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.