Sequence Kernel Association Test of Multiple Continuous Phenotypes.

Pubmed ID: 26782911

Pubmed Central ID: PMC4724299

Journal: Genetic epidemiology

Publication Date: Feb. 1, 2016

MeSH Terms: Humans, Algorithms, Genetic Predisposition to Disease, Atherosclerosis, Analysis of Variance, Transcription Factors, Models, Genetic, Phenotype, Genetic Association Studies, Exome, Quantitative Trait, Heritable, Adaptor Proteins, Signal Transducing, Phosphoproteins, YAP-Signaling Proteins

Grants: HHSN268201100005C, HHSN268201100006C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100012C, HHSN268201100001C, HHSN268201100002C, RC2 HL102419, 5RC2HL102419, HHSN268201000010C, R01 CA134848, GM083345, CA134848, R01 GM083345, HHSN268201100009I, HHSN268201100005G, HHSN268201100008I, HHSN268201100005I, HHSN268201100001I, HHSN268201100002I, HHSN268201000012C

Authors: Pankow JS, Wu B

Cite As: Wu B, Pankow JS. Sequence Kernel Association Test of Multiple Continuous Phenotypes. Genet Epidemiol 2016 Feb;40(2):91-100. Epub 2016 Jan 18.

Studies:

Atherosclerosis Risk in Communities (ARIC)

Abstract

Genetic studies often collect multiple correlated traits, which could be analyzed jointly to increase power by aggregating multiple weak effects and provide additional insights into the etiology of complex human diseases. Existing methods for multiple trait association tests have primarily focused on common variants. There is a surprising dearth of published methods for testing the association of rare variants with multiple correlated traits. In this paper, we extend the commonly used sequence kernel association test (SKAT) for single-trait analysis to test for the joint association of rare variant sets with multiple traits. We investigate the performance of the proposed method through extensive simulation studies. We further illustrate its usefulness with application to the analysis of diabetes-related traits in the Atherosclerosis Risk in Communities (ARIC) Study. We identified an exome-wide significant rare variant set in the gene YAP1 worthy of further investigations.