Rheumatoid arthritis (RA) is a prevalent autoimmune disorder that significantly reduces quality of life and imposes a substantial burden on society. This study addresses the critical gaps in current diagnostic and therapeutic modalities by aiming to identify improved biomarkers and potential therapeutic targets. Using data from 2 gene expression omnibus databases, we executed a comprehensive differential gene expression analysis integrated with Mendelian randomization. This approach employed advanced bioinformatics tools to scrutinize expression quantitative trait loci (eQTLs) and RA genome-wide association study data to pinpoint crucial genes involved in RA. The selection of these pivotal genes was strategically based on the intersection of upregulated gene expressions with eQTLs exhibiting odds ratios >1, and conversely, downregulated gene expressions aligned with eQTLs displaying odds ratios <1. Our enrichment analyses, including gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis, provided robust validation of these genes’ roles, further supported by external validation from an additional gene expression omnibus dataset. The study identified 13 critical genes related to RA susceptibility, including CKAP2, GABBR1, HLA-DPA1, ST6GAL1, FCGR1A, ADCY7, MAP4K1, CD37, ERAP2, and SEMA3C, alongside protective genes. An in-depth analysis of immune cell infiltration underscored the dominant roles of M2 macrophages and CD8+ T cells in the RA immune microenvironment, highlighting their significant contributions to disease pathogenesis. By identifying novel biomarkers and elucidating the dynamic immune landscape of RA, our findings lay the groundwork for innovative therapeutic strategies. This study significantly advances our understanding of the complex genetic mechanisms underlying RA, offering insights that pave the way for targeted therapeutic interventions and further research into the molecular drivers of RA.
Shao et al. (Fri,) studied this question.