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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., Yilmaz, Y.E., Janke, J., Bergmann, M.M., 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 |
| ISSN: | 0741-0395 |
| Publisher: | Wiley |
| Volume: | 44 |
| Number: | 1 |
| 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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