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Funded Studies

Analytic Models in Biomarker Development

Non-invasive tests or biomarkers may aid clinical trials if they help to identify a subgroup of individuals at high risk of Parkinson's disease (PD), or if they are able to objectively assess changes in individuals with PD, and those at higher risk for PD. Such markers include smell, walking assessment, writing measures, memory tests, mood tests, assessment of sleep, and evaluation of the structures at the base of the brain involved in PD. However the statistics of measure of some of the bedside biomarkers, particularly in relation to LRRK2, are not well understood. In this proposal, we will expand on the analytic methods used to lead to a better understanding of these markers.

Project Description: 
This grant will focus on a group of novel non-invasive, low-cost biomarkers, which can be performed at the bedside. It will include analysis of data collected from the Ashkenazi Jewish LRRK2 Consortium from Beth Israel Medical Center (New York), Columbia University and the University of Tel Aviv, and an NIH-supported project to Beth Israel, as well as from Dr. Eduardo Tolosa’s Group in Barcelona. We propose to perform specific advanced statistical tests and analyses to better understand these measures.

Relevance to Diagnosis/Treatment of Parkinson’s Disease:
Biomarker development is pivotal to trials for medications that target the LRRK2 protein. With the current FDA approval of non-selective LRRK2 kinase inhibitors, and development of more selective kinase inhibitors underway, exciting opportunities for prevention of PD lie in the identification of agents for individuals who harbor LRRK2 mutations but have not yet developed PD. Biomarkers are essential in this process.

Anticipated Outcome: 
Through this work, we plan to better understand non-invasive markers of this genetic subtype of PD. We will use advanced statistical methods to develop profiles of these markers.


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