Multi-trait analysis of gene-by-environment interactions in large-scale genetic studies

Author:

Luo Lan1,Mehrotra Devan V2,Shen Judong1ORCID,Tang Zheng-Zheng3

Affiliation:

1. Biostatistics and Research Decision Sciences, Merck & Co. , Inc., Rahway, NJ 07065, USA

2. Biostatistics and Research Decision Sciences, Merck & Co., Inc. , North Wales, PA 19454, USA

3. Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison , 330 N Orchard St, Madison, WI 53715, USA

Abstract

SummaryIdentifying genotype-by-environment interaction (GEI) is challenging because the GEI analysis generally has low power. Large-scale consortium-based studies are ultimately needed to achieve adequate power for identifying GEI. We introduce Multi-Trait Analysis of Gene–Environment Interactions (MTAGEI), a powerful, robust, and computationally efficient framework to test gene–environment interactions on multiple traits in large data sets, such as the UK Biobank (UKB). To facilitate the meta-analysis of GEI studies in a consortium, MTAGEI efficiently generates summary statistics of genetic associations for multiple traits under different environmental conditions and integrates the summary statistics for GEI analysis. MTAGEI enhances the power of GEI analysis by aggregating GEI signals across multiple traits and variants that would otherwise be difficult to detect individually. MTAGEI achieves robustness by combining complementary tests under a wide spectrum of genetic architectures. We demonstrate the advantages of MTAGEI over existing single-trait-based GEI tests through extensive simulation studies and the analysis of the whole exome sequencing data from the UKB.

Funder

University of Wisconsin-Madison Office of the Chancellor

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

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