Parkinson’s disease (PD) symptoms and progression vary greatly, making each Parkinson’s experience unique. The goal of this study is to winnow out the most relevant factors influencing individual Parkinson’s experience from a large pool of clinical data. Identifying these factors will help researchers predict how Parkinson’s progression in each case. Also, targeting processes that influence these factors could give clinicians a greater control over the course of disease.
We aim to identify causes of variability in symptoms and disease progression among people living with PD.
We will develop a mathematical way to distill a large set of clinical measurements collected from people with PD over many years into a small number of factors that affect the disease progression. We will also understand how these factors influence the disease. Then, we will determine how genes and biological processes that influence these factors contribute to individual differences in Parkinson’s disease symptoms and disease progression.
Impact on Diagnosis/Treatment of Parkinson’s disease:
The genes and processes that cause Parkinson’s symptoms to vary would lead us to new therapeutic targets. Knowing which individuals are most likely to be affected by these processes would help us predict the disease progression in those individuals.
Next Steps for Development:
Once a small number of factors responsible for the diversity of clinical observations have been identified, our mathematical method could be used on a large scale to evaluate people with Parkinson’s. It would also be useful as a tool for discovery and evaluation of disease-modifying therapies.