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Searching Brain Scan Data for Patterns of Activity Associated with Parkinson's Disease

Study Rationale:
There is a pressing need for Parkinson's disease (PD) biomarkers -- objective measures of disease -- that will enable early and accurate diagnosis and allow to track disease progression and therapeutic improvement. We have developed a new mathematical method to characterize PD-related brain networks. This method is based on a mathematical analysis of data collected via resting state functional magnetic resonance imaging (fMRI), a brain scan that measures changes in blood flow reflective of brain activity in individuals at rest, i.e., awake but not engages in a specific activity. This approach has enabled us to identify two distinct PD-related brain networks -- patterns of brain activity -- by analyzing and comparing scans from people with and without PD. We aim to confirm our findings and further examine these disease-related networks using the data from the Parkinson's Progression Markers Initiative (PPMI), a landmark study to find Parkinson's disease biomarkers.

Hypothesis:
We hypothesize that the presence of these brain activity patterns discriminates people with and without PD and correlates with clinical measures of motor and cognitive dysfunction and with the loss of dopamine transporter (the protein on brain cells that is reduced in PD). It also serves as a way to track disease progression.

Study Design:
We aim to apply our innovative method to resting state fMRI data from PPMI to identify and measure disease-related networks in PD. We will search for correlation between these brain activity patterns and motor and cognitive ability as well as for the extent of dopamine transporter loss. The PPMI data will be used to identify new brain patterns and to verify brain patterns already discovered. Because we are interested in tracking the progression of PD, we will include in the study a large number of people with at least two fMRI scans in the PPMI dataset.

Impact on Diagnosis/Treatment of Parkinson's disease:
With the resting state fMRI data available in PPMI, we can establish a way to use the PD-related brain networks to objectively diagnose PD and track its progression. Hence, these networks can be used as biomarkers in clinical trials.

Next Steps for Development:
Next, we aim to discover specific roles brain regions play within the PD-related networks. This information will help identify the key regions within the disease networks and target these regions in developing new therapeutic approaches.


Researchers

  • An Vo, PhD

    Manhasset, NY United States


  • David Eidelberg, MD

    Manhasset, NY United States


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