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Funded Studies

Predicting the Risk of Parkinson’s Disease with a Mathematical Formula

Study Rationale:
Currently, there is no way to predict whether a person will develop Parkinson's disease (PD) and, if so, when. We have created a mathematical formula for calculating a person's risk of getting Parkinson's. The formula, which we call PREDIGT, is based on the currently known factors that cause PD. The formula has been created, tested and perfected using information from a small group of patients. In this project, we will test and further improve the formula using information from a large group of patients.

A person's risk of developing PD can be calculated using a mathematical formula that combines the individual influences of the five specific risk factors for Parkinson's disease (PR): Environment; DNA (Genetics); Interactions of genetic and environmental factors; Gender; and Time, i.e., PREDIGT. The influence of each of these factors is expressed as a score.

Study Design:
The PREDIGT formula needs to be tested to see how well it determines a person's risk of developing PD. For this, we will use information collected from cohorts, or groups, of people with and without Parkinson's. As a first step, we will partner with The Michael J. Fox Foundation for Parkinson's Research (MJFF) to organize and standardize the information that has been collected from these different cohorts. This will allow us to combine the information and use it as one large set. Using such a large set will help us more effectively determine how well the predictions of the PREDIGT formula matches real data, or how accurate the formula is. At the end of this step, we will improve the PREDIGT formula itself and/or the scores assigned to the risk factors.

Impact on Diagnosis/Treatment of Parkinson's disease:
Currently, PD is diagnosed late in the course of disease, when many brains cells have already been lost. An accurate tool that could help identify a person at risk of Parkinson's would be helpful in many ways. From a clinical research perspective, it would help to identify the people at risk who might benefit more from a preventive course. Also, since some of the risk factors included in this formula can be modified, risk-lowering strategies could be used based on an individual's risk profile.

Next Steps for Development:
The PREDIGT formula will need to be tested and made more accurate. To accomplish this, we will use several groups of individuals who already had PD when they enrolled in the study. The predictive ability of the formula also will be tested in a group of people who were identified as being at-risk but had not developed the disease when they enrolled in the study.


  • Tiago A. Mestre, MD, MSc

    Ottawa Canada

  • Douglas G. Manuel, MD, MSc

    Ottawa Canada

  • Michael G. Schlossmacher, MD

    Ottawa ON Canada

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