Clinical, sociodemographic, and genetic predictors of depressive episode duration in the UK Biobank
TL;DR
Clinical features captured most of the predictable variance in episode duration, with the same predictors largely operating in opposite directions for short and long episodes, consistent with a continuum of chronicity.
Abstract
Background: The course of major depressive disorder is heterogeneous, with UK Biobank (UKB) participants reporting episode durations ranging from <1 month to >24 months. Here, we identify predictors of episode duration, characterise its genetic architecture, and examine links to treatment seeking and response. Methods: In UKB participants meeting criteria for major depressive disorder, we examined clinical, sociodemographic, and genetic predictors of short (0-3 months) and long (>24 months) episode duration, fitted in predictor-specific, domain-level, and combined models. We also conducted genome-wide association studies in European-ancestry participants (n = 40,858) and estimated common-variant heritability. Results: Clinical features were most informative: higher childhood trauma scores, a stressful trigger, and recurrence showed the most consistent associations with short and long durations across models (ORcombined: short = 0.75-0.95; long = 1.13-1.45; all p[≤]0.02). Higher neuroticism scores were also associated with both durations (ORcombined: short = 0.977; long = 1.053; p<0.001). Polygenic risk for depression was associated with episode duration, though its independent contribution was modest. Long episodes were more predictable than short in validation analyses (AUC = 0.705 vs 0.601) and were associated with greater treatment engagement but lower perceived benefit; SNP-based heritability was nominally significant. Conclusions: Clinical features captured most of the predictable variance in episode duration, with the same predictors largely operating in opposite directions for short and long episodes, consistent with a continuum of chronicity. Those at risk for long episodes emerge as a priority for early identification and intervention.