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Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network
Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic a...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561060/ https://www.ncbi.nlm.nih.gov/pubmed/23382687 http://dx.doi.org/10.1371/journal.pgen.1003087 |
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author | Pendergrass, Sarah A. Brown-Gentry, Kristin Dudek, Scott Frase, Alex Torstenson, Eric S. Goodloe, Robert Ambite, Jose Luis Avery, Christy L. Buyske, Steve Bůžková, Petra Deelman, Ewa Fesinmeyer, Megan D. Haiman, Christopher A. Heiss, Gerardo Hindorff, Lucia A. Hsu, Chu-Nan Jackson, Rebecca D. Kooperberg, Charles Le Marchand, Loic Lin, Yi Matise, Tara C. Monroe, Kristine R. Moreland, Larry Park, Sungshim L. Reiner, Alex Wallace, Robert Wilkens, Lynn R. Crawford, Dana C. Ritchie, Marylyn D. |
author_facet | Pendergrass, Sarah A. Brown-Gentry, Kristin Dudek, Scott Frase, Alex Torstenson, Eric S. Goodloe, Robert Ambite, Jose Luis Avery, Christy L. Buyske, Steve Bůžková, Petra Deelman, Ewa Fesinmeyer, Megan D. Haiman, Christopher A. Heiss, Gerardo Hindorff, Lucia A. Hsu, Chu-Nan Jackson, Rebecca D. Kooperberg, Charles Le Marchand, Loic Lin, Yi Matise, Tara C. Monroe, Kristine R. Moreland, Larry Park, Sungshim L. Reiner, Alex Wallace, Robert Wilkens, Lynn R. Crawford, Dana C. Ritchie, Marylyn D. |
author_sort | Pendergrass, Sarah A. |
collection | PubMed |
description | Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits. |
format | Online Article Text |
id | pubmed-3561060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35610602013-02-04 Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network Pendergrass, Sarah A. Brown-Gentry, Kristin Dudek, Scott Frase, Alex Torstenson, Eric S. Goodloe, Robert Ambite, Jose Luis Avery, Christy L. Buyske, Steve Bůžková, Petra Deelman, Ewa Fesinmeyer, Megan D. Haiman, Christopher A. Heiss, Gerardo Hindorff, Lucia A. Hsu, Chu-Nan Jackson, Rebecca D. Kooperberg, Charles Le Marchand, Loic Lin, Yi Matise, Tara C. Monroe, Kristine R. Moreland, Larry Park, Sungshim L. Reiner, Alex Wallace, Robert Wilkens, Lynn R. Crawford, Dana C. Ritchie, Marylyn D. PLoS Genet Research Article Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits. Public Library of Science 2013-01-31 /pmc/articles/PMC3561060/ /pubmed/23382687 http://dx.doi.org/10.1371/journal.pgen.1003087 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Pendergrass, Sarah A. Brown-Gentry, Kristin Dudek, Scott Frase, Alex Torstenson, Eric S. Goodloe, Robert Ambite, Jose Luis Avery, Christy L. Buyske, Steve Bůžková, Petra Deelman, Ewa Fesinmeyer, Megan D. Haiman, Christopher A. Heiss, Gerardo Hindorff, Lucia A. Hsu, Chu-Nan Jackson, Rebecca D. Kooperberg, Charles Le Marchand, Loic Lin, Yi Matise, Tara C. Monroe, Kristine R. Moreland, Larry Park, Sungshim L. Reiner, Alex Wallace, Robert Wilkens, Lynn R. Crawford, Dana C. Ritchie, Marylyn D. Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network |
title | Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network |
title_full | Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network |
title_fullStr | Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network |
title_full_unstemmed | Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network |
title_short | Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network |
title_sort | phenome-wide association study (phewas) for detection of pleiotropy within the population architecture using genomics and epidemiology (page) network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561060/ https://www.ncbi.nlm.nih.gov/pubmed/23382687 http://dx.doi.org/10.1371/journal.pgen.1003087 |
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