@article{d48475e2deab4fc5a4cb1bef699ac3e4,
title = "Statistical methods for testing genetic pleiotropy",
abstract = "Genetic pleiotropy is when a single gene influences more than one trait. Detecting pleiotropy and understanding its causes can improve the biological understanding of a gene in multiple ways, yet current multivariate methods to evaluate pleiotropy test the null hypothesis that none of the traits are associated with a variant; departures from the null could be driven by just one associated trait. A formal test of pleiotropy should assume a null hypothesis that one or no traits are associated with a genetic variant. For the special case of two traits, one can construct this null hypothesis based on the intersection-union (IU) test, which rejects the null hypothesis only if the null hypotheses of no association for both traits are rejected. To allow for more than two traits, we developed a new likelihood-ratio test for pleiotropy. We then extended the testing framework to a sequential approach to test the null hypothesis that k + 1 traits are associated, given that the null of k traits are associated was rejected. This provides a formal testing framework to determine the number of traits associated with a genetic variant, while accounting for correlations among the traits. By simulations, we illustrate the type I error rate and power of our new methods; describe how they are influenced by sample size, the number of traits, and the trait correlations; and apply the new methods to multivariate immune phenotypes in response to smallpox vaccination. Our new approach provides a quantitative assessment of pleiotropy, enhancing current analytic practice.",
keywords = "Constrained model, Likelihood-ratio test, Multivariate analysis, Seemingly unrelated regression, Sequential testing",
author = "Schaid, {Daniel J.} and Xingwei Tong and Beth Larrabee and Kennedy, {Richard B.} and Poland, {Gregory A.} and Sinnwell, {Jason P.}",
note = "Funding Information: This research was supported by (1) the U.S. Public Health Service, National Institutes of Health (NIH), grant GM065450 (to D.J.S.); (2) federal funds from the National Institute of Allergies and Infectious Diseases, NIH, Department of Health and Human Services, under contract HHSN266200400025C (N01AI40065) (to G.A.P.); and (3) the National Natural Science Foundation of China (grant 11371062), Beijing Center for Mathematics and Information Interdisciplinary Sciences, China Zhongdian Project (grant 11131002) (to X.T.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. G.A.P. is the chair of a Safety Evaluation Committee for novel investigational vaccine trials being conducted by Merck Research Laboratories. G.A.P. offers consultative advice on vaccine development to Merck & Co. Inc., CSL Biotherapies, Avianax, Dynavax, Novartis Vaccines and Therapeutics, Emergent Biosolutions, Adjuvance, and Microdermis. G.A.P. holds two patents related to vaccinia and measles peptide research. R.B.K. has grant funding from Merck Research Laboratories to study immune responses to mumps vaccine. These activities have been reviewed by the Mayo Clinic Conflict of Interest Review Board and are conducted in compliance with Mayo Clinic Conflict of Interest policies. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and was conducted in compliance with Mayo Clinic Conflict of Interest policies. Publisher Copyright: {\textcopyright} 2016 by the Genetics Society of America.",
year = "2016",
month = oct,
doi = "10.1534/genetics.116.189308",
language = "English (US)",
volume = "204",
pages = "483--497",
journal = "Genetics",
issn = "0016-6731",
publisher = "Genetics Society of America",
number = "2",
}