Exploring Risk Drugs and Mechanisms in Dystonia: Insights from Pharmacovigilance and Proteogenomics

INTRODUCTION: Dystonia is a movement disorder (MD), which is the third most common MD after Parkinson's disease and essential tremor. Although drugs are one of the main risk factors for dystonia, they are often not fully recognized. This study aims to identify drugs related to dystonia and explore the potential molecular mechanism of drug-induced dystonia. METHODS: We used disproportionality analysis to analyze the data of the FDA Adverse Event Reporting System (FAERS) to identify risk drugs associated with dystonia. The molecular target information of these drugs comes from the DrugBank database. In order to explore the causal relationship, we integrated proteomics data from deCODE research and the UK Biobank Pharma Proteomics Project with the genome-wide association study data from FinnGen to carry out proteome-wide Mendelian randomization (MR) analysis. The application of Bayesian colocalization analysis enhances the reliability of causal inference. In addition, we have built a protein-protein interaction (PPI) network to examine the relationship between dystonia-related proteins and drug target genes. RESULTS: We found that in the reports of 18,286 cases of dystonia, 84 drugs showed continuous positive pharmacovigilance signals. The top 30 drugs are mainly antipsychotics and antidepressants. Metoclopramide has the strongest correlation, followed by prochlorperazine, haloperidol, and ziprasidone. MR and colocalization analysis identified 58 proteins related to susceptibility to dys-tonia, of which 6 were verified in different cohorts. PPI analysis revealed that 21 dystonia-related genes interacted with 22 drug target genes, which are enriched in neuronal signaling pathways, metabolic regulation, and xenobiotic metabolism. DISCUSSION: This integrated framework transcends traditional pharmacovigilance because it combines real-world drug safety data with causal inference of proteogenomics. For the first time, we have constructed a proteogenomic map of drug-induced dystonia. Starting from the drug-disease relationship, we deeply explored the causal mechanisms, such as dopamine-cholinergic imbalance, thus providing mechanism-level insights for drug-induced susceptibility. CONCLUSION: Our study highlights risk drugs for dystonia and their molecular mechanisms and provides evidence for the safer and more individualized use of antipsychotics, antidepressants, and other drugs related to dystonia.