The assessment, management, and prognostication of spinal cord injury (SCI) mainly rely upon observer-based ordinal scales measures. ¹H 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.

The neuropathological sequelae of stroke and subsequent recovery are incompletely understood. Here, we investigated the metabolic dynamics following stroke to advance the understanding of the pathophysiological mechanisms orchestrating stroke recovery. Using a nuclear magnetic resonance (NMR)-driven metabolomic profiling approach for urine samples obtained from a clinical group, the objective of this research was to (1) identify novel biomarkers indicative of severity and recovery following stroke, and (2) uncover the biochemical pathways underlying repair and functional recovery after stroke. Urine samples and clinical stroke assessments were collected during the acute (2–11 days) and chronic phases (6 months) of stroke. Using a 700 MHz ¹H NMR spectrometer, metabolomic profiles were acquired followed by a combination of univariate and multivariate statistical analyses, along with biological pathway analysis and clinical correlations. The results revealed changes in phenylalanine, tyrosine, tryptophan, purine, and glycerophospholipid biosynthesis and metabolism during stroke recovery. Pseudouridine was associated with a change in post-stroke motor recovery. Thus, NMR-based metabolomics is able to provide novel insights into post-stroke cellular functions and establish a foundational framework for future investigations to develop targeted therapeutic interventions, advance stroke diagnosis and management, and enhance overall quality of life for individuals with stroke.

Metabolomic biomarkers hold promise in aiding the diagnosis and prognostication of traumatic brain injury. In Canada, over 165,000 individuals annually suffer from a traumatic brain injury (TBI), making it one of the most prevalent neurological conditions. In this pilot investigation, we examined blood-derived biomarkers as proxy measures that can provide an objective approach to TBI diagnosis and monitoring. Using a ¹H nuclear magnetic resonance (NMR)-based quantitative metabolic profiling approach, this study determined whether (1) blood-derived metabolites change during recovery in male participants with mild to severe TBI; (2) biological pathway analysis reflects mechanisms that mediate neural damage/repair throughout TBI recovery; and (3) changes in metabolites correlate to initial injury severity. Eight male participants with mild to severe TBI (with intracranial lesions) provided morning blood samples within 1–4 days and again 6 months post-TBI. Following NMR analysis, the samples were subjected to multivariate statistical and machine learning-based analyses. Statistical modelling displayed metabolic changes during recovery through group separation, and eight significant metabolic pathways were affected by TBI. Metabolic changes were correlated to injury severity. L-alanine (R= −0.63, p < 0.01) displayed a negative relationship with the Glasgow Coma Scale. This study provides pilot data to support the feasibility of using blood-derived metabolites to better understand changes in biochemistry following TBI.