Routine multisystem physiological function and future depression risk in the UK Biobank.

BACKGROUND: Depression risk may be preceded by measurable changes in peripheral physiology, but most studies have focused on isolated biomarkers. We examined whether routine physiological indicators across body systems were associated with future depression risk and whether genetic analyses supported directional relationships. METHODS: We studied 128,766 UK Biobank participants free of depression at baseline. Sixty-eight routinely measured physiological indicators across 13 physical health domains were assessed, and incident depression was ascertained during follow-up. System-level and indicator-level associations were evaluated using block-wise Cox models, multivariable Cox models, restricted cubic splines, a covariate-matched sensitivity analysis, and multiple imputation. A composite physical-health burden score was constructed from FDR-significant indicators. Bidirectional two-sample Mendelian randomization provided complementary genetic evidence. RESULTS: During a median follow-up of 14.37 years, 5595 participants developed depression. All 13 physical health domains showed significant global association signals after FDR correction. At the indicator level, 31 of 68 physiological indicators were significantly associated with incident depression after covariate adjustment and FDR correction, with associations spanning functional, inflammatory, hematological, renal, hepatic, metabolic, and protein-related measures. A composite physical-health burden score showed a graded association with depression risk; each 1-SD increase was associated with higher incident depression risk (HR = 1.23, 95% CI: 1.20-1.27), and the highest quartile had greater risk than the lowest quartile (HR = 1.71, 95% CI: 1.56-1.87). Forward MR did not identify FDR-significant evidence that physical health indicators increased depression risk, whereas reverse MR linked genetic liability to depression with higher C-reactive protein levels. CONCLUSIONS: Multisystem physiological function measured in routine health data captures a broad physical-health background associated with future depression risk. These findings support a shift from single-biomarker models toward an integrated routine-physiology framework for understanding depression vulnerability.