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Rare genetic variant analysis on blood pressure in related samples
The genetic variants associated with blood pressure identified so far explain only a small proportion of the total heritability of this trait. With recent advances in sequencing technology and statistical methodology, it becomes feasible to study the association between blood pressure and rare genet...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143757/ https://www.ncbi.nlm.nih.gov/pubmed/25519320 http://dx.doi.org/10.1186/1753-6561-8-S1-S35 |
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author | Chen, Han Choi, Seung Hoan Hong, Jaeyoung Lu, Chen Milton, Jacqueline N Allard, Catherine Lacey, Sean M Lin, Honghuang Dupuis, Josée |
author_facet | Chen, Han Choi, Seung Hoan Hong, Jaeyoung Lu, Chen Milton, Jacqueline N Allard, Catherine Lacey, Sean M Lin, Honghuang Dupuis, Josée |
author_sort | Chen, Han |
collection | PubMed |
description | The genetic variants associated with blood pressure identified so far explain only a small proportion of the total heritability of this trait. With recent advances in sequencing technology and statistical methodology, it becomes feasible to study the association between blood pressure and rare genetic variants. Using real baseline phenotype data and imputed dosage data from Genetic Analysis Workshop 18, we performed a candidate gene association analysis. We focused on 8 genes shown to be associated with either systolic or diastolic blood pressure to identify the association with both common and rare genetic variants, and then did a genome-wide rare-variant analysis on blood pressure. We performed association analysis for rare coding and splicing variants within each gene region and all rare variants in each sliding window, using either burden tests or sequence kernel association tests accounting for familial correlation. With a sample size of only 747, we failed to find any novel associated genetic loci. Consequently, we performed analyses on simulated data, with knowledge of the underlying simulating model, to evaluate the type I error rate and power for the methods used in real data analysis. |
format | Online Article Text |
id | pubmed-4143757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41437572014-09-02 Rare genetic variant analysis on blood pressure in related samples Chen, Han Choi, Seung Hoan Hong, Jaeyoung Lu, Chen Milton, Jacqueline N Allard, Catherine Lacey, Sean M Lin, Honghuang Dupuis, Josée BMC Proc Proceedings The genetic variants associated with blood pressure identified so far explain only a small proportion of the total heritability of this trait. With recent advances in sequencing technology and statistical methodology, it becomes feasible to study the association between blood pressure and rare genetic variants. Using real baseline phenotype data and imputed dosage data from Genetic Analysis Workshop 18, we performed a candidate gene association analysis. We focused on 8 genes shown to be associated with either systolic or diastolic blood pressure to identify the association with both common and rare genetic variants, and then did a genome-wide rare-variant analysis on blood pressure. We performed association analysis for rare coding and splicing variants within each gene region and all rare variants in each sliding window, using either burden tests or sequence kernel association tests accounting for familial correlation. With a sample size of only 747, we failed to find any novel associated genetic loci. Consequently, we performed analyses on simulated data, with knowledge of the underlying simulating model, to evaluate the type I error rate and power for the methods used in real data analysis. BioMed Central 2014-06-17 /pmc/articles/PMC4143757/ /pubmed/25519320 http://dx.doi.org/10.1186/1753-6561-8-S1-S35 Text en Copyright © 2014 Chen et al.; 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 Chen, Han Choi, Seung Hoan Hong, Jaeyoung Lu, Chen Milton, Jacqueline N Allard, Catherine Lacey, Sean M Lin, Honghuang Dupuis, Josée Rare genetic variant analysis on blood pressure in related samples |
title | Rare genetic variant analysis on blood pressure in related samples |
title_full | Rare genetic variant analysis on blood pressure in related samples |
title_fullStr | Rare genetic variant analysis on blood pressure in related samples |
title_full_unstemmed | Rare genetic variant analysis on blood pressure in related samples |
title_short | Rare genetic variant analysis on blood pressure in related samples |
title_sort | rare genetic variant analysis on blood pressure in related samples |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143757/ https://www.ncbi.nlm.nih.gov/pubmed/25519320 http://dx.doi.org/10.1186/1753-6561-8-S1-S35 |
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