Objective: Sepsis presents great threat to human health. Here we aimed to understand its pathogenesis and discover effective therapeutic targets.
Materials and methods: Gene expression data for sepsis samples was compared with healthy controls to identify differentially expressed genes (DEGs), then we constructed PPI network to detect the network clustering. Gene Ontology (GO) analysis was also done to identify over-represented biological pathways.
Results: KEGG pathway analysis revealed that PI3K-AKT signaling pathway, chemokine signaling pathway and MAPK signaling pathway were significantly over-represented in these DEGs. Given proteins work together to exert certain biological functions, network analysis was done to identify genes closely associated with these DEGs. Using Fisher's exact test, 8 genes such as NEDD8, CUL1 and CUL3 were screened out.
Conclusions: Overall, our findings not only supplement the knowledge about sepsis, but also provide a number of potential biomarkers for diagnosis and treatment.