This study identifies diagnostic biomarkers of OA-related synovitis from synovial tissue expression and develops a validated diagnostic nomogram (differentially expressed genes = differentially expressed genes; single-sample gene set enrichment analysis ssGSEA). We analyzed GEO synovium datasets (training: GSE55235, GSE55457, GSE82107, OA = 30 vs controls = 27; validation: GSE89408, OA = 22 vs controls = 28; cartilage comparator: GSE129147, OA = 10 vs controls = 9) and applied weighted gene correlation network analysis to identify phenotype-linked modules, followed by 4 machine learning models (random forest RF, support vector machine SVM, xtreme gradient boosting (XGB), generalized linear model GLM) to rank genes, selection of hub genes from the top SVM features, construction and validation of a multigene nomogram predicting OA-related synovitis vs control, and integrative pathway and immune profiling (gene ontology/kyoto encyclopedia of genes and genomes, ssGSEA), competitive endogenous RNA network analysis, and hypothesis-generating protein–ligand docking. In the training synovium set (GSE55235 + GSE55457 + GSE82107; outcome = OA-related synovitis vs control), model area under the curves (AUCs; 95% confidence intervals) were RF 0.944 (0.882–1.000), SVM 1.000 (0.997–1.000), XGB 0.917 (0.842–0.992), and GLM 0.944 (0.882–1.000). In the external synovium validation dataset GSE89408 (outcome = OA-related synovitis vs control), AUCs (95% confidence intervals) were RF 0.729 (0.585–0.873), SVM 0.792 (0.662–0.922), XGB 0.717 (0.571–0.863), and GLM 0.771 (0.636–0.906), emphasizing external validation as the fairer test of model generalizability. The cartilage comparator GSE129147 (outcome = OA vs control in cartilage) yielded SVM AUC 0.833 (0.333–1.000), supporting tissue-specific yet cross-tissue consistency. Five hub genes – CTSH, ephrin-B2, YIPF2, ZNF671, SLC27A6 – were identified from 462 intersecting genes, selected from the SVM model because it showed the smallest residuals and best internal discrimination among the 4 tested algorithms. The 5-gene nomogram showed good calibration and decision-curve net benefit across 10% to 40% threshold probabilities, confirming its diagnostic utility. ssGSEA analysis revealed enriched immune-related pathways and higher infiltration of B cells, macrophages, mast cells, and T-cell subsets in OA synovium, closely associated with the expression of hub genes such as YIPF2 and ZNF671 linked to adaptive-immune and inflammatory signaling. Molecular docking indicated that dexamethasone and triamcinolone acetonide bind to the protein products of the hub genes (–7.1 to –8.5 kcal/mol). The 5-gene synovium-based SVM model provides a validated diagnostic nomogram for OA-related synovitis; docking findings are hypothesis-generating and not evidence of therapeutic efficacy.
Wang et al. (Fri,) studied this question.