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Animal models of Parkinson's disease: a guide to selecting the optimal model for your research.

Authors :
Lama J
Buhidma Y
Fletcher EJR
Duty S
Source :
Neuronal signaling [Neuronal Signal] 2021 Dec 08; Vol. 5 (4), pp. NS20210026. Date of Electronic Publication: 2021 Dec 08 (Print Publication: 2021).
Publication Year :
2021

Abstract

Parkinson's disease (PD) is a complex, multisystem disorder characterised by α-synuclein (SNCA) pathology, degeneration of nigrostriatal dopaminergic neurons, multifactorial pathogenetic mechanisms and expression of a plethora of motor and non-motor symptoms. Animal models of PD have already been instructive in helping us unravel some of these aspects. However, much remains to be discovered, requiring continued interrogation by the research community. In contrast with the situation for many neurological disorders, PD benefits from of a wide range of available animal models (pharmacological, toxin, genetic and α-synuclein) but this makes selection of the optimal one for a given study difficult. This is especially so when a study demands a model that displays a specific combination of features. While many excellent reviews of animal models already exist, this review takes a different approach with the intention of more readily informing this decision-making process. We have considered each feature of PD in turn - aetiology, pathology, pathogenesis, motor dysfunctions and non-motor symptoms (NMS) - highlighting those animal models that replicate each. By compiling easily accessible tables and a summary figure, we aim to provide the reader with a simple, go-to resource for selecting the optimal animal model of PD to suit their research needs.<br />Competing Interests: The authors declare that there are no competing interests associated with the manuscript.<br /> (© 2021 The Author(s).)

Details

Language :
English
ISSN :
2059-6553
Volume :
5
Issue :
4
Database :
MEDLINE
Journal :
Neuronal signaling
Publication Type :
Academic Journal
Accession number :
34956652
Full Text :
https://doi.org/10.1042/NS20210026