Integrative analysis of lncRNAs in rheumatoid arthritis: from bioinformatics to experimental validation.

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive joint damage and systemic inflammation. Despite advances in treatment, challenges persist in early diagnosis and personalized therapy. Long non-coding RNAs (lncRNAs) have emerged as pivotal regulators in immune pathways and inflammation, offering potential as diagnostic biomarkers and therapeutic targets. Using GEO datasets (GSE169082, GSE124373), we identified differentially expressed genes in peripheral blood mononuclear cells of RA patients. Functional enrichment and pathway analyses were conducted to elucidate their roles. Key lncRNAs (LINC00963, SNHG15, SNHG3) were experimentally validated via real-time PCR in patient samples. Protein-protein interaction networks and ceRNA networks were constructed to explore molecular interactions. Analysis revealed significant up-regulation of LINC00963, SNHG15, and SNHG3 in RA patients, correlating with inflammatory markers and immune cell profiles. ROC analysis demonstrated high diagnostic potential, particularly for SNHG3 (AUC: 84.3%). Pathway enrichment highlighted immune activation and disrupted autophagic processes. This study identifies novel lncRNAs with diagnostic and therapeutic potential in RA, emphasizing the integration of computational and experimental approaches. These findings lay the groundwork for precision medicine strategies to improve RA management.