Molecular mechanisms of osteoarthritis using gene microarrays

Abstract

This study aimed to investigate the molecular mechanisms of osteoarthritis (OA) by microarray analysis. Three gene expression datasets GSE1919, 19664 and 55235 were downloaded from the Gene Expression Omnibus, and data of OA samples and healthy controls were used. After data preprocessing, differential expression analysis between the OA group and controls was performed using LIMMA (Linear Models for Microarray Data) package and genes with |log2FC (fold change)|>1 and P<0.05 were screened as DEGs (differentially expressed genes). The screened DEGs were then subject to functional annotation and pathway enrichment analysis using DAVID (Database for Annotation Visualization and Integrated Discovery). Next, gene-set enrichment analysis was performed using Enrichment map Cytoscape plug-in, followed by detecting sub-networks using clusterONE. Finally, risk subpathways were screened using iSubpathwayMiner package. A total of 141 DEGs were screened, including 52 up-regulated ones and 89 down-regulated ones. These DEGs were enriched in 48 GO terms that were mainly related to locomotory behavior, taxis, adhesion, and 11 pathways that were related to cytokine-cytokine receptor interaction, ECM-receptor interaction, focal adhesion, as well as several signaling pathways. The enrichment map enriched gene-sets mainly related to cell death and apoptosis, and extracellular components. The risk pathways up-regulated DEGs were exclusively related to arachidonic acid metabolism and glycosphingolipid biosynthesis, and the top two risk pathways were tyrosine metabolism for the down-regulated ones. From this study we conclude that genes involved in cell death and apoptosis, as well as cell–extracellular matrix interaction, may be essential for OA pathogenesis by altering multiple signaling pathways.