Secondary Phenotype Data Analysis in Case-Control Genomewide Association Studies

• Activity Number: 646
• Type: Invited
• Date/Time: Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Huilin Li*+ and Mitchell H. Gail and Sonja Berndt and Nilanjan Chatterjee
• Companies: National Cancer Institute and National Cancer Institute and National Cancer Institute and National Cancer Institute
• Keywords: adaptively weighted ; case-control study ; genome-wide association study ; maximum likelihood ; secondary phenotype

Abstract

The Genome-wide association study (GWAS) is a powerful tool to identify genetic associations with disease. A GWAS may also provide a great amount of information on secondary phenotypes that are measured for all subjects. Added value could be gained from a GWAS by studying the association between genes and the secondary phenotypes. From the GWAS, we know that most SNPs are not associated with the disease, and when this is true, both controls and cases can be used for studies the association with a secondary phenotype. However, if the SNP is associated with both the disease and the secondary phenotype, including cases may introduce bias in the estimation of association. We consider a two-stage model to incorporate the bias from using cases, and propose an Empirical Bayes method to combine the case and control data to estimate the association with reduced mean square error.