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Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure
Genetic variants that predispose adults and the elderly to high blood pressure are largely unknown. We used a bivariate linear mixed model approach to jointly test the associations of common single-nucleotide polymorphisms with systolic and diastolic blood pressure using data from a genome-wide asso...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143667/ https://www.ncbi.nlm.nih.gov/pubmed/25519403 http://dx.doi.org/10.1186/1753-6561-8-S1-S75 |
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author | Neupane, Binod Beyene, Joseph |
author_facet | Neupane, Binod Beyene, Joseph |
author_sort | Neupane, Binod |
collection | PubMed |
description | Genetic variants that predispose adults and the elderly to high blood pressure are largely unknown. We used a bivariate linear mixed model approach to jointly test the associations of common single-nucleotide polymorphisms with systolic and diastolic blood pressure using data from a genome-wide association study consisting of genetic variants from chromosomes 3 and 9 and longitudinal measured phenotypes and environment variables from unrelated individuals of Mexican American ethnicity provided by the Genetic Analysis Workshop 18. Despite the small sample size of a maximum of 131 unrelated subjects, a few single-nucleotide polymorphisms appeared significant at the genome-wide level. Simulated data, which was also provided by Genetic Analysis Workshop 18 organizers, showed higher power of the bivariate approach over univariate analysis to detect the association of a selected single-nucleotide polymorphism with modest effect. This suggests that the bivariate approach to longitudinal data of jointly measured and correlated phenotypes can be a useful strategy to identify candidate single-nucleotide polymorphisms that deserve further investigation. |
format | Online Article Text |
id | pubmed-4143667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41436672014-09-02 Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure Neupane, Binod Beyene, Joseph BMC Proc Proceedings Genetic variants that predispose adults and the elderly to high blood pressure are largely unknown. We used a bivariate linear mixed model approach to jointly test the associations of common single-nucleotide polymorphisms with systolic and diastolic blood pressure using data from a genome-wide association study consisting of genetic variants from chromosomes 3 and 9 and longitudinal measured phenotypes and environment variables from unrelated individuals of Mexican American ethnicity provided by the Genetic Analysis Workshop 18. Despite the small sample size of a maximum of 131 unrelated subjects, a few single-nucleotide polymorphisms appeared significant at the genome-wide level. Simulated data, which was also provided by Genetic Analysis Workshop 18 organizers, showed higher power of the bivariate approach over univariate analysis to detect the association of a selected single-nucleotide polymorphism with modest effect. This suggests that the bivariate approach to longitudinal data of jointly measured and correlated phenotypes can be a useful strategy to identify candidate single-nucleotide polymorphisms that deserve further investigation. BioMed Central 2014-06-17 /pmc/articles/PMC4143667/ /pubmed/25519403 http://dx.doi.org/10.1186/1753-6561-8-S1-S75 Text en Copyright © 2014 Neupane and Beyene; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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. |
spellingShingle | Proceedings Neupane, Binod Beyene, Joseph Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
title | Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
title_full | Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
title_fullStr | Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
title_full_unstemmed | Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
title_short | Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
title_sort | bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143667/ https://www.ncbi.nlm.nih.gov/pubmed/25519403 http://dx.doi.org/10.1186/1753-6561-8-S1-S75 |
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