Detecting and Correcting for Population Genetic Structure in Large-Scale Case-Control Association Studies

• Activity Number: 13
• Type: Topic Contributed
• Date/Time: Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Ilana Belitskaya-Levy*+ and Iryna Lobach and Judith D. Goldberg
• Companies: New York University School of Medicine and New York University School of Medicine and New York University School of Medicine
• Keywords: population genetic structure ; genetic association study ; melanoma ; population stratification ; ancestry informative markers ; disease susceptibility

Abstract

Recent advances in genetics suggest that complex diseases, such as cancer, are likely to have a genetic component. Genetic case-control association studies can be used to identify disease susceptibility markers. One of the major difficulties in the analysis of genetic association studies is that variation in allele frequencies among populations of different ancestries can confound analysis. We propose a statistical approach for inferring population genetic structure using a panel of ancestry informative markers (AIMs). A unique feature of the proposed methodology is that it addresses the situation when some AIMs may in fact also be disease susceptibility markers. Performance of the proposed approach is demonstrated using simulation studies. The application of the proposed methodology to a melanoma case-control study is presented.