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Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients.
Henriksen, Hanne H; Marín de Mas, Igor; Nielsen, Lars K; Krocker, Joseph; Stensballe, Jakob; Karvelsson, Sigurður T; Secher, Niels H; Rolfsson, Óttar; Wade, Charles E; Johansson, Pär I.
Afiliación
  • Henriksen HH; Section for Transfusion Medicine, Capital Region Blood Bank, Rigshospitalet, University of Copenhagen, 2100 Copenhagen, Denmark.
  • Marín de Mas I; CAG Center for Endotheliomics, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.
  • Nielsen LK; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.
  • Krocker J; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.
  • Stensballe J; Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, 4072 Brisbane, Australia.
  • Karvelsson ST; Center for Translational Injury Research, Department of Surgery, University of Texas Health Science Center, Houston, TX 77030, USA.
  • Secher NH; Section for Transfusion Medicine, Capital Region Blood Bank, Rigshospitalet, University of Copenhagen, 2100 Copenhagen, Denmark.
  • Rolfsson Ó; CAG Center for Endotheliomics, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.
  • Wade CE; Department of Anesthesia and Trauma Center, Center of Head and Orthopedics, Rigshospitalet, 2100 Copenhagen, Denmark.
  • Johansson PI; Center for Systems Biology, University of Iceland, 101 Reykjavik, Iceland.
Int J Mol Sci ; 24(3)2023 Jan 23.
Article en En | MEDLINE | ID: mdl-36768579
ABSTRACT
In trauma patients, shock-induced endotheliopathy (SHINE) is associated with a poor prognosis. We have previously identified four metabolic phenotypes in a small cohort of trauma patients (N = 20) and displayed the intracellular metabolic profile of the endothelial cell by integrating quantified plasma metabolomic profiles into a genome-scale metabolic model (iEC-GEM). A retrospective observational study of 99 trauma patients admitted to a Level 1 Trauma Center. Mass spectrometry was conducted on admission samples of plasma metabolites. Quantified metabolites were analyzed by computational network analysis of the iEC-GEM. Four plasma metabolic phenotypes (A-D) were identified, of which phenotype D was associated with an increased injury severity score (p < 0.001); 90% (91.6%) of the patients who died within 72 h possessed this phenotype. The inferred EC metabolic patterns were found to be different between phenotype A and D. Phenotype D was unable to maintain adequate redox homeostasis. We confirm that trauma patients presented four metabolic phenotypes at admission. Phenotype D was associated with increased mortality. Different EC metabolic patterns were identified between phenotypes A and D, and the inability to maintain adequate redox balance may be linked to the high mortality.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Choque Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Mol Sci Año: 2023 Tipo del documento: Article País de afiliación: Dinamarca

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Choque Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Mol Sci Año: 2023 Tipo del documento: Article País de afiliación: Dinamarca