Network structure of brain atrophy in de novo Parkinson's Disease
Abstract
We mapped the distribution of atrophy in Parkinson's Disease (PD) using MRI and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation.
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Author details
Ethics
Human subjects: For the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data)Each participating PPMI site received approval from a local research ethics committee before study initiation, and obtained written informed consent from all subjects participating in the study.For the resting state fMRI data collected in our lab, We acquired resting state fMRI in 51 healthy, right-handed volunteers.The experimental protocol was reviewed and approved by Research Ethics Board of Montreal Neurological Institute. All subjects gave informed consent.
Reviewing Editor
- David C Van Essen, Washington University in St Louis, United States
Publication history
- Received: April 30, 2015
- Accepted: September 5, 2015
- Accepted Manuscript published: September 7, 2015 (version 1)
- Version of Record published: October 8, 2015 (version 2)
Copyright
© 2015, Zeighami et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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