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Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes
Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of w...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063971/ https://www.ncbi.nlm.nih.gov/pubmed/30054458 http://dx.doi.org/10.1038/s41467-018-04951-w |
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author | Xue, Angli Wu, Yang Zhu, Zhihong Zhang, Futao Kemper, Kathryn E. Zheng, Zhili Yengo, Loic Lloyd-Jones, Luke R. Sidorenko, Julia Wu, Yeda McRae, Allan F. Visscher, Peter M. Zeng, Jian Yang, Jian |
author_facet | Xue, Angli Wu, Yang Zhu, Zhihong Zhang, Futao Kemper, Kathryn E. Zheng, Zhili Yengo, Loic Lloyd-Jones, Luke R. Sidorenko, Julia Wu, Yeda McRae, Allan F. Visscher, Peter M. Zeng, Jian Yang, Jian |
author_sort | Xue, Angli |
collection | PubMed |
description | Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants. |
format | Online Article Text |
id | pubmed-6063971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60639712018-07-30 Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes Xue, Angli Wu, Yang Zhu, Zhihong Zhang, Futao Kemper, Kathryn E. Zheng, Zhili Yengo, Loic Lloyd-Jones, Luke R. Sidorenko, Julia Wu, Yeda McRae, Allan F. Visscher, Peter M. Zeng, Jian Yang, Jian Nat Commun Article Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants. Nature Publishing Group UK 2018-07-27 /pmc/articles/PMC6063971/ /pubmed/30054458 http://dx.doi.org/10.1038/s41467-018-04951-w 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 Xue, Angli Wu, Yang Zhu, Zhihong Zhang, Futao Kemper, Kathryn E. Zheng, Zhili Yengo, Loic Lloyd-Jones, Luke R. Sidorenko, Julia Wu, Yeda McRae, Allan F. Visscher, Peter M. Zeng, Jian Yang, Jian Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
title | Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
title_full | Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
title_fullStr | Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
title_full_unstemmed | Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
title_short | Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
title_sort | genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063971/ https://www.ncbi.nlm.nih.gov/pubmed/30054458 http://dx.doi.org/10.1038/s41467-018-04951-w |
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