To screen key pathogenic genes in septic cardiomyopathy (SCM) by bioinformatics analysis.

The GSE79962 dataset was downloaded from the gene expression omnibus (GEO). The dataset contained genome-wide expression levels of heart gene profiles from patients who had died of sepsis and from healthy donors. The differentially expressed genes (DEGs) were screened and analyzed using an online GEO2R analysis tool, and the functional enrichment analysis of DEGs was carried out using the DAVID 6.8 database. The protein-protein interaction (PPI) network analysis was performed using the STRING database, and the CytoHubba software was used to screen the top 10 key genes.

A total of 228 DEGs were identified from the GSE79962 dataset, including 156 up-regulated genes and 72 down-regulated genes. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of 228 DEGs showed that DEGs mainly involved three GO functional annotations (including two cellular component pathways and a biological process pathway) and three KEGG pathways (including a metabolic pathway, an olfactory transduction, and a neuroendocrine gland). The PPI network screened out 10 key genes, five of which were up-regulated, including nucleolar complex protein 3 homolog (NOC3L), SDA1 domain containing 1 (SDAD1), patched 1 (PTCH1), clathrin heavy chain (CLTC), and inhibitor of nuclear factor kappa B kinase subunit beta (IKBKB), and five of which were down-regulated, including WD repeat domains (WDR4, WDR36, and WDR82), transmembrane and coiled-coil domains 1 (TMCO1), and Toll like receptor 9 (TLR9).

NOC3L, SDAD1, PTCH1, CLTC, IKBKB, WDR4, WDR36, WDR82, TMCO1, and TLR9 are key pathogenic genes of SCM, and in-depth study of these genes, especially family of WDR genes, can be conducted to further clarify the occurrence and development mechanism of SCM.