TY - JOUR
T1 - Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis
AU - BioBank Japan Project
AU - Ishigaki, Kazuyoshi
AU - Sakaue, Saori
AU - Terao, Chikashi
AU - Luo, Yang
AU - Sonehara, Kyuto
AU - Yamaguchi, Kensuke
AU - Amariuta, Tiffany
AU - Too, Chun Lai
AU - Laufer, Vincent A
AU - Scott, Ian C
AU - Viatte, Sebastien
AU - Takahashi, Meiko
AU - Ohmura, Koichiro
AU - Murasawa, Akira
AU - Hashimoto, Motomu
AU - Ito, Hiromu
AU - Hammoudeh, Mohammed
AU - Emadi, Samar Al
AU - Masri, Basel K
AU - Halabi, Hussein
AU - Badsha, Humeira
AU - Uthman, Imad W
AU - Wu, Xin
AU - Lin, Li
AU - Li, Ting
AU - Plant, Darren
AU - Barton, Anne
AU - Orozco, Gisela
AU - Verstappen, Suzanne M M
AU - Bowes, John
AU - MacGregor, Alexander J
AU - Honda, Suguru
AU - Koido, Masaru
AU - Tomizuka, Kohei
AU - Kamatani, Yoichiro
AU - Tanaka, Hiroaki
AU - Tanaka, Eiichi
AU - Suzuki, Akari
AU - Maeda, Yuichi
AU - Yamamoto, Kenichi
AU - Miyawaki, Satoru
AU - Xie, Gang
AU - Zhang, Jinyi
AU - Amos, Christopher I
AU - Keystone, Edward
AU - Wolbink, Gertjan
AU - van der Horst-Bruinsma, Irene
AU - Cui, Jing
AU - Eyre, Stephen
AU - Raychaudhuri, Soumya
N1 - © 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2022/11/4
Y1 - 2022/11/4
N2 - Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
AB - Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
U2 - 10.1038/s41588-022-01213-w
DO - 10.1038/s41588-022-01213-w
M3 - Article
C2 - 36333501
SN - 1061-4036
JO - Nature Genetics
JF - Nature Genetics
ER -