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Research Article
Piotr Młynarz
Wrocław University of Science and Technology
Corresponding Author
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There is a clear difference between severe brain damage and brain death. However, in clinical practice, the differentiation of these states can be challenging. Currently, there are no laboratory tools that facilitate brain death diagnosis. The aim of our study was to evaluate the utility of serum metabolomic analysis in differentiating coma patients (CP) from individuals with brain death (BD). Serum samples were collected from 23 adult individuals with established diagnosis of brain death and 24 patients in coma with Glasgow Coma Scale 3 or 4, with no other clinical symptoms of brain death for at least 7 days after sample collection. Serum metabolomic profiles were investigated using proton nuclear magnetic resonance (NMR) spectroscopy. The results obtained were examined by univariate and multivariate data analysis (PCA, PLS-DA, and OPLS-DA). Metabolic profiling allowed us to quantify 43 resonance signals, of which 34 were identified. Multivariate statistical modeling revealed a highly significant separation between coma patients and brain-dead individuals, as well as strong predictive potential. The findings not only highlight the potential of the metabolomic approach for distinguishing patients in coma from those in the state of brain death but also may provide an understanding of the pathogenic mechanisms underlying these conditions.
Keywords
brain death, coma patients, NMR spectroscopy, metabolomics analysis, multivariate data analysis, univariate data analysis
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No competing interests reported.
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This preprint is under consideration at Scientific Reports. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Piotr Młynarz
Wrocław University of Science and Technology
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 27 Apr, 2021
No community comments so far
Editorial decision: Major revision
On 09 Jun, 2021
Reviews received
Received 27 May, 2021
Reviewers agreed
On 17 May, 2021
Reviewers invited
Invitations sent on 07 May, 2021
Editor assigned
On 07 May, 2021
Editor invited
On 26 Apr, 2021
Submission checks complete
On 26 Apr, 2021
First submitted
On 22 Apr, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
There is a clear difference between severe brain damage and brain death. However, in clinical practice, the differentiation of these states can be challenging. Currently, there are no laboratory tools that facilitate brain death diagnosis. The aim of our study was to evaluate the utility of serum metabolomic analysis in differentiating coma patients (CP) from individuals with brain death (BD). Serum samples were collected from 23 adult individuals with established diagnosis of brain death and 24 patients in coma with Glasgow Coma Scale 3 or 4, with no other clinical symptoms of brain death for at least 7 days after sample collection. Serum metabolomic profiles were investigated using proton nuclear magnetic resonance (NMR) spectroscopy. The results obtained were examined by univariate and multivariate data analysis (PCA, PLS-DA, and OPLS-DA). Metabolic profiling allowed us to quantify 43 resonance signals, of which 34 were identified. Multivariate statistical modeling revealed a highly significant separation between coma patients and brain-dead individuals, as well as strong predictive potential. The findings not only highlight the potential of the metabolomic approach for distinguishing patients in coma from those in the state of brain death but also may provide an understanding of the pathogenic mechanisms underlying these conditions.
Figure 1
Figure 3
Figure 4
Figure 5
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