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

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 , , , , , , , , , , , and , which all could be used as biomarkers to differentiate KOA samples from healthy controls. More importantly, we found that , , , and were significantly upregulated and compared with the controls ( < .01).

CONCLUSIONS

The expression levels of , , , and were elevated and had good prognostic values as biomarkers in KOA.