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Usage Information

Direct targeting of wild-type glucocerebrosidase by antipsychotic quetiapine improves pathogenic phenotypes in Parkinson’s disease models
Lena F. Burbulla, … , Patrik Brundin, Dimitri Krainc
Lena F. Burbulla, … , Patrik Brundin, Dimitri Krainc
Published October 8, 2021
Citation Information: JCI Insight. 2021;6(19):e148649. https://doi.org/10.1172/jci.insight.148649.
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Research Article Neuroscience

Direct targeting of wild-type glucocerebrosidase by antipsychotic quetiapine improves pathogenic phenotypes in Parkinson’s disease models

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Abstract

Current treatments for Parkinson’s disease (PD) provide only symptomatic relief, with no disease-modifying therapies identified to date. Repurposing FDA-approved drugs to treat PD could significantly shorten the time needed for and reduce the costs of drug development compared with conventional approaches. We developed an efficient strategy to screen for modulators of β-glucocerebrosidase (GCase), a lysosomal enzyme that exhibits decreased activity in patients with PD, leading to accumulation of the substrate glucosylceramide and oxidized dopamine and α-synuclein, which contribute to PD pathogenesis. Using a GCase fluorescent probe and affinity-based fluorescence polarization assay, we screened 1280 structurally diverse, bioactive, and cell-permeable FDA-approved drugs and found that the antipsychotic quetiapine bound GCase with high affinity. Moreover, quetiapine treatment of induced pluripotent stem cell–derived (iPSC-derived) dopaminergic neurons from patients carrying mutations in GBA1 or LRRK2 led to increased wild-type GCase protein levels and activity and partially lowered accumulation of oxidized dopamine, glucosylceramide, and α-synuclein. Similarly, quetiapine led to activation of wild-type GCase and reduction of α-synuclein in a GBA mutant mouse model (Gba1D409V/+ mice). Together, these results suggest that repurposing quetiapine as a modulator of GCase may be beneficial for patients with PD exhibiting decreased GCase activity.

Authors

Lena F. Burbulla, Jianbin Zheng, Pingping Song, Weilan Jiang, Michaela E. Johnson, Patrik Brundin, Dimitri Krainc

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Usage data is cumulative from December 2022 through December 2023.

Usage JCI PMC
Text version 466 281
PDF 68 69
Figure 93 5
Supplemental data 20 7
Citation downloads 18 0
Totals 665 362
Total Views 1,027

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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