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Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients

BACKGROUND: Traumatic brain injury (TBI) is recognized as a metabolic disease, characterized by acute cerebral glucose hypo-metabolism. Adaptive metabolic responses to TBI involve the utilization of alternative energy substrates, such as ketone bodies. Cerebral microdialysis (CMD) has evolved as an...

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Autores principales: Eiden, Michael, Christinat, Nicolas, Chakrabarti, Anirikh, Sonnay, Sarah, Miroz, John-Paul, Cuenoud, Bernard, Oddo, Mauro, Masoodi, Mojgan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606955/
https://www.ncbi.nlm.nih.gov/pubmed/31202815
http://dx.doi.org/10.1016/j.ebiom.2019.05.054
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author Eiden, Michael
Christinat, Nicolas
Chakrabarti, Anirikh
Sonnay, Sarah
Miroz, John-Paul
Cuenoud, Bernard
Oddo, Mauro
Masoodi, Mojgan
author_facet Eiden, Michael
Christinat, Nicolas
Chakrabarti, Anirikh
Sonnay, Sarah
Miroz, John-Paul
Cuenoud, Bernard
Oddo, Mauro
Masoodi, Mojgan
author_sort Eiden, Michael
collection PubMed
description BACKGROUND: Traumatic brain injury (TBI) is recognized as a metabolic disease, characterized by acute cerebral glucose hypo-metabolism. Adaptive metabolic responses to TBI involve the utilization of alternative energy substrates, such as ketone bodies. Cerebral microdialysis (CMD) has evolved as an accurate technique allowing continuous sampling of brain extracellular fluid and assessment of regional cerebral metabolism. We present the successful application of a combined hypothesis- and data-driven metabolomics approach using repeated CMD sampling obtained routinely at patient bedside. Investigating two patient cohorts (n = 26 and n = 12), we identified clinically relevant metabolic patterns at the acute post-TBI critical care phase. METHODS: Clinical and CMD metabolomics data were integrated and analysed using in silico and data modelling approaches. We used both unsupervised and supervised multivariate analysis techniques to investigate structures within the time series and associations with patient outcome. FINDINGS: The multivariate metabolite time series exhibited two characteristic brain metabolic states that were attributed to changes in key metabolites: valine, 4-methyl-2-oxovaleric acid (4-MOV), isobeta-hydroxybutyrate (iso-bHB), tyrosyine, and 2-ketoisovaleric acid (2-KIV). These identified cerebral metabolic states differed significantly with respect to standard clinical values. We validated our findings in a second cohort using a classification model trained on the cerebral metabolic states. We demonstrated that short-term (therapeutic intensity level (TIL)) and mid-term patient outcome (6-month Glasgow Outcome Score (GOS)) can be predicted from the time series characteristics. INTERPRETATION: We identified two specific cerebral metabolic patterns that are closely linked to ketometabolism and were associated with both TIL and GOS. Our findings support the view that advanced metabolomics approaches combined with CMD may be applied in real-time to predict short-term treatment intensity and long-term patient outcome.
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spelling pubmed-66069552019-07-15 Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients Eiden, Michael Christinat, Nicolas Chakrabarti, Anirikh Sonnay, Sarah Miroz, John-Paul Cuenoud, Bernard Oddo, Mauro Masoodi, Mojgan EBioMedicine Research paper BACKGROUND: Traumatic brain injury (TBI) is recognized as a metabolic disease, characterized by acute cerebral glucose hypo-metabolism. Adaptive metabolic responses to TBI involve the utilization of alternative energy substrates, such as ketone bodies. Cerebral microdialysis (CMD) has evolved as an accurate technique allowing continuous sampling of brain extracellular fluid and assessment of regional cerebral metabolism. We present the successful application of a combined hypothesis- and data-driven metabolomics approach using repeated CMD sampling obtained routinely at patient bedside. Investigating two patient cohorts (n = 26 and n = 12), we identified clinically relevant metabolic patterns at the acute post-TBI critical care phase. METHODS: Clinical and CMD metabolomics data were integrated and analysed using in silico and data modelling approaches. We used both unsupervised and supervised multivariate analysis techniques to investigate structures within the time series and associations with patient outcome. FINDINGS: The multivariate metabolite time series exhibited two characteristic brain metabolic states that were attributed to changes in key metabolites: valine, 4-methyl-2-oxovaleric acid (4-MOV), isobeta-hydroxybutyrate (iso-bHB), tyrosyine, and 2-ketoisovaleric acid (2-KIV). These identified cerebral metabolic states differed significantly with respect to standard clinical values. We validated our findings in a second cohort using a classification model trained on the cerebral metabolic states. We demonstrated that short-term (therapeutic intensity level (TIL)) and mid-term patient outcome (6-month Glasgow Outcome Score (GOS)) can be predicted from the time series characteristics. INTERPRETATION: We identified two specific cerebral metabolic patterns that are closely linked to ketometabolism and were associated with both TIL and GOS. Our findings support the view that advanced metabolomics approaches combined with CMD may be applied in real-time to predict short-term treatment intensity and long-term patient outcome. Elsevier 2019-06-13 /pmc/articles/PMC6606955/ /pubmed/31202815 http://dx.doi.org/10.1016/j.ebiom.2019.05.054 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Eiden, Michael
Christinat, Nicolas
Chakrabarti, Anirikh
Sonnay, Sarah
Miroz, John-Paul
Cuenoud, Bernard
Oddo, Mauro
Masoodi, Mojgan
Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
title Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
title_full Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
title_fullStr Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
title_full_unstemmed Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
title_short Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
title_sort discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606955/
https://www.ncbi.nlm.nih.gov/pubmed/31202815
http://dx.doi.org/10.1016/j.ebiom.2019.05.054
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