Using a Bayesian latent variable approach to detect pleiotropy in the Genetic Analysis Workshop 18 data

BMC Proceedings

Proceedings

Andriy Derkach¹  Lizhen Xu¹  Radu V Craiu¹  Lei Sun²  Andrew D Paterson³ 

[1] Department of Statistical Sciences, University of Toronto, M5S 3G3, Toronto, Ontario, Canada;Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, M5S 3G3, Ontario, Canada;Department of Statistical Sciences, University of Toronto, M5S 3G3, Toronto, Ontario, Canada;Program in Genetics and Genome Biology, The Hospital for Sick Children, M5G 1X8, Toronto, Canada;Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, M5S 3G3, Ontario, Canada;

关键词: Quantitative Trait Locus;    Diastolic Blood Pressure;    Latent Variable;    Markov Chain Monte Carlo;    Deviance Information Criterion;   

DOI  :  10.1186/1753-6561-8-S1-S77

来源: Springer

【 摘 要 】

Pleiotropy, which occurs when a single genetic factor influences multiple phenotypes, is present in many genetic studies of complex human traits. Longitudinal family data, such as the Genetic Analysis Workshop 18 data, combine the features of longitudinal studies in individuals and cross-sectional studies in families, thus providing richer information about the genetic and environmental factors associated with the trait of interest. We recently proposed a Bayesian latent variable methodology for the study of pleiotropy, in the presence of longitudinal and family correlation. The purpose of this work is to evaluate the Bayesian latent variable method in a real data setting using the Genetic Analysis Workshop 18 blood pressure phenotypes and sequenced genotype data. To detect single-nucleotide polymorphisms with pleiotropic effect on both diastolic and systolic blood pressure, we focused on a set of 6 single-nucleotide polymorphisms from chromosome 3 that was reported in the literature to be significantly associated with either diastolic blood pressure or the binary hypertension trait. Our analysis suggests that both diastolic blood pressure and systolic blood pressure are associated with the latent hypertension severity variable, but the analysis did not find any of the 6 single-nucleotide polymorphisms to have statistically significant pleiotropic effect on both diastolic blood pressure and systolic blood pressure.

【 授权许可】

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© Xu et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.