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Activity Number: 84
Type: Contributed
Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #313253 View Presentation
Title: Controlling Type I Error in Genome-Wide Investigations of Gene-Environment Interaction with Infrequent Environmental Exposures
Author(s): Colleen Sitlani*+ and Josée Dupuis and L. Adrienne Cupples and Kenneth Rice
Companies: University of Washington and Boston University School of Public Health and Boston University and University of Washington
Keywords: Gene-environment interaction ; Genome-wide association studies ; Robust variance estimates ; Type I error ; Generalized Estimating Equations ; Family data
Abstract:

Genetic association studies only partially account for the heritability of many complex human traits. Gene-environment interactions are one proposed mechanism that could account for some of the "missing" heritability. In the context of gene-environment interactions, robust variance estimates should be used to properly estimate variability in effect sizes, but traditional sandwich variance estimates perform poorly with small gene-environment strata. Therefore, despite the large sample sizes that are achieved by collaborations within genetic consortia, genome-wide statistical tests of interaction often have inflated type I error when binary environmental exposures are infrequent. For quantitative traits, the performance of such tests can be improved by modifying the standard error estimates and/or the reference distribution used to compute p-values. We evaluate several approaches to control type-I error rate when testing gene-environment interactions. Methods for both cross-sectional and longitudinal studies, including studies with family data, are compared.


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