Metabolic Networks
and the Cognitive
Treatment Response
in Parkinson’s Disease


logo_udal_300px

Tracking the Effects of Drug Therapy on Learning, Decision-making,
and the Cognition-related Metabolic Network in the Brain

Team Leaders: David Eidelberg, MD, and Mark Gluck, PhD

Parkinson’s disease patient responds to a test of cognitive capacity (video screen) while a PET scanner creates images of physiological processes in the patient’s brain


Overview and Specific Aims

Cognitive deficits and behavioral abnormalities are well documented clinical manifestations of Parkinson’s disease (PD). The prevalence of dementia in PD patients is at least 25 percent, and some circumscribed disturbances of executive, memory, and visuospatial functions are even more common in nondemented PD patients.

It is particularly disturbing, however, that dopaminergic therapy itself can alter executive functioning and prompt some patients to develop risky behaviors, such as compulsive gambling. Cognitive impairment in PD has been attributed to abnormalities of dopaminergic and/or cholinergic neurotransmission, as well as to the deposition of protein aggregates in the cerebral cortex. It is not known how these factors influence cognitive functioning in PD patients undergoing routine antiparkinsonian therapy.

The overarching aim of project 2 is to define the functional circuitry that mediates the cognitive response to dopaminergic therapy in PD. PET imaging of metabolic activity in the brain clearly shows that some brain regions are more active, and some less active, in PD patients than the corresponding regions are in healthy people. Such imaging, combined with spatial covariance analysis, has recently identified a “PD-related cognitive pattern” (PDCP), which correlates with performance on psychometric tests of learning and executive functioning in multiple PD cohorts [1].

In this project we are undertaking a set of resting state PET imaging studies to examine the regional metabolism, which we hypothesize will substantiate the use of PDCP as an objective biomarker of patients’ psychometric responses to treatment.

Based on our preliminary data, we are testing the hypothesis that changes induced by drug (dopaminergic) therapy in the expression of PDCP correlate with the cognitive responses to medication.

We are further exploring the hypothesis that dopaminergic treatment can either enhance or depress learning and decision-making, depending on whether the feedback on a cognitive task incorporates a reward or a punishment.

Finally, we are investigating how measurements of PDCP at baseline could serve as predictors of the cognitive effects of treatment.

Our studies quantify changes in cognitive functioning and PDCP expression in the following three clinically relevant scenarios: (1) acute levodopa administration (chronically treated PD patients receiving an intravenous infusion of levodopa); (2) daily dopaminergic therapy (with either levodopa/carbidopa or a dopamine agonist in drug-naïve patients) before and three months after the initiation of daily oral medication; and (3) long-term washout (three months of daily dopaminergic therapy followed by a 4-week washout). In the first two scenarios, we perform cognitive testing and FDG PET to quantify PDCP expression in standardized off- and on-state conditions (off and on medication); in the third scenario, these tests are repeated at the end of the washout period. The measurements obtained in these treatment scenarios are used to address the following issues:

Return to Top

    • Aim 1: Ascertain how pharmacological therapy modulates PDCP (the cognitive-related metabolic network expression in PD).
      In Aim 1 we are determining how treatment modifies cognitive metabolic network activity and to what extent these changes will result in cognitive changes (impairment or improvement). We expect to find a strong relation between baseline PDCP and response to dopamine therapy. We would like to investigate not only the immediate effect of the treatment on PDCP, but also its long-term effects. Our recent observations indicate that we will find a sustained suppression of PDCP that parallel the beneficial behavioral effects of therapy. Gaining a better understanding of the long-term effects of the dopamine treatment on the cognitive network is one of the most exciting parts of this project.

 

    • Aim 2: Delineate the effects of dopaminergic treatment on dynamic cognitive processing and associated activation responses.
      In Aim 2 we are examining the changes in behavior and in neural activation that accompany dopaminergic treatment. To understand the fine interplay of these processes, we monitor our subjects as they perform dopamine-sensitive tasks during imaging with functional MRI (fMRI). If our expectations are correct, we will find evidence that dopamine can disrupt the balance between the processing of positive and negative feedbacks. Our results could also help us to identify differences between the therapeutic effect of levodopa and that of dopamine agonists, because their behavioral effects can differ. The longitudinal effect of the drugs over a long term will also be accessible in the washout data. Needless to say, both task performance and the associated activation responses in PD patients will be compared to those in a healthy control cohort. (Studies for Aim 2 are being done in collaboration with the Center for Molecular & Behavioral Neuroscience at the State University of New Jersey at Rutgers–Newark, under the direction of Dr. Mark Gluck.)

 

  • Aim 3: Develop predictive biomarkers of the cognitive-treatment response.
    In Aim 3 we are investigating factors (striatal DAT binding, COMT genotype, cortical protein aggregate load) that might contribute to the individual variability of the imaging data and behavioral findings after dopaminergic treatment. We expect that the results from this effort as well as from the work of the other two aims will provide the basis for a predictive model of the cognitive response to dopaminergic treatment in individual patients, and give us the power to set up a model that could predict the therapeutic effect of a chosen drug in a given individual.

Return to Top

Key Personnel

Principal Investigator and Team Leader: David Eidelberg, MD

Team Leader and Site Principal Investigator: Mark Gluck, PhD, Professor of Neuroscience, Director of the Rutgers Memory Disorders Project at Rutgers University-Newark, New Jersey

Co-Investigator: Vijay Dhawan, PhD

Co-Investigator: Martin Niethammer, MD, PhD

Site Principal Investigator: Steven Frucht, MD, Professor of Neurology, Director of Movement Disorders in the Robert and John M. Bendheim Parkinson and Movement Disorders Center at Mount Sinai Medical Center, New York, NY

Literature Cited

1. Eidelberg D. Metabolic brain networks in neurodegenerative disorders: a functional imaging approach. Trends Neurosci, 2009;32:548-57.

Return to Top