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2025, Vol. 29 ›› Issue (8): 1585-1592

Metabolomic analysis of urine in a rat model of chronic myofascial trigger points

Liu Lin, Liu Shixuan, Lu Xinyue, Wang Kan   

  1. School of Sport and Health, Nanjing Sport Institute, Nanjing 210014, Jiangsu Province, China

  • Received:2024-03-20 Accepted:2024-05-09 Online:2025-03-18 Published:2024-07-05

  • Contact: Wang Kan, MD, Lecturer, School of Sport and Health, Nanjing Sport Institute, Nanjing 210014, Jiangsu Province, China

  • About author:School of Sport and Health, Nanjing Sport Institute, Nanjing 210014, Jiangsu Province, China Liu Lin, MD, Lecturer, School of Sport and Health, Nanjing Sport Institute, Nanjing 210014, Jiangsu Province, China

  • Supported by:

    the National Natural Science Foundation of China, No. 32000829 (to LL); Jiangsu Province University “Blue Engineering” Project (to LL)

Abstract: BACKGROUND: Chronic myofascial trigger points can identify differential metabolite changes through non targeted metabolomics techniques, helping to understand and further explore the pathophysiological processes and pathogenesis of chronic myofascial trigger points from the perspective of endogenous small molecule metabolites.
OBJECTIVE: To investigate potential biomarkers and related metabolic pathways based on urine metabolomics in the rat model of chronic myofascial trigger points.
METHODS: Sixteen Sprague-Dawley rats were randomly divided into a model group and a normal group. The model group was used to establish a chronic myofascial trigger point animal model by combining blunt hitting with centrifugal exercise (treadmill slope: -16°, running speed: 16 m/min, training time: 90 minutes each), once a week for 8 continuous weeks, with 4 weeks off. After 12 weeks of modeling, the metabolic cage method was used to collect urine from rats at 24 hours after modeling. Liquid chromatography-mass spectrometry non-targeted metabolomics technology was used to detect metabolic profiles in the urine samples, screen common differential metabolites, and conduct bioinformatics analysis.
RESULTS AND CONCLUSION: Compared with the normal group, there were 32 differential metabolic markers in the model group, of which 21 were upregulated and 11 were downregulated. A total of 14 differential metabolites were identified as potential biomarkers based on the value of variable important in projection greater than 3. The enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes indicated that the formation of chronic myofascial trigger points is closely related to metabolic pathways such as primary bile acid biosynthesis and arachidonic acid metabolism.
Key words: myofascial trigger point, rat, urine, metabolomics, bioinformatics, biomarker, differential metabolite, metabolic cage method, sports injuries

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