STATISTICAL METHOD FOR GENE/ENVIRONMENT INTERACTION AND GENETIC SUSCEPTIBILITY

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Summary of Work: This project seeks to develop new statistical tools and to apply existing ones in evaluating gene-environment interactions and genetic susceptibility. Work proceeded in three areas: (1) improving epidemiologic study designs, (2) devising a statistical modeling approach to enhance a data analyst's ability to detect genotype-exposure interactions, and (3) combining results from published studies to better assess the putative relationship between a vitamin D receptor polymorphism and bone density. Genotyping control subjects may not be feasible if they are reluctant to contribute tissue or have concerns about privacy with genetic information. Under the often-plausible assumption that genotype and exposure are independent in a study population, we found that study designs where controls are not genotyped can use fewer subjects than other designs to achieve the same precision in estimating exposure and genotype-exposure interactions effects. To estimate genotype effects, however, requires external data about gene prevalence. Genotype-environment interactions become difficult to detect when genes have more than two alleles in part because describing interactions requires many parameters. We have proposed a way to parameterize interactions parsimoniously that allows investigators to detect certain interactions that traditional methods would miss. Combining results from 16 studies, we found evidence that a poly-morphism in the vitamin D receptor gene was associated with about a 2.5% decline in bone mineral density.