Efficient Designs for Genetic Epidemiology and Gene-Environment Association Studies
• Duncan Thomas
University of Southern California
Department of Preventive Medicine
Los Angeles, CA, United States

Over the past decade the use of association studies in genetic epidemiology has rapidly increased. These studies most commonly have case-control designs, whereby the frequency of particular genetic variants in cases are compared to those observed in controls. Association studies have greater statistical power to detect small to modest genetic effects compared to linkage. Moreover, pathway-based and genome-wide association studies (GWAS) allow for more comprehensive evaluation of the genome than single candidate gene association studies. Unique challenges exist for determining how to best design these studies, and how to detect gene-gene and gene-environment interactions. In this session we will consider new developments in efficient association study designs and corresponding analytic issues, with a focus on GWAS and pathway-based approaches.

Dr. Thomas is Professor of Preventive Medicine, Director of the Biostatistics Division, and Verna R. Richter Chair in Cancer Research at the University of Southern California Keck School of Medicine. His primary research interest has been in the development of statistical methods for environmental and genetic epidemiology. Dr. Thomas has numerous publications, including the textbooks Statistical Methods in Genetic Epidemiology (Oxford University Press, 2004) and Statistical Methods in Environmental Epidemiology (Oxford University Press, in press) and is a past President of the International Genetic Epidemiology Society. These three broad areas of interest make him uniquely qualified to address methodological challenges in studying gene-environment interactions.