Abstract
Alpha-synucleinopathies are neurodegenerative diseases characterized by the spread of alpha-synuclein (α-syn) aggregates throughout the central nervous system in a stereotypical manner. These diseases include Lewy body disease (LBD), which encompass Dementia with Lewy bodies (DLB), Parkinson's Disease (PD), and Parkinson's Disease Dementia (PDD), and Multiple System Atrophy (MSA). LBD and MSA chiefly contain α-syn aggregates in neurons and oligodendrocytes, respectively, although glial α-syn pathology in LBD is increasingly being recognized. Semi-quantitative and machine learning-based quantifications of neuronal, oligodendrocytic and astrocytic α-syn pathology were implemented on a cohort of LBD and MSA post-mortem tissue samples. The neuroanatomical distribution of each cell-type specific α-syn pathology was evaluated using conditional probability matrices and Subtype and Stage Inference (SuStaIn) algorithm. We revealed extensive glial α-syn pathology in LBD, emphasizing the disease- and region-specific profile of astrocytic α-syn pathology, which was absent in MSA and minimal in the substantia nigra of LBD. Furthermore, we have described distinct morphologies of astrocytic α-syn pathology, which were found to correlate with the density of astrocytic α-syn inclusions. Astrocytic α-syn pathology was mainly centered in the amygdala and exhibited a unique stereotypical progression whilst oligodendrocytes displayed a distribution akin to the established neuronal progression pattern. SuStaIn modeling was further used to test for heterogeneity in the spatiotemporal progression, revealing that a subset of cases might follow an alternative pattern. Based on these findings, we introduce a novel multimodal progression framework that integrates, for the first time, the temporal and spatial progression of astrocytic and oligodendrocytic α-syn pathology alongside neuronal pathology in PD, providing further information regarding the role of neurons and glia in disease pathogenesis.