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

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Version: Final published version
License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_CA19E139164B
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Discovery and validation of temporal patterns involved in human brain ketometabolism in cerebral microdialysis fluids of traumatic brain injury patients.
Journal
EBioMedicine
Author(s)
Eiden M., Christinat N., Chakrabarti A., Sonnay S., Miroz J.P., Cuenoud B., Oddo M., Masoodi M.
ISSN
2352-3964 (Electronic)
ISSN-L
2352-3964
Publication state
Published
Issued date
06/2019
Peer-reviewed
Oui
Volume
44
Pages
607-617
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
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.
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.
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.
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.
Keywords
Cerebral microdialysis, Ketometabolism, Metabolic state, Traumatic brain injury
Pubmed
Web of science
Open Access
Yes
Create date
30/06/2019 14:49
Last modification date
15/01/2021 7:11
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