Comprehensive analysis of DNA methylation for periodontitis

Abstract

Abstract Background Periodontitis is an infectious disease, and a risk factor for peri-implantitis that could result in the implant loss. DNA methylation has an essential role in the etiology and pathogenesis of inflammatory disease. However, there is lack of study on methylation status of genes in periodontitis. This study sought to explore the gene methylation profiling microarray in periodontitis. Methods Through searching in the Gene Expression Omnibus database, a gene methylation profiling data set GSE173081 was identified, which included 12 periodontitis samples and 12 normal samples, respectively. Thereafter, the data of GSE173081 was downloaded and analyzed to determined differentially methylated genes (DMGs), which then were used to perform Gene Ontology analysis and pathway enrichment analyses through online database. In addition, the DMGs were applied to construct the protein–protein interaction (PPI) network information, predict the hub genes in pathology of periodontitis. Results In total 668 DMGs were sorted and identified from the data set, which included 621 hypo-methylated genes and 47 hyper-methylated genes. Through the function and ontology analysis, these 668 genes are mainly classified into intracellular signaling pathway, cell components, cell–cell interaction, and cellular behaviors. The pathway analysis showed that the hypo-methylated genes were mostly enriched in the pathway of cGMP–PKG signaling pathway; RAF/MAP kinase; PI3K–Akt signaling pathway, while hyper-methylated genes were mostly enriched in the pathway of bacterial invasion of epithelial cells; sphingolipid signaling pathway and DCC mediated attractive signaling. The PPI network contained 630 nodes and 1790 interactions. Moreover, further analysis identified top 10 hub genes (APP; PAX6; LPAR1; WNT3A; BMP2; PI3KR2; GATA4; PLCB1; GATA6; CXCL12) as central nodes that are involved in the immune system and the inflammatory response. Conclusions This study provides comprehensive information of methylation status of genes to the revelation of periodontitis pathogenesis that may contribute to future research on periodontitis.

Keywords

• DNA methylation
• Periodontitis
• Gene expression
• Bioinformatitics