A cross-population atlas of genetic associations for 220 human phenotypes View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-09-30

AUTHORS

Saori Sakaue, Masahiro Kanai, Yosuke Tanigawa, Juha Karjalainen, Mitja Kurki, Seizo Koshiba, Akira Narita, Takahiro Konuma, Kenichi Yamamoto, Masato Akiyama, Kazuyoshi Ishigaki, Akari Suzuki, Ken Suzuki, Wataru Obara, Ken Yamaji, Kazuhisa Takahashi, Satoshi Asai, Yasuo Takahashi, Takao Suzuki, Nobuaki Shinozaki, Hiroki Yamaguchi, Shiro Minami, Shigeo Murayama, Kozo Yoshimori, Satoshi Nagayama, Daisuke Obata, Masahiko Higashiyama, Akihide Masumoto, Yukihiro Koretsune, Kaoru Ito, Chikashi Terao, Toshimasa Yamauchi, Issei Komuro, Takashi Kadowaki, Gen Tamiya, Masayuki Yamamoto, Yusuke Nakamura, Michiaki Kubo, Yoshinori Murakami, Kazuhiko Yamamoto, Yoichiro Kamatani, Aarno Palotie, Manuel A. Rivas, Mark J. Daly, Koichi Matsuda, Yukinori Okada

ABSTRACT

Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (ntotal = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics. More... »

PAGES

1415-1424

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  • Journal

    TITLE

    Nature Genetics

    ISSUE

    10

    VOLUME

    53

    Author Affiliations

  • Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
  • Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
  • Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
  • Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Sendai, Japan
  • Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
  • Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
  • Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
  • Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
  • Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
  • Department of Urology, Iwate Medical University, Iwate, Japan
  • Department of Internal Medicine and Rheumatology, Juntendo University Graduate School of Medicine, Tokyo, Japan
  • Department of Respiratory Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
  • Division of Genomic Epidemiology and Clinical Trials, Clinical Trials Research Center, Nihon University School of Medicine, Tokyo, Japan
  • Tokushukai Group, Tokyo, Japan
  • Department of Hematology, Nippon Medical School, Tokyo, Japan
  • Department of Bioregulation, Nippon Medical School, Kawasaki, Japan
  • Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
  • Fukujuji Hospital, Japan Anti-Tuberculosis Association, Tokyo, Japan
  • The Cancer Institute Hospital of the Japanese Foundation for Cancer Research, Tokyo, Japan
  • Center for Clinical Research and Advanced Medicine, Shiga University of Medical Science, Otsu, Japan
  • Department of General Thoracic Surgery, Osaka International Cancer Institute, Osaka, Japan
  • Aso Iizuka Hospital, Fukuoka, Japan
  • National Hospital Organization Osaka National Hospital, Osaka, Japan
  • Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
  • Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
  • Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
  • Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
  • Toranomon Hospital, Tokyo, Japan
  • Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan
  • Graduate School of Medicine, Tohoku University, Sendai, Japan
  • Cancer Precision Medicine Center, Japanese Foundation for Cancer Research, Tokyo, Japan
  • RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
  • Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
  • Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
  • Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Analytic and Translational Genetics Unit, Department of Medicine, and the Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
  • Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, Japan
  • Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41588-021-00931-x

    DOI

    http://dx.doi.org/10.1038/s41588-021-00931-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1141514274

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/34594039


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