Genome-by-Trauma Exposure Interaction Effects in Depression
Authors: Chuong T.M. , Adams M.J. , Kwong A.S.F. , Haley C.S. , Amador C , McIntosh A.M 
Published: March 2022

Background

Self-reported trauma exposure has consistently been found to be a risk factor for Major Depressive Disorder (MDD) and several studies have reported interactions with genetic liability. To date, most studies have examined interaction effects with trauma exposure using genome-wide variants (single nucleotide polymorphisms SNPs) or polygenic scores, both typically capturing less than 3% of phenotypic risk variance. We sought to re-examine genome-by-trauma interaction effects using genetic measures utilising all available genotyped data and thus, maximising accounted variance.

Methods

Measures of self-reported depression, neuroticism and trauma exposure for 148 129 participants with whole genome SNP data are available from the UK Biobank study. Here, we used a mixed-model statistical approach utilising genetic, trauma exposure and genome-by-trauma exposure interaction similarity matrices to explore sources of variation in depression and neuroticism.

Findings

Our approach estimated the heritability of MDD to be approximately 0·160 [SE 0·016]. Subtypes of self-reported trauma exposure (catastrophic, adult, childhood and full trauma) accounted for a significant proportion of the variance of each trait, ranging from 0·056 [SE 0·013] to 0·176 [SE 0·025]. The proportion of MDD risk variance accounted for by significant genome-by-trauma interaction ranged from 0·074 [SE 0·006] to 0·201 [SE 0·009]. Results from sex-specific analyses found genome-by-trauma interaction variance estimates approximately 5-fold greater for MDD in males than in females.

Interpretation

This is the first study to utilise an approach combining all genome-wide SNP data when exploring genome-by-trauma interaction effects in MDD and present evidence that interaction effects are influential in depression manifestation. This effect accounts for greater trait variance within males which points to potential differences in depression aetiology between the sexes. The methodology utilised in this study can be extrapolated to other environmental factors to identify modifiable risk environments and at-risk groups to target with interventions.

Research In Context

Evidence before this study

We searched PubMed up to January 30th 2022, with the following terms: (“gene environment interaction” OR “gene environment” OR “genome wide by environment” OR “GWEIS” OR “polygenic environment” OR (“gene” AND “environment”)) AND (“polygenic risk score” OR “polygenic score” OR “genomic relationship matrix” OR “GRM”) AND (“trauma” OR “environmental adversity” OR “stressful life events”) AND (“depression” OR “major depressive disorder” OR “MDD” OR “depressive symptoms”). Date or language restrictions were not applied. We further reviewed the reference lists of identified articles. This search was supplemented by reviewing related articles identified by Google Scholar. We identified 12 relevant articles. Studies to date have not explored genome-by-environment interaction effects in depression using genomic similarity matrices, however, these effects have been explored using individual single nucleotide polymorphisms (SNPs) from genome-wide studies and polygenic scores (PGSs). Some findings suggest genome-by-environment interaction effects increase risk of depression. However, replication attempts have produced either inconsistent or null findings. Taken together, it is evident that findings have failed to provide consistent evidence of substantial interaction effects. These findings may be a result of limited statistical power in analyses due to genome-wide variants and PGSs failing to capture the polygenic nature of depression with sufficient precision.

Added value of this study

This study is the first to explore genome-by-trauma interaction effects on MDD through the estimation of variance components using relationship matrices. Genomic relationship matrices (GRMs) utilise all available genotyped variants, thus, capturing a greater proportion of the trait variance and potentially providing greater power to detect genetic effects in comparison to PGSs. Additional relationship matrices capturing trauma exposure, and genome-by-trauma exposure similarity are computed and included into mixed linear models. We found evidence for substantial genome-by-trauma (including subtypes of trauma) exposure interaction effects on depression manifestation. Estimated genome-by-trauma interaction effects were larger in males than in females.

Implications of all the available evidence

Our findings are the first to show substantial genome-by-trauma effects on depression using whole genome methods. These findings highlight that the role of trauma exposure on depression manifestation may be non-additive and different between sexes. Exploring these effects in depth may yield important insight into various mechanisms, which may explain prevalence differences observed between males and females. Future work can build upon the framework we propose to explore genome-by-trauma interaction effects and the underlying molecular sites and mechanisms which are involved in depression manifestation.