Genetic risk impacts stroke mortality and pathogenesis in patients with ischemic stroke: cohort study of BioBank Japan
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Background
Previous multi-ancestry genome-wide association studies (GWAS) of stroke reported 32 stroke risk loci in the MEGASTROKE study. Most studies on the genetic risk score (GRS) of stroke have reported a predominance in the European general population. We aimed to explore the association among GRS, clinical characteristics, and mortality in patients with ischemic stroke registered in the BioBank Japan (BBJ) database.
Methods
This is a cohort study of BBJ participants. The project participants were recruited between June 2003 and March 2018. We conducted a GWAS for stroke in 19,702 Japanese patients with ischemic stroke (controls, n=159,610). GRS was generated using 29 stroke risk single nucleotide polymorphisms (SNPs) from 32 stroke-related loci identified in the MEGASTROKE. A multivariate logistic regression model was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for comorbidities and stroke etiology across the GRS. The Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% CIs for mortality associated with GRS.
Results
The ORs for atrial fibrillation were significantly higher in those at Intermediate GRS [20–80 th percentile of GRS; ORs 1.59 (1.25-1.90)] and High GRS [top 20 th percentile of GRS; ORs 2.12 (1.69-2.67)] after a full adjustment than in those at Low GRS (bottom 20 th percentile of GRS). Regarding stroke etiology, the ORs for cardioembolism were significantly higher in those at Intermediate GRS [ORs 1.31 (1.04-1.61)] and High GRS [ORs 1.44 (1.13-1.89)] than in those at Low GRS. During a median follow-up of 10.0 years, the risk of stroke mortality was significantly higher in those at High GRS [HRs 1.27 (1.04-1.56)] than in those at Low GRS in a fully adjusted model.
Conclusions
In Japanese, a higher GRS was significantly associated with atrial fibrillation, cardioembolism, and stroke mortality. Our findings suggest that the GRS may predict the risk of stroke mortality and provide insights into the pathogenesis of stroke.