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Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis

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Publicado en:BMC Infectious Diseases vol. 24 (2024), p. 1
Autor principal: Liang, Pingping
Otros Autores: Wu, Yongjian, Qu, Siying, Younis, Muhammad, Wang, Wei, Wu, Zhilong, Huang, Xi
Publicado:
Springer Nature B.V.
Materias:
World Health Organization
Infections
Helper cells
Vaccines
Datasets
Genes
Disease
Mortality
Sepsis
Lymphocytes T
Bioinformatics
Immunology
Enrichment
Drugs
Cell differentiation
Differentiation (biology)
Flow cytometry
Confidence intervals
Drug development
Cell activation
Inflammation
Lymphocytes
Proteins
Medical prognosis
Inflammatory response
Gene expression
Itk protein
Prevention
Biomarkers
Medical research
Hospitals
Immunosuppressive agents
Drug delivery
Viral infections
Regulatory mechanisms (biology)
Pathophysiology
Social
Acceso en línea:Citation/Abstract
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Resumen:BackgroundSepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear.ResultsIn this study, bioinformatics analysis revealed the novel key biomarkers associated with sepsis and potential regulators. Three public datasets (GSE28750, GSE57065 and GSE95233) were employed to recognize the differentially expressed genes (DEGs). Taking the intersection of DEGs from these three datasets, GO and KEGG pathway enrichment analysis revealed 537 shared DEGs and their biological functions and pathways. These genes were mainly enriched in T cell activation, differentiation, lymphocyte differentiation, mononuclear cell differentiation, and regulation of T cell activation based on GO analysis. Further, pathway enrichment analysis revealed that these DEGs were significantly enriched in Th1, Th2 and Th17 cell differentiation. Additionally, five hub immune-related genes (CD3E, HLA-DRA, IL2RB, ITK and LAT) were identified from the protein–protein interaction network, and sepsis patients with higher expression of hub genes had a better prognosis. Besides, 14 drugs targeting these five hub related genes were revealed on the basis of the DrugBank database, which proved advantageous for treating immune-related diseases.ConclusionsThese results strengthen the new understanding of sepsis development and provide a fresh perspective into discriminating the candidate biomarkers for predicting sepsis as well as identifying new drugs for treating sepsis.
ISSN:1471-2334
DOI:10.1186/s12879-023-08883-9
Fuente:Health & Medical Collection