Exploring polygenic-environment and residual-environment interactions for depressive symptoms within the UK Biobank

Area of Science:

• Psychiatry and Genetics
• Behavioral Science

Background:

• Identifying genetic contributions to depression is advancing.
• Understanding gene-environment interactions in depression remains limited.
• Environmental factors significantly modulate genetic predispositions.

Purpose of the Study:

• To investigate gene-environment interactions in depressive symptoms.
• To determine if polygenic and residual variance components of depression are modulated by environmental and biomarker covariates.
• To utilize multivariate reaction norm models (MRNMs) for unbiased interaction estimates.

Main Methods:

• Employed multivariate reaction norm models (MRNMs) on UK Biobank data (N=61294-91644).
• Assessed 17 covariate traits (12 environmental, 5 biomarkers) for their modulation of depressive symptoms.
• Implemented mixed-effects models controlling for outcome-covariate correlations and residual-covariate interactions.

Main Results:

• 11 of 17 covariates significantly modulated depressive symptoms.
• Most significant modulations were driven by residual-covariate interactions, not polygenic ones.
• Average sleep duration exhibited a small, yet statistically significant, polygenic-covariate interaction (1.22% variation).

Conclusions:

• Gene-environment interactions play a role in depressive symptom variability.
• Residual-covariate interactions are more prevalent than polygenic-environment interactions in depression.
• Limited evidence for substantial polygenic-environment interactions suggests a need for further research into depression's etiology.