The Potential for Enhancing the Power of Genetic Association Studies in African Americans through the Reuse of Existing Genotype Data

We consider the feasibility of reusing existing control data obtained in genetic association studies in order to reduce costs for new studies. We discuss controlling for the population differences between cases and controls that are implicit in studies utilizing external control data. We give theoretical calculations of the statistical power of a test due to Bourgain et al (Am J Human Genet 2003), applied to the problem of dealing with case-control differences in genetic ancestry related to population isolation or population admixture. Theoretical results show that there may exist bounds for the non-centrality parameter for a test of association that places limits on study power even if sample sizes can grow arbitrarily large. We apply this method to data from a multi-center, geographically-diverse, genome-wide association study of breast cancer in African-American women. Our analysis of these data shows that admixture proportions differ by center with the average fraction of European admixture ranging from approximately 20% for participants from study sites in the Eastern United States to 25% for participants from West Coast sites. However, these differences in average admixture fraction between sites are largely counterbalanced by considerable diversity in individual admixture proportion within each study site. Our results suggest that statistical correction for admixture differences is feasible for future studies of African-Americans, utilizing the existing controls from the African-American Breast Cancer study, even if case ascertainment for the future studies is not balanced over the same centers or regions that supplied the controls for the current study.Author Summary: This paper discusses and provides unique insight into an important problem raised by the current state of genetic studies into disease susceptibility, namely whether we can reuse genetic data from participants genotyped as controls in one study when cases (people with a disease of interest) are obtained from other studies, or whether each new study needs its own controls. We are interested in whether studies where cases and controls are sampled differently will give correct answers and are as powerful statistically as when new control data is also genotyped. Because of the huge investments made recently in large scale genotyping of cases and controls for various diseases, this is a timely question. This question is especially important in understanding the genetic causes of disease in as-yet relatively understudied population groups, such as African-Americans, in order to speed up progress when this is possible. We give theoretical results about the power of studies that reuse existing control genotypes based on statistical considerations. We also provide analysis of real data from a major study of the genetic causes of breast cancer in African-American women in order to shed practical light upon this issue.