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Genetic susceptibility to depressive symptoms in middle-aged to older Americans: time-varying effects and effect modification by early psychosocial factors

Research output: Contribution to journal › Article › peer-review

Abstract

Purpose: We examined age-varying genetic influences on depression across young adulthood to older adulthood and the moderating role of early psychosocial factors. Methods: Data are from the Health and Retirement Study (HRS) with 6,977 European Americans (57% women) from 2006 to 2016 (M age 62.4 ± 14.3, range 26–101 years in 2006). The polygenic score (PGS) for major depression was operationalized as a binary variable at the 75th percentile. Early psychosocial factors examined included maternal warmth, parental education, perceived financial status, and childhood stressful events. Depressive symptoms were measured by the Center for Epidemiological Studies Depression Scale (CES-D; range: 0–8). We utilized time-varying effect modeling to determine the survey wave when genetic risk most affected depressive symptoms. Within this wave, we analyzed the age-varying effect of genetic risk on depressive symptoms and conducted interaction analyses between PGS with each early psychosocial factor. Results: The wave-varying effect model revealed that the genetic effect was strongest in 2006. During that year, genetic effects remained significant and stable across age groups, from middle-aged to older adults. In 2006, without negative experiences, those at high genetic risk for depression had 51–60% higher odds of depressive symptoms (CES-D ≥ 3). Conversely, without genetic risk, adverse early psychosocial factors raised depression risk by 37–54%. No multiplicative or additive interaction was observed between genetic risk and psychosocial factors. Conclusion: Identifying individuals with higher genetic susceptibility and adverse early experiences may inform targeted preventive approaches.

Original languageEnglish (US)
Pages (from-to)1139-1149
Number of pages11
JournalSocial Psychiatry and Psychiatric Epidemiology
Volume61
Issue number6
DOIs
StatePublished - Jun 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Health(social science)
  • Social Psychology
  • Psychiatry and Mental health

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