Computing differential sample size for case-control studies of gene-environment interaction.
The rates for diseases such as cancer, cardiovascular disease, and diabetes are known to differ by ethnic/racial groups. However, neither genetic nor environmental factors fully explain the observed differences. Failure to account for genetic expression in the absence or presence of an environmental factor, and vice-versa, may lead to erroneous conclusions regarding the importance of these factors in disease etiology. We present a novel method for computing sample size for case-control studies involving the interaction of genetic and environmental factors. The method is based on an indirect estimate of the odds ratio for gene-environment interaction given only the odds ratio for environmental exposure and population genotype frequency. A table is presented providing sample sizes required for detecting a minimum odds ratio for gene-environment interaction given varying genotype frequencies and environmental exposure odds ratio values. Sample size increases proportionately with genotype frequency for a given environment exposure odds ratio.
Efird
Jimmy Thomas
JT
Biostatistics and Data Management Facility, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA. jimmy.efird@stanfordlumni.org
Hong
Mi-Kyung
MK
D016022:Case-Control Studies; D004777:Environment; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D016017:Odds Ratio; D012107:Research Design; D012307:Risk Factors; D018401:Sample Size