| Title: | Exploring polygenic-environment and residual-environment interactions for depressive symptoms within the UK Biobank |
| Journal: | Genetic Epidemiology |
| Published: | 19 Apr 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35438196/ |
| DOI: | https://doi.org/10.1002/gepi.22449 |
| URL: | https://kclpure.kcl.ac.uk/portal/en/publications/7f655bee-82ab-4d84-8fb1-2aaec85f7d7d |
| Citations: | 4 (3 in last 2 years) as of 8 Aug 2024 |
Publication 12405
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Abstract
Substantial advances have been made in identifying genetic contributions to depression, but little is known about how the effect of genes can be modulated by the environment, creating a gene-environment interaction. Using multivariate reaction norm models (MRNMs) within the UK Biobank (N = 61294-91644), we investigate whether the polygenic and residual variance components of depressive symptoms are modulated by 17 a priori selected covariate traits-12 environmental variables and 5 biomarkers. MRNMs, a mixed-effects modelling approach, provide unbiased polygenic-covariate interaction estimates for a quantitative trait by controlling for outcome-covariate correlations and residual-covariate interactions. A continuous depressive symptom variable was the outcome in 17 MRNMs-one for each covariate trait. Each MRNM had a fixed-effects model (fixed effects included the covariate trait, demographic variables, and principal components) and a random effects model (where polygenic-covariate and residual-covariate interactions are modelled). Of the 17 selected covariates, 11 significantly modulate deviations in depressive symptoms through the modelled interactions, but no single interaction explains a large proportion of phenotypic variation. Results are dominated by residual-covariate interactions, suggesting that covariate traits (including neuroticism, childhood trauma, and BMI) typically interact with unmodelled variables, rather than a genome-wide polygenic component, to influence depressive symptoms. Only average sleep duration has a polygenic-covariate interaction explaining a demonstrably nonzero proportion of the variability in depressive symptoms. This effect is small, accounting for only 1.22% (95% confidence interval: [0.54, 1.89]) of variation. The presence of an interaction highlights a specific focus for intervention, but the negative results here indicate a limited contribution from polygenic-environment interactions.</p>
8 Keywords
- Biological Specimen Banks
- Depression
- Gene-Environment Interaction
- Genome-Wide Association Study
- Humans
- Models, Genetic
- Multifactorial Inheritance
- United Kingdom
9 Authors
- Alexandra C. Gillett
- Bradley S. Jermy
- Sang Hong Lee
- Oliver Pain
- David M. Howard
- Saskia P. Hagenaars
- Ken B. Hanscombe
- Jonathan R. I. Coleman
- Cathryn M. Lewis
1 Application
| Application ID | Title |
|---|---|
| 18177 | Multi-trait GWAS analyses in the UK Biobank |
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