Novel loci and multi-omics risk models for rheumatoid arthritis through a million-participant genome-wide association meta-analysis

Researchers conducted a large-scale genome-wide association study involving approximately one million participants of European ancestry to better understand rheumatoid arthritis (RA). They identified eight novel genomic risk loci for general RA and six for seropositive RA. New polygenic risk scores were developed that better predict disease than traditional clinical risk factors. Integration of metabolomic data into models further improved risk stratification, particularly for seropositive RA, where the hazard ratio in the highest-risk group increased from 4.869 to 5.697. The research revealed relevant biological pathways including immune processes and estrogen metabolism. These findings expand understanding of genetic factors in RA and support the inclusion of polygenic risk scores in risk assessment.