No open-access location is known for this record yet.
No open-access location is known for this record yet.
Abstract How life-course experiences shape depression in later life remains one of the central questions in human aging. We analyzed approximately 35 years of sociogenomic longitudinal data from 9,005 European-ancestry individuals in the Wisconsin Longitudinal Study. Machine learning models were applied to 426 variables measured at mean ages 35.6, 53.0, and 64.2 to predict depressive symptoms at mean age 70.6. Psychological resources, including environmental mastery, self-acceptance, purpose in life, and optimism, consistently emerged as the strongest predictors, accounting for substantially greater variance (R² = 0.20) than socioeconomic, behavioral, or genetic factors. Polygenic risk for neuroticism selectively moderated the negative association between the psychological resource composite and late-life depression, supported by linear regression (β = -0.049; 95% CI, -0.075 to -0.024) and generalized structured component analysis (β = -0.037; 95% CI, -0.060 to -0.017). Our findings suggest psychological resource enhancement in genetically vulnerable adults as a potential precision-prevention strategy for late-life depression.
Loading…
Imported from OpenAlex (CC0) — nothing here is generated.