Abstract
Loss of physical and emotional health due to spinal cord injury (SCI) has been rapidly increasing worldwide. Effective evaluation of the severity of SCI is crucial to its prognosis. Herein, we constructed rat models of SCI with four different degrees of injury (sham group, light injury group, moderate injury group, and heavy injury group), using the surgical approach. Cerebrospinal fluid (CSF), plasma, and spinal cord were sampled at the sub-acute spinal cord (72 h post-injury) from each rat. The LC–MS-based metabolic profiling of these samples was performed according to a universal metabolome standard (UMS). The results demonstrated that 130, 104, and 128 metabolites were significantly altered within the CSF, plasma, and spinal cord samples, respectively. Among them, there were four differential metabolites, including uric acid, phosphorycholine, pyridoxine, and guanidoacetic acid, which were commonly identified within the CSF, plasma, and spinal cord samples. Further pathway analysis of these differential metabolites demonstrated a disturbance in the metabolism of glyoxylate and dicarboxylate and glycine, serine, and threonine which were associated with pathophysiologic consequence of spinal cord injury. In particular, phosphorycholine, pyridoxine, and guanidoacetic acid demonstrated a relationship with SCI severity. Thus, they could be utilized as potential metabolite biomarkers for SCI severity assessment.
Highlights
There is a significant rise in the occurrence of spinal cord injury (SCI) each year due to the fast development of transport, mining, sports, and construction sectors (SinghHua Yang, Pengwei Zhang, Min Xie contributed to this work.SCI has been evaluated clinically for quantification of neurologic impairment, as well as level of injury, which has impeded the validity for further efforts in order to intervene in the SCI setting (Wu et al 2016)
Novel treatments for spinal cord injury can be evaluated based on biomarkers, which are able to characterize the severity of injury, and correctly predict neurologic recovery
The identified metabolites were subjected to principal component analysis (PCA) in order to assess the effects of SCI (Fig. 2)
Summary
SCI has been evaluated clinically for quantification of neurologic impairment, as well as level of injury, which has impeded the validity for further efforts in order to intervene in the SCI setting (Wu et al 2016). Novel treatments for spinal cord injury can be evaluated based on biomarkers, which are able to characterize the severity of injury, and correctly predict neurologic recovery While prior studies have reported the metabolite changes after SCI (Dulin et al 2013; Peng et al 2014; Jiang et al 2010), a global profiling of the metabolic network as a feedback to different degrees of subacute SCI has remained previously unreported
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