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Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis

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 E...

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Detalles Bibliográficos
Autores principales: Liang, Guibin, Li, Jiuang, Pu, Shiqian, He, Zhihui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9529510/
https://www.ncbi.nlm.nih.gov/pubmed/36199375
http://dx.doi.org/10.1155/2022/6788569
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author Liang, Guibin
Li, Jiuang
Pu, Shiqian
He, Zhihui
author_facet Liang, Guibin
Li, Jiuang
Pu, Shiqian
He, Zhihui
author_sort Liang, Guibin
collection PubMed
description 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.
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spelling pubmed-95295102022-10-04 Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis Liang, Guibin Li, Jiuang Pu, Shiqian He, Zhihui J Healthc Eng Research Article 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. Hindawi 2022-09-26 /pmc/articles/PMC9529510/ /pubmed/36199375 http://dx.doi.org/10.1155/2022/6788569 Text en Copyright © 2022 Guibin Liang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liang, Guibin
Li, Jiuang
Pu, Shiqian
He, Zhihui
Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis
title Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis
title_full Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis
title_fullStr Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis
title_full_unstemmed Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis
title_short Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis
title_sort screening of sepsis biomarkers based on bioinformatics data analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9529510/
https://www.ncbi.nlm.nih.gov/pubmed/36199375
http://dx.doi.org/10.1155/2022/6788569
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