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Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals
Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Di...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285412/ https://www.ncbi.nlm.nih.gov/pubmed/34272381 http://dx.doi.org/10.1038/s41467-021-24491-0 |
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author | Stanzick, Kira J. Li, Yong Schlosser, Pascal Gorski, Mathias Wuttke, Matthias Thomas, Laurent F. Rasheed, Humaira Rowan, Bryce X. Graham, Sarah E. Vanderweff, Brett R. Patil, Snehal B. Robinson-Cohen, Cassiane Gaziano, John M. O’Donnell, Christopher J. Willer, Cristen J. Hallan, Stein Åsvold, Bjørn Olav Gessner, Andre Hung, Adriana M. Pattaro, Cristian Köttgen, Anna Stark, Klaus J. Heid, Iris M. Winkler, Thomas W. |
author_facet | Stanzick, Kira J. Li, Yong Schlosser, Pascal Gorski, Mathias Wuttke, Matthias Thomas, Laurent F. Rasheed, Humaira Rowan, Bryce X. Graham, Sarah E. Vanderweff, Brett R. Patil, Snehal B. Robinson-Cohen, Cassiane Gaziano, John M. O’Donnell, Christopher J. Willer, Cristen J. Hallan, Stein Åsvold, Bjørn Olav Gessner, Andre Hung, Adriana M. Pattaro, Cristian Köttgen, Anna Stark, Klaus J. Heid, Iris M. Winkler, Thomas W. |
author_sort | Stanzick, Kira J. |
collection | PubMed |
description | Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up. |
format | Online Article Text |
id | pubmed-8285412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82854122021-07-23 Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals Stanzick, Kira J. Li, Yong Schlosser, Pascal Gorski, Mathias Wuttke, Matthias Thomas, Laurent F. Rasheed, Humaira Rowan, Bryce X. Graham, Sarah E. Vanderweff, Brett R. Patil, Snehal B. Robinson-Cohen, Cassiane Gaziano, John M. O’Donnell, Christopher J. Willer, Cristen J. Hallan, Stein Åsvold, Bjørn Olav Gessner, Andre Hung, Adriana M. Pattaro, Cristian Köttgen, Anna Stark, Klaus J. Heid, Iris M. Winkler, Thomas W. Nat Commun Article Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up. Nature Publishing Group UK 2021-07-16 /pmc/articles/PMC8285412/ /pubmed/34272381 http://dx.doi.org/10.1038/s41467-021-24491-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Stanzick, Kira J. Li, Yong Schlosser, Pascal Gorski, Mathias Wuttke, Matthias Thomas, Laurent F. Rasheed, Humaira Rowan, Bryce X. Graham, Sarah E. Vanderweff, Brett R. Patil, Snehal B. Robinson-Cohen, Cassiane Gaziano, John M. O’Donnell, Christopher J. Willer, Cristen J. Hallan, Stein Åsvold, Bjørn Olav Gessner, Andre Hung, Adriana M. Pattaro, Cristian Köttgen, Anna Stark, Klaus J. Heid, Iris M. Winkler, Thomas W. Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
title | Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
title_full | Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
title_fullStr | Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
title_full_unstemmed | Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
title_short | Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
title_sort | discovery and prioritization of variants and genes for kidney function in >1.2 million individuals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285412/ https://www.ncbi.nlm.nih.gov/pubmed/34272381 http://dx.doi.org/10.1038/s41467-021-24491-0 |
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