Long non-coding RNA TGFB2-OT1 as a diagnostic biomarker and ceRNA regulator in rheumatoid arthritis

长链非编码RNA TGFB2-OT1作为类风湿性关节炎的诊断生物标志物和ceRNA调节因子

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Abstract

OBJECTIVE: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. Growing evidence highlights the critical role of lncRNAs in RA initiation and progression. However, the pathogenic contributions of many lncRNAs remain unclear. METHODS: Whole-transcriptome sequencing of PBMCs from 5 RA patients and 5 healthy controls identified differentially expressed lncRNAs. Candidate lncRNAs, selected by fold-change and expression level, were validated via qRT-PCR in an expanded cohort (56 RA, 18 SLE, 20 pSS, and 39 HCs). Diagnostic performance was assessed by ROC analysis, and bioinformatic predictions explored potential miRNA-mRNA-protein interactions and functional mechanisms of lncRNAs. RESULTS: A study identified 2,162 differentially expressed lncRNAs, with 1,212 upregulated and 950 downregulated. Six lncRNAs with notable expression changes were chosen for qRT-PCR validation. TGFB2-OT1(NR_125715.1) and ENST00000413791 were significantly altered in RA PBMCs, with NR_125715.1 showing high diagnostic accuracy (AUC = 0.8610) and RA-specific expression. NR_125715.1 expression correlated positively with rheumatoid factor (r = 0.297, p = 0.036) and anti-cyclic citrullinated peptide antibodies (r = 0.3809, p = 0.0041). Bioinformatics suggested NR_125715.1 might act as a ceRNA regulating E2F2 via miR-6756-3p and interact with the FUS protein, affecting RNA metabolism and inflammatory signaling. No m6A methylation or CpG islands were found. CONCLUSION: NR_125715.1 shows RA-associated dysregulation in PBMCs and demonstrates diagnostic discrimination in our cohort. Bioinformatic analyses suggest that NR_125715.1 may participate in RA-related regulatory programs, potentially involving a ceRNA axis (miR-6756-3p/E2F2) and a predicted interaction with the RNA-binding protein FUS. These mechanistic inferences are hypothesis-generating and require functional validation in future studies.

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