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Proteinopathy and longitudinal changes in functional connectivity networks in Parkinson disease

Authors :
Jonathan M. Koller
Paul T. Kotzbauer
Joshua J. Jackson
Meghan C. Campbell
Joel S. Perlmutter
Abraham Z. Snyder
Source :
Neurology
Publication Year :
2019

Abstract

ObjectiveTo evaluate resting-state functional connectivity as a potential prognostic biomarker of Parkinson disease (PD) progression. The study examined longitudinal changes in cortical resting-state functional connectivity networks in participants with PD compared to controls as well as in relation to baseline protein measures and longitudinal clinical progression.MethodsIndividuals with PD without dementia (n = 64) and control participants (n = 27) completed longitudinal resting-state MRI scans and clinical assessments including full neuropsychological testing after overnight withdrawal of PD medications (“off”). A total of 55 participants with PD and 20 control participants also completed baseline β-amyloid PET scans and lumbar punctures for CSF protein levels of α-synuclein, β-amyloid, and tau. Longitudinal analyses were conducted with multilevel growth curve modeling, a type of mixed-effects model.ResultsFunctional connectivity within the sensorimotor network and the interaction between the dorsal attention network with the frontoparietal control network decreased significantly over time in participants with PD compared to controls. Baseline CSF α-synuclein protein levels predicted decline in the sensorimotor network. The longitudinal decline in the dorsal attention–frontoparietal internetwork strength correlated with the decline in cognitive function.ConclusionsThese results indicate that α-synuclein levels may influence longitudinal declines in motor-related functional connectivity networks. Further, the interaction between cortical association networks declines over time in PD prior to dementia onset and may serve as a prognostic marker for the development of dementia.

Details

ISSN :
1526632X
Volume :
94
Issue :
7
Database :
OpenAIRE
Journal :
Neurology
Accession number :
edsair.doi.dedup.....8a47c2254c0a3ebc63486fc9a0bc061e