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Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study
Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred...
| 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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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666191/ https://www.ncbi.nlm.nih.gov/pubmed/33188205 http://dx.doi.org/10.1038/s41597-020-00716-7 |
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| author | Cai, Lina Wheeler, Eleanor Kerrison, Nicola D. Luan, Jian’an Deloukas, Panos Franks, Paul W. Amiano, Pilar Ardanaz, Eva Bonet, Catalina Fagherazzi, Guy Groop, Leif C. Kaaks, Rudolf Huerta, José María Masala, Giovanna Nilsson, Peter M. Overvad, Kim Pala, Valeria Panico, Salvatore Rodriguez-Barranco, Miguel Rolandsson, Olov Sacerdote, Carlotta Schulze, Matthias B. Spijkerman, Annemieke M. W. Tjonneland, Anne Tumino, Rosario van der Schouw, Yvonne T. Sharp, Stephen J. Forouhi, Nita G. Riboli, Elio McCarthy, Mark I. Barroso, Inês Langenberg, Claudia Wareham, Nicholas J. |
| author_facet | Cai, Lina Wheeler, Eleanor Kerrison, Nicola D. Luan, Jian’an Deloukas, Panos Franks, Paul W. Amiano, Pilar Ardanaz, Eva Bonet, Catalina Fagherazzi, Guy Groop, Leif C. Kaaks, Rudolf Huerta, José María Masala, Giovanna Nilsson, Peter M. Overvad, Kim Pala, Valeria Panico, Salvatore Rodriguez-Barranco, Miguel Rolandsson, Olov Sacerdote, Carlotta Schulze, Matthias B. Spijkerman, Annemieke M. W. Tjonneland, Anne Tumino, Rosario van der Schouw, Yvonne T. Sharp, Stephen J. Forouhi, Nita G. Riboli, Elio McCarthy, Mark I. Barroso, Inês Langenberg, Claudia Wareham, Nicholas J. |
| author_sort | Cai, Lina |
| collection | PubMed |
| description | Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D. |
| format | Online Article Text |
| id | pubmed-7666191 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2020 |
| publisher | Nature Publishing Group UK |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-76661912020-11-17 Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study Cai, Lina Wheeler, Eleanor Kerrison, Nicola D. Luan, Jian’an Deloukas, Panos Franks, Paul W. Amiano, Pilar Ardanaz, Eva Bonet, Catalina Fagherazzi, Guy Groop, Leif C. Kaaks, Rudolf Huerta, José María Masala, Giovanna Nilsson, Peter M. Overvad, Kim Pala, Valeria Panico, Salvatore Rodriguez-Barranco, Miguel Rolandsson, Olov Sacerdote, Carlotta Schulze, Matthias B. Spijkerman, Annemieke M. W. Tjonneland, Anne Tumino, Rosario van der Schouw, Yvonne T. Sharp, Stephen J. Forouhi, Nita G. Riboli, Elio McCarthy, Mark I. Barroso, Inês Langenberg, Claudia Wareham, Nicholas J. Sci Data Data Descriptor Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D. Nature Publishing Group UK 2020-11-13 /pmc/articles/PMC7666191/ /pubmed/33188205 http://dx.doi.org/10.1038/s41597-020-00716-7 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/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
| spellingShingle | Data Descriptor Cai, Lina Wheeler, Eleanor Kerrison, Nicola D. Luan, Jian’an Deloukas, Panos Franks, Paul W. Amiano, Pilar Ardanaz, Eva Bonet, Catalina Fagherazzi, Guy Groop, Leif C. Kaaks, Rudolf Huerta, José María Masala, Giovanna Nilsson, Peter M. Overvad, Kim Pala, Valeria Panico, Salvatore Rodriguez-Barranco, Miguel Rolandsson, Olov Sacerdote, Carlotta Schulze, Matthias B. Spijkerman, Annemieke M. W. Tjonneland, Anne Tumino, Rosario van der Schouw, Yvonne T. Sharp, Stephen J. Forouhi, Nita G. Riboli, Elio McCarthy, Mark I. Barroso, Inês Langenberg, Claudia Wareham, Nicholas J. Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study |
| title | Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study |
| title_full | Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study |
| title_fullStr | Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study |
| title_full_unstemmed | Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study |
| title_short | Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study |
| title_sort | genome-wide association analysis of type 2 diabetes in the epic-interact study |
| topic | Data Descriptor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666191/ https://www.ncbi.nlm.nih.gov/pubmed/33188205 http://dx.doi.org/10.1038/s41597-020-00716-7 |
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