Parkinson’s Disease: Exploring Different Animal Model Systems

Engila Khan, Ikramul Hasan, M. Emdadul Haque

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number9088
JournalInternational journal of molecular sciences
Volume24
Issue number10
DOIs
Publication statusPublished - May 2023

Keywords

  • Lewy body
  • Parkinson’s disease
  • animal model
  • dopaminergic neurons
  • motor impairment
  • neurodegeneration
  • oxidative stress
  • α-synuclein

ASJC Scopus subject areas

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry

Fingerprint

Dive into the research topics of 'Parkinson’s Disease: Exploring Different Animal Model Systems'. Together they form a unique fingerprint.

Cite this