Parkinson’s Disease: Exploring Different Animal Model Systems

• Published in: International journal of molecular sciences Vol. 24; no. 10; p. 9088
• Main Authors: Khan, Engila, Hasan, Ikramul, Haque, M. Emdadul
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 22.05.2023; MDPI
• Subjects: alpha-Synuclein - metabolism; Animals; Behavior; Disease Models, Animal; Dopaminergic Neurons - metabolism; Genetic engineering; Genetics; Investigations; Laboratory animals; Lewy Bodies - metabolism; Medical research; Medicine, Experimental; Neurodegeneration; Oxidative stress; Parkinson Disease - metabolism; Parkinson's disease; Pars Compacta - metabolism; Pathology; Review; Substantia Nigra - metabolism; dopaminergic neurons; neurodegeneration; animal model; Parkinson’s disease; oxidative stress; α-synuclein; Lewy body; motor impairment
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms24109088

Disease modeling in non-human subjects is an essential part of any clinical research. To gain proper understanding of the etiology and pathophysiology of any disease, experimental models are required to replicate the disease process. Due to the huge diversity in pathophysiology and prognosis in different diseases, animal modeling is customized and specific accordingly. As in other neurodegenerative diseases, Parkinson’s disease is a progressive disorder coupled with varying forms of physical and mental disabilities. The pathological hallmarks of Parkinson’s disease are associated with the accumulation of misfolded protein called α-synuclein as Lewy body, and degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc) area affecting the patient’s motor activity. Extensive research has already been conducted regarding animal modeling of Parkinson’s diseases. These include animal systems with induction of Parkinson’s, either pharmacologically or via genetic manipulation. In this review, we will be summarizing and discussing some of the commonly employed Parkinson’s disease animal model systems and their applications and limitations.