Integrated analysis for drug repositioning in migraine using genetic evidence and claims database

Front Big Data. 2025 Nov 21;8:1677167. doi: 10.3389/fdata.2025.1677167. eCollection 2025.

ABSTRACT

INTRODUCTION: Migraine is a prevalent neurological disorder with a substantial socioeconomic burden, underscoring the need for continued identification of therapeutic targets. Given the significant role of genetic factors in migraine pathogenesis, a genetic-based approach is considered effective for identifying potential therapeutic targets. This study aimed to identify candidate treatments for migraine by integrating genome-wide association study (GWAS) data, perturbagen profiles, and a large-scale claims database.

METHODS: We used published GWAS data to impute disease-specific gene expression profiles using a transcriptome-wide association study approach. The imputed gene signatures were cross-referenced with perturbagen signatures from the LINCS Connectivity Map to identify candidate compounds capable of reversing the disease-associated gene expression. A real-world claims database was subsequently utilized to assess the clinical efficacy of the identified perturbagens on acute migraine, employing a cohort study design and mixed-effects log-linear models with the frequency of prescribed acute migraine medications as the outcome.

RESULTS: Eighteen approved drugs were identified as candidate therapeutics based on the perturbagen profiles. Real-world analysis using the claims database demonstrated potential inhibitory effects of metformin (relative risk [RR]: 0.81; 95% confidence interval [CI]: 0.77-0.86), statins (RR: 0.94; 95% CI: 0.92-0.96), thiazolidines (RR: 0.84; 95% CI: 0.73-0.97), and angiotensin receptor neprilysin inhibitors (RR: 0.69; 95% CI: 0.61-0.77) on migraine attacks.

CONCLUSION: This multidisciplinary approach highlights a cost-effective framework for drug repositioning for migraine treatment by integrating genetic, pharmacological, and real-world clinical database.

PMID:41355896 | PMC:PMC12678156 | DOI:10.3389/fdata.2025.1677167