Abstract
Background: Osteoarthritis (OA) is a common joint disorder with a complex and multifactorial pathogenesis. Proteomics analysis using two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) enables high-throughput identification of differentially expressed proteins related to OA. However, the etiology, pathophysiology, and early diagnostic markers of OA are still poorly understood. Methods: Synovial fluid protein biomarkers were compared between OA patients and healthy controls. It was fractionated using DEAE cellulose and Sephadex G-200 columns, followed by SDS‒PAGE and 2D-PAGE for visualization and identification. Mass spectrometry and Mascot were used for protein analysis, and serum metabolite profiles were also investigated using 1D 1H CPMG NMR spectra. Multivariate data analysis, including PCA and PLS-DA, was performed to detect metabolic differences between groups. Results: Proteomics analysis revealed differential expression of synovial fluid proteins, such as serine protease inhibitors, complement components, and apolipoproteins, which may be involved in inflammation and cartilage breakdown. Additionally, serum metabolite profiles differed significantly between OA patients and controls, involving amino acid, lipid, glucose, and energy metabolism. The pathway analysis indicated disruption of the metabolic pathways associated with these metabolites. Conclusions: This study provides insights into the molecular and metabolic changes in OA. Protein biomarkers and serum metabolite alterations enhance the understanding of OA pathogenesis and offer potential opportunities for early diagnosis and disease management. Further validation and translation of these findings into clinical applications are needed for improved OA detection and intervention strategies.