Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

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

Saori Sakaue, Masahiro Kanai, Yosuke Tanigawa, Juha Karjalainen, Mitja Kurki, S. 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, FinnGen, 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

Nature Genetics · 2021

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Summary

This 2021 Nature Genetics paper presents a large-scale cross-population genetic association atlas encompassing 220 human phenotypes, substantially advancing the inclusivity of genomic research by integrating data from Japanese and Finnish biobanks alongside other ancestry groups. By reducing the historical over-representation of European ancestry in GWAS, the work provides evidence-grounded estimates of genetic effects on health traits across diverse populations. The atlas supports more equitable translation of genomic discoveries into clinical and public health practice.

Regional applicability

The findings provide genetic effect estimates that are more representative of global ancestry diversity, which may improve the clinical validity of polygenic risk scores and genomic prediction tools when applied to United Kingdom populations with mixed ancestry backgrounds. The inclusive approach supports more equitable genomic medicine practices in NHS settings and research contexts.

Key measures

Genome-wide association statistics (effect sizes, p-values) for 220 phenotypes; ancestry group representation and allele frequency variation; genetic contribution to phenotypic variance across populations

Outcomes reported

The study mapped genetic associations for 220 human phenotypes across multiple ancestry groups, integrating data from diverse biobanks including Japanese cohorts and FinnGen. The work quantified genetic effects on health-related traits whilst reducing ancestry bias in genome-wide association study (GWAS) findings.

Theme
Nutrition & health
Subject
Measurement methods & nutrient profiling
Study type
Meta-analysis
Study design
Meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Human clinical
DOI
10.1038/s41588-021-00931-x
Catalogue ID
SNmoi53hbn-bcsind

Topic tags

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