A Class of General Score Tests for Detecting Genetic Associations Integrating Environmental Exposures

• Activity Number: 110
• Type: Topic Contributed
• Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Summer S Han*+ and Philip S Rosenberg and Nilanjan Chatterjee
• Companies: National Cancer Institute and National Cancer Institute and National Cancer Institute
• Keywords: genetic associations ; GWAS ; G-E interaction ; additive risk model ; environmental exposure ; score test

Abstract

There has been considerable success in genome-wide association studies (GWAS) for identifying susceptibility loci for various complex traits; however, a large proportion of their heritability still remained unexplained. A major limitation of current methods for detecting associations in case control studies is a lack of full consideration of environmental exposure effects. It's well known that environmental exposures play important roles in contributing to disease risk in many complex traits, and often modify genetic effects. Another fundamental limitation of current methods is that they rely on a specific risk model-multiplicative risk model via logistic regression-which is not based on any biological reasoning or evidence from data, but on statistical convention. In this article, we propose a unified test for identifying genetic associations, which integrates the effects of environmental exposures; the proposed method will maximize suitable score statistics over a range of underlying disease risk models including multiplicative, super-multiplicative, additive and probit risk model. We evaluate the finite sample performance using simulations, and apply them to NCI GWAS data.