Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis

Multi-ancestry genome-wide association analyses identify 124 risk loci for rheumatoid arthritis, of which 34 are novel. A polygenic risk score based on multi-ancestry data showed comparable performance between populations of European and East Asian ancestries. 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 x 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.

Automated summary

This study conducted multi-ancestry genome-wide association analyses and identified 124 risk loci for rheumatoid arthritis, of which 34 are novel. The fine-mapping analysis revealed potential causal variants and improved the genetic predictability of rheumatoid arthritis.