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Clinical correlates of similar pathologies in parkinsonian syndromes


  • Relevant conflicts of interest/financial disclosures: Tissues were received from the Sydney Brain Bank, which is supported by the National Health and Medical Research Council of Australia (Enabling Grant #282933), Neuroscience Research Australia and the University of New South Wales. Y.J.C. Song was an Australian Postgraduate and Parkinson's NSW Scholar and G.M. Halliday is a Senior Principal Research Fellow of the National Health and Medical Research Council of Australia. Full financial disclosures and author roles may be found in the online version of this article.



There have been no previous studies assessing the severity of regional atrophy, cell loss and lesion densities between the overlapping conditions of Parkinson's disease (PD), progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) and relating these pathologies to different clinical features.


Clinical indices and basal ganglia, brainstem, and cerebellar pathology from 43 longitudinally studied cases (PD = 8, PSP = 15, MSA = 12, controls = 8) were compared. A point-counting method was used to evaluate subregional volumes, and α-synuclein and phospho-tau immunohistochemistry was used to assess pathological inclusions and stage disease severity. Logistic regression analyses were used to identify pathological associations with clinical features.


All PD, PSP, and MSA cases had severe degeneration of the substantia nigra. Clinical features correlated with tissue loss and the severity of inclusion pathologies. Levodopa responsiveness and a lack of resting tremor was associated with preservation of pallidal volume, the presence of gait ataxia was associated with atrophy of the putamen, and the parkinsonian-plus phenotype with early falls and supranuclear vertical gaze abnormalities had more substantial midbrain atrophy and greater inclusion pathology in the caudate nucleus.


This is the first study to compare the severity of regional pathologies across parkinsonian conditions. The data show that tissue loss and inclusion densities in certain regions correlate with clinical indices, with regional volume changes likely to be the best indicator of clinical progression of disease. © 2011 Movement Disorder Society

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