Funded Studies
Study Rationale:
The symptoms and course of Parkinson’s disease (PD) show remarkable variation from one person to another, indicating differences in the underlying disease process that may also be important for treatment response. In previous studies, we and others have shown that genetics contribute to these variations. By considering the effect of a combination of gene variants, it is possible to generate risk scores that reflect the genetic vulnerability to different molecular aspects of the disease process in individuals. This project will take advantage of such genetic risk profiles to link disease mechanisms to clinical outcomes in PD.
Hypothesis:
We hypothesize that genetic risk scores for major disease pathways in PD are associated with specific symptoms and measures of disease progression.
Study Design:
We will calculate polygenic risk scores related to eight major disease pathways in PD and analyze the association between these scores and clinical outcomes such as motor progression, cognitive progression and REM sleep behavior disorder. We will perform initial analyses in a large collection of clinical datasets generated in a traditional research context and then compare our findings with patient-reported data from Fox Insight. Finally, we will generate online tools to make our method and results available to the scientific community for further research.
Impact on Diagnosis/Treatment of Parkinson’s Disease:
The project will lead to the development of tools that could be used to define disease subgroups and improve selection of patients for clinical trials and ultimately personalized therapies. Demonstrating that patient-reported data can be used effectively for genetic profiling would encourage further large-scale online data collection.
Next Steps for Development:
Aiming towards clinical application of mechanism-specific genetic risk profiling, it will be important to assess how risk scores relate to treatment response. Clinical trials for novel disease-modifying therapies should explore the potential of genetic risk profiling to target specific subgroups of participants based on their predominant molecular disease mechanisms.