GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data

Genome Biol. 2021 Jun 21;22(1):183. doi: 10.1186/s13059-021-02403-1.


Genetic variation in response to the environment, that is, genotype-by-environment interaction (GxE), is fundamental in the biology of complex traits and diseases. However, existing methods are computationally demanding and infeasible to handle biobank-scale data. Here, we introduce GxEsum, a method for estimating the phenotypic variance explained by genome-wide GxE based on GWAS summary statistics. Through comprehensive simulations and analysis of UK Biobank with 288,837 individuals, we show that GxEsum can handle a large-scale biobank dataset with controlled type I error rates and unbiased GxE estimates, and its computational efficiency can be hundreds of times higher than existing GxE methods.

Keywords: Biobank-scale data; GxE interaction; LDSC; Reaction norm model; Whole-genome approach.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Biological Specimen Banks
  • Body Mass Index
  • Diabetes Mellitus, Type 2 / genetics*
  • Diabetes Mellitus, Type 2 / metabolism
  • Diabetes Mellitus, Type 2 / pathology
  • Gene-Environment Interaction*
  • Genetic Variation*
  • Genome, Human*
  • Genome-Wide Association Study
  • Genotype*
  • Humans
  • Hypertension / genetics*
  • Hypertension / metabolism
  • Hypertension / pathology
  • Models, Genetic
  • Multifactorial Inheritance
  • Quantitative Trait, Heritable