Topic: 123-I Ioflupane SPECT Measures of Parkinson Disease Progression in the Parkinson Progression Markers Initiative (PPMI) Trial

Presented by: John Seibyl, MD on June 10, 2013 at 12:30 PM

Abstract: Objective: The objective of this study is to report initial quantitative 123-I Ioflupane SPECT one year disease progression data in the PPMI PD cohort.

Background: The Parkinson’s Progression marker initiative (PPMI) is a multicenter, international, longitudinal study evaluating clinical, biochemical, and imaging measures of Parkinson’s disease (PD) progression.

Methods: In this on-going study, baseline and one year follow-up123-I Ioflupane SPECT scans from 22 imaging centers include 117 Parkinson’s subjects. Data were centrally reconstructed, attenuation corrected, and analyzed with a standardized volume of interest template for extraction of regional count densities in the left and right caudate and putamen. Striatal binding ratios (SBR) were calculated using the occipital lobe reference region. Mean percent changes in striatal composite, ipsilateral putamen, and contralateral putamen SBRs were calculated.

Results: PD subjects at baseline had a mean age of 61.1 y and average disease duration of 8.5 ± 8.2 months. Total UPDRS score was 34.0 ± 12.9 at baseline and 41.1 ± 16.0 at one year follow up. Mean average SBR change encompassing left and right caudate and putamen was -13.3% ± 16.0% (p< 0.0001). Ipsilateral and contralateral striatum showed 13.0% ± 16.5% and 13.5% ± 16.7% change, respectively. No significant differences were noted between ipsilateral and contralateral striatum.

Conclusions: Quantitative DAT 123-I Ioflupane SPECT imaging data acquired at baseline and one year follow-up in PD demonstrate reductions in striatal ratios for both mean striatum and ipsilateral and contralateral putamen. Symmetric rates of striatal signal loss are noted in this preliminary data.

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Abstract:

Title: Relationship between Serum Urate and Clinical Features in Early Parkinson’s Disease: PPMI Baseline Data

Authors: Radu Constantinescu, MD1, Danna Jennings, MD2, Eric D Foster, PhD3, Christopher S Coffey, PhD3, Ken Marek, MD2 and Parkinson’s Progression Marker Initiative. 1Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, NY, United States, 14642; 2Institute for Neurodegenerative Disorders, New Haven, CT, United States, 06510 and 3Clinical Trials Statistical and Data Management Center, University of Iowa, Iowa City, IA, United States, 52240.

Objective: To investigate serum urate (S-urate) levels and their relationship with clinical features at baseline in the early Parkinson’s disease (PD) and healthy control (HC) cohort enrolled in the Parkinson Progression Marker Initiative (PPMI) study.

Background: Previous studies found higher S-urate levels to be associated with a lower risk for developing PD [1] and with a slower rate of disease progression in PD.

Methods: Cross-sectional sub-analysis of PPMI baseline data for the first 507 enrolled subjects (PD=343 [224 M, 119 F], HC=164 [100 M, 64 F]). S-urate was measured by a commercial laboratory (Covance). Cerebrospinal fluid (CSF) a-synuclein was analyzed using a commercially available ELISA. Clinical features were assessed per PPMI protocol. Two sample t-tests were used to assess the difference in mean S-urate between PD and HC subjects, adjusting for gender. Within PD subjects, the association of S-urate with other biomarkers and clinical variables was investigated using univariate linear regressions and correlations.

Results: S-urate levels were not significantly different in PD (M 350.2+72.5, F 258.7±54.0) compared with HC subjects (M 343.7±63.7, F 270.5±50.3). In PD, there were no significant correlations between S-urate levels and clinical features, assessed using the Movement Disorder Society UPDRS part III, the Montreal Cognitive Assessment, and the Geriatric Depression Scale, or with CSF a-synuclein levels.

Conclusions: According to these preliminary results using this simplified means analysis, there was no significant difference in baseline S-urate levels in PD subjects compared with HC. Baseline S-urate levels were not associated with various clinical features at early PD stages in the PPMI population. Additional, more detailed analyses are underway.

[1] Davis JW, Grandinetti A, Waslien CI, Ross GW, White LR, Morens DM. Observations on serum uric acid levels and the risk of idiopathic Parkinson’s disease. American journal of epidemiology. 1996;144:480-4.

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Here is an excerpt from the article:

“This is one of the most important studies going on right now in Parkinson’s disease,” Isaacson said. “Because while we have a lot of medicines to treat the symptoms, we are in desperate need of diagnosing the disease earlier so we can slow, arrest or reverse it. We need to identify the biomarkers in order to do that.”

South Florida has one of the world’s three largest concentrations of Ashkenazi Jews, a group that is more likely to carry the LRRK2 gene than the general population, Isaacson said.

PPMI’s focus on the LRRK2 gene in South Florida was also profiled in local paper The Jewish Journal.

Applying to use PPMI’s specimens is a two-stage process. First, applicants must submit a letter of intent (LOI) and agree to the parameters of use. The BRC reviews LOI’s and provides feedback for those it selects to submit a full proposal. This process is meant to help applicants design the most robust possible use of the biospecimens. Standard evaluation criteria is used to vet every application.

According to Mark Frasier, PhD, Vice President of Research Programs at MJFF, scientists are eagerly awaiting the opportunity to begin taking advantage of this incredible resource in biomarker discovery. Now that recruitment is complete, and we’ll soon have baseline samples from all of PPMI’s participants, he explains, there will be a greater opportunity for researchers to submit projects using PPMI’s sample inventory.  Even more interesting is that more and more volunteers have now provided samples at six and 12 month intervals, which will allow for longitudinal validation studies looking into changes in the specimens.

Scientists need to have some preliminary data to be able to build on when requesting samples, he says. PPMI is a biomarker validation study, so it’s critical that applications to use specimens demonstrate that preliminary data supports hypotheses that can be further solidified through testing in a larger population.

Already, two scientists have been granted access to the samples. Clemens Scherzer, MD, of Harvard University is analyzing RNA samples in PPMI. The University of Pennsylvania’s Alice Chen-Plotkin, MD, is looking at serum samples in PPMI to find proteins she’s already identified, and which potentially, could be implicated in Parkinson’s disease.  To learn more about these analyses, visit the new Ongoing Analysis section of the site.

An inventory of PPMI biospecimens available through the PPMI biorepository is maintained on the PPMI Web site. Comprehensive clinical and imaging data collected from PPMI research participants is also available to enable researchers to develop studies that might correlate biospecimen analysis with relevant subject data.

Learn more about the inventory of more than 2,700 samples collected through the end of 2012.

Hyposmia: PPMI seeks 20,000 people to take a smell survey and then be smell tested using the UPSIT to determine their ability to smell. Those scored as being less than the 10^th percentile will be invited to consent for the study.

RBD: Individuals with a diagnosis of RBD through a polysomnogram will be recruited through sleep centers at select PPMI sites and invited to consent for the study.

LRRK2: People who are 60 or older who do not have PD and know they have a LRRK2 mutation will be invited to participate. Genetic Counseling and testing will be available to those who are able to travel to the Boca Raton area and who are of Eastern European (Ashkenazi) Jewish descent.

To get more information, click here or review the updated protocol.

“Having everyone enrolled means that we will soon have a complete baseline dataset,” says Chris Coffey, PhD, director of the Clinical Trials Statistical and Data Management Center at the University of Iowa. “This makes it possible for scientists to begin to do cross-sectional analysis of everyone that has signed up to participate in PPMI.  That’s powerful.”

In addition to demographic profiles of individuals who have participated, those accessing PPMI data also have access to the results of a variety of assessments, including the Montreal Cognitive Assessment (MOCA) and the University of Pennsylvania Smell Identification Test (UPSIT). They can also access data culled from participants’ DaTSCAN images and view a full inventory of available biospecimens (read more).

One resource in the database which is particularly useful, and innovative, explains Mark Frasier, PhD, vice president of research programs at The Michael J. Fox Foundation (MJFF), is the “Visualize Data” function, which allows scientists to compare data across populations with imaging data with assessment results.

The “Visualize Data” function at work in the PPMI Database

“There are a ton of options for researchers to pursue with this function, depending on their research interest,” says Frasier. “The visual aspect makes it easy to make correlations quickly, and easily.”

In the coming months, the PPMI Steering Committee plans to present at various meetings and publish a paper that will reference the baseline data as a description of the 600+ participants enrolled in PPMI.  The first presentation of the baseline data has been accepted for the Movement Disorders Society International Congress in June.  Coffey says that a series of follow-up papers from each of the study’s nine cores is planned to follow.  These papers will go into further depth into specific measures germane to each of the Cores.

“It will mean a lot to have this complete dataset at our fingertips to be able to publish a description of the complete cohort,” says Coffey. “When this happens, the hypothetical will become concrete, which will make the data an easier sell to scientists who may want to use it. Then, we will really begin to see real progress from PPMI.”

Coffey says that he expects “the floodgates to open” in terms of available, and useful data, over the course of the next six months, as more and more of the study’s volunteers will have reached their one-year visit. After subjects are enrolled for one year, their data and samples really support longitudinal analyses, which could begin to home in on whether or not levels of certain potential biomarkers, such as alpha-synuclein in CSF, change over time.

“Reaching the end of recruitment is a big accomplishment,” he says. “But from a data perspective we are just getting started. I’m looking forward to diving into this so much more moving forward.”

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