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

BackgroundChronic 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. Methods: Publicly 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.

Results: CD74, 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.