Efficient Designs for Genetic Epidemiology and Gene-Environment Association Studies
• John Witte
Professor & Associate Director
Department of Epidemiology / Biostatistics & Center for Human Genetics, University of California, San Francisco, 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. Witte received his PhD in Epidemiology from UCLA and had his first faculty appointment in the Department of Preventive Medicine at the University of Southern California. Before coming to UCSF, he spent 8 years at Case Western Reserve University, in the Division of Genetic and Molecular Epidemiology. Dr. Witte's work encompasses a synthesis of applied and methodologic cancer, genetic, and epidemiologic research. At the present time his applied research is primarily focused on deciphering risk factors for the initiation and progression of prostate cancer. This applied work helps motivate his methodological research, which primarily involves issues surrounding the design and analysis of genetic and epidemiologic studies.