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Genet Epidemiol. 2018 Sep;42(6):551-558. doi: 10.1002/gepi.22135. Epub 2018 Jun 13.

Gene-environment interactions in case-control studies with silent disease.

Author information

1
Department of Epidemiology and Biostatistics, University of California, San Francisco, California.
2
National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
3
Applied Mathematics and Computer Science Department, Belarusian State University, Minsk, Belarus.
4
Department of Medicine, University of California, San Francisco, California.

Abstract

Genome-wide association studies (GWAS) often measure gene-environment interactions (G × E). We consider the problem of accurately estimating a G × E in a case-control GWAS when a subset of the controls have silent, or undiagnosed, disease and the frequency of the silent disease varies by the environmental variable. We show that using case-control status without accounting for misdiagnosis can lead to biased estimates of the G × E. We further propose a pseudolikelihood approach to remove the bias and accurately estimate how the relationship between the genetic variant and the true disease status varies by the environmental variable. We demonstrate our method in extensive simulations and apply our method to a GWAS of prostate cancer.

KEYWORDS:

case-control study; gene-environment interactions; prostate cancer; pseudolikelihood; silent disease

PMID:
29896809
PMCID:
PMC6237277
DOI:
10.1002/gepi.22135
[Indexed for MEDLINE]
Free PMC Article

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