Genetic association analysis of complex diseases incorporating intermediate phenotype information.

ABSTRACT: Genetic researchers often collect disease related quantitative traits in addition to disease status because they are interested in understanding the pathophysiology of disease processes. In genome-wide association (GWA) studies, these quantitative phenotypes may be relevant to disease development and serve as intermediate phenotypes or they could be behavioral or other risk factors that predict disease risk. Statistical tests combining both disease status and quantitative risk factors should be more powerful than case-control studies, as the former incorporates more information about the disease. In this paper, we proposed a modified inverse-variance weighted meta-analysis method to combine disease status and quantitative intermediate phenotype information. The simulation results showed th

SUBMITTER: Li Y 

PROVIDER: S-EPMC3477105 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature