Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

Chia Jung Lee; Ting Huei Chen; Aylwin Ming Wee Lim; Chien Ching Chang; Jia Jyun Sie; Pei Lung Chen; Su Wei Chang; Shang Jung Wu; Chia Lin Hsu; Ai Ru Hsieh; Wei Shiung Yang; Cathy S.J. Fann

doi:10.1038/s42003-022-04168-0

Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

Chia Jung Lee, Ting Huei Chen, Aylwin Ming Wee Lim, Chien Ching Chang, Jia Jyun Sie, Pei Lung Chen, Su Wei Chang, Shang Jung Wu, Chia Lin Hsu, Ai Ru Hsieh^*, Wei Shiung Yang^*, Cathy S.J. Fann^*

^*此作品的通信作者

人工智慧學系(含學碩博士班)

研究成果: 期刊稿件 › 文章 › 同行評審

11 引文斯高帕斯（Scopus）

摘要

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.

原文	英語
文章編號	1175
期刊	Communications Biology
卷	5
發行號	1
DOIs	https://doi.org/10.1038/s42003-022-04168-0
出版狀態	已出版 - 12 2022

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title = "Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes",

abstract = "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 HbA1c) 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.",

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AU - Lee, Chia Jung

AU - Chen, Ting Huei

AU - Lim, Aylwin Ming Wee

AU - Chang, Chien Ching

AU - Sie, Jia Jyun

AU - Chen, Pei Lung

AU - Chang, Su Wei

AU - Wu, Shang Jung

AU - Hsu, Chia Lin

AU - Hsieh, Ai Ru

AU - Yang, Wei Shiung

AU - Fann, Cathy S.J.

PY - 2022/12

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N2 - 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 HbA1c) 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.

AB - 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 HbA1c) 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.

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Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

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