Abstract
Objective The purpose of the present study is to screen the hub genes associated with sepsis, comprehensively understand the occurrence and progress mechanism of sepsis, and provide new targets for clinical diagnosis and treatment of sepsis. Methods The microarray data of GSE9692 and GSE95233 were downloaded from the Gene Expression Omnibus (GEO) database. The dataset GSE9692 contained 29 children with sepsis and 16 healthy children, while the dataset GSE95233 included 102 septic subjects and 22 healthy volunteers. Differentially expressed genes (DEGs) were screened by GEO2R online analysis. The DAVID database was applied to conduct functional enrichment analysis of the DEGs. The STRING database was adopted to acquire protein-protein interaction (PPI) networks. Results We identified 286 DEGs (217 upregulated DEGs and 69 downregulated DEGs) in the dataset GSE9692 and 357 DEGs (236 upregulated DEGs and 121 downregulated DEGs) in the dataset GSE95233. After the intersection of DEGs of the two datasets, a total of 98 co-DEGs were obtained. DEGs associated with sepsis were involved in inflammatory responses such as T cell activation, leukocyte cell-cell adhesion, leukocyte-mediated immunity, cytokine production, immune effector process, lymphocyte-mediated immunity, defense response to fungus, and lymphocyte-mediated immunity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that sepsis was connected to bacterial and viral infections. Through PPI network analysis, we screened the most important hub genes, including ITK, CD247, MMP9, CD3D, MMP8, KLRK1, and GZMK. Conclusions In conclusion, the present study revealed an unbalanced immune response at the transcriptome level of sepsis and identified genes for potential biomarkers of sepsis, such as ITK, CD247, MMP9, CD3D, MMP8, KLRK1, and GZMK.
Highlights
Sepsis can lead to multiple organ dysfunction syndrome (MODS) and circulatory failure in critical condition, which is a common acute and severe disease in clinic. e incidence rate and mortality rate of sepsis are very high. 30 million people worldwide are infected with sepsis every year, in which 8 million people are dead [2]
Gene Ontology (GO) annotation analysis of GSE9692 indicated the differential genes participated in inflammatory responses, including regulation of immune effector process, regulation of leukocyte-mediated immunity, regulation of lymphocyte-mediated immunity, positive regulation of cytokine production, immune response-regulating signaling pathway, regulation of leukocyte-mediated cytotoxicity, and immune response-regulating cell surface receptor signaling pathway (Figure 3(a))
GO analysis of GSE95233 suggested Differentially expressed genes (DEGs) involved in biological functions, such as T cell activation, leukocyte cell-cell adhesion, positive regulation of leukocyte activation, positive regulation of leukocyte cell-cell adhesion, and leukocyte-mediated immunity (Figure 3(b))
Summary
Sepsis is a systemic inflammatory reaction mainly caused by pathogen infection, which is often characterized by high fever, leukocytosis, and headache [1]. E incidence rate and mortality rate of sepsis are very high. The number of morbidity and mortality has been underestimated in countries with backward development and poor economy. In order to reduce the mortality of patients and improve the quality of life of patients with sepsis, relevant research has been widely carried out, but little progress has been made. Screening the genes that play a key role in disease among many different genes has become a key research goal. Bioinformatics analysis based on gene expression profile may screen hub genes and regulatory pathways, which plays an important role in early diagnosis of sepsis and establishment of early warning mechanism
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
