Set-Based Inference for Gene-Environment Interaction in Longitudinal Studies

• Activity Number: 5
• Type: Invited
• Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): Seunggeun Lee and Zihuai He and Min Zhang and Bhramar Mukherjee*
• Companies: University of Michigan and University of Michigan and University of Michigan and University of Michigan
• Keywords: gene-environment correlation ; selection of main effects ; splines

Abstract

Longitudinal studies allow us the possibility to characterize variations in phenotype and exposure data over time. Set-based inference using collapsed and variance components tests have become increasingly popular for genetic association studies, specially for rare variants. In this talk I will present a robust score test for set-based inference in studies of gene-environment interaction with outcomes and exposures measured over time. I will indicate the role of gene-environment correlation and effect of misspecification of main effects on robust tests for gene-environment interaction. Based on these newly developed methods, I will illustrate design aspects of a longitudinal study, in terms of collecting outcome and exposure data and what helps with characterization of interaction over time. The methods will be illustrated by analyzing repeated measures of chronic risk factors like blood pressure in the multi-ethnic study of atherosclerosis.