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Updated: Sep 20, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
GBA1 in Parkinson's disease: past, present and future
Ziv Gan-Or1,2,3,4
1Department of Neurology and Neurosurgery, McGill University, Montreal, QC, H3A 2B4, Canada.
Abstract:
GBA1 variants represent some of the most important genetic risk factors for Parkinson's disease (PD), present in a substantial proportion of patients across populations. This review provides a comprehensive overview of the field, tracing the historical path from the first description of Gaucher disease (GD) in 1882 to the recognition of GBA1 as a key contributor to PD risk, and highlighting major scientific and translational milestones along the way. We summarize current understanding of the biological mechanisms linking GBA1 to PD, including both loss-of-function and gain-of-function hypotheses, and discuss how reduced glucocerebrosidase (GCase) activity may lead to α-synuclein accumulation and neurodegeneration. Remaining gaps in knowledge, especially regarding downstream lipidomic effects and cell-type-specific mechanisms, are emphasized as key priorities for future research. This review also examines clinical and translational advances, including the development of GCase-targeted therapies such as small molecules, chaperones, substrate reduction therapies, and gene-based approaches. We discuss outcomes from recent and ongoing clinical trials, highlighting both promising strategies and notable failures that inform our evolving understanding of disease biology. In addition, we address the heterogeneity of PD and the importance of stratifying patients based on genetic background. Finally, we outline critical challenges and future directions, including the need for precision medicine approaches based on variant-specific mechanisms, improved biomarkers to define true GBA1-associated PD, and optimized clinical trial design. We propose that coordinated, open-science efforts and large-scale collaborative frameworks will be essential to accelerate discovery and translate mechanistic insights into effective disease-modifying therapies.
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