Back

Trans-ancestry genome-wide association study identifies novel genetic mechanisms in rheumatoid arthritis

Ishigaki, K.; Sakaue, S.; Terao, C.; Luo, Y.; Sonehara, K.; Yamaguchi, K.; Amariuta, T.; Too, C. L.; Laufer, V. A.; Scott, I. C.; Viatte, S.; Takahashi, M.; Ohmura, K.; Murasawa, A.; Hashimoto, M.; Ito, H.; Hammoudeh, M.; Al Emadi, S.; Masri, B. K.; Halabi, H.; Badsha, H.; Uthman, I. W.; Wu, X.; Lin, L.; Lin, T.; Plant, D.; Barton, A.; Orozco, G.; Verstappen, S. M.; Bowes, J.; MacGregor, A. J.; Honda, S.; Koido, M.; Tomizuka, K.; Kamatani, Y.; Tanaka, H.; Tanaka, E.; Suzuki, A.; Maeda, Y.; Yamamoto, K.; Miyawaki, S.; Xie, G.; Zhang, J.; Amos, C.; Keystone, E.; Wolbink, G.; van der Horst-Bruins

2021-12-05 genetic and genomic medicine
10.1101/2021.12.01.21267132 medRxiv
Show abstract

Trans-ancestry genetic research promises to improve power to detect genetic signals, fine-mapping resolution, and performances of polygenic risk score (PRS). We here present a large-scale genome-wide association study (GWAS) of rheumatoid arthritis (RA) which includes 276,020 samples of five ancestral groups. We conducted a trans-ancestry meta-analysis and identified 124 loci (P < 5 x 10-8), of which 34 were novel. Candidate genes at the novel loci suggested essential roles of the immune system (e.g., TNIP2 and TNFRSF11A) and joint tissues (e.g., WISP1) in RA etiology. Trans-ancestry fine mapping identified putatively causal variants with biological insights (e.g., LEF1). Moreover, PRS based on trans-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between European and East Asian populations. Our study provides multiple insights into the etiology of RA and improves genetic predictability of RA.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.