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Article
Testing gene-environment interactions in the presence of measurement error
UW Biostatistics Working Paper Series (Working Paper 405) (2014)
  • Chongzhi Di, Fred Hutchinson Cancer Research Center
  • Li Hsu, Fred Hutchinson Cancer Research Center
  • Charles Kooperberg, Fred Hutchinson Cancer Research Center
  • Alex Reiner, Fred Hutchinson Cancer Research Center
  • Ross Prentice, Fred Hutchinson Cancer Research Center
Abstract

In genetic and genomic studies, it is important to study gene-environment interactions (GxE) in order to understand the etiology of complex diseases. Compared to marginal analysis, one difficulty with GxE arises from the fact that environmental exposures are often time-varying and measured with error. In this talk, we focus on testing GxE in the presence of measurement error and time-varying exposures. We first investigate the naïve test that ignores measurement error and show that it typically leads to biased estimates of the GxE effect and inflated type I errors under the null hypothesis of no interaction. This is different from the well-established result in testing main effects of E with measurement error, where the naive approach is valid for hypothesis testing purposes. We then obtain the analytic form of the bias term, and consider a regression calibration based approach for testing GxE when either validation data or replicates are available. Simulation studies are conducted to illustrate the performance of various tests in finite samples. The proposed methods are applied to study the gene-blood pressure interaction for coronary heart disease in an ancillary study of the Women's Health Initiative.

Publication Date
2014
Publisher Statement
Di, Chongzhi; Hsu, Li; Kooperberg, Charles; Reiner, Alex; and Prentice, Ross, "Testing Gene-Environment Interactions in the Presence of Measurement Error" (2014). UW Biostatistics Working Paper Series. Working Paper 405. http://biostats.bepress.com/uwbiostat/paper405
Citation Information
Chongzhi Di, Li Hsu, Charles Kooperberg, Alex Reiner, et al.. "Testing gene-environment interactions in the presence of measurement error" UW Biostatistics Working Paper Series (Working Paper 405) (2014)
Available at: http://works.bepress.com/di/20/