A validation of the diathesis-stress model for depression in Generation Scotland

Transl Psychiatry. 2019 Jan 18;9(1):25. doi: 10.1038/s41398-018-0356-7.

Abstract

Depression has well-established influences from genetic and environmental risk factors. This has led to the diathesis-stress theory, which assumes a multiplicative gene-by-environment interaction (GxE) effect on risk. Recently, Colodro-Conde et al. empirically tested this theory, using the polygenic risk score for major depressive disorder (PRS, genes) and stressful life events (SLE, environment) effects on depressive symptoms, identifying significant GxE effects with an additive contribution to liability. We have tested the diathesis-stress theory on an independent sample of 4919 individuals. We identified nominally significant positive GxE effects in the full cohort (R2 = 0.08%, p = 0.049) and in women (R2 = 0.19%, p = 0.017), but not in men (R2 = 0.15%, p = 0.07). GxE effects were nominally significant, but only in women, when SLE were split into those in which the respondent plays an active or passive role (R2 = 0.15%, p = 0.038; R2 = 0.16%, p = 0.033, respectively). High PRS increased the risk of depression in participants reporting high numbers of SLE (p = 2.86 × 10-4). However, in those participants who reported no recent SLE, a higher PRS appeared to increase the risk of depressive symptoms in men (β = 0.082, p = 0.016) but had a protective effect in women (β = -0.061, p = 0.037). This difference was nominally significant (p = 0.017). Our study reinforces the evidence of additional risk in the aetiology of depression due to GxE effects. However, larger sample sizes are required to robustly validate these findings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Cohort Studies
  • Depression / etiology
  • Depression / genetics*
  • Depressive Disorder, Major / etiology
  • Depressive Disorder, Major / genetics*
  • Female
  • Gene-Environment Interaction
  • Genetic Predisposition to Disease
  • Humans
  • Life Change Events*
  • Linear Models
  • Male
  • Middle Aged
  • Multifactorial Inheritance*
  • Polymorphism, Single Nucleotide*
  • Risk Factors
  • Scotland
  • Young Adult