Extending Concepts of Gene-Environment Interaction Testing to a DNA Methylation Framework

• Activity Number: 540
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Emily Slade* and Peter Kraft
• Companies: Harvard School of Public Health and Harvard School of Public Health
• Keywords: DNA methylation ; interaction ; measurement error

Abstract

This paper was motivated by the successes of leveraging gene-environment interaction to increase the power of genetic association tests as well as considering the role played by DNA methylation in complex disease susceptibility. We extend the joint test for discrete genetic and environmental exposure data to the case of continuous methylation and environmental data to create a joint test that is powerful to detect methylation association even in the presence of effect modification by an environmental exposure. Through simulation, we show that this test has optimal or nearly optimal power as compared to a marginal test for methylation main effect and a standard test for methylation-environment interaction. We also show that this holds in the presence of methylation-environment correlation and measurement error in the environmental exposure. Thus, our joint test is a good option for detecting methylation association when little is known about the potential presence of effect modification by an exposure a priori due to its flexibility to be powerful across a wide range of true methylation-environment models.