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Funded Studies

Longitudinal Investigation of Statistical Subtype Analysis in Genetic Forms of Parkinson’s Disease

Study Rationale: People with Parkinson’s disease (PD) experience different symptoms and disease course, even individuals with the same genetic form of PD. Because we do not yet understand the range of causes and factors that contribute to PD progression, designing and choosing medications that will work on a particular individual is challenging. In this project, we will conduct rigorous statistical analyses of people with known genetic PD factors, such as mutations in LRRK2 and GBA. Because these individuals are more likely to share similar disease mechanisms, they represent an excellent group in which to study the differences that characterize PD subtypes.

Hypothesis: We hypothesize that focusing on people with PD associated with mutations in LRRK2 and GBA will facilitate identification of subgroups of PD that share similar disease progression and determination of the genetic, clinical and demographic features they share.

Study Design: To identify PD subgroups, we will use data from multiple studies conducted over a period of years on the same cohort of individuals, including LRRK2-associated PD, GBA-associated PD and people whose PD is of unknown cause. Using powerful statistical analyses, we will determine subgroups of individuals with PD that segregate based on how their disease progresses over time. We will then study how these similar groups relate to the genetic, clinical, demographic and biochemical data for each group.

Impact on Diagnosis/Treatment of Parkinson’s disease: Identifying PD subgroups will guide research and facilitate identification of new therapies related to specific etiologies or factors, and it also has the potential to increase likelihood of clinical trial success and enhance clinical decisions. 

Next Steps for Development: Successful completion of this study will provide the scientific and medical community with a better understanding of the drivers of PD progression. Specifically, the results will guide research understanding, clinical trial design and give clinicians a clearer understanding of their patients’ disease course.


  • Rachel Saunders-Pullman MD, MPH, MS

    New York, NY United States

  • Cuiling Wang, PhD

    Bronx, NY United States

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