Analysis of gene-gene interactions using gene-trait similarity regression

Hum Hered. 2014;78(1):17-26. doi: 10.1159/000360161. Epub 2014 Jun 21.

Abstract

Objective: Gene-gene interactions (G×G) are important to study because of their extensiveness in biological systems and their potential in explaining missing heritability of complex traits. In this work, we propose a new similarity-based test to assess G×G at the gene level, which permits the study of epistasis at biologically functional units with amplified interaction signals.

Methods: Under the framework of gene-trait similarity regression (SimReg), we propose a gene-based test for detecting G×G. SimReg uses a regression model to correlate trait similarity with genotypic similarity across a gene. Unlike existing gene-level methods based on leading principal components (PCs), SimReg summarizes all information on genotypic variation within a gene and can be used to assess the joint/interactive effects of two genes as well as the effect of one gene conditional on another.

Results: Using simulations and a real data application to the Warfarin study, we show that the SimReg G×G tests have satisfactory power and robustness under different genetic architecture when compared to existing gene-based interaction tests such as PC analysis or partial least squares. A genome-wide association study with approx. 20,000 genes may be completed on a parallel computing system in 2 weeks.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Computer Simulation
  • Epistasis, Genetic*
  • Genotype
  • Humans
  • Models, Genetic*
  • Polymorphism, Single Nucleotide*
  • Principal Component Analysis
  • Regression Analysis*