Association between 23 drugs and Parkinson's disease: A two-sample Mendelian randomization study

Area of Science:

• Neuroscience
• Genetics
• Pharmacology

Background:

• Parkinson's disease (PD) is a prevalent neurodegenerative disorder with limited treatment options for disease modification.
• Exploring novel therapeutic targets and drugs is crucial for managing PD progression.
• Mendelian randomization (MR) offers a robust method to investigate causal relationships between drug targets and diseases.

Purpose of the Study:

• To investigate the potential causal relationship between 23 approved drugs and the risk of developing Parkinson's disease.
• To identify specific drug classes that may influence PD pathogenesis.
• To provide evidence for repurposing existing medications for PD prevention or treatment.

Main Methods:

• Utilized two-sample Mendelian randomization (MR) analysis.
• Employed Genome-Wide Association Study (GWAS) data for 23 drugs from the UK Biobank and PD from FinnGen.
• Selected Single-Nucleotide Polymorphisms (SNPs) as instrumental variables and applied various statistical methods, including inverse variance weighting (IVW), weighted median, and MR-Egger, alongside sensitivity analyses (MR-PRESSO, Cochran's Q test).

Main Results:

• Salicylates (e.g., aspirin) showed a statistically significant negative causal association with PD risk (OR=0.73, P=0.039).
• Antithrombotic agents (e.g., warfarin, aspirin) also demonstrated a significant negative causal relationship with PD risk (OR=0.70, P=0.027).
• No significant causal associations were found for the remaining 21 drugs investigated.

Conclusions:

• Salicylates and antithrombotic agents may play a protective role in reducing the risk of Parkinson's disease.
• These findings suggest a potential therapeutic benefit of these drug classes in the context of PD.
• This study opens new avenues for future drug discovery and repositioning strategies for Parkinson's disease.