Diagnostic biomarkers in knee osteoarthritis: Based on bioinformatics and experimental verification in vivo and in vitro

Abstract

Background: Knee osteoarthritis (KOA) is a multifactorial whole-joint disease with a high rate of disability. Considering the complexity of KOA, there is an urgent need to discover new molecular pathological markers and multi-target treatment strategies. Methods: Two datasets, GSE51588 and GSE57218, were downloaded from the Gene Expression Omnibus database and screened for differentially expressed genes (DEGs) using the Gene Expression Omnibus 2R (GEO2R). Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed. A protein-protein interaction (PPI) network was constructed and hub genes were identified using Molecular Complex Detection (MCODE). Receiver-operating characteristic curves (ROC) were plotted for the genes, and their prognostic values were evaluated. The expression levels of the hub genes in the monosodium iodoacetate (MIA)-induced KOA rat model and lipopolysaccharide (LPS)-stimulated C28/I2 cells were verified using reverse transcription quantitative real-time PCR (RT-qPCR). Results: Overall, 33 DEGs were up-regulated and 6 DEGs were down-regulated in the two datasets. A total of 12 hub genes were identified, including COL15A1, THY1, COL1A1, COL5A1, CTHRC1, MXRA5, FN1, COL1A2, COL3A1, SPARC, COL8A1, and COL2A1, which all could be used as biomarkers to differentiate KOA samples from healthy controls. More importantly, we found that THY1, CTHRC1, SPARC, and COL8A1 were significantly upregulated in vivo and in vitro compared with the controls (p