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Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients

Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients


Title: Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients
Author: Henriksen, Hanne H.
Marín de Mas, Igor
Nielsen, Lars K.
Krocker, Joseph
Stensballe, Jakob
Karvelsson, Sigurður T.
Secher, Niels H.
Rolfsson, Óttar   orcid.org/0000-0003-4258-6057
Wade, Charles E.
Johansson, Pär I.
Date: 2023-01-23
Language: English
Scope: 2172912
Department: Faculty of Medicine
Series: International Journal of Molecular Sciences; 24(3)
ISSN: 1661-6596
DOI: 10.3390/ijms24032257
Subject: endotheliopathy; genome-scale metabolic model; metabolomics; systems biology; trauma; tricarboxylic acid cycle; Shock; Metabolomics; Phenotype; Prospective Studies; Endothelial Cells; Humans; Molecular Biology; Spectroscopy; Catalysis; Inorganic Chemistry; Computer Science Applications; Physical and Theoretical Chemistry; Organic Chemistry
URI: https://hdl.handle.net/20.500.11815/4445

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Citation:

Henriksen , H H , Marín de Mas , I , Nielsen , L K , Krocker , J , Stensballe , J , Karvelsson , S T , Secher , N H , Rolfsson , Ó , Wade , C E & Johansson , P I 2023 , ' Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients ' , International Journal of Molecular Sciences , vol. 24 , no. 3 , 2257 . https://doi.org/10.3390/ijms24032257

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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Funding Information: HHH has been supported by a PhD-scholarship from Rigshospitalet, Denmark, and would like to thank The Candys Foundation for the grant (2018-279). IMdM and LKN were supported by The Novo Nordisk Foundation (NNF Grant numbers: NNF20CC0035580; NNF14OC0009473; and NNF20SA0066621). Publisher Copyright: © 2023 by the authors.

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