Abstract
BACKGROUND: To investigate the associations of methylation, expression, and protein quantitative trait loci (mQTL, eQTL, and pQTL) with ankylosing spondylitis (AS) and find out genetically supported drug targets for AS. METHODS: The summary-data-based Mendelian randomization (SMR) and Bayesian co-localization analysis were used to assess the potential causality between AS and relevant genes. The GWAS data obtained from the International Genetics of Ankylosing Spondylitis Consortium (IGAS) were set as the discovery stage, and the FinnGen and UK Biobank databases were used to replicate the analysis as an external validation. We further integrated the multi-omics results to screen overlapped genes at different levels. The protein-protein interaction (PPI) network and enrichment analyses were used to explore the biological effect of SMR-identified genes on AS. Drug prediction and molecular docking were used to validate the medicinal value of candidate drug targets. RESULTS: Based on the results of multi-omics evidence screening, we identified potential associations of TNFRSF1A, B3GNT2, ERAP1, and FCGR2A with AS at different regulatory levels. At the protein level, AIF1, TNXB, APOM, and B3GNT2 were found to be negatively associated with AS risk, whereas higher levels of FCGR2A, FCGR2B, IL12B, TNFRSF1A, and ERAP1 were associated with an increased risk of AS. The bioinformatics analyses showed that the SMR-identified genes were mainly involved in immune response. Molecular docking results displayed stable binding between predicted candidate drugs and these aforementioned proteins. CONCLUSION: Our study found four AS-associated genes with multi-omics evidence and nine promising drug targets for AS, which may contribute to the understanding of the genetic mechanisms of AS and provide innovative perspectives into targeted therapy for AS.