Funded Studies
Study Rationale:
Individuals with Parkinson’s disease (PD) show elevated markers of inflammation in their brains, cerebrospinal fluid and blood. We think that inflammation drives the worsening of PD by increasing the production of neurotoxic byproducts of metabolism. We discovered that a number of these metabolic byproducts are present at elevated levels in people with Parkinson’s, and that the levels of the markers correlate with the severity of the disease. Now, we will validate the use of these compounds as biomarkers of disease in another group of individuals with PD. Ultimately, we wish to develop biomarkers that can be used to monitor and predict treatment response, and to assess whether these metabolic pathways could serve as potential targets for the treatment of PD.
Hypothesis:
With this study we expect to confirm that neurotoxic metabolic byproducts are linked to the worsening of PD.
Study Design:
We will measure a number of compounds that reflect changes in the metabolism of the amino acid tryptophan using our optimized and well-established method to analyze the blood and cerebrospinal fluid of people with and without PD. We will then use statistical methods to assess the relationship between the concentrations of the compounds and the stage of disease progression. We will also determine if similar amounts of these compounds are produced regardless of whether individuals are taking medications to treat their PD.
Impact on Diagnosis/Treatment of Parkinson’s Disease:
We believe our work will impact both the diagnosis and the treatment of PD. If our biomarkers are sufficiently accurate, they can be used to detect early cases of PD and assess the effectiveness of new treatments. Moreover, drugs that target this metabolic pathway could be tested as novel treatments for Parkinson’s disease.
Next Steps for Development:
Next we will be work with individuals in the early stages of PD or who exhibit signs of the disease but do not yet meet the diagnostic criteria to determine whether our biomarkers will allow us to predict Parkinson’s before clear motor symptoms appear.