Back to Search Start Over

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

Authors :
Yukinori Okada
Hiroki Yamaguchi
Kazuyoshi Ishigaki
Shigeo Murayama
Yosuke Tanigawa
Gen Tamiya
Masayuki Yamamoto
Yoichiro Kamatani
Akihide Masumoto
Manuel A. Rivas
Yusuke Nakamura
Issei Komuro
Akira Narita
Masahiro Kanai
Ken Yamaji
Shiro Minami
Yasuo Takahashi
Toshimasa Yamauchi
Takahiro Konuma
Mark J. Daly
Yoshinori Murakami
Chikashi Terao
Koichi Matsuda
Kazuhisa Takahashi
Michiaki Kubo
Masahiko Higashiyama
Kaoru Ito
Saori Sakaue
Akari Suzuki
Nobuaki Shinozaki
Takao Suzuki
Satoshi Asai
Ken Suzuki
Kazuhiko Yamamoto
Takashi Kadowaki
Yukihiro Koretsune
Wataru Obara
Kenichi Yamamoto
Seizo Koshiba
Juha Karjalainen
Kozo Yoshimori
FinnGen
Daisuke Obata
Masato Akiyama
Satoshi Nagayama
Mitja I. Kurki
Aarno Palotie
Source :
Nature Genetics. 53:1415-1424
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

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.

Details

ISSN :
15461718 and 10614036
Volume :
53
Database :
OpenAIRE
Journal :
Nature Genetics
Accession number :
edsair.doi...........f92ff241b9e6afec4c4644f78f482606