The lack of biomarkers for Parkinson’s has been a major challenge to developing better treatments. The “Parkinson’s Disease Biomarkers Program” (PDBP) at http://pdbp.ninds.nih.gov is being launched by NINDS which is part of NIH. PDBP supports research efforts to find new technologies and analysis tools to discover biomarkers, to identify and validate biomarkers in patients, and to share biomarker data and resources across the Parkinson’s community. A new online resource will support data sharing.
Biomarkers can include changes in body chemistry or physiology, in genes, how they are regulated, and even subtle changes in a person’s behavior. For example, certain antibodies in the blood can be biomarkers for different types of infection. The range of potential biomarkers for Parkinson’s is vast but there have been promising leads.
So far, nine research teams have been funded through the program. One research program with Dr. Dubois Bowman as Principle Investigator will be conducted at Emory University to develop statistical tools to determine the risk for Parkinson’s. The challenge will be to extract modality-specific and multimodal biomarkers for Parkinson’s from possibly hundreds of thousands of variables combined from multiple neuroimaging modalities, genetic, molecular, and clinical information.
The goal for this specific research study is to identify early risk factors from a massive patient database to include diagnostic information, medication history, and lab results. The researchers plan to use state-of-the-art statistical variable selection to quantify an individual’s risk score to determine their risk for Parkinson’s.
The researchers will use the tools developed to analyze data from subjects in the Kaiser-Permanente database and from the Emory University Morris K. Udall Center of Excellence in Parkinson’s disease. They will also use the tools to examine data collected via the PDBP.
In the private sector, Great Lakes Neuro Technologies (GLNT) with SBIR funding of $283,828 from NINDS, is launching a study to determine the feasibility of using intelligent algorithms to assist with programming deep brain stimulation settings for Parkinson’s disease.
Deep Brain Stimulation (DBS) represents a growing therapy for movement disorders such as Parkinson’s disease. DBS involves implanting an electrode in a specific area of the brain, and then adjusting stimulation settings to a level that alleviates Parkinson’s symptoms without causing side effects.
While the therapy has been shown to be effective for treating Parkinson’s motor symptoms, there is a great disparity in outcomes among implanted patients due to varied postoperative management particularly concerning DBS programming optimization.
The technology will be developed at GLNT at www.glneurotech.com and the clinical feasibility study will be completed at the University of Alabama at Birmingham.
