This study aims to integrate disease-associated variants with diverse genomic and biological datasets to provide insights into the biology of rheumatoid arthritis (RA) and guide drug discovery. The authors conducted a genome-wide association study (GWAS) meta-analysis involving over 100,000 subjects of European and Asian ancestry, identifying 42 novel RA risk loci, bringing the total to 101. They developed an in-silico pipeline to identify 98 biological candidate genes at these risk loci, which are targets of approved therapies for RA and may be repurposed for treatment. The study highlights the role of genetics in drug discovery, demonstrating that human genetic data can be integrated with other biological information to derive insights and support drug development. The findings provide a comprehensive understanding of RA pathogenesis and offer potential therapeutic targets.This study aims to integrate disease-associated variants with diverse genomic and biological datasets to provide insights into the biology of rheumatoid arthritis (RA) and guide drug discovery. The authors conducted a genome-wide association study (GWAS) meta-analysis involving over 100,000 subjects of European and Asian ancestry, identifying 42 novel RA risk loci, bringing the total to 101. They developed an in-silico pipeline to identify 98 biological candidate genes at these risk loci, which are targets of approved therapies for RA and may be repurposed for treatment. The study highlights the role of genetics in drug discovery, demonstrating that human genetic data can be integrated with other biological information to derive insights and support drug development. The findings provide a comprehensive understanding of RA pathogenesis and offer potential therapeutic targets.