Chinese Journal of Tissue Engineering Research ›› 2024, Vol. 28 ›› Issue (在线): 1-6.

   

Metabolomics analysis of serum and urine in patients with traumatic spinal cord injury

Song Jiating, Chen Jianmin, Wang Kewen, Huang Lanying, Xu Senming, Gui Yuchang, Xu Jianwen   

  1. Department of Rehabilitation Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
  • Received:2023-06-27 Accepted:2023-07-29 Online:2024-01-08 Published:2023-10-19
  • Contact: Xu Jianwen, MD, Chief physician, Professor, Doctoral supervisor, Department of Rehabilitation Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
  • About author:Song Jiating, Master candidate, Physician, Department of Rehabilitation Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
  • Supported by:
    National Natural Science Foundation of China, No. 81960417 (to XJW); Guangxi Key Research and Development Program, No. GuiKeAB20159027 (to XJW and GYC); Guangxi Natural Science Foundation for the Youth, No. 2022GXNSFBA035545 (to GYC); Innovation Project of Guangxi Graduate Education, No. YCBZ2022082 (to XSM)

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Abstract: BACKGROUND: Traumatic spinal cord injury primarily relies on scale assessment and imaging examinations in clinical practice. However, there are limitations in predicting the prognosis of the injury. Therefore, the use of metabolomics technology for biomarker screening is significant for estimating the extent of damage, injury and recovery, as well as developing new therapies.
OBJECTIVE: To characterize the metabolic features of patients with traumatic spinal cord injury using metabolomics technology and explore potential biomarkers and disrupted metabolic pathways. 
METHODS: Serum and urine samples were collected from 20 patients with traumatic spinal cord injury (observation group) and 10 healthy subjects (control group). Metabolites were analyzed and multivariate statistical analysis was then performed for data processing to screen differential metabolites. Metabolic pathway enrichment was performed using MetaboAnalyst software. Logistic regression was applied to construct a biomarker combination model, and its relationship with the American Spinal Injury Association grading was analyzed. 
RESULTS AND CONCLUSION: Significant differences in 160 and 73 metabolites were detected in the serum and urine samples of the two groups, respectively. Pathway enrichment analysis showed evident disturbances in lipid metabolism after traumatic spinal cord injury, including sphingolipid, arachidonic acid, α-linolenic acid, and arachidonic acid metabolism, as well as glycerophospholipid and inositol phosphate biosynthesis. The combination of two identified biomarkers, telmisartan and quercetin glycoside, showed a correlation with the American Spinal Injury Association grading in both serum and urine levels. Thus, metabolomics technology provides assistance in further understanding the pathological mechanisms of traumatic spinal cord injury and screening therapeutic targets. The identified metabolic biomarker combination may serve as a reference for assessing the severity of traumatic spinal cord injury.

Key words: traumatic spinal cord injury, metabolomics, biomarker, differential metabolites, ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry

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