Identification and experimental validation of CD74, PGLYRP1, and TXN as potential biomarkers in rheumatoid arthritis: an integrative bulk and ScRNA-seq study.

Chronic joint inflammation, the hallmark of rheumatoid arthritis (RA), is an autoimmune condition that commonly leads to progressive joint damage and dysfunction. While several clinical biomarkers are available for diagnosing and predicting RA, their specificity and sensitivity are still insufficient. Therefore, the objective was to discover biomarkers associated with RA and delineate their functional mechanisms.

methodsPublicly available RA transcriptomic datasets were utilized in this study. A combination of machine learning algorithms and expression validation led to the identification of relevant biomarkers. To elucidate their functional roles in RA, we performed enrichment analysis, immune microenvironment profiling, computational screening of compound-protein binding affinities, molecular docking, and molecular dynamics simulations (MDs). In parallel, single-cell RNA sequencing (scRNA-seq) was employed to pinpoint critical cell subsets and track changes in biomarker expression. Finally, biomarker levels were validated in clinical samples using reverse transcription quantitative PCR (RT-qPCR), western blotting (WB), and immunohistochemical (IHC) staining.

resultsCD74, PGLYRP1, and TXN were identified as potential biomarkers. Their enrichment in pathways associated with immune response, inflammation, and redox processes highlights their possible roles in RA. Additionally, CD56dim natural killer cells displayed a marked positive association with CD74 (cor = 0.66, P < 0.001) and the strongest negative association with TXN (cor = -0.75, P < 0.001). Bergamottin and diphenylcyclopropenone exhibited high binding affinities for CD74 and TXN, respectively. MDs simulations confirmed the stability of these complexes. In a pilot analysis, scRNA-seq indicated myeloid cells as the potential key cell population. During myeloid cell differentiation, CD74 and TXN expression levels initially increased and then declined. RT-qPCR, WB, and IHC analyses consistently demonstrated that CD74 expression was significantly downregulated, whereas PGLYRP1 and TXN were markedly upregulated in RA clinical samples compared with controls, confirming the reliability of the bioinformatics predictions and supporting their potential roles as RA biomarkers.

conclusionBy integrating bulk RNA sequencing with scRNA-seq, CD74, PGLYRP1, and TXN were identified as biomarkers, with myeloid cells suggested as a potential key cell type, providing new insights into RA diagnosis and meriting further investigation of their functional roles.