Genome-wide association studies (GWASs) have identified more than 20 genetic loci as risk predictors associated with stroke. However, these studies were generally performed for single-trait and failed to consider the pleiotropic effects of these risk genes among the multiple risk factors for stroke. In this study, we applied a novel metaCCA method followed by gene-based VEGAS2 analysis to identify the risk genes for stroke that may overlap between seven correlated risk factors (including atrial fibrillation, hypertension, coronary artery disease, heart failure, diabetes, body mass index, and total cholesterol level) by integrating seven corresponding GWAS data. We detected 20 potential pleiotropic genes that may be associated with multiple risk factors of stroke. Furthermore, using gene-to-trait pathway analysis, we suggested six potential risk genes (FUT8, GMIP, PLA2G6, PDE3A, SMARCA4, SKAPT) that may affect ischemic or hemorrhage stroke through multiple intermediate factors such as MAPK family. These findings provide novel insight into the genetic determinants contributing to the concurrent development of biological conditions that may influence stroke susceptibility, and also indicate some potential therapeutic targets that can be further studied for the prevention of cerebrovascular disease.

全基因组关联研究 (GWAS) 已确定 20 多个基因位点作为与中风相关的风险预测因子。然而，这些研究通常是针对单一性状进行的，没有考虑这些风险基因在卒中的多个危险因素中的多效性。在这项研究中，我们应用了一种新的 metaCCA 方法，然后是基于基因的 VEGAS2 分析来识别可能在七个相关风险因素（包括心房颤动、高血压、冠状动脉疾病、心力衰竭、糖尿病、体重）之间重叠的中风风险基因。指数和总胆固醇水平）通过整合七个相应的 GWAS 数据。我们检测到 20 个可能与卒中的多种危险因素相关的潜在多效性基因。此外，使用基因到性状通路分析，FUT8、GMIP、PLA2G6、PDE3A、SMARCA4、SKAPT）可能通过MAPK家族等多种中间因素影响缺血性或出血性中风。这些发现提供了对可能影响中风易感性的生物条件同时发展的遗传决定因素的新见解，并且还表明了一些可以进一步研究以预防脑血管疾病的潜在治疗靶点。