ArticlemedRxiv : the preprint server for health sciences2026
Exposome factors predict the association between sleep health and depression.
Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Sleep health and depression are multidimensional constructs, yet their shared determinants remain obscure. We aim to identify the key exposome factors in predicting sleep-related depression (SRD). Methods: We integrated regularized canonical correlation analysis with machine-learning models within a nested cross-validation to identify a shared phenotype (i.e., sleep-related depression (SRD)) and to predict SRD from exposome factors in the UK Biobank (n = 64,781). The best-performing model was validated in an independent subsample at baseline and follow-up (n = 8,139) and in a clinical depression subsample (n = 3,046) to assess generalizability. Subsequently, we conducted complementary analyses to assess the exposome's role in other latent phenotypes of sleep and depression. Findings: We identified a robust multivariate association between sleep and depression in GP1 (canonical r = 0.42). Exposome factors moderately predicted SRD (r = 0.25; 95% CI [0.25, 0.26]; R Interpretation: Our generalizable predictive model identifies critical modifiable predictors of the association between sleep health and depression that could serve as potential targets for personalized interventions.
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