Multi-omics analysis of the potential association between ageing and rheumatoid arthritis and screening of potential therapeutic targets.

Ageing is increasingly recognized as a significant risk factor for RA, yet the molecular mechanisms linking the two remain poorly understood. This study aimed to explore the association between ageing and RA and to identify potential therapeutic targets using multi-omics approaches. By analysing the GBD database, we observed a notable increase in RA incidence and prevalence among individuals aged 55 and older from 1990 to 2021. Through integrative analysis of transcriptomic data and ageing-related gene sets, we identified 145 shared genes between ageing and RA. Machine learning algorithms further refined these to five hub genes, among which STAT1, MCL1, and BCL6 were validated via single-cell RNA sequencing as key players in RA pathogenesis. Immune infiltration analysis revealed distinct immune cell profiles in RA patients compared to controls. These findings underscore the strong molecular link between ageing and RA and highlight STAT1, MCL1, and BCL6 as promising therapeutic targets. This study provides a foundation for developing targeted interventions for RA in the context of ageing.