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Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts
Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nev...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6987107/ https://www.ncbi.nlm.nih.gov/pubmed/31992710 http://dx.doi.org/10.1038/s41467-020-14288-y |
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author | Cirulli, Elizabeth T. White, Simon Read, Robert W. Elhanan, Gai Metcalf, William J. Tanudjaja, Francisco Fath, Donna M. Sandoval, Efren Isaksson, Magnus Schlauch, Karen A. Grzymski, Joseph J. Lu, James T. Washington, Nicole L. |
author_facet | Cirulli, Elizabeth T. White, Simon Read, Robert W. Elhanan, Gai Metcalf, William J. Tanudjaja, Francisco Fath, Donna M. Sandoval, Efren Isaksson, Magnus Schlauch, Karen A. Grzymski, Joseph J. Lu, James T. Washington, Nicole L. |
author_sort | Cirulli, Elizabeth T. |
collection | PubMed |
description | Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data. |
format | Online Article Text |
id | pubmed-6987107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69871072020-01-30 Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts Cirulli, Elizabeth T. White, Simon Read, Robert W. Elhanan, Gai Metcalf, William J. Tanudjaja, Francisco Fath, Donna M. Sandoval, Efren Isaksson, Magnus Schlauch, Karen A. Grzymski, Joseph J. Lu, James T. Washington, Nicole L. Nat Commun Article Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data. Nature Publishing Group UK 2020-01-28 /pmc/articles/PMC6987107/ /pubmed/31992710 http://dx.doi.org/10.1038/s41467-020-14288-y Text en © The Author(s) 2020 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 Cirulli, Elizabeth T. White, Simon Read, Robert W. Elhanan, Gai Metcalf, William J. Tanudjaja, Francisco Fath, Donna M. Sandoval, Efren Isaksson, Magnus Schlauch, Karen A. Grzymski, Joseph J. Lu, James T. Washington, Nicole L. Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
title | Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
title_full | Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
title_fullStr | Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
title_full_unstemmed | Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
title_short | Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
title_sort | genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6987107/ https://www.ncbi.nlm.nih.gov/pubmed/31992710 http://dx.doi.org/10.1038/s41467-020-14288-y |
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