Revealing Long Noncoding RNAs as Potential Biomarkers for Rheumatoid Arthritis Through High‐Throughput Sequencing and Differential PBMC Expression Analysis

Long non-coding RNAs (lncRNAs) are emerging as critical epigenetic regulators within the gene-environment interaction networks and have been implicated in the progression of rheumatoid arthritis (RA). In the present study, we employed high-throughput RNA sequencing to elucidate the differential expression profiles of lncRNAs in peripheral blood mononuclear cells (PBMCs) from a discovery cohort (3 RA patients vs. 3 healthy controls). Following comprehensive sequencing analysis, 8 lncRNAs were identified as potential biomarkers for RA. Through reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation, we confirmed that LINC01881 (p < 0.01) and MIR3142HG (p < 0.01) exhibited expression patterns consistent with our sequencing results. Both showed moderate diagnostic performance (AUC = 0.713 and 0.723, respectively), and their combination improved diagnostic efficacy (AUC = 0.786). LINC01881 expression was negatively correlated with CRP and ESR, while MIR3142HG correlated positively with platelet count. Bioinformatic analysis suggested that LINC01881 may influence the PI3K-Akt pathway through interactions with PTEN-targeting miRNAs, and MIR3142HG may be involved in hematopoietic and platelet-related processes. In summary, MIR3142HG and LINC01881 are potential diagnostic biomarkers for RA. LINC01881 may act as a compensatory regulator of inflammation via PI3K-Akt signaling, while MIR3142HG may influence platelet biology. Further functional studies are warranted to confirm these mechanisms and explore their clinical utility in multi-marker diagnostic panels.