Decoding Parkinson’s Disease through Animal Models: Mechanistic Insights and Therapeutic Roadmaps

Parkinson’s disease (PD) is a complex neurodegenerative disorder characterized by progressive dopaminergic neuronal loss, α-synuclein aggregation, and a range of motor and non-motor symptoms. Animal models have been indispensable in elucidating PD mechanisms and testing therapeutic strategies; however, no single model fully recapitulates the multifaceted human pathology. This review presents a comprehensive and comparative analysis of neurotoxic (e.g., 6-OHDA, MPTP, rotenone), genetic (e.g., α-synuclein, LRRK2, PINK1, Parkin, DJ-1), and pharmacological (e.g., reserpine, haloperidol) models of PD. We highlight each model’s mechanistic relevance, behavioural features, and limitations, particularly regarding non-motor symptoms, disease progression, and translational applicability. Special focus is given to the emerging use of humanized models, iPSC-based systems, and multi-hit protocols that combine genetic and environmental factors. Novel dimensions such as sex differences, the gut-brain axis, peripheral pathology, and immune system involvement are critically examined. Furthermore, the integration of biomarkers (e.g., phosphorylated α-synuclein, DJ-1, cytokines) and advanced imaging tools (PET, MRI) is discussed as a refinement in model validation and disease monitoring. We also explore how AI-driven approaches can enhance data analysis and predictive modelling. By synthesizing traditional and emerging insights, this review provides a multidimensional perspective on PD modelling. It underscores the need for strategic, integrative model selection to bridge preclinical research with clinical translation and to facilitate the development of effective, personalized therapies.