ArticleCritical care (London, England)2025
Plasma proteomics identifies molecular subtypes in sepsis.
Article in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- The molecular ICU: a primer on omics, informatics and the future of precision critical care.Critical care (London, England) · 2026Review
- 7-day longitudinal proteomics of critically ill patients: a pilot study.Scientific reports · 2026Observational
- The Tip of the Iceberg: Pathway Biology Must Anchor the Next Generation of Critical Care Trials.Critical care explorations · 2026Article
- Plasma Proteomic Signatures of Pediatric Sepsis Reveal Persistent Inflammation and Phase-Specific Biomarkers.FASEB bioAdvances · 2026Article
- Microvascular phenotypes in pediatric sepsis identified by machine learning: prognostic implications for organ dysfunction and mortality.Critical care (London, England) · 2026Article
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- Exploring proteomic signatures in sepsis and non-infectious systemic inflammatory response syndrome.PloS one · 2026Observational
- CXCL10 rs8878 identifies a genotype-associated immune phenotype linked to T-lymphocyte preservation and survival in sepsis.Frontiers in immunology · 2026Article
- Genomic and integrative based progression biomarker discovery in adult sepsis: toward clinical stratification and precision medicine.Annals of intensive care · 2026Review
- Clinical subphenotypes and molecular endotypes in sepsis: toward an integrated and dynamic framework.Annals of intensive care · 2026Review
- Identification of distinct immune subtypes in sepsis through dual immunomarker trajectory.Annals of intensive care · 2026Article
- Strength of Omics in Uncovering Sepsis Mechanisms-A Perspective.Current health sciences journalReview
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Authors and funding
25 authors.
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Abstract
backgroundThe heterogeneity of sepsis represents a significant challenge to the development of personalized sepsis therapies. Sepsis subtyping has therefore emerged as an important approach to this problem, but its impact on clinical practice was limited due to insufficient molecular insights. Modern proteomics techniques allow the identification of subtypes and provide molecular and mechanistical insights. In this study, we analyzed a prospective multi-center sepsis cohort using plasma proteomics to describe and characterize sepsis plasma proteome subtypes.
methodsPlasma samples were collected from 333 patients at days 1 and 4 of sepsis and analyzed using liquid chromatography coupled to tandem mass spectrometry. Plasma proteome subtypes were identified using K-means clustering and characterized based on clinical routine data, cytokine measurements, and proteomics data. A random forest machine learning classifier was generated to showcase future assignment of patients to subtypes.
resultsFour subtypes with different sepsis severity were identified. Cluster 0 represented the most severe form of sepsis, with 100% mortality. Cluster 1, 2 and 3 showed a gradual decrease of the median SOFA score, as reflected by clinical data and cytokine measurements. At the proteome level, the subtypes were characterized by distinct molecular features. We observed an alternating immune response, with cluster 1 showing prominent activation of the adaptive immune system, as indicated by elevated levels immunoglobulin (Ig) levels, which were verified using orthogonal measurements. Cluster 2 was characterized by acute inflammation and the lowest Ig levels. Cluster 3 represented the sepsis proteome baseline of the investigated cohort. We generated an ML classifier and optimized it for the minimum number of proteins that could realistically be implemented into routine diagnostics. The model, which was based on 10 proteins and Ig quantities, allowed the assignment of patients to clusters 1, 2 and 3 with high confidence.
conclusionThe identified plasma proteome subtypes provide insights into the immune response and disease mechanisms and allow conclusions on appropriate therapeutic measures, enabling predictive enrichment in clinical trials. Thus, they represent a step forward in the development of targeted therapies and personalized medicine for sepsis.
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