Study Rationale: Mutations in the GBA1 gene, which encodes glucocerebrocidase (GCase), is the most prevalent risk factor for Parkinson’s disease (PD). The resulting deficit in GCase activity leads to accumulation of the cellular fats glucosylceramide and glucosylsphingosine. However, how these fats contribute to PD is not fully understood. Our research is aimed at understanding these complex essential fats and their upstream and downstream metabolic products, collectively referred as glycosphingolipids. In particular, we will explore the structural heterogeneity, local concentrations and distributions of the glycosphingolipids in different regions in the PD brain.
Hypothesis: Our hypothesis is that alterations in the metabolism of selective glycosphingolipids in specific brain regions contributes to early PD onset and accelerated progression rates.
Study Design: We will use a high-resolution, two-dimensional approach to measure precise content and localization of brain glycosphingolipids in tissues from people with PD and Gaucher disease. We will determine whether certain glycosphingolipids stand out in specific brain regions in diseased tissues and conduct deep-learning computational approaches to better understand how these region-selective glycosphingolipid levels can be restored to a healthy state. In this way, we intend to get a more complete picture of the how alterations in glycosphingolipids contribute to PD and in what ways we can restore lipid imbalances for PD therapies.
Impact on Diagnosis/Treatment of Parkinson’s disease: Results in support of our hypothesis will shed new light on the role of glycosphingolipid metabolism and brain localization in PD pathology. Understanding aberrant glycosphingolipid in specific brain regions in PD will lay the foundation for future studies identifying new biomarkers and therapeutic avenues for PD treatment.
Next Steps for Development: Characterizing new potential targets and biomarkers could be undertaken to identify more selective targets and diagnostic measurements for PD. Identifying a more translatable preclinical PD model could open up new strategies to accelerate the therapeutics of PD.