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Phenome-wide association studies across large population cohorts support drug target validation

Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-...

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Autores principales: Diogo, Dorothée, Tian, Chao, Franklin, Christopher S., Alanne-Kinnunen, Mervi, March, Michael, Spencer, Chris C. A., Vangjeli, Ciara, Weale, Michael E., Mattsson, Hannele, Kilpeläinen, Elina, Sleiman, Patrick M. A., Reilly, Dermot F., McElwee, Joshua, Maranville, Joseph C., Chatterjee, Arnaub K., Bhandari, Aman, Nguyen, Khanh-Dung H., Estrada, Karol, Reeve, Mary-Pat, Hutz, Janna, Bing, Nan, John, Sally, MacArthur, Daniel G., Salomaa, Veikko, Ripatti, Samuli, Hakonarson, Hakon, Daly, Mark J., Palotie, Aarno, Hinds, David A., Donnelly, Peter, Fox, Caroline S., Day-Williams, Aaron G., Plenge, Robert M., Runz, Heiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191429/
https://www.ncbi.nlm.nih.gov/pubmed/30327483
http://dx.doi.org/10.1038/s41467-018-06540-3
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author Diogo, Dorothée
Tian, Chao
Franklin, Christopher S.
Alanne-Kinnunen, Mervi
March, Michael
Spencer, Chris C. A.
Vangjeli, Ciara
Weale, Michael E.
Mattsson, Hannele
Kilpeläinen, Elina
Sleiman, Patrick M. A.
Reilly, Dermot F.
McElwee, Joshua
Maranville, Joseph C.
Chatterjee, Arnaub K.
Bhandari, Aman
Nguyen, Khanh-Dung H.
Estrada, Karol
Reeve, Mary-Pat
Hutz, Janna
Bing, Nan
John, Sally
MacArthur, Daniel G.
Salomaa, Veikko
Ripatti, Samuli
Hakonarson, Hakon
Daly, Mark J.
Palotie, Aarno
Hinds, David A.
Donnelly, Peter
Fox, Caroline S.
Day-Williams, Aaron G.
Plenge, Robert M.
Runz, Heiko
author_facet Diogo, Dorothée
Tian, Chao
Franklin, Christopher S.
Alanne-Kinnunen, Mervi
March, Michael
Spencer, Chris C. A.
Vangjeli, Ciara
Weale, Michael E.
Mattsson, Hannele
Kilpeläinen, Elina
Sleiman, Patrick M. A.
Reilly, Dermot F.
McElwee, Joshua
Maranville, Joseph C.
Chatterjee, Arnaub K.
Bhandari, Aman
Nguyen, Khanh-Dung H.
Estrada, Karol
Reeve, Mary-Pat
Hutz, Janna
Bing, Nan
John, Sally
MacArthur, Daniel G.
Salomaa, Veikko
Ripatti, Samuli
Hakonarson, Hakon
Daly, Mark J.
Palotie, Aarno
Hinds, David A.
Donnelly, Peter
Fox, Caroline S.
Day-Williams, Aaron G.
Plenge, Robert M.
Runz, Heiko
author_sort Diogo, Dorothée
collection PubMed
description Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P < 0.05) and identify nine study-wide significant novel associations (of 71 with FDR < 0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.
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spelling pubmed-61914292018-10-19 Phenome-wide association studies across large population cohorts support drug target validation Diogo, Dorothée Tian, Chao Franklin, Christopher S. Alanne-Kinnunen, Mervi March, Michael Spencer, Chris C. A. Vangjeli, Ciara Weale, Michael E. Mattsson, Hannele Kilpeläinen, Elina Sleiman, Patrick M. A. Reilly, Dermot F. McElwee, Joshua Maranville, Joseph C. Chatterjee, Arnaub K. Bhandari, Aman Nguyen, Khanh-Dung H. Estrada, Karol Reeve, Mary-Pat Hutz, Janna Bing, Nan John, Sally MacArthur, Daniel G. Salomaa, Veikko Ripatti, Samuli Hakonarson, Hakon Daly, Mark J. Palotie, Aarno Hinds, David A. Donnelly, Peter Fox, Caroline S. Day-Williams, Aaron G. Plenge, Robert M. Runz, Heiko Nat Commun Article Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P < 0.05) and identify nine study-wide significant novel associations (of 71 with FDR < 0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery. Nature Publishing Group UK 2018-10-16 /pmc/articles/PMC6191429/ /pubmed/30327483 http://dx.doi.org/10.1038/s41467-018-06540-3 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Diogo, Dorothée
Tian, Chao
Franklin, Christopher S.
Alanne-Kinnunen, Mervi
March, Michael
Spencer, Chris C. A.
Vangjeli, Ciara
Weale, Michael E.
Mattsson, Hannele
Kilpeläinen, Elina
Sleiman, Patrick M. A.
Reilly, Dermot F.
McElwee, Joshua
Maranville, Joseph C.
Chatterjee, Arnaub K.
Bhandari, Aman
Nguyen, Khanh-Dung H.
Estrada, Karol
Reeve, Mary-Pat
Hutz, Janna
Bing, Nan
John, Sally
MacArthur, Daniel G.
Salomaa, Veikko
Ripatti, Samuli
Hakonarson, Hakon
Daly, Mark J.
Palotie, Aarno
Hinds, David A.
Donnelly, Peter
Fox, Caroline S.
Day-Williams, Aaron G.
Plenge, Robert M.
Runz, Heiko
Phenome-wide association studies across large population cohorts support drug target validation
title Phenome-wide association studies across large population cohorts support drug target validation
title_full Phenome-wide association studies across large population cohorts support drug target validation
title_fullStr Phenome-wide association studies across large population cohorts support drug target validation
title_full_unstemmed Phenome-wide association studies across large population cohorts support drug target validation
title_short Phenome-wide association studies across large population cohorts support drug target validation
title_sort phenome-wide association studies across large population cohorts support drug target validation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191429/
https://www.ncbi.nlm.nih.gov/pubmed/30327483
http://dx.doi.org/10.1038/s41467-018-06540-3
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