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Neutrophil dysregulation differentiates pediatric septic shock biomarker-based mortality-risk strata: insights from weighted gene co-expression network and transcriptomic analyses.

Publication ,  Journal Article
Dunwoodie, L; Huang, M; Moore, AR; Stanski, NL; Standage, SW; Kaplan, JM; Zingarelli, B; Harmon, K; Fitzgerald, JC; Weiss, SL; Bigham, MT ...
Published in: Front Immunol
2025

BACKGROUND: Pediatric sepsis is a leading cause of global mortality, particularly among children, with limited therapeutic options beyond antibiotics and organ support. The Pediatric Sepsis Biomarker Risk Model (PERSEVERE-II) stratifies mortality risk in pediatric septic shock, yet the molecular mechanisms underlying high mortality risk remain incompletely understood. METHODS: We analyzed whole blood transcriptomes collected from 81 children with septic shock on day 1 of meeting study criteria. Patients were stratified into high- and low-mortality risk groups according to the PERSEVERE-II biomarker risk model. Using weighted gene co-expression network analysis (WGCNA) and differential gene expression analyses, we identified molecular pathways and transcription factors (TFs) associated with mortality risk. Cell type differences were inferred using CIBERSORTx and using a reference single-cell dataset inclusive of neutrophils and their subsets. FINDINGS: We identified distinct molecular profiles with high-risk patients displaying significant overexpression of genes related to neutrophil degranulation and innate immunity, alongside suppressed adaptive immune responses. The predominance of developing neutrophils underscored a major role of emergency granulopoiesis. Key TFs identified, including LTF, FOXM1, KLF1, and CEBPB, were linked to high-risk gene expression signatures. Our findings indicate a pathological shift toward a dysregulated neutrophil-driven hyperinflammation and adaptive immune suppressive state, which together are associated with adverse outcomes. INTERPRETATION: Our results suggest that neutrophil dysregulation underpins the high mortality risk conferred by the PERSEVERE-II model. The identified transcriptional regulators may provide potential targets to mitigate neutrophil dysregulation and improve outcomes among high-risk patients.

Duke Scholars

Published In

Front Immunol

DOI

EISSN

1664-3224

Publication Date

2025

Volume

16

Start / End Page

1663704

Location

Switzerland

Related Subject Headings

  • Transcriptome
  • Shock, Septic
  • Neutrophils
  • Male
  • Infant
  • Humans
  • Gene Regulatory Networks
  • Gene Expression Profiling
  • Female
  • Child, Preschool
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Dunwoodie, L., Huang, M., Moore, A. R., Stanski, N. L., Standage, S. W., Kaplan, J. M., … Lautz, A. J. (2025). Neutrophil dysregulation differentiates pediatric septic shock biomarker-based mortality-risk strata: insights from weighted gene co-expression network and transcriptomic analyses. Front Immunol, 16, 1663704. https://doi.org/10.3389/fimmu.2025.1663704
Dunwoodie, Leland, Min Huang, Andrew R. Moore, Natalja L. Stanski, Stephen W. Standage, Jennifer M. Kaplan, Basilia Zingarelli, et al. “Neutrophil dysregulation differentiates pediatric septic shock biomarker-based mortality-risk strata: insights from weighted gene co-expression network and transcriptomic analyses.Front Immunol 16 (2025): 1663704. https://doi.org/10.3389/fimmu.2025.1663704.
Dunwoodie L, Huang M, Moore AR, Stanski NL, Standage SW, Kaplan JM, Zingarelli B, Harmon K, Fitzgerald JC, Weiss SL, Bigham MT, Schwarz AJ, Lutfi R, Thomas NJ, Haileselassie B, Jain PN, Sweeney TE, Kamaleswaran R, Atreya MR, Lautz AJ. Neutrophil dysregulation differentiates pediatric septic shock biomarker-based mortality-risk strata: insights from weighted gene co-expression network and transcriptomic analyses. Front Immunol. 2025;16:1663704.

Published In

Front Immunol

DOI

EISSN

1664-3224

Publication Date

2025

Volume

16

Start / End Page

1663704

Location

Switzerland

Related Subject Headings

  • Transcriptome
  • Shock, Septic
  • Neutrophils
  • Male
  • Infant
  • Humans
  • Gene Regulatory Networks
  • Gene Expression Profiling
  • Female
  • Child, Preschool