Funded Studies
Study Rationale: We have generated a computer-based model that simulates alterations in molecular mechanisms associated with Parkinson’s disease (PD) genes. This model suggested that, in sporadic forms of PD, mediators of the inflammatory response of the immune-system (in particular, pro-inflammatory molecules called cytokines) might be altered. In this project, we will use large biochemical and genetics datasets to validate this prediction and determine how these immune system mediators can be used to discriminate samples collected from individuals with PD from those of healthy volunteers. Such a biomarker would provide a simple diagnostic tool for PD.
Hypothesis: We hypothesize that we will be able to validate our earlier prediction regarding pro-inflammatory cytokines being altered in sporadic PD, and that evaluation of pro-inflammatory cytokines in biological samples will allow us to discriminate between PD and control samples.
Study Design: To prove our hypothesis, we need access to large numbers of samples from people with PD and healthy volunteers. Large datasets of this type have already been generated. Therefore, instead of investing money in generating new datasets, we will make use of existing data, accessible via resources such as the MJFF-promoted PPMI repository. We will access biochemical and genetics data from hundreds of samples and extract information on the immune-system mediators. We will compare these data between cases and controls and train the computer with a process called “machine-learning” to discriminate PD from control samples.
Impact on Diagnosis/Treatment of Parkinson’s disease: There is no simple, early diagnostic tool for PD, and the disease is diagnosed when the brain is already irreversibly damaged. Therefore, any new, early diagnostic strategy will improve disease management and facilitate drug discovery, as individuals enrolled in clinical trials could be better stratified, improving trials’ design and power.
Next Steps for Development: We are evaluating our model using a preexisting, large dataset. Next, we will move on to the more expensive and demanding recruitment of a new cohort of individuals with PD to validate our predictions and translate our new diagnostic approach into the clinical setting.