ArticleMolecular medicine reports2018
Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database.
Article in Molecular medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Pooled it
- A four-gene signature from blood to exclude bacterial etiology of lower respiratory tract infection in adults.Nature communications · 2025Article
- Construction of Diagnostic Model for Regulatory T Cell-Related Genes in Sepsis Based on Machine Learning.Biomedicines · 2025Article
- A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia.iScience · 2025Article
- FUNCTIONAL IMMUNOPHENOTYPING FOR PRECISION THERAPIES IN SEPSIS.Shock (Augusta, Ga.) · 2025Review
- PathIN: an integrated tool for the visualization of pathway interaction networks.Computational and structural biotechnology journal · 2023Article
- Mapping the splicing landscape of the human immune system.Frontiers in immunology · 2023Article
- The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination.Frontiers in immunology · 2023Article
- Alterations in leukocyte DNA methylome are associated to immunosuppression in severe clinical phenotypes of septic patients.Frontiers in immunology · 2023Article
- Article
- Effects ofViruses · 2022Article
- The Interplay of Oxidative Stress and ROS Scavenging: Antioxidants as a Therapeutic Potential in Sepsis.Vaccines · 2022Review
- Article
- Differential Gene Sets Profiling in Gram-Negative and Gram-Positive Sepsis.Frontiers in cellular and infection microbiology · 2022Article
- MiR-539-5p inhibits the inflammatory injury in septic H9c2 cells by regulating IRAK3.Molecular biology reports · 2022Article
- Long noncoding RNA GSEC promotes neutrophil inflammatory activation by supporting PFKFB3-involved glycolytic metabolism in sepsis.Cell death & disease · 2021Article
- DNA Methylation Analysis to Unravel Altered Genetic Pathways Underlying Early Onset and Late Onset Neonatal Sepsis. A Pilot Study.Frontiers in immunology · 2021Article
- Development of Exhausted Memory Monocytes and Underlying Mechanisms.Frontiers in immunology · 2021Article
- Screening and identification of key gene in sepsis development: Evidence from bioinformatics analysis.Medicine · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis is a life-threatening condition in which an uncontrolled inflammatory host response is triggered. The exact pathogenesis of sepsis remains unclear. The aim of the present study was to identify key genes that may aid in the diagnosis and treatment of sepsis. mRNA expression data from blood samples taken from patients with sepsis and healthy individuals was downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) between the two groups were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein‑protein interaction (PPI) network construction, was performed to investigate the function of the identified DEGs. Furthermore, for validation of these results, the expression levels of several DEGs were analyzed by reverse transcription quantitative‑polymerase chain reaction (RT‑qPCR) in three patients with sepsis and three healthy blood samples to support the results obtained from the bioinformatics analysis. Receiver operating characteristic analyses were also used to analyze the diagnostic ability of the identified DEGs for sepsis. The results demonstrated that a total of 4,402 DEGs, including 1,960 upregulated and 2,442 downregulated genes, were identified between patients with sepsis and healthy individuals. KEGG pathway analysis revealed that 39 DEGs were significantly enriched in toll‑like receptor signaling pathways. The top 20 upregulated and downregulated DEGs were used to construct the PPI network. Hub genes with high degrees, including interleukin 1 receptor‑associated kinase 3 (IRAK3), S100 calcium‑binding protein (S100)A8, angiotensin II receptor‑associated protein (AGTRAP) and S100A9, were demonstrated to be associated sepsis. Furthermore, RT‑qPCR results demonstrated that IRAK3, adrenomedullin (ADM), arachidonate 5‑lipoxygenase (ALOX5), matrix metallopeptidase 9 (MMP9) and S100A8 were significantly upregulated, while ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1) was upregulated but not significantly, in blood samples from patients with sepsis compared with healthy individuals, which was consistent with bioinformatics analysis results. Therefore, AGTRAP, IRAK3, ADM, ALOX5, MMP9, S100A8 and ENTPD1 were identified to have potential diagnostic value in sepsis. In conclusion, dysregulated levels of the AGTRAP, IRAK3, ADM, ALOX5, MMP9, S100A8 and ENTPD1 genes may be involved in sepsis pathophysiology and may be utilized as potential diagnostic biomarkers or therapeutic targets.
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