Association Between Monocyte Cell DNA Methylation and Risk of Sepsis: Insights from Bioinformatics

To compare the intersection of gene expression levels and DNA methylation in monocyte cells of septic patients and healthy individuals, and to elucidate the primary molecular mechanisms by which monocyte cell DNA methylation contributes to the pathogenesis of sepsis. Sepsis is an extremely severe systemic infectious disease, triggered by a dysregulated immune response to the source of infection, leading to systemic inflammatory response syndrome (SIRS) and ultimately resulting in multiple organ dysfunction syndrome (MODS). The mortality rate of sepsis is extremely high, especially among intensive care unit patients, with a mortality rate exceeding 30%, imposing significant psychological and economic burdens on patients’ families and society. This study aims to determine the correlation between DNA methylation and the occurrence of sepsis through bioinformatics, hoping to provide a reference for future clinical treatment. R programming was used to analyze the differential genes between monocyte cells of septic patients and healthy individuals from the GSE9960 dataset available on the GEO website. DNA methylation-related genes were downloaded from the Genecards website, and Venn diagrams were employed to obtain intersecting genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for intersecting genes. STRING 13.0 was used for online analysis of co-expressed genes, and Cytoscape 3.8.0 was employed to analyze key proteins. The crucial sites affected by DNA methylation leading to sepsis were determined, and the clinical significance of Hub proteins corresponding to genes was evaluated using ROC curve analysis. The role of Hub genes in related pathways was explored through KEGG analysis. A total of 105 differential genes were identified in the GSE9960 dataset, including 73 upregulated and 32 downregulated genes. In the Genecards dataset, 11,867 relevant genes associated with DNA methylation and with a Relevance score of not less than 1 were found. The Venn diagram analysis revealed 76 intersecting genes. Biological processes (BP) enriched in the intersecting genes included regulation of cyclin-dependent protein serine/threonine kinase activity, and so on. Cellular components (CC) enriched in the intersecting genes included specific granule, and so on. Molecular functions (MF) included protein kinase regulator activity, and so on. KEGG analysis revealed enrichment in the Cell cycle pathway. Among the STRING interactions, genes such as CDKN3 showed significant relationships. KEGG analysis determined that CDC20 was involved in the Cell cycle pathway in monocyte cells of septic patients, and ROC curve analysis indicated the clinical diagnostic significance of CDC20. Genomic analysis suggests that DNA methylation in monocyte cells may increase the risk of sepsis, which is associated with the activation of the CDC20 gene in monocyte cells.