Parkinson's disease (PD) is characterized by both motor and non-motor symptoms (cognitive impairment, affective disorder, and other clinical features). Data from experimental animal models and patients with PD indicate that the manifestations of this disease cannot be attributed to isolated dysfunction of the basal ganglia. Rather, the highly localized loss of nigral dopamine cells is associated with a broad, spatially distributed set of functional abnormalities involving cortico-striato-pallido-thalamocortical (CSPTC) loops and related pathways. By quantifying the activity of spatially distributed (large-scale) functional brain networks, comprising multiple interconnected brain regions, modern techniques of image-based analysis can provide valuable information concerning the widespread circuit abnormalities that underlie neurodegenerative disorders such as PD. The investigators at the Center for Neurosciences at The Feinstein Institute, led by Dr. Eidelberg, have pioneered the use of functional brain imaging and network analysis for the study of PD and related neurodegenerative diseases. Because of the noise inherent in """"""""small signals"""""""" analyses of this sort, we have emphasized rigorous validation of the disease-related functional patterns from both statistical and empiric standpoints. Indeed, high levels of measurement precision are needed before quantitative network measures can be considered as potential biomarkers of the disease process and its response to treatment. In this proposal, we seek to take this approach to a new level by employing rigorously validated PD-related networks to address a number of vital issues that impact heavily on the care of today's PD patients. Project 1 addresses the serious clinical problem of levodopa-induced dyskinesias, which ultimately affect nearly all PD patients. Project 2 examines the network basis for individual differences in the cognitive response to dopaminergic treatment with a view to predicting which patients will develop untoward cognitive side effects under different treatment conditions. Project 3 aims to establish the feasibility of a new network-based algorithm for providing earlier and more accurate differential diagnosis than is currently possible.

Public Health Relevance

Because dopaminergic treatment is generally so effective for the motor symptoms of PD, at least early on, it is easy to dismiss the very real problems that ultimately develop: levodopa-induced dyskinesias and cognitive and behavioral changes for some patients. Understanding these phenomena should not only help us improve the lives of patients, but will provide unique insight into the pathophysiology of PD and perhaps other neurodegenerative disorders. Likewise, the validation of an automated pattern-based method for early diagnosis will help streamline trials of new therapies for PD as well as for atypical parkinsonian syndromes. PROJECT 1 Principal Investigator: David Eidelberg and Angela Cenci Title: Microvascular Changes in Parkinson's Disease: Relationship to Levodopa-lnduced Dyskinesia Description (provided by applicant): The dopamine precursor levodopa is the most effective medication available for the treatment of Parkinson's disease (PD), but eventually it causes levodopa-induced dyskinesias (LID) in the vast majority of the patients. Experimental studies in a rodent model indicate that following peripheral levodopa administration there is a larger and prompter surge in striatal dopamine levels (DA) in animals with LID. Because the passage of levodopa through the blood-brain barrier (BBB) is critically regulated at the level of the endothelium, neurovascular alterations need to be thoroughly investigated as a possible contributing factor in LID. To that end, we will expand upon our recent observation in PD patients, that levodopa has divergent effects on regional cerebral metabolism and blood flow, and that the magnitude of local flow metabolism dissociation, a quantitative index of treatment-mediated hemodynamic alterations, is much greater in patients with LID than those with uncomplicated treatment responses.
In Specific Aim 1, we will study two groups of patients, those with LID and those with uncomplicated levodopa responses, using [18F]-FDG PET (for cerebral metabolism), [150]-H20 PET (for cerebral blood flow), and [82Rb]-Rubidium PET (for BBB permeability) to compare levodopa-mediated changes across groups.
In Specific Aim 2, we will determine whether localized vasomotor and/or BBB changes exist in drug-naive PD patients and whether flow-metabolism dissociation develops following one year of treatment with levodopa, but not dopamine agonist.
In Specific Aim 3, we will use a rat model of LID to determine whether changes in local cerebral blood flow relate to structural alterations of the microvasculature and BBB permeability in the affected regions. Previous studies in this animal model have indeed revealed increased angiogenesis and BBB permeability in the basal ganglia. Given that analogous changes have very recently been noted in the basal ganglia of human PD brains at autopsy, this project provides a unique opportunity for translational investigation directed at a major challenge confronting PD patients and their caretakers. Public Health Relevance: The development of levodopa-induced dyskinesias (LID) in Parkinson's disease (PD) is poorly understood. Using a translational approach, this project will further the understanding of the pathophysiology of this potentially disabling side effect of therapy, and should open avenues for the development of new treatments of LID. Furthermore, improved understanding of the role of angiogenesis and blood-brain barrier in PD is likely also relevant to other neurodegenerative diseases.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Specialized Center (P50)
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Special Emphasis Panel (ZNS1-SRB-E (34))
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Sieber, Beth-Anne
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Feinstein Institute for Medical Research
United States
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Ko, Ji Hyun; Spetsieris, Phoebe G; Eidelberg, David (2018) Network Structure and Function in Parkinson's Disease. Cereb Cortex 28:4121-4135
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