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Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study
The assessment, management, and prognostication of spinal cord injury (SCI) mainly rely upon observer-based ordinal scales measures. (1)H nuclear magnetic resonance (NMR) spectroscopy provides an effective approach for the discovery of objective biomarkers from biofluids. These biomarkers have the p...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224260/ https://www.ncbi.nlm.nih.gov/pubmed/37233646 http://dx.doi.org/10.3390/metabo13050605 |
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author | Bykowski, Elani A. Petersson, Jamie N. Dukelow, Sean Ho, Chester Debert, Chantel T. Montina, Tony Metz, Gerlinde A. S. |
author_facet | Bykowski, Elani A. Petersson, Jamie N. Dukelow, Sean Ho, Chester Debert, Chantel T. Montina, Tony Metz, Gerlinde A. S. |
author_sort | Bykowski, Elani A. |
collection | PubMed |
description | The assessment, management, and prognostication of spinal cord injury (SCI) mainly rely upon observer-based ordinal scales measures. (1)H nuclear magnetic resonance (NMR) spectroscopy provides an effective approach for the discovery of objective biomarkers from biofluids. These biomarkers have the potential to aid in understanding recovery following SCI. This proof-of-principle study determined: (a) If temporal changes in blood metabolites reflect the extent of recovery following SCI; (b) whether changes in blood-derived metabolites serve as prognostic indicators of patient outcomes based on the spinal cord independence measure (SCIM); and (c) whether metabolic pathways involved in recovery processes may provide insights into mechanisms that mediate neural damage and repair. Morning blood samples were collected from male complete and incomplete SCI patients (n = 7) following injury and at 6 months post-injury. Multivariate analyses were used to identify changes in serum metabolic profiles and were correlated to clinical outcomes. Specifically, acetyl phosphate, 1,3,7-trimethyluric acid, 1,9-dimethyluric acid, and acetic acid significantly related to SCIM scores. These preliminary findings suggest that specific metabolites may serve as proxy measures of the SCI phenotype and prognostic markers of recovery. Thus, serum metabolite analysis combined with machine learning holds promise in understanding the physiology of SCI and aiding in prognosticating outcomes following injury. |
format | Online Article Text |
id | pubmed-10224260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102242602023-05-28 Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study Bykowski, Elani A. Petersson, Jamie N. Dukelow, Sean Ho, Chester Debert, Chantel T. Montina, Tony Metz, Gerlinde A. S. Metabolites Article The assessment, management, and prognostication of spinal cord injury (SCI) mainly rely upon observer-based ordinal scales measures. (1)H nuclear magnetic resonance (NMR) spectroscopy provides an effective approach for the discovery of objective biomarkers from biofluids. These biomarkers have the potential to aid in understanding recovery following SCI. This proof-of-principle study determined: (a) If temporal changes in blood metabolites reflect the extent of recovery following SCI; (b) whether changes in blood-derived metabolites serve as prognostic indicators of patient outcomes based on the spinal cord independence measure (SCIM); and (c) whether metabolic pathways involved in recovery processes may provide insights into mechanisms that mediate neural damage and repair. Morning blood samples were collected from male complete and incomplete SCI patients (n = 7) following injury and at 6 months post-injury. Multivariate analyses were used to identify changes in serum metabolic profiles and were correlated to clinical outcomes. Specifically, acetyl phosphate, 1,3,7-trimethyluric acid, 1,9-dimethyluric acid, and acetic acid significantly related to SCIM scores. These preliminary findings suggest that specific metabolites may serve as proxy measures of the SCI phenotype and prognostic markers of recovery. Thus, serum metabolite analysis combined with machine learning holds promise in understanding the physiology of SCI and aiding in prognosticating outcomes following injury. MDPI 2023-04-28 /pmc/articles/PMC10224260/ /pubmed/37233646 http://dx.doi.org/10.3390/metabo13050605 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Bykowski, Elani A. Petersson, Jamie N. Dukelow, Sean Ho, Chester Debert, Chantel T. Montina, Tony Metz, Gerlinde A. S. Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study |
title | Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study |
title_full | Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study |
title_fullStr | Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study |
title_full_unstemmed | Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study |
title_short | Identification of Serum Metabolites as Prognostic Biomarkers Following Spinal Cord Injury: A Pilot Study |
title_sort | identification of serum metabolites as prognostic biomarkers following spinal cord injury: a pilot study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224260/ https://www.ncbi.nlm.nih.gov/pubmed/37233646 http://dx.doi.org/10.3390/metabo13050605 |
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