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

Abstract

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.

Methods We used latent class analysis (LCA) on eight binary self-reported symptoms of manic and irritable mood in 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 (PRS). Results Five latent classes were derived in UK Biobank (N=42,183) and were replicated in the independent PROTECT cohort (N=4,445), including ‘minimally affected’, ‘inactive restless’, active restless’, ‘focused creative’, and ‘extensively affected’ individuals. These classes differed in disorder risk, PRS, and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood was largely comprised of cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment.

Conclusion Findings suggest that data-driven investigations of psychopathological symptoms that include sub56 diagnostic threshold conditions, can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, towards a more dimensional classification of mood disorders.