Integrative Modeling of Expression and Methylation Quantitative Trait Loci into Genetic Association Studies of Complex Diseases

• Activity Number: 537
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Yen-Tsung Huang*+
• Companies: Brown University
• Keywords: Causal Inference ; Data Integration ; Epigenetics ; Mediation Analysis ; SNP Set Analysis ; Variance Component Test

Abstract

Genome-wide association studies (GWAS) and expression-/methylation- quantitative trait loci (eQTL/mQTL) studies constitute popular approaches for investigating the association of single nucleotide polymorphisms (SNPs) with disease and expression/methylation, respectively. Here we propose to integrate eQTL and mQTL studies to more powerfully test the SNP effect on disease in GWAS. We propose a model for the joint effect of SNPs, methylation and gene expression on disease risk and obtain the marginal model for SNPs by integrating out methylation and expression. We develop a score variance component test to evaluate the marginal SNP effect, using SNPs as well as the observed methylation/expression or the predicted values from external mQTL/eQTL models. Under different relations among SNPs, methylation and expression, no SNP effect corresponds to different sets of regression coefficients to be zero in the joint model. We construct tests for various disease models determined by SNPs, methylation, expression and interactions, and propose an omnibus test to accommodate different models. We illustrate the utility of the proposed method in an asthma study and numerical simulation.