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The Morris K. Udall Center for Parkinson’s Disease Research at The Feinstein Institute for Medical Research

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Director: David Eidelberg, M.D.

Title: Functional Brain Networks: A Novel Approach to Address Clinical Challenges in PD

Website: http://feinsteinneuroscience.org/udall-center

Public Health Statement

The Udall Center at The Feinstein Institute for Medical Research employs rigorously validated Parkinson’s disease (PD)-related networks to address vital issues that impact heavily on the care of today’s PD patients.
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.

Central Theme

The Udall Center at The Feinstein Institute for Medical Research focuses on a unique patient-oriented approach using validated functional brain networks to develop novel approaches/solutions to basic problems of diagnosis and management confronted each day by Parkinson’s disease (PD) patients, clinicians and caretakers. Findings from Center projects will shed light on the relationship between functional brain organization in the resting state (PET, rest state fMRI) and neural activation during cognitive processing (event-related fMRI), and provide unique information on how both interact to shape performance in PD patients and healthy people. 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.

Center Structure

Six cores support the research activities of three Projects: the Administrative, Clinical, Cognitive and Behavioral, Statistics and Data Management, Imaging, and Training and Education cores.  The activities of each core are independent. That said, these activities are highly coordinated across the Clinical, Cognitive and Behavioral, and Imaging Cores in that the data output of these cores are entered into a database created in the Statistics and Data Management core.

The specialized Udall Center mechanism allows Feinstein investigators to collaborate with scientific leaders in important translational research areas. For instance, the involvement of Dr. Angela Cenci-Nilsson at Lund University (Sweden) offers a true translational collaboration in the study of the role of the microvasculature in the pathogenesis of levodopa-induced dyskinesias (LID). Professor Cenci-Nilsson’s unique expertise provides the basis for a unique collaboration spanning the gap between experimental animal studies and human investigation in Parkinson’s disease.  Similarly, investigators in Dr. Eidelberg’s laboratory have developed a productive working relationship with Dr. Mark Gluck and his team at Rutgers University (Newark, NJ) in the area of cognitive processing in Parkinson’s disease. Over the past five years, this collaboration has developed further during the course of the fMRI/behavioral studies of probabilistic category learning and neuro-economic decision making.  Moreover, studies conducted at the sleep disorders centers at North Shore – LIJ Health System, Stanford University, and the University of Pennsylvania offer insights into the network abnormalities that appear in individuals at risk for PD prior to the onset of motor symptoms.  

Recent Significant Advances

Project 1: Microvascular Changes in PD: Relationship to Levodopa-Induced Dyskinesia

  1. An interim analysis of the Feinstein Udall Center data confirms that significant uncoupling of cerebral blood flow and metabolism is induced by levodopa in key network regions. Uncoupling was substantially greater in PD subjects with LID relative to their counterparts with stable clinical responses to levodopa. Further analysis linked this effect to an exaggeration of local vasomotor responses to dopamine in the putamen of LID subjects.
  2. Results from the experimental rodent model (Dr. Cenci) indicate that antidyskinetic drugs may improve LID by inhibiting the excessive increases in local CBF that accompany levodopa administration.

In aggregate, data from both human subjects and rodents support the proposed hypotheses. If validated, the results of these studies may lead to new therapeutic strategies for LID and related side-effects of PD treatment.

Project 2: Metabolic Networks and the Cognitive Treatment Response in Parkinson's Disease

We have previously characterized a specific metabolic network abnormality associated with cognitive dysfunction in non-demented PD subjects. In recent studies from the Udall Center at the Feinstein Institute, we have validated this PD cognition-related covariance pattern (PDCP) in an independent patient population. In addition to correlating consistently with performance on tests of executive function, PDCP expression related specifically to changes in dopaminergic input to the caudate nucleus (rather than the putamen). These findings create the basis for developing circuit-specific interventions for cognitive dysfunction in PD patients, with the PDCP modulation as a quantitative biomarker of treatment efficacy.

Project 3: Early Differential Diagnosis of Parkinsonism with Metabolic Imaging and Pattern Analysis

  1. To study prodromal PD, Feinstein Udall Center investigators (with collaborators at University of Pennsylvania and Stanford) are conducting a network imaging study of individuals with idiopathic REM behavior disorder (RBD). Preliminary analysis of the data from the first 12 subjects revealed significant network-level abnormalities in this population, consistent with prodromal disease. Apart from showing that the characteristic PD motor-related metabolic pattern (PDRP) is expressed in idiopathic RBD, we found that individual network values in these subjects correlated with the likelihood of subsequent phenoconversion. If verified, these data will support the use of the PDRP as a preclinical disease biomarker.
  2. Our findings thus far demonstrate the utility of automated network-based classification methods in enhancing the accuracy of clinical differential diagnosis. The data also point to the preferential advantage of this approach for individuals with early stage parkinsonism of uncertain cause. If validated, network-based classification algorithms are likely to have a role in selecting suitable participants for clinical trials of new PD therapies.

Resources Available

Animal Models: Rat model of L-dopa-induced dyskinesia (LID) at Lund University.

Other Resources: Clinical ratings (off-state UPDRS), a standardized neuropsychological testing battery, off-state FDG PET data, off-state, routine anatomical MRI, DNA banking, and brain donation/banking.

Plans for the Coming Year

Project 1: (1) We plan to continue increasing our recruitment efforts for Aims 1 and 2 of the project. We will update the interim analyses on the newly collected data, particularly for local vasoreactivity in drug-naïve patients; (2) In the coming year, we will establish a microPET method to measure blood flow and glucose metabolism in rats utilizing the same multi-tracer approach as already performed in the human PET studies. This task is currently being carried out at the Feinstein Institute.

Project 2: (1) We will focus on recruitment in this project as well as perform interim analyses on the data and present the results in the next annual progress report; (2) We also plan to improve the sequence learning tasks and collect behavioral and imaging data with the modified tasks in PD patients and healthy controls for interim analysis.

Project 3: (1) We expect to complete recruitment for Aim 2 and will continue to enroll subjects for Aims 1 and 3. (2) We will further develop the automated diagnostic approach by adding a cortical basal ganglionic degeneration (CBGD) pattern to the classification algorithm. We will then apply the updated algorithm to the subjects enrolled in this Project. (3) Network analysis will be performed on REM behavior disorder (RBD) and healthy control subjects to identify potential metabolic covariance patterns relating specifically to prodromal disease states. As more RBD subjects return for follow-up imaging and sufficient longitudinal scan data become available, we will search for specific "preclinical" progression-related metabolic topographies. Such patterns may be particularly valuable as biomarkers in disease modification trials targeting individuals with early/preclinical disease.

Select Recent Publications

Parkinson's disease cognitive network correlates with caudate dopamine.
Niethammer M, Tang CC, Ma Y, Mattis PJ, Ko JH, Dhawan V, Eidelberg D.
Neuroimage. 2013 Sep;78:204-9. PMID: 23578575

Identification of disease-related spatial covariance patterns using neuroimaging data.
Spetsieris P, Ma Y, Peng S, Ko JH, Dhawan V, Tang CC,
J Vis Exp. 2013 Jun 26;(76). PMID: 23851955 

Parkinson's disease: increased motor network activity in the absence of movement.
Ko JH, Mure H, Tang CC, Ma Y, Dhawan V, Spetsieris P, Eidelberg D.
J Neurosci. 2013 Mar 6;33(10):4540-9..PMID: 23467370 Free PMC Article

Dissociating the cognitive effects of levodopa versus dopamine agonists in a neurocomputational model of learning in Parkinson's disease.
Moustafa AA, Herzallah MM, Gluck MA.
Neurodegener Dis. 2013;11(2):102-11. PMID: 23128796

Additional Information

Collaboration with Other Udall Centers

  1. We continue to work closely with the University of Pennsylvania Udall Center in our study of network-based diagnosis utilizing PET and resting state fMRI imaging techniques. We are also continuing our ongoing collaboration with the UPenn Udall team to determine whether baseline Parkinson’s disease cognitive pattern expression levels accurately predict subsequent cognitive decline in PD patients.
  2. Dr. Eidelberg is collaborating with Dr. Grabowski at the Pacific Northwest Udall Center (PANUC) on applications of resting state fMRI images as a means of evaluating cognitive dysfunction in PD patients.  A separate collaborative effort is underway between the PANUC Clinical (Dr. Leverenz) and Genetics-Biomarker-Neuropathology Cores (Dr. Zabetian) and the Feinstein Behavioral Core (Dr. Mattis) to investigate genetic factors associated with PD dementia. As part of the project, blood samples from Feinstein Udall subjects are routinely sent to the University of Washington for genetic analysis.
  3. Another collaboration has developed with the Northwestern University Udall Center (Dr. Darren Gittelman) to share PD-related network constructs, as well as computational routines developed at the Feinstein Udall Center. This collaboration will facilitate the implementation of the disease patterns on fMRI platforms.

PD Research Collaborations

  1. Canada: We are continuing our collaboration with Drs. Jacques Montplaisir, Ron Postuma and Jean-François Gagnon at the Center for Advanced Research in Sleep Medicine at the Hôpital du Sacré-Coeur de Montréal, Canada. These internationally acclaimed investigators in the REM behavior disorder (RBD) field are known for their intensive clinical follow-up assessments of their subjects. Using baseline perfusion scans obtained in the Montreal RBD cohort, and network measurements conducted blind to long-term clinical outcome (i.e., phenoconversion status), we have confirmed the preliminary Udall findings (Project 3) of prodromal network abnormalities in RBD subjects. The Montreal data additionally were used to generate the hypothesis that baseline network expression levels predict later phenoconversion to PD in these individuals (Holtbrend et al., 2013; manuscript submitted). This hypothesis is currently being tested prospectively in RBD subjects followed at both sites.
  2. Netherlands: Our ongoing collaboration with Dr. K.L. Leenders at the University of Groningen, Netherlands continues. Metabolic brain networks associated with PD and related disorders are being optimized in subjects studied at the Feinstein Udall Center and validated in independent Dutch testing cohorts. The goal is to develop an international imaging database to assist in the differential diagnosis of these conditions.
  3. China: Dr. Yilong Ma, a biophysicist and co-leader of the Imaging Core at the Feinstein Udall Center was awarded an NIH grant (R01 NS083490-01, “A Multiracial MRI/PET Study of Parkinsonism: Diagnosis and Disease Progression”) as part of a US-China program for biomedical collaborative research. Dr. Ma will be working with Dr. Chuantao Zuo at the Huashan PET Center of Fudan University in Shanghai. The study will support collaborative network validation efforts in Chinese populations with the goal of optimizing network constructs obtained using PET and fMRI techniques.
  4. Other: The Feinstein Udall Center is continuing to work with investigators world-wide who are interested in applying network methods for the clinical investigation of neurodegenerative disorders. We are continuing our ongoing collaborations with imaging groups in Cologne, Germany (Dr. Carsten Eggers), New Delhi, India (Dr. Madhavi Tripathi), and Seoul, South Korea (Dr. Chung Lee).

Community Outreach

  1. Dr. Martin Niethammer (Co-Investigator) and Toni Fitzpatrick (Coordinator) attended a local American Parkinson Disease Association's "Paws for Parkinson's" fundraiser at Belmont State Park in Bethpage, NY on October 6, 2012. They spoke with patients and family members about the current Udall projects and obtained contact information of those who wished to participate. The Feinstein Institute was a sponsor of the event.
  2. The Feinstein Udall Center had a featured article in the March 2013 issue of "Focus on Research", a quarterly, external newsletter that is distributed to 65,000 residents in the following counties of New York: New York, Nassau, Suffolk, Queens, and Kings. [http://www.northshorelij.com/NSLIJ/News+Publications, http://www.feinsteininstitute.org/Feinstein/Focus+on+Research].
  3. Feinstein Institute Leadership organized a Merinoff Symposium, which was held on May 1, 2013. The topic of the symposium was to discuss the future of telemedicine in the management of Parkinson’s disease.

Last updated October 30, 2013