ArticleCritical care (London, England)2012
Identification of sepsis subtypes in critically ill adults using gene expression profiling.
Article in Critical care (London, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed, 69 citations in OpenAlex.
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- Septic Cardiomyopathy: Difficult Definition, Challenging Diagnosis, Unclear Treatment.Journal of clinical medicine · 2025Review
- Blood from septic patients with necrotising soft tissue infection treated with hyperbaric oxygen reveal different gene expression patterns compared to standard treatment.BMC medical genomics · 2025Observational
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- Stratification of Experimental LPS-Induced Systemic Inflammatory Response by Expression Level of Hif1a and NFkb Genes.Bulletin of experimental biology and medicine · 2024Article
- Biological basis of critical illness subclasses: from the bedside to the bench and back again.Critical care (London, England) · 2024Review
- Machine learning reveals ferroptosis features and a novel ferroptosis classifier in patients with sepsis.Immunity, inflammation and disease · 2024Article
- The immune landscape of sepsis and using immune clusters for identifying sepsis endotypes.Frontiers in immunology · 2024Article
- Whole blood transcriptomics identifies subclasses of pediatric septic shock.Critical care (London, England) · 2023Article
- Sustained Perturbation of Metabolism and Metabolic Subphenotypes Are Associated With Mortality and Protein Markers of the Host Response.Critical care explorations · 2023Article
- Insights into COVID-19-associated critical illness: a narrative review.Annals of translational medicine · 2023Review
- Sepsis-Induced myocardial dysfunction: heterogeneity of functional effects and clinical significance.Frontiers in cardiovascular medicine · 2023Review
- Classification of subtypes and identification of dysregulated genes in sepsis.Frontiers in cellular and infection microbiology · 2023Article
- Sepsis biomarkers and diagnostic tools with a focus on machine learning.EBioMedicine · 2022Review
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
introductionSepsis is a syndromic illness that has traditionally been defined by a set of broad, highly sensitive clinical parameters. As a result, numerous distinct pathophysiologic states may meet diagnostic criteria for sepsis, leading to syndrome heterogeneity. The existence of biologically distinct sepsis subtypes may in part explain the lack of actionable evidence from clinical trials of sepsis therapies. We used microarray-based gene expression data from adult patients with sepsis in order to identify molecularly distinct sepsis subtypes.
methodsWe used partitioning around medoids (PAM) and hierarchical clustering of gene expression profiles from neutrophils taken from a cohort of septic patients in order to identify distinct subtypes. Using the medoids learned from this cohort, we then clustered a second independent cohort of septic patients, and used the resulting class labels to evaluate differences in clinical parameters, as well as the expression of relevant pharmacogenes.
resultsWe identified two sepsis subtypes based on gene expression patterns. Subtype 1 was characterized by increased expression of genes involved in inflammatory and Toll receptor mediated signaling pathways, as well as a higher prevalence of severe sepsis. There were differences between subtypes in the expression of pharmacogenes related to hydrocortisone, vasopressin, norepinephrine, and drotrecogin alpha.
conclusionsSepsis subtypes can be identified based on different gene expression patterns. These patterns may generate hypotheses about the underlying pathophysiology of sepsis and suggest new ways of classifying septic patients both in clinical practice, and in the design of clinical trials.
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