Modeling neurodegeneration and neuroinflammation in Parkinson’s Disease: Animal-based strategies

Loading...
Thumbnail Image

Full text at PDC

Publication date

2025

Advisors (or tutors)

Editors

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier
Citations
Google Scholar

Citation

Morales-García, J. A. (2025). Modeling neurodegeneration and neuroinflammation in Parkinson’s Disease: Animal-based strategies. En Methods in cell biology. https://doi.org/10.1016/bs.mcb.2025.02.006

Abstract

Parkinson disease (PD) is the second most prevalent neurodegenerative disorder globally, trailing only Alzheimer´s disease. It currently affects nearly 3 % of individuals aged 65 and above. The disease is characterized by the progressive loss of dopaminergic neurons accompanied by a chronic neuroinflammatory process, which is responsible for both motor symptoms (tremor, rigidity, bradykinesia) and non-motor symptoms (depression, dysphagia, anxiety, constipation, and anosmia). To gain a deeper comprehension of the fundamental mechanisms underlying PD and to facilitate the development of efficacious therapeutic interventions, it is imperative to utilize animal models that accurately reflect the pathological characteristics observed in humans. This chapter provides a comprehensive overview of the methodologies employed in the generation of animal models of Parkinson’s disease in laboratory settings. These models, which encompass a range of approaches, serve as invaluable tools for reproducing key aspects of neurodegeneration and neuroinflammation associated with PD. By establishing reliable animal models, we can investigate the cellular and molecular pathways driving disease progression, thereby gaining insights into potential therapeutic targets. Furthermore, the chapter discusses the limitations and advantages of different model systems, emphasizing their relevance in translational research aimed at finding effective treatments for PD patients.

Research Projects

Organizational Units

Journal Issue

Description

Unesco subjects

Keywords

Collections