دورية أكاديمية
أعرض في EDS

Testing cross-phenotype effects of rare variants in longitudinal studies of complex traits.

التفاصيل البيبلوغرافية
العنوان: Testing cross-phenotype effects of rare variants in longitudinal studies of complex traits.
المؤلفون: Rudra P; Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, United States of America., Broadaway KA; Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America., Ware EB; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America.; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America., Jhun MA; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America., Bielak LF; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America., Zhao W; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America., Smith JA; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America., Peyser PA; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America., Kardia SLR; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America., Epstein MP; Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America., Ghosh D; Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, United States of America.
المصدر: Genetic epidemiology [Genet Epidemiol] 2018 Jun; Vol. 42 (4), pp. 320-332. Date of Electronic Publication: 2018 Mar 30.
نوع المنشور: Journal Article; Research Support, N.I.H., Extramural
اللغة: English
بيانات الدورية: Publisher: Wiley-Liss Country of Publication: United States NLM ID: 8411723 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1098-2272 (Electronic) Linking ISSN: 07410395 NLM ISO Abbreviation: Genet Epidemiol Subsets: MEDLINE
أسماء مطبوعة: Publication: New York, NY : Wiley-Liss
Original Publication: New York, N.Y. : Alan R. Liss, c1984-
مواضيع طبية MeSH: Genetic Variation* , Quantitative Trait, Heritable*, Computer Simulation ; Databases, Genetic ; Exome ; Genome-Wide Association Study ; Humans ; Longitudinal Studies ; Models, Genetic ; Phenotype
مستخلص: Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of next-generation sequencing technology, there has been substantial interest in identifying rare variants in genes that possess cross-phenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rare-variant approaches exist for testing cross-phenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for cross-phenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genome-wide scale due to the use of a closed-form test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy.
(© 2018 WILEY PERIODICALS, INC.)
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معلومات مُعتمدة: R56 MH071537 United States MH NIMH NIH HHS; R01 MH071537 United States MH NIMH NIH HHS; R01 AR060893 United States AR NIAMS NIH HHS; R01 HL086694 United States HL NHLBI NIH HHS; R01 HL119443 United States HL NHLBI NIH HHS; U10 HL054457 United States HL NHLBI NIH HHS; R01 GM117946 United States GM NIGMS NIH HHS; U01 HL054457 United States HL NHLBI NIH HHS; R01 HG007508 United States HG NHGRI NIH HHS
فهرسة مساهمة: Keywords: complex human traits; gene mapping; longitudinal data; pleiotropy; rare variant
تواريخ الأحداث: Date Created: 20180331 Date Completed: 20180827 Latest Revision: 20231112
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC5980726
DOI: 10.1002/gepi.22121
PMID: 29601641
قاعدة البيانات: MEDLINE
الوصف
تدمد:1098-2272
DOI:10.1002/gepi.22121