Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis

Guibin Liang; Jiuang Li; Shiqian Pu; Zhihui He

doi:10.1155/2022/6788569

Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis

J Healthc Eng. 2022 Sep 26:2022:6788569. doi: 10.1155/2022/6788569. eCollection 2022.

Authors

Guibin Liang¹, Jiuang Li¹, Shiqian Pu¹, Zhihui He¹

Affiliation

¹ Department of Critical Care Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.

Abstract

Methods: Gene expression profiles of GSE13904, GSE26378, GSE26440, GSE65682, and GSE69528 were obtained from the National Center for Biotechnology Information (NCBI). The differentially expressed genes (DEGs) were searched using limma software package. Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs and screen hub genes.

Results: A total of 108 DEGs were identified in the study, of which 67 were upregulated and 41 were downregulated. 15 superlative diagnostic biomarkers (CCL5, CCR7, CD2, CD27, CD274, CD3D, GNLY, GZMA, GZMH, GZMK, IL2RB, IL7R, ITK, KLRB1, and PRF1) for sepsis were identified by bioinformatics analysis.

Conclusion: 15 hub genes (CCL5, CCR7, CD2, CD27, CD274, CD3D, GNLY, GZMA, GZMH, GZMK, IL2RB, IL7R, ITK, KLRB1, and PRF1) have been elucidated in this study, and these biomarkers may be helpful in the diagnosis and therapy of patients with sepsis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers
Computational Biology*
Data Analysis
Gene Expression Profiling
Gene Regulatory Networks
Humans
Receptors, CCR7
Sepsis* / diagnosis
Sepsis* / genetics

Substances

Biomarkers
Receptors, CCR7