ArticleJournal of inflammation research2022
Identification of Immune-Related Key Genes as Potential Diagnostic Biomarkers of Sepsis in Children.
Article in Journal of inflammation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Cuproptosis of endothelial cells in a hypoxic environment: from molecular classification to PMAIP1-targeted intervention.Hereditas · 2026Article
- Combination of machine learning and protein‑protein interaction network established one ATM‑DPP4‑TXN ferroptotic diagnostic model with experimental validation.Molecular medicine reports · 2025Article
- Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.Inflammation · 2025Article
- Article
- Identification of key biomarkers and therapeutic targets in sepsis through coagulation-related gene expression and immune pathway analysis.Frontiers in immunology · 2024Article
- Development of a Prognosis Prediction Model for Pediatric Sepsis Based on the NLPR.Journal of inflammation research · 2024Article
- Identification of immune-related lncRNA in sepsis by construction of ceRNA network and integrating bioinformatic analysis.BMC genomics · 2023Article
- Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis.European journal of medical research · 2023Article
- Study on the expression of TRIM7 in peripheral blood mononuclear cells of patients with sepsis and its early diagnostic value.BMC infectious diseases · 2022Article
- The Presence of PDL-1 on CD8+ Lymphocytes Is Linked to Survival in Neonatal Sepsis.Children (Basel, Switzerland) · 2022Article
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Authors and funding
8 authors.
Funding
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Abstract
Objective: The pathogenesis of sepsis is still unclear due to its complexity, especially in children. This study aimed to analyse the immune microenvironment and regulatory networks related to sepsis in children at the molecular level and to identify key immune-related genes to provide a new basis for the early diagnosis of sepsis. Methods: The GSE145227 and GSE26440 datasets were downloaded from the Gene Expression Omnibus. The analyses included differentially expressed genes (DEGs), functional enrichment, immune cell infiltration, the competing endogenous RNA (ceRNA) interaction network, weighted gene coexpression network analysis (WGCNA), protein-protein interaction (PPI) network, key gene screening, correlation of sepsis molecular subtypes/immune infiltration with key gene expression, the diagnostic capabilities of key genes, and networks describing the interaction of key genes with transcription factors and small-molecule compounds. Finally, real-time quantitative PCR (RT-qPCR) was performed to verify the expression of key genes. Results: A total of 236 immune-related DEGs, most of which were enriched in immune-related biological functions, were found. Further analysis of immune cell infiltration showed that M0 macrophages and neutrophils infiltrated more in the sepsis group, while fewer activated memory CD4 Conclusion: Our results offer new insights into the pathogenesis of sepsis in children and provide new potential diagnostic biomarkers for the disease.
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