Code for "A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex Traits"
This repository contains the code used in the analysis presented in the following paper:
Zhu, Xiaofeng; Yang, Yihe; Lorincz-Comi, Noah; Li, Gen; Bentley, Amy; de Vries, Paul S; Brown, Michael; Morrison, Alanna C; Rotimi, Charles; Gauderman, W James; et al. (2023). "A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits". Research Square. American Journal Experts.
There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the CHARGE Gene-Lifestyle Interactions Working Group has been spearheading efforts to investigate G×E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identified and confirmed 5 loci (6 independent signals) interacting with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrated that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated contribution ranges from 1.76% to 14.05% of SNP heritability of serum lipids in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.
For any questions or issues regarding the code, please open an issue in this repository or contact one of the authors:
- Xiaofeng Zhu (
[email protected]) - Yihe Yang (
[email protected])