Predicting the Future of Genetic Risk Prediction

• Activity Number: 147
• Type: Invited
• Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Nilanjan Chatterjee*+ and JuHyun Park and Mitchell Gail
• Companies: National Cancer Institute and National Cancer Institute and National Cancer Institute
• Keywords: genome-wide association study ; gene-environment interaction ; ROC curve ; Complex traits

Abstract

Although recent genome-wide association studies have led to the identification of many susceptibility loci for a variety of complex traits, the utility of these discoveries for predicting individualized risk has been modest. This talk will examine the potential utility of future risk models that may include additional susceptibility loci as well as non-genetic risk factors. In particular, we will describe methods for estimating number of underlying susceptibility loci for a trait and the distribution of their effect-sizes using data from recent genome-wide association studies. We will then show how such estimates together with existing risk factors for diseases can be used to assess the limits of performance of future prediction models Conversely, we also evaluate the magnitude of effect-sizes and number of risk factors needed for risk models to have substantial discriminatory power and hence have major impact for public health applications.