Permutation-Based Genomewide Association Test for Case-Dependent Quantitative Trait

• Activity Number: 555
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Wei Xue*
• Companies: The University of North Carolina at Chapel Hill
• Keywords: SNP ; case-control genome-wide association study ; inverse probability weighting (IPW) ; temporomandibular disorder (TMD) ; severity of orofacial pain ; permutation-based method

Abstract

In case-control genome-wide association studies, we want to identify genetic markers associated with intermediate phenotypes correlated with case status, where naïve regression methods will produce biased estimates. This may be corrected by using methods such as inverse probability weighting (IPW), which assigns weights to the observations to correct for overrepresenting cases. However, IPW regression coefficient estimates may be unreliable when evaluating the association between genetic markers and intermediate phenotypes are strongly associated with case status. In a case-control study of temporomandibular disorder (TMD), we want to identify markers associated with the severity of orofacial pain. Nearly all controls will report no orofacial pain, causing inaccurate results. We propose a novel permutation-based method and compared it with IPW. Simulations indicate that whereas IPW produces inflated type I error rates, our method produces correct type I error rates with no loss in power. This method were applied to identify SNPs associated with the severity of orofacial pain using data from OPPERA study, a large-scale case-control study of TMD, and two novel SNPs were identified.