Back to Search Start Over

A global atlas of genetic associations of 220 deep phenotypes

Authors :
Nobuaki Shinozaki
Manuel A. Rivas
Kazuyoshi Ishigaki
Mitja I. Kurki
Aarno Palotie
Ken Yamaji
Akari Suzuki
Masayuki Yamamoto
Yoichiro Kamatani
Hiroki Yamaguchi
Issei Komuro
Kenichi Yamamoto
Kaoru Ito
Finn Gen
Saori Sakaue
Mark J. Daly
Masahiro Kanai
Juha Karjalainen
Takao Suzuki
Satoshi Asai
Shigeo Murayama
Koichi Matsuda
Masato Akiyama
Ken Suzuki
Kozo Yoshimori
Chikashi Terao
Seizo Koshiba
Daisuke Obata
Akira Narita
Kazuhiko Yamamoto
Masahiko Higashiyama
Yusuke Nakamura
Yosuke Tanigawa
Kazuhisa Takahashi
Takahiro Konuma
Gen Tamiya
Akihide Masumoto
Shiro Minami
Yasuo Takahashi
Satoshi Nagayama
Toshimasa Yamauchi
Yoshinori Murakami
Michiaki Kubo
Yukinori Okada
Yukihiro Koretsune
Wataru Obara
Takashi Kadowaki
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

The current genome-wide association studies (GWASs) do not yet capture sufficient diversity in terms of populations and scope of phenotypes. To address an essential need to expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype GWASs (disease endpoints, biomarkers, and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining results of electronic medical records. Meta-analyses with the harmonized phenotypes in the UK Biobank and FinnGen (ntotal = 628,000) identified over 4,000 novel loci, which substantially deepened the resolution of the genomic map of human traits, benefited from East Asian endemic diseases and East Asian specific variants. This atlas elucidated the globally shared landscape of pleiotropy as represented by the MHC locus, where we conducted fine-mapping by HLA imputation. Finally, to intensify the value of deep-phenotype GWASs, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified the latent genetic components, which pinpointed the responsible variants and shared biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (e.g., allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human disease classifications through genetics.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........fc338adde36b6d573d8c900a0599830b
Full Text :
https://doi.org/10.1101/2020.10.23.20213652