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Open forum infectious diseases · 2025

Examining Transcriptomic Markers Associated With Neutrophil Extracellular Traps to Predict Mortality Risk in Neonatal Sepsis.

СтатьяНазвание и аннотация: Перевод в очереди
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Shaw Deepshikha, Santhanam Sridhar, Som Tapas Kumar, Bhattacharjee Samsiddhi, Mohapatra Saroj Kant

Аннотация

BACKGROUND: Neonates are highly susceptible to sepsis, which is often accompanied by fatal coagulopathy. Anticoagulant therapies have not reduced sepsis-related mortality in clinical trials, possibly due to patient heterogeneity. Neutrophil extracellular traps (NETs) enhance coagulation by activating platelets, suggesting that NET-specific biomarkers may identify patients who may benefit from targeted anticoagulant treatment. This study evaluated the association between NET gene expression and adverse outcomes in neonatal sepsis.

METHODS: We analyzed whole blood transcriptomes from 123 neonates with sepsis and developed a predictive model, the NET score, based on NET-related gene expression. Model performance was assessed in two independent validation sets. Mediation and correlation analyses explored the relationship between the NET score and a coagulation score. Temporal transcriptomic data from septic shock cases further tested this interaction.

RESULTS: The NET score achieved AUCs of 88.7% and 85.4% in validation Sets 1 and 2, respectively, indicating strong predictive performance. Mediation and temporal analyses supported a sequential relationship between NETosis and coagulation in sepsis. Age-specificity of the model was confirmed using pediatric (n = 163) and adult (n = 86) sepsis transcriptomic datasets. Neonates with disseminated intravascular coagulation exhibited a trend toward elevated NET scores.

CONCLUSIONS: Our findings support a novel risk stratification approach using the NET score to identify neonates at increased risk for sepsis-associated coagulopathy and poor outcomes, potentially guiding targeted therapeutic strategies.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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