BACKGROUND: Intracranial aneurysm (IA) is a common neurovascular disorder; rupture causes aneurysmal subarachnoid hemorrhage with high mortality. Despite available interventions, effective preventative therapies are lacking. We aimed to identify novel genetic determinants of IA and aneurysmal subarachnoid hemorrhage to improve risk prediction and nominate hypothesis-generating therapeutic candidates for future evaluation. METHODS: We conducted a multiancestry genome-wide association study and statistical fine-mapping study across European and East Asian cohorts and applied rigorous multiancestry and multitrait meta-analyses to identify IA-associated loci. Utilizing the Multi-Ancestry Sum of Single Effects model tool for fine mapping, we fine-mapped ancestry-specific and shared signals across loci. To derive a credible set of candidate genes, we integrated data from functional mapping and annotation, polygenic priority score, multivariate set-based association test (combined), transcriptome-wide association study, and summary data–based Mendelian randomization, focusing on genes identified by at least 4 methods. Machine learning algorithms developed diagnostic models, and a polygenic score model was evaluated using the UK Biobank data set. RESULTS: We identified 3 novel IA-associated loci and observed significant genetic correlations between IA and systemic phenotypes. We prioritized a credible set of 40 candidate genes, including GPX1 and NPC1 among the top-ranked candidates, and an expression-based K-nearest neighbor classifier achieved an area under the curve of 0.89 for case-control discrimination between IA cases and controls. We evaluated an IA polygenic score in the UK Biobank evaluation sample, which yielded an area under the curve of 0.83 (95% CI, 0.81–0.84); this performance reflects discrimination in this evaluation setting and warrants further validation in additional independent cohorts before clinical implementation. We observed nominal evidence of interaction between polygenic score and smoking ( P =1.09×10 −2 ), suggesting an interplay between genetic susceptibility and a modifiable lifestyle factor. Computational drug repurposing nominated 32 drug classes, including JAK inhibitors and dopamine receptor antagonists, as hypothesis-generating candidates for future experimental evaluation. CONCLUSIONS: These findings refine IA/aneurysmal subarachnoid hemorrhage-associated loci, prioritize credible candidate genes for functional follow-up, and provide hypothesis-generating translational leads that may inform future studies, pending validation in independent cohorts and experimental models.
Maimaiti et al. (2026) studied this question.