Funded Studies
Objective/Rationale:
The cells and tissues of the body can “communicate” with one another using small secreted proteins that can be found in the blood. There are several hundred of these cellular communication factors in the blood and the levels of many of them change in response to many things, including disease. We believe that there is a pattern of these changes that will constitute a “biological fingerprint” of Parkinson’s disease (PD).
Project Description:
Blood samples provided through our collaboration with Dr. Bernard Ravina at the University of Rochester have been collected from 25 patients with PD and 25 healthy people. Using antibody microarrays, we will measure the relative abundance of more than 500 cellular communication factors and proteins previously identified as important in neurodegenerative diseases from each sample. The results from the healthy and disease groups will then be compared to identify those proteins that show differences. Based on these differences, we hope to identify a “biological fingerprint” specific to Parkinson’s disease.
Relevance to Diagnosis/Treatment of Parkinson’s Disease:
A blood test for PD is needed for improved patient management and in the development and monitoring of new therapies. Currently, the best methods of diagnosis for PD involve multiple neurological tests of motor and cognitive skills and may include expensive neurological imaging scans. A blood test would provide physicians with a more reliable, cost-effective, and objective diagnosis tool. The first step in developing such a blood test is to identify a unique “biological fingerprint” of the disease.
Anticipated Outcome:
This study is designed to determine whether there is a “biological fingerprint” of PD in blood samples by comparing the relative amounts of more than 500 molecules from the blood of PD patients and healthy individuals. If successful, further studies would be required to develop and validate the “fingerprint” as an indicator of Parkinson’s disease.
Final Outcome
With support from the Michael J. Fox Foundation and in collaboration with Bernard Ravina, MD of the University of Rochester, we tested a set of 63 plasma samples (25 Parkinson’s disease—PD; 25 healthy controls—HC; and 13 other motor control disorders-- OMCD) using a Luminex based panel of 189 protein analytes (Rules-Based Medicine DiscoveryMAP). Utilizing a variety of statistical tools including SAM (Significance Analysis Microarrays) and PAM (Predictive Analysis Micorarrays) we identified a number of markers showing significant concentration differences between classes, and predictive models that discriminate between PD and HC with 72% accuracy (cross validation).