Metabolic Disturbances in a Mouse Model of MPTP/Probenecid-Induced Parkinson’s Disease: Evaluation Using Liquid Chromatography-Mass Spectrometry

Abstract

Purpose: Parkinson’s disease (PD) is a common neurodegenerative disease that severely affects patients’ daily lives and places a significant burden on the global economy. There are currently no specific biomarkers for distinguishing between the different stages of PD. Methods: We divided 78 mice into six equal groups, including five model PD groups (W1–W5; based on the PD stage induced by length of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/propofol induction time) and a control group. Then, we used metabolomics technology to detect the serum small-molecule metabolites present in each group. Ultimately, we screened for potential biomarkers using the variable importance in the projection of the orthogonal partial least squares discriminant analysis and the coefficient value of LASSO ordinal logistic regression. Results: We identified 12 potential biomarkers, including dehydroepiandrosterone sulfate, pipecolic acid, N-acetylleucine, 2-aminoa-dipic acid, L-tyrosine, uric acid, and 5-hydroxyindoleacetaldehyde. Pathway analysis revealed their involvement in amino acid metabolism, caffeine metabolism, steroid hormone biosynthesis, and purine metabolism. Additionally, the receiver operating char-acteristic curve indicated that a biomarker panel comprising the 12 biomarkers could differentiate between the different PD stages. Conclusion: Different PD stages are characterized by different metabolites. The biomarkers identified in this study are helpful to understand the PD process.