROTECT study was performed at deCODE Genetics. The authors acknowledge use of the research computing facility at King's College London, Rosalind (https://rosalind.kcl.ac.uk), which is delivered in partnership with the NIHR Biomedical Research Centre at South London & Maudsley and Guy's & St. Thomas’ NHS Foundation Trusts, and part-funded by capital equipment grants from the Maudsley Charity (grant 980) and Guy's & St. Thomas’ Charity (grant TR130505). C.F. was supported by Fondazione Umberto Veronesi (https://www.fondazioneveronesi.it). S.H. was supported by the Medical Research Council (grant MR/S0151132). This research has been conducted using the UK Biobank Resource under application number 18177