Bayesian Genetic Association Test when Secondary Phenotypes Are Available Only in the Case Group

Abstract

In many case-control genetic association studies, a secondary phenotype that may have common genetic factors with disease status can be identified. When information on the secondary phenotype is available only for the case group due to cost and different data sources, a fitting linear regression model ignoring supplementary phenotype data may provide limited knowledge regarding genetic association. We set up a joint model and use a Bayesian framework to estimate and test the effect of genetic covariates on disease status considering the secondary phenotype as an instrumental variable. The application of our proposed procedure is demonstrated through the rheumatoid arthritis data provided by the 16th Genetic Analysis Workshop.

Keywords

• genome-wide association study
• Bayesian testing
• secondary phenotype
• Bayes factor
• case-control design
• incomplete data