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Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes
To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. F...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633758/ https://www.ncbi.nlm.nih.gov/pubmed/36329257 http://dx.doi.org/10.1038/s42003-022-04168-0 |
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author | Lee, Chia-Jung Chen, Ting-Huei Lim, Aylwin Ming Wee Chang, Chien-Ching Sie, Jia-Jyun Chen, Pei-Lung Chang, Su-Wei Wu, Shang-Jung Hsu, Chia-Lin Hsieh, Ai-Ru Yang, Wei-Shiung Fann, Cathy S. J. |
author_facet | Lee, Chia-Jung Chen, Ting-Huei Lim, Aylwin Ming Wee Chang, Chien-Ching Sie, Jia-Jyun Chen, Pei-Lung Chang, Su-Wei Wu, Shang-Jung Hsu, Chia-Lin Hsieh, Ai-Ru Yang, Wei-Shiung Fann, Cathy S. J. |
author_sort | Lee, Chia-Jung |
collection | PubMed |
description | To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA(1c)) was performed and identified 115 significant loci with four novel genetic variants (HACL1, RAD21, ASH1L and GAK). Transcriptomics data also strengthen the relevancy of the findings to metabolic disorders, thus contributing to better understanding of pathogenesis. In addition, genetic risk scores are constructed and validated for absolute risks prediction of T2D in Taiwanese population. In conclusion, our data-driven approach without a priori hypothesis is useful for novel gene discovery and validation on top of disease risk prediction for unique non-European population. |
format | Online Article Text |
id | pubmed-9633758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96337582022-11-05 Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes Lee, Chia-Jung Chen, Ting-Huei Lim, Aylwin Ming Wee Chang, Chien-Ching Sie, Jia-Jyun Chen, Pei-Lung Chang, Su-Wei Wu, Shang-Jung Hsu, Chia-Lin Hsieh, Ai-Ru Yang, Wei-Shiung Fann, Cathy S. J. Commun Biol Article To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA(1c)) was performed and identified 115 significant loci with four novel genetic variants (HACL1, RAD21, ASH1L and GAK). Transcriptomics data also strengthen the relevancy of the findings to metabolic disorders, thus contributing to better understanding of pathogenesis. In addition, genetic risk scores are constructed and validated for absolute risks prediction of T2D in Taiwanese population. In conclusion, our data-driven approach without a priori hypothesis is useful for novel gene discovery and validation on top of disease risk prediction for unique non-European population. Nature Publishing Group UK 2022-11-03 /pmc/articles/PMC9633758/ /pubmed/36329257 http://dx.doi.org/10.1038/s42003-022-04168-0 Text en © The Author(s) 2022 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 Lee, Chia-Jung Chen, Ting-Huei Lim, Aylwin Ming Wee Chang, Chien-Ching Sie, Jia-Jyun Chen, Pei-Lung Chang, Su-Wei Wu, Shang-Jung Hsu, Chia-Lin Hsieh, Ai-Ru Yang, Wei-Shiung Fann, Cathy S. J. Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes |
title | Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes |
title_full | Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes |
title_fullStr | Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes |
title_full_unstemmed | Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes |
title_short | Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes |
title_sort | phenome-wide analysis of taiwan biobank reveals novel glycemia-related loci and genetic risks for diabetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633758/ https://www.ncbi.nlm.nih.gov/pubmed/36329257 http://dx.doi.org/10.1038/s42003-022-04168-0 |
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