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Powerful rare variant association testing in a copula-based joint analysis of multiple phenotypes

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Item Type:Article
Title:Powerful rare variant association testing in a copula-based joint analysis of multiple phenotypes
Creators Name:Konigorski, S. and Yilmaz, Y.E. and Janke, J. and Bergmann, M.M. and Boeing, H. and Pischon, T.
Abstract:In genetic association studies of rare variants, the low power of association tests is one of the main challenges. In this study, we propose a new single‐marker association test called C‐JAMP (Copula-based Joint Analysis of Multiple Phenotypes), which is based on a joint model of multiple phenotypes given genetic markers and other covariates. We evaluated its performance and compared its empirical type I error and power with existing univariate and multivariate single-marker and multi-marker rare-variant tests in extensive simulation studies. C-JAMP yielded unbiased genetic effect estimates and valid type I errors with an adjusted test statistic. When strongly dependent traits were jointly analyzed, C-JAMP had the highest power in all scenarios except when a high percentage of variants were causal with moderate/small effect sizes. When traits with weak or moderate dependence were analyzed, whether C-JAMP or competing approaches had higher power depended on the effect size. When C‐JAMP was applied with a misspecified copula function, it still achieved high power in some of the scenarios considered. In a real-data application, we analyzed sequencing data using C‐JAMP and performed the first genome-wide association studies of high-molecular-weight and medium-molecular-weight adiponectin plasma concentrations. C-JAMP identified 20 rare variants with p-values smaller than 10(−5), while all other tests resulted in the identification of fewer variants with higher p-values. In summary, the results indicate that C-JAMP is a powerful, flexible, and robust method for association studies, and we identified novel candidate markers for adiponectin. C‐JAMP is implemented as an R package and freely available from https://cran.r-project.org/package=CJAMP.
Keywords:Adipokines, Adiponectin, Copula Models, Ggenetic Association Study, Joint Modeling, Multiple Phenotypes, Obesity, Rare Variant Analysis
Source:Genetic Epidemiology
Page Range:26-40
Date:January 2020
Official Publication:https://doi.org/10.1002/gepi.22265
PubMed:View item in PubMed

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