Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores
Year: 2022
Type: article
Source: Nature Genetics
Authors: Omer Weissbrod, Masahiro Kanai, Huwenbo Shi, Steven Gazal, Wouter J. Peyrot, Amit V. Khera, Yukinori Okada, The Biobank Japan Project, Koichi Matsuda, Yuji Yamanashi, Yoichi Furukawa, Takayuki Morisaki, Yoshinori Murakami, Yoichiro Kamatani, Kaori Muto, Akiko Nagai, Wataru Obara, Ken Yamaji, Kazuhisa Takahashi, Satoshi Asai, Yasuo Takahashi, Takao Suzuki, Nobuaki Sinozaki, Hiroki Yamaguchi, Shiro Minami, Shigeo Murayama, Kozo Yoshimori, Satoshi Nagayama, Daisuke Obata, Masahiko Higashiyama, Akihide Masumoto, Yukihiro Koretsune, Alicia R. Martin, Hilary K. Finucane, Alkes L. Price
Institutions: Harvard University, Broad Institute, The University of Osaka, University of Southern California, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Verve Therapeutics (United States), RIKEN Center for Integrative Medical Sciences, Institute of Medical Science, The University of Tokyo, The University of Tokyo, IMSUT Hospital, Iwate Medical University, Juntendo University, Nihon University, Nippon Medical School, Tokyo Metropolitan Institute of Gerontology, Tokyo Metropolitan Geriatric Hospital, Japan Anti Tuberculosis Association, Fukujuji Hospital, The Cancer Institute Hospital, Japanese Foundation For Cancer Research, Shiga University of Medical Science, Osaka International Cancer Institute, Aso Iizuka Hospital, Osaka National Hospital, Massachusetts General Hospital
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funders: U.S. Department of Health and Human Services, Japan Agency for Medical Research and Development, Masason Foundation, Ministry of Education, Culture, Sports, Science and Technology, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Heiwa Nakajima Foundation, P. A. Messerschmidt og Hustrus Fond, National Institutes of Health, Medical Research Council, Japan Society for the Promotion of Science, Japan Science and Technology Agency, National Institute of Mental Health, National Human Genome Research Institute, National Institute of Diabetes and Digestive and Kidney Diseases, Moonshot Research and Development Program, IBM Research, Eric and Wendy Schmidt
Awards: G1231356974, G1291584575, Polygenic prediction of common, complex diseases, G1476793446, 複雑臓器制御系の数理的包括理解と超早期精密医療への挑戦, G2211565120, G223491490, G2480081892, Generalizing polygenic risk prediction methods across populations for insights into psychiatric disease, 臓器連関の包括的理解に基づく認知症関連疾患の克服に向けて, メタゲノムワイド関連解析による疾患特異的微生物叢解明と個別化医療実装, G3302796291, G3326939414, G3466122215, G3634655263, G408796590, G4320204098, Leveraging functional data to predict disease risk in multi-ethnic populations, G4766248584, Generalizing polygenic risk prediction methods across populations for insights into psychiatric disease, G5065495553, 横断的オミクス解析を駆使した肺胞蛋白症の病態解明とインシリコ・リポジショニング創薬, G5368403867, Re-annotation of large-scale human genome data by integration of statistical genetics and operations research, G543711581, G5850737185, G5930682987, G6053344668, G6165002790, G6186324268, Elucidation of disease biology and tissue specificity by trans-layer omics analysis and whole-genome sequencing, G6544258490, Functionally specialized components of disease heritability in ENCODE data, G6687757193, G7523544532, G7548765082, G8616852836, G9000230536, G9000286330, Enabling improved applicability and transferability of polygenic scores across populations, Statistical methods to localize disease heritability and identify biological mechanisms, Functional and population genetic architectures of complex disease, Center for the Study of Inflammatory Bowel Disease at Massachusetts General Hospital, Predicting the impact of genetic variants, genes and pathways on human Disease
OpenAlex ID: W4223474278