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Drug Repurposing for Parkinson’s Disease: A Large-Scale Multi-Cohort Study
Output Details
Description
Background Progress in Parkinson's disease (PD) is hampered by two critical obstacles: the lack of disease-modifying drugs and the difficulty of identify individuals at early, prodromal disease stages for clinical trials. Methods We conducted a retrospective, multi-cohort study using data from the Mass General Brigham (MGB) Biobank for discovery and the Accelerating Medicines Partnership Parkinson's Disease (AMP-PD) program for replication. Logistic regression was used to estimate the associations between drug exposure and the subsequent risk of PD. Sensitivity analyses addressed dose effects and reverse causality. Longitudinal changes in cognitive and motor function were analyzed using linear mixed-effects models. We also mapped drug target genes to cell types to explore potential therapeutic targets for PD. Findings We included a total of 44,388 individuals in the discovery cohort (15,032 cases and 29,356 controls) and 4010 individuals in the validation cohort (2,351 cases and 1659 controls). In this study, 18 drugs were replicated, with five associated with reduced PD risk and 13 with increased risk. Notably, salbutamol (discovery: 0.84, 95% CI 0.80-0.88; replication: 0.70, 95% CI 0.49-0.99) and losartan prescriptions (discovery: 0.90, 95% CI 0.84-0.96; replication: 0.67, 95% CI 0.51-0.88) were associated with reduced risk of PD with lag times of 0-5 years. Moreover, in longitudinal analyses of patients with PD over 10 years, cognitive function over time was improved in patients taking losartan compared to patients not on this drug. Solifenacin was associated with less severe motor impairment. Furthermore, eight differentially expressed drug target genes were identified in PD, including significant downregulation of CFTR in oligodendrocytes and NR3C2 in microglia. Interpretation Salbutamol and losartan show significant associations with PD risk and can be further tested mechanistically and clinically. Drugs for non-motor symptoms show promise for identifying putative prodromal PD at scale using data science. CFTR and NR3C2 represent compelling druggable target candidates for therapeutic development in PD and warrant further functional validation.
Identifier (DOI)
10.1101/2025.05.20.25327943