Reverse engineering Lewy bodies: how far have we come and how far can we go?

神经退行性变 神经科学 疾病 帕金森病 生物 路易氏体型失智症 病理 路易体 医学 痴呆
作者
Mohamed Fares,Somanath Jagannath,Hilal A. Lashuel
出处
期刊:Nature Reviews Neuroscience [Springer Nature]
卷期号:22 (2): 111-131 被引量:85
标识
DOI:10.1038/s41583-020-00416-6
摘要

Lewy bodies (LBs) are α-synuclein (α-syn)-rich intracellular inclusions that are an important pathological hallmark of Parkinson disease and several other neurodegenerative diseases. Increasing evidence suggests that the aggregation of α-syn has a central role in LB formation and is one of the key processes that drive neurodegeneration and pathology progression in Parkinson disease. However, little is known about the mechanisms underlying the formation of LBs, their biochemical composition and ultrastructural properties, how they evolve and spread with disease progression, and their role in neurodegeneration. In this Review, we discuss current knowledge of α-syn pathology, including the biochemical, structural and morphological features of LBs observed in different brain regions. We also review the most used cellular and animal models of α-syn aggregation and pathology spreading in relation to the extent to which they reproduce key features of authentic LBs. Finally, we provide important insights into molecular and cellular determinants of LB formation and spreading, and highlight the critical need for more detailed and systematic characterization of α-syn pathology, at both the biochemical and structural levels. This would advance our understanding of Parkinson disease and other neurodegenerative diseases and allow the development of more-reliable disease models and novel effective therapeutic strategies. Lewy bodies, which are α-synuclein-rich intracellular inclusions, are pathological hallmarks of several neurodegenerative diseases, notably Parkinson disease. In this Review, Fares, Jagannath and Lashuel examine the biochemical, structural and morphological features of Lewy bodies as well as how α-synuclein pathology may form and spread.
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