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Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database

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 sam...

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Autores principales: Lu, Xinxing, Xue, Lu, Sun, Wenbin, Ye, Jilu, Zhu, Zhiyun, Mei, Haifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783525/
https://www.ncbi.nlm.nih.gov/pubmed/29257295
http://dx.doi.org/10.3892/mmr.2017.8258
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author Lu, Xinxing
Xue, Lu
Sun, Wenbin
Ye, Jilu
Zhu, Zhiyun
Mei, Haifeng
author_facet Lu, Xinxing
Xue, Lu
Sun, Wenbin
Ye, Jilu
Zhu, Zhiyun
Mei, Haifeng
author_sort Lu, Xinxing
collection PubMed
description 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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spelling pubmed-57835252018-02-12 Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database Lu, Xinxing Xue, Lu Sun, Wenbin Ye, Jilu Zhu, Zhiyun Mei, Haifeng Mol Med Rep Articles 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. D.A. Spandidos 2018-02 2017-12-12 /pmc/articles/PMC5783525/ /pubmed/29257295 http://dx.doi.org/10.3892/mmr.2017.8258 Text en Copyright: © Lu et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Lu, Xinxing
Xue, Lu
Sun, Wenbin
Ye, Jilu
Zhu, Zhiyun
Mei, Haifeng
Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
title Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
title_full Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
title_fullStr Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
title_full_unstemmed Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
title_short Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
title_sort identification of key pathogenic genes of sepsis based on the gene expression omnibus database
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783525/
https://www.ncbi.nlm.nih.gov/pubmed/29257295
http://dx.doi.org/10.3892/mmr.2017.8258
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