Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses.
Autor: | Ojima T; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.; Graduate School of Medicine, Tohoku University, Sendai, Japan.; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.; Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan., Namba S; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan., Suzuki K; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.; Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan., Yamamoto K; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.; Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan.; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan.; Laboratory of Children's Health and Genetics, Division of Health Science, Osaka University Graduate School of Medicine, Osaka, Japan., Sonehara K; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan., Narita A; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan., Kamatani Y; Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan., Tamiya G; Graduate School of Medicine, Tohoku University, Sendai, Japan.; Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan., Yamamoto M; Graduate School of Medicine, Tohoku University, Sendai, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan., Yamauchi T; Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan., Kadowaki T; Toranomon Hospital, Tokyo, Japan., Okada Y; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan. yuki-okada@m.u-tokyo.ac.jp.; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. yuki-okada@m.u-tokyo.ac.jp.; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.; Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Osaka, Japan. yuki-okada@m.u-tokyo.ac.jp. |
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Jazyk: | angličtina |
Zdroj: | Nature genetics [Nat Genet] 2024 Jun; Vol. 56 (6), pp. 1100-1109. Date of Electronic Publication: 2024 Jun 11. |
DOI: | 10.1038/s41588-024-01782-y |
Abstrakt: | Type 2 diabetes (T2D) shows heterogeneous body mass index (BMI) sensitivity. Here, we performed stratification based on BMI to optimize predictions for BMI-related diseases. We obtained BMI-stratified datasets using data from more than 195,000 individuals (n (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.) |
Databáze: | MEDLINE |
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