Parkinson's disease (PD) is marked clinically by asymmetrical presentation of motor dysfunction, pathologically by the nigrostriatal dopamine (DA) neuronal loss in the basal ganglia (BG), and often is accompanied by extranigral, non-dopaminergic, non-motor symptoms. The pathogenesis of most PD is unproven, and there are no therapies proven to slow, arrest, or reverse cell death and disease progression. Moreover, both the understanding of PD-associated cell loss and evaluation of potential neuroprotective therapies have been hindered by the lack of a reliable, objective, in vivo marker for cell loss associated with PD progression. The best available in vivo techniques are functional radioimaging (PET &SPECT), assessing either DA transporter density or neuronal activity. While valuable, these endpoints reflect DA cell loss indirectly, are modulated by the symptomatic treatments in PD, are not able to assess non-dopaminergic systems, and are not widely available. Alternatively, structural volumetric imaging can reflect in vivo macroscopic atrophy (caused by cell loss), is less likely to be influenced by purely symptomatic treatments, can assess extranigral/nondopaminergic systems, and is widely available. Yet this approach has not been as exhaustively explored because of the difficulty in relating atrophic changes to a specific mechanism or function;and because of inconsistent findings in prior structural imaging studies in PD. The latter may be a result of cross-sectional designs, small sample sizes, and/or imaging analysis methods with low reliability. Our goal is to pursue structural imaging studies in PD, thus providing a more sophisticated understanding of PD-related cell loss, and a determination of whether MRI can be a useful and non-invasive marker of disease progression. Supported by strong preliminary data, our central hypothesis is that PD patients undergo significant brain atrophic changes focally (e.g., in BG structures) and globally relative to a normative age-matched sample. Not only can these changes be quantified reliably using high resolution MRI coupled with sophisticated analysis techniques, but they may have functional implications that are relevant to PD at both the clinical and heuristic levels. We propose to do longitudinal studies of a cohort of 80 PD subjects within 10 years of clinical diagnosis, and 54 Controls (matched 3:2 in age, gender, handedness, &education).
Our aims are to: 1) Establish the age trend of lateral ventricle enlargement and select BG regional atrophy in PD patients compared to Controls;2) Characterize the lateralization and time-course of longitudinal volumetric changes of lateral ventricles and select BG regions during the course of PD progression in relation to PD motor asymmetry and duration;3) Explore the potential of the volumetric measures of different structures of interest as a marker(s) of individual aspects of PD motor and non-motor dysfunction during the disease progression;and 4) Explore the interrelationships of changes among different brain regions and PD-related functional changes.

Public Health Relevance

Parkinson's disease (PD) is an age-related neurological disorder that affects about one million Americans'quality of life by causing motor and other dysfunctions, despite patients being on the best treatments available. Understanding the exact cause, and assessing a treatment to slow, or stop, the progression of the disease are hindered by the lack of a widely available, yet reliable, marker for its progression as it unfolds in PD patients. The goal of this grant is to establish MRI measurements as such a marker, thereby leading to a better understanding of the cause of PD and improved assessment of potential neuroprotective agents in PD.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
1R01NS060722-01A2
Application #
7591476
Study Section
Special Emphasis Panel (ZRG1-CND-E (90))
Program Officer
Sieber, Beth-Anne
Project Start
2009-05-15
Project End
2014-04-30
Budget Start
2009-05-15
Budget End
2010-04-30
Support Year
1
Fiscal Year
2009
Total Cost
$591,862
Indirect Cost
Name
Pennsylvania State University
Department
Neurology
Type
Schools of Medicine
DUNS #
129348186
City
Hershey
State
PA
Country
United States
Zip Code
17033
Lewis, Mechelle M; Du, Guangwei; Baccon, Jennifer et al. (2018) Susceptibility MRI captures nigral pathology in patients with parkinsonian syndromes. Mov Disord 33:1432-1439
Zhang, Lijun; Wang, Ming; Sterling, Nicholas W et al. (2018) Cortical Thinning and Cognitive Impairment in Parkinson's Disease without Dementia. IEEE/ACM Trans Comput Biol Bioinform 15:570-580
Rossi, Alexander; Berger, Kristin; Chen, Honglei et al. (2018) Projection of the prevalence of Parkinson's disease in the coming decades: Revisited. Mov Disord 33:156-159
Du, Guangwei; Lewis, Mechelle M; Sica, Christopher et al. (2018) Magnetic resonance T1w/T2w ratio: A parsimonious marker for Parkinson disease. Ann Neurol :
Lee, Eun-Young; Flynn, Michael R; Lewis, Mechelle M et al. (2018) Welding-related brain and functional changes in welders with chronic and low-level exposure. Neurotoxicology 64:50-59
Falaki, Ali; Jo, Hang Jin; Lewis, Mechelle M et al. (2018) Systemic effects of deep brain stimulation on synergic control in Parkinson's disease. Clin Neurophysiol 129:1320-1332
Du, Guangwei; Lewis, Mechelle M; Sica, Christopher et al. (2018) Distinct progression pattern of susceptibility MRI in the substantia nigra of Parkinson's patients. Mov Disord 33:1423-1431
Liu, Guodong; Sterling, Nicholas W; Kong, Lan et al. (2017) Statins may facilitate Parkinson's disease: Insight gained from a large, national claims database. Mov Disord 32:913-917
Sterling, Nicholas W; Du, Guangwei; Lewis, Mechelle M et al. (2017) Cortical gray and subcortical white matter associations in Parkinson's disease. Neurobiol Aging 49:100-108
Wang, Ming; Li, Zheng; Lee, Eun Young et al. (2017) Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model. BMC Med Res Methodol 17:147

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