ArticleBMC infectious diseases2024
Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis.
Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Integrated bioinformatics analysis identifies hub genes and immune regulatory networks in HIV infection.Frontiers in immunology · 2025Article
- Crossing Age Boundaries: The Unifying Potential of Presepsin in Sepsis Diagnosis Across Diverse Age Groups.Journal of clinical medicine · 2024Review
- Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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