Abstract
We attempted to perform a comprehensive bioinformatics analysis on osteoarthritis (OA) based on the NKT-related genes and explore the clinically related critical genes. Differentially expressed genes (DEGs) and NKT-related genes from WGCNA were obtained using the dataset GSE114007, followed by intersection analysis to obtain NKT-related DEGs. Lasso regression, support vector machine, and random forest were performed to screen feature genes, followed by verification with receiver operator curves and a nomogram model. Protein-protein interaction network, gene set enrichment analysis was performed based on the four marker genes. Finally, the immune infiltration of 64 types of immune cells was analyzed between OA samples and normal samples. The significance of biomarkers was validated in clinical samples and OA mice models. A total of four NKT-related biomarker genes (CCNJ, CFI, PREX2, and SMIM13) were identified. These genes were all upregulated in OA samples. CFI exerted promising diagnostic value for OA with an AUC of 0.994 in GSE114007 training dataset and 0.98 in the validation dataset. A significantly negative correlation between CFI and NKT cells and a significantly positive correlation between CFI and conventional dendritic cells (cDC) were found. All the biomarkers were determined to be upregulated in OA patients by clinical samples. CFI knockdown significantly reduced DC infiltration and inflammation in the knee joints of OA mice models. CFI has potential value in the pathogenesis of OA and can be used as a candidate biomarker for OA diagnosis and treatment.