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Models of multiple system atrophy

Multiple system atrophy (MSA) is a neurodegenerative disease with diverse clinical manifestations, including parkinsonism, cerebellar syndrome, and autonomic failure. Pathologically, MSA is characterized by glial cytoplasmic inclusions in oligodendrocytes, which contain fibrillary forms of α-synucle...

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Detalles Bibliográficos
Autores principales: Lee, He-Jin, Ricarte, Diadem, Ortiz, Darlene, Lee, Seung-Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861264/
https://www.ncbi.nlm.nih.gov/pubmed/31740682
http://dx.doi.org/10.1038/s12276-019-0346-8
Descripción
Sumario:Multiple system atrophy (MSA) is a neurodegenerative disease with diverse clinical manifestations, including parkinsonism, cerebellar syndrome, and autonomic failure. Pathologically, MSA is characterized by glial cytoplasmic inclusions in oligodendrocytes, which contain fibrillary forms of α-synuclein. MSA is categorized as one of the α-synucleinopathy, and α-synuclein aggregation is thought to be the culprit of the disease pathogenesis. Studies on MSA pathogenesis are scarce relative to studies on the pathogenesis of other synucleinopathies, such as Parkinson’s disease and dementia with Lewy bodies. However, recent developments in cellular and animal models of MSA, especially α-synuclein transgenic models, have driven advancements in research on this disease. Here, we review the currently available models of MSA, which include toxicant-induced animal models, α-synuclein-overexpressing cellular models, and mouse models that express α-synuclein specifically in oligodendrocytes through cell type-specific promoters. We will also discuss the results of studies in recently developed transmission mouse models, into which MSA brain extracts were intracerebrally injected. By reviewing the findings obtained from these model systems, we will discuss what we have learned about the disease and describe the strengths and limitations of the models, thereby ultimately providing direction for the design of better models and future research.