Cognitive dysfunction develops in many Parkinson's disease (PD) patients, and elucidating its underlying mechanisms is critical. Recent functional and anatomic imaging studies suggest the involvement of a variety of brain regions, but there are conflicting reports regarding which regions are consistently involved. Furthermore, few studies directly compare PD patients with and without cognitive syndromes (e.g. PD with mild cognitive impairment (PD-MCI)), and few MRI-based studies have investigated brain region connectivity (i.e. combined functional and structural neuroanatomic networks) underlying such cognitive impairment. What brain networks are involved in PD-MCI, which are dopaminergically sensitive, and the role of structural pathology within these circuits remain important unanswered questions. Furthermore, an MRI-based tool clinically useful in diagnosing, tracking, and monitoring response to treatment in PD-MCI has yet to be developed. To address these issues, we propose to use a combined functional-MRI (fMRI) and Diffusion Tensor MRI (DTI) analysis to investigate cortico-striatal and whole-brain networks that underlie cognition in PD patients with PD-MCI and with no cognitive impairment (PD-NCI), as well as in healthy controls (No-PD). We will test the hypothesis that dorsal v. ventral cortico-striatal functional (Aim 1; fMRI) and structural (Aim 2; DTI) connectivity is differentially affected in PD-MCI and PD-NCI, and we will track the evolution of functional and structural network dysfunction as PD-MCI patients cognitively decline (Aim 3). We will determine the cognitive status of each group according to recently proposed neuropsychometric criteria. We will investigate fMRI-based resting-state networks of functional connectivity in both clinically defined 'on' and 'off' dopaminergic medication conditions in PD-MCI and PD-NCI participants, as well as in No-PD controls. We will also investigate structural connectivity networks in these participants using DTI-based tractographic analyses. We will correlate network findings with both disease and cognitive status of participants, as well as determine correlations between the functional and structural networks themselves. Furthermore, we will track the evolution of functional and structural neuroanatomic network abnormalities in PD-MCI participants longitudinally as these participants decline cognitively, and we will determine if new network changes evolve as new cognitive domains are affected in these participants. These studies will provide insight into the neural-network basis of cognitive impairment in PD, and may lead to a novel MRI-based imaging biomarker for evaluating the nature, degree, and progression of PD-MCI. This Project interacts with Project 1 of this COBRE proposal, uses the clinical cohort of the Clinical and Translational Research Core (CTRC), and uses the data resources of the Data Management and Statistics Core (DMSC) of the proposed Center for Neurodegeneration and Translational Neuroscience (CNTN).

Public Health Relevance

Cognitive dysfunction develops in many PD patients, thus elucidating its underlying mechanisms is critical: currently, there is no clinical imaging method that can predict which PD patients will develop such cognitive problems. We propose to use a combined functional and structural MRI analysis of PD patients with and without cognitive impairment to investigate the neural networks related to cognitive dysfunction in PD. These studies will provide insight into the basis of cognitive impairment in PD, and may lead to development of a novel MRI-based imaging biomarker.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory Grants (P20)
Project #
1P20GM109025-01A1
Application #
8812120
Study Section
Special Emphasis Panel (ZGM1-TWD-0)
Project Start
Project End
Budget Start
2015-09-01
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
$319,855
Indirect Cost
$108,501
Name
Cleveland Clinic Lerner
Department
Type
DUNS #
City
Cleveland
State
OH
Country
United States
Zip Code
44195
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