ArticleBMC medicine2009
Identification of pediatric septic shock subclasses based on genome-wide expression profiling.
Article in BMC medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 196 papers, 3 of them syntheses that pooled it.
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Who cites it
196 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A consensus immune dysregulation framework for sepsis and critical illnesses.Nature medicine · 2025Guideline
- A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock.Molecular medicine reports · 2020Pooled it
- Transcriptomic meta-analysis reveals up-regulation of gene expression functional in osteoclast differentiation in human septic shock.PloS one · 2017Pooled it
- Latent class analysis of ARDS subphenotypes: a secondary analysis of the statins for acutely injured lungs from sepsis (SAILS) study.Intensive care medicine · 2018Trial
- Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.JCI insight · 2018Trial
- Cross-Cohort Integration of Blood DNA Methylation and Sepsis Transcriptomes Prioritizes TP53INP1 as a Candidate Associated with B-Cell Transcriptomic Patterns in Pediatric HAdV-7-Associated Sepsis.Pathogens (Basel, Switzerland) · 2026Article
- Deltex E3 ubiquitin ligase 2 prevents sepsis-induced myocardial injury through degrading TfR1 via promoting K27-linked ubiquitination.Cell death and differentiation · 2026Article
- Deleterious variants in LTBP4 are associated with severe pediatric sepsis.Pediatric research · 2026Article
- Longitudinal blood transcriptome profiling reveals immune dynamics in sepsis.BMC infectious diseases · 2026Article
- Age-related differences and common pathways of lymphocyte subsets in sepsis: a comparative review of elderly and pediatric patients.Cell death & disease · 2026Review
- The Dual Role of Interleukin-10 in Sepsis: Research Progress and Therapeutic Prospects.Inflammation · 2026Review
- Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Pathophysiology and Management of Sepsis-associated Acute Kidney Injury.Clinics in chest medicine · 2026Review
- Pediatric Sepsis: Evolving Subphenotypes, Overlap Syndromes, and the Path to Precision Therapies.Clinics in chest medicine · 2026Review
- Identification of Glycolysis-Related Signature and Molecular Subtypes in Child Sepsis Through Machine Learning and Consensus Clustering: Implications for Diagnosis and Therapeutics.Molecular biotechnology · 2026Article
- Identification of immune status subtypes and prognostic analysis of septic patients based on Th1/Th2 cytokine assays.Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- Alveolar Immune Profiling Identifies Distinct Subphenotypes of Acute Respiratory Failure.medRxiv : the preprint server for health sciences · 2026Article
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- Multi-omic and computational approaches for biomarker discovery and clinical translation in pediatric sepsis.Frontiers in pharmacology · 2026Review
- Systems biology approaches to unravelling neonatal sepsis and potential for precision diagnostics and therapeutics.Frontiers in pharmacology · 2026Review
136 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundSeptic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling.
methodsGenome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization.
resultsThree putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the three putative subclasses (analysis of variance, Bonferonni correction, P < 0.05) identified 6,934 differentially regulated genes. K-means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the three subclasses. Leave one out cross-validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C.
conclusionGenome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.
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