Identifing the gender-specific genes and pathways in osteoarthritis by bioinfromatics

Abstract

Purpose: Female population shows higher OA incidence rates and severity compare to male in large joint. Except the effects of hormone, the underlying mechanisms are still largely unknown. The purpose of this study was to identify the key genes and pathways in gender differences of OA, and to explore the potential mechanisms. Methods: Three different Series (GSE12021, GSE55475 and GSE55584) were obtained from the Gene Expression Omnibus (GEO) database. The raw data were integrated and divided into four groups (female OA, female normal, male OA and male normal group) before we screened the differently expressed genes (DEGs) using R programing language. The Venn diagrams were used to visualize the relationships of up and down regulated genes. The Gene Ontology functional and KEGG pathway enrichment of DEGs were analyzed using DAVID online analyses. We also created the protein-protein interaction networks of the DEGs. Final hub genes for both genders were identified respectively using nine different topological methods through CytoHubba. And some of the important final hub genes were validated by RT-qPCR. Results: A total of 90 DEGs in female and 375 DEGs in male were identified by R language, and 9 downregulated and 15 upregulated genes were discovered as co-regulated genes by Venn diagram in both genders. After a series of analysis we performed, 9 genes (JUN, CTNNB1, CCR2, PTPRC, FLT1 CTGF, CX3CR1, TGBR2 and KDR) were identified as final hub genes in female OA patients and 5 genes (JUN, ISG15, STAT1, MYC and IL6) were identified in male OA patients. Interestingly, within these final hub genes, JUN genes were identified in both genders. Besides, several pathways also showed promising potential in exploring the gender differences in OA. To test the accuracy of the results, the expression levels of 9 final hub genes including JUN, CTGR, CX3CR1, TGBR2, KDR, ISG15, STAT1, MYC and IL6 were validated based on the gender they identified from. Conclusions: These genes and pathways we identified could be the reason of different incidence rates between the genders and could also be further studied as possible diagnostic indicators of OA.