ArticlePloS one2025
Dissecting the role of NETosis-related biomarkers in Sepsis: An integrated multi-dataset analysis for diagnostic and prognostic applications.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Cell death crosstalk in NET-Driven inflammation: mechanisms, disease contexts, and therapeutic perspectives.Biomarker research · 2026Review
- Neutrophil extracellular traps associated with severity and prognosis of community-acquired pneumonia.Clinical and experimental medicine · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis is a life-threatening condition with high mortality and economic burdens. The study analyzed non-redundant differentially expressed genes (DEGs) to elucidate neutrophil extracellular trap (NET) formation's role in sepsis pathogenesis using high-throughput microarray and bioinformatics. Our comprehensive analysis meticulously identified a total of 629 DEGs, encompassing 348 upregulated and 281 downregulated genes. Through further scrutiny, we discovered 37 NETosis-related differentially expressed genes (NRDEGs) that showcased distinct expression patterns. Enrichment analysis vividly revealed the significant involvement of these NRDEGs in pathways related to NET formation, phagocytosis, and lymphocyte migration, thereby highlighting the crucial role of neutrophils in the immune response during sepsis. Additionally, CIBERSORT algorithm analysis indicated substantial differences in the abundance of 17 immune cell types between the sepsis and control groups, further reinforcing the altered immune landscape in sepsis patients. A protein-protein interaction (PPI) network constructed from the NRDEGs identified nine core genes, suggesting their potential central position in the pathophysiology of sepsis. Receiver operating characteristic (ROC) curve analysis demonstrated that ITGAM, CXCR2, and FCGR3B exhibited extremely high accuracy in distinguishing sepsis from controls (with an area under the curve greater than 0.9). These remarkable findings strongly underscore the potential of these genes as biomarkers for early diagnosis and therapeutic targets in sepsis, emphasizing the urgent need for further validation in clinical settings to enhance diagnostic accuracy and refine treatment strategies. Overall, this study provides novel insights into the molecular mechanisms underlying sepsis, paving the way for improved clinical interventions.
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Registered trials
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