Identification of differentially expressed genes in synovial tissue of osteoarthritis based on a more robust integrative analysis method.

OBJECTIVE

This study aimed to identify osteoarthritis (OA) related genes based on microarray data in synovium with a more robust integrative analysis method.

METHODS

Four series GSE55457, GSE12021, GSE55235, and GSE55584 (36 OA and 29 normal samples) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) of GSE55457, GSE12021, and GSE55235 were identified using the LIMMA package. Overlapping DEGs from the intersection of the three series were detected. Simultaneously, samples in the four series were pooled to identify DEGs with integrated analysis using the Sva package.

RESULTS

In total, 74 overlapping DEGs and 242 DEGs by integrating four series were detected. Based on them, 70 common DEGs were used to construct a protein-protein interaction (PPI) network, involving 61 nodes and 206 edges. Also, three gene modules and five hub genes, named JUN, IL6, VEGFA, MYC, and EGR1, were identified.

CONCLUSIONS

Seventy DEGs were finally identified with a more robust integrative analysis method. JUN, IL6, VEGFA, MYC, and EGR1 were identified as hub genes in the development of OA. Key Points • 76 overlapping DEGs were detected from the intersection of DEGs in GSE55457, GSE12021, and GSE55235. • 242 DEGs were identified by integrating four series using Sva package. • 72 common DEGs were finally identified based on the overlapping DEGs and the integrated DEGs. • JUN, IL6, VEGFA, MYC, and EGR1 were identified as hub genes in the development of OA.