Back to Search Start Over

Population-specific and trans-ancestry genome-wide analyses identify distinct and shared genetic risk loci for coronary artery disease

Authors :
Naoyuki Takashima
Yasushi Sakata
Shoichiro Tsugane
Momoko Horikoshi
Yasuhiko Sakata
Hiroshi Akazawa
Yukihide Momozawa
Kaoru Ito
Hiroaki Ikezaki
Michiaki Kubo
Teruhide Koyama
Mariko Naito
Masato Akiyama
Satoshi Koyama
Kenji Wakai
Hiroyuki Morita
Hiroshi Sato
Atsushi Takahashi
Taiki Yamaji
Chikashi Terao
Seitaro Nomura
Jeong-Sun Seo
Hirotaka Ieki
Koichiro Higasa
Yoshihiro Onouchi
Kokichi Arisawa
Koichi Matsuda
Keitaro Tanaka
Fumihiko Matsuda
Yoichiro Kamatani
Shinichiro Suna
Norie Sawada
Yoshinori Murakami
Issei Komuro
Hiroshi Matsunaga
Changhoon Kim
Kiyonori Kuriki
Motoki Iwasaki
Kouichi Ozaki
Hiroyuki Aburatani
Masatsugu Hori
Source :
Nature Genetics. 52:1169-1177
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

To elucidate the genetics of coronary artery disease (CAD) in the Japanese population, we conducted a large-scale genome-wide association study of 168,228 individuals of Japanese ancestry (25,892 cases and 142,336 controls) with genotype imputation using a newly developed reference panel of Japanese haplotypes including 1,781 CAD cases and 2,636 controls. We detected eight new susceptibility loci and Japanese-specific rare variants contributing to disease severity and increased cardiovascular mortality. We then conducted a trans-ancestry meta-analysis and discovered 35 additional new loci. Using the meta-analysis results, we derived a polygenic risk score (PRS) for CAD, which outperformed those derived from either Japanese or European genome-wide association studies. The PRS prioritized risk factors among various clinical parameters and segregated individuals with increased risk of long-term cardiovascular mortality. Our data improve the clinical characterization of CAD genetics and suggest the utility of trans-ancestry meta-analysis for PRS derivation in non-European populations.

Details

ISSN :
15461718 and 10614036
Volume :
52
Database :
OpenAIRE
Journal :
Nature Genetics
Accession number :
edsair.doi.dedup.....b98685f926d75addcdfe334a4d99c4d6
Full Text :
https://doi.org/10.1038/s41588-020-0705-3