Neurotoxicity, α-synuclein pathology, and mitochondrial dysfunction: A comparative study of different mouse models of Parkinson’s disease

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The causes of Parkinson’s disease are complex, and it is difficult for a single animal model to fully mimic its pathological characteristics. In this study, a comprehensive analysis of behaviors, Parkinson’s disease–like pathologies, and gene and protein expression profiles was carried out in three mouse models of disease: 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced, α-synuclein (α-syn) A53T transgenic, and MitoPark, revealing both shared and model-specific pathogenic pathways to guide model selection and identify potential therapeutic targets. All three Parkinson’s disease models exhibited motor impairments, with particularly pronounced age-related decline observed in MitoPark mice. Pathologically, nigrostriatal pathway damage was observed in all models, yet with distinct patterns of glial cell activation. Sixteen-month-old α-syn A53T mice displayed a few pS129-α-syn-positive signals in the substantia nigra, while no α-syn aggregates were observed in any of the models. RNA sequencing and proteomics analysis revealed significant changes in gene and protein expression, with both unique and common features among the three models. Five common differentially expressed genes (Ifi27l2a, Ifitm3, Oasl2, Rtp4, and Ankk1) and two common differentially expressed proteins (Timm8a1 and Sephs1) were identified. Functional enrichment analysis indicated that immune responses, cytokines, and neurotransmitter transport were crucial in Parkinson’s disease pathogenesis. Notably, multiple iron-related cell damage (ferroptosis)-related differentially expressed genes were identified across all three models, while interleukin 17 pathway activation was altered in MitoPark mice. In summary, we analyzed the commonalities and specificities of pathological simulation capabilities and common disease mechanisms in different mouse models of Parkinson’s disease from multiple perspectives. Our findings offer valuable insights into the multifaceted characteristics of Parkinson’s disease and will assist in model selection for mechanistic exploration in the future.

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