Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks

Yuzhuo Ma, Yanlong Zhao, Ji-Feng Zhang and Wenjian Bi ()
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Yuzhuo Ma: Peking University
Yanlong Zhao: Chinese Academy of Sciences
Ji-Feng Zhang: Chinese Academy of Sciences
Wenjian Bi: Peking University

Nature Communications, 2025, vol. 16, issue 1, 1-21

Abstract: Abstract Gene-environment interaction (G×E) analysis elucidates the interplay between genetic and environmental factors. Genome-wide association studies (GWAS) have expanded to encompass complex traits like time-to-event and ordinal traits, which provide richer phenotypic information. However, most existing scalable approaches focus only on quantitative or binary traits. Here we propose SPAGxECCT, a scalable and accurate framework for diverse trait types. SPAGxECCT fits a genotype-independent model and employs a hybrid strategy including saddlepoint approximation (SPA) for accurate p value calculation, especially for low-frequency variants and unbalanced phenotypic distributions. We extend SPAGxECCT to SPAGxEmixCCT, which accounts for population stratification and is applicable to multi-ancestry or admixed populations. SPAGxEmixCCT can further be extended to SPAGxEmixCCT-local, which identifies ancestry-specific G×E effects using local ancestry. Through extensive simulations and real data analyses of UK Biobank data, we demonstrate that SPAGxECCT and SPAGxEmixCCT are scalable to analyze large-scale study cohort, control type I error rates effectively, and maintain power.

Date: 2025
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DOI: 10.1038/s41467-025-57887-3

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