Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits.

Journal Article (Journal Article)

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

Full Text

Duke Authors

Cited Authors

  • Patel, RA; Musharoff, SA; Spence, JP; Pimentel, H; Tcheandjieu, C; Mostafavi, H; Sinnott-Armstrong, N; Clarke, SL; Smith, CJ; V.A. Million Veteran Program, ; Durda, PP; Taylor, KD; Tracy, R; Liu, Y; Johnson, WC; Aguet, F; Ardlie, KG; Gabriel, S; Smith, J; Nickerson, DA; Rich, SS; Rotter, JI; Tsao, PS; Assimes, TL; Pritchard, JK

Published Date

  • July 7, 2022

Published In

Volume / Issue

  • 109 / 7

Start / End Page

  • 1286 - 1297

PubMed ID

  • 35716666

Pubmed Central ID

  • PMC9300878

Electronic International Standard Serial Number (EISSN)

  • 1537-6605

Digital Object Identifier (DOI)

  • 10.1016/j.ajhg.2022.05.014

Language

  • eng

Conference Location

  • United States