Cited by 39Sepsis Diagnosis and TreatmentInflammation biomarkers and pathwaysCOVID-19 Clinical Research Studies

Multi-Omics Endotypes in ICU Sepsis-Induced Immunosuppression

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Garduno, Alexis, Cusack, Rachael, Leone, Marc, Einav, Sharon, Martin-Loeches, Ignacio·2023·Microorganisms

Abstract

It is evident that the admission of some patients with sepsis and septic shock to hospitals is occurring late in their illness, which has contributed to the increase in poor outcomes and high fatalities worldwide across age groups. The current diagnostic and monitoring procedure relies on an inaccurate and often delayed identification by the clinician, who then decides the treatment upon interaction with the patient. Initiation of sepsis is accompanied by immune system paralysis following “cytokine storm”. The unique immunological response of each patient is important to define in terms of subtyping for therapy. The immune system becomes activated in sepsis to produce interleukins, and endothelial cells express higher levels of adhesion molecules. The proportions of circulating immune cells change, reducing regulatory cells and increasing memory cells and killer cells, having long-term effects on the phenotype of CD8 T cells, HLA-DR, and dysregulation of microRNA. The current narrative review seeks to highlight the potential application of multi-omics data integration and immunological profiling at the single-cell level to define endotypes in sepsis and septic shock. The review will consider the parallels and immunoregulatory axis between cancer and immunosuppression, sepsis-induced cardiomyopathy, and endothelial damage. Second, the added value of transcriptomic-driven endotypes will be assessed through inferring regulatory interactions in recent clinical trials and studies reporting gene modular features that inform continuous metrics measuring clinical response in ICU, which can support the use of immunomodulating agents.

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  • Omics data were absent from the multimodal studies included in this review.

    “although omics data have been used in unimodal AI models for the ICU [74–76], they were absent from the multimodal studies included in this review.”

    From Multimodal Artificial Intelligence for Precision Critical Care: A Scoping Review (2026) · cites this paper as [74]

    The Introduction describes using gene-expression data with machine-learning algorithms for sepsis and cites an ICU artificial-neural-network study. It does not establish that those AI models were unimodal. The statement that omics data were absent from the citing review’s multimodal studies is the citing authors’ own finding, not a claim attributed to this source. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Garduno, A., Cusack, R., Leone, M., Einav, S., & Martin-Loeches, I.
Affiliations
  • Trinity College Dublin (IE)
  • St. James's Hospital (IE)
  • Department of Anesthesia, Intensive Care and Trauma Center, Nord University Hospital, Aix Marseille University, APHM, 13015 Marseille, France
  • Hebrew University of Jerusalem (IL)
  • Department of Clinical Medicine, Trinity College, University of Dublin, D02 PN40 Dublin, Ireland
Venue
Microorganisms
Publisher
MDPI AG
Published
2023-04-25
Volume
11
Issue
5
Pages
1119
ISSN
2076-2607 (ISSN-L)
OpenAlex
W4366987332
Cited by
39
References
7
Citations by year
2026: 20 · 2025: 11 · 2024: 5 · 2023: 3
FWCI
1.52
Type
journal article
Language
en
Open access
Locations
  • Microorganisms (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
SFI (Science Foundation Ireland) (20/COV/0038)
Topics
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
  • Life Sciences › Immunology and Microbiology › Immunology › Inflammation biomarkers and pathways
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
sepsis, septic shock, sepsis-induced immunosuppression, endotypes, multi-omics integration, cytokine storm, HLA-DR, microRNA dysregulation, septic cardiomyopathy, endothelial injury, tumor immunosuppression, gene regulatory interactions, immunomodulating agents

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