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    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. © 2021. The Author(s).


    Hua Yang, Pengwei Zhang, Min Xie, Jianxian Luo, Jing Zhang, Guowei Zhang, Yang Wang, Hongsheng Lin, Zhisheng Ji. Parallel Metabolomic Profiling of Cerebrospinal Fluid, Plasma, and Spinal Cord to Identify Biomarkers for Spinal Cord Injury. Journal of molecular neuroscience : MN. 2022 Jan;72(1):126-135

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    PMID: 34498202

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