Environmental exposure data may improve statistical power in genetic studies when gene–environment interaction is present. However, resources invested in obtaining exposure data could instead be applied to measure disease status and genotype on more subjects. In a cohort-study setting, we consider the tradeoff between measuring only disease status and genotype for a larger study sample and measuring disease status, genotype, and environmental exposure for a smaller sample, under the gene–environment independence assumption in the study population. We focus on the power of tests for gene–disease association, applied in situations where a gene modifies risk of disease due to environmental exposure. Our results are equally applicable to exploratory genome-wide association studies and to more hypothesis-driven candidate gene investigations. We further consider the impact of misclassification for environmental exposures. We identify circumstances under which higher power is achieved via the larger study sample without measurements of environmental exposure.
Supplemental Digital Content is available in the text.
From the aDepartment of Statistics, University of British Columbia, Vancouver, BC, Canada; and bDepartment of Environmental and Occupational Heath, Drexel University, Philadelphia, PA.
Supported by Natural Sciences and Engineering Research Council of Canada.
Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com). This content is not peer-reviewed or copy-edited; it is the sole responsibility of the author.
Correspondence: Paul Gustafson, Room 3182, Earth Sciences Building, 220 Main Mall, Vancouver BC V6T 1Z4, Canada. E-mail: email@example.com.
Received May 22, 2012
Accepted January 25, 2013