Whole Genome Sequence Analysis of Ischemic Stroke in the Women's Health Initiative

摘要 中风是研究不足的疾病之一，尽管它在美国对发病率和死亡率造成了很高的负担。 脑血管闭塞所致的缺血性卒中占80%。缺血性中风是一种 复杂的、多因素疾病，按年龄、性别和卒中亚型具有异质性。相当大的比例 中风风险的原因仍不清楚。到目前为止，中风基因研究的相对较低的成果可能反映了 各亚型的病因和临床表现各不相同。参与的许多研究 纳入的中风GWA几乎没有或几乎没有关于中风特定风险因素或其他心血管疾病的数据 结果，这是理解因果机制和潜在的基因-环境相互作用的关键。 下一代测序(NGS)和多组学综合生物学研究为 我们研究和理解中风的方式。全基因组序列(WGS)数据，包括编码和 功能非编码变体是识别不常见变体的全谱贡献所必需的 中风的风险。目前，在11,000多名WHI参与者中正在通过 NHLBI TOPMed项目，包括4000多例缺血性中风病例。在这里，我们建议应用创新 使用统计方法执行强大的分析，以发现、复制和确定功能特征 缺血性卒中的新基因座(特别是罕见或低频编码和非编码调节变异)(和 其亚型)使用WGS和归因法。将在约4,000例发生的缺血性中风病例中进行发现 以及来自WHI、WGS和TOPMed的超过5,000个控制。单一变种和基于基因的测试将是 根据之前的GWAS和当前的表观基因组和蛋白质组，执行并优先排序约100个基因组区域 分析。复制将通过最先进的基于WGS的外显子组和GWAS在 通过英国生物库获得多达约77,000例额外的缺血性中风病例(和对照)，百万退伍军人 计划，以及SIGN和MetaStroke中风基因组学联盟。以评估其生物学机制。 中风相关的遗传基因座，我们将进一步测试任何新发现的中风基因座与：(1)丰富的 一组心血管危险因素和~40个与动脉粥样硬化、血栓形成、炎症和 可在WHI中获得的激素；(2)一个由184个与神经血管相关的新兴生物标志物组成的新的商业小组 2000年WHI TOPMed样本中的疾病和心血管疾病是根据基因型选择的。使用随意性推理 方法，我们将进行中介分析来确定基因和基因之间的机制关系， 中间生物标记物表型和卒中结局。

ABSTRACT Stroke is among the understudied disorders despite its high burden to morbidity and mortality in the US. Ischemic stroke, which is due to cerebral vessel occlusion, accounts for 80% of cases. Ischemic stroke is a complex, multi-factorial disease, with heterogeneity by age, sex, and stroke subtype. A substantial proportion of stroke risk remains unexplained. The relatively low yield of stroke genetic studies to date may reflect the heterogeneous causes and clinical presentations of the various subtypes. Many of the studies participating in stroke GWAS have included have had little or no data available on stroke-specific risk factors or other CVD outcomes, which are key to understanding causal mechanisms and potential gene–environment interactions. Next generation sequencing (NGS) and multi-omics integrative biology research offer new opportunities in the way we research and understand stroke. Whole genome sequence (WGS) data, including both coding and functional non-coding variants, are required to identify the full spectrum of contributions of uncommon variants to stroke risk. Deep WGS data are currently being generated in over 11,000 WHI participants through the NHLBI TOPMed project, including over 4,000 ischemic stroke cases. Here we propose to apply innovative statistical approaches to perform a well-powered analysis to discover, replicate, and functionally characterize new loci (particularly rare or low frequency coding and non-coding regulatory variants) for ischemic stroke (and its subtypes) using WGS and imputation. Discovery will be performed in ~4,000 incident ischemic stroke cases and over 5,000 controls from WHI with WGS through TOPMed. Single variant and gene-based tests will be performed, prioritizing ~100 genomic regions based on prior GWAS and current epigenomic and proteomic analyses. Replication will be performed through state-of-the art WGS-based exome and GWAS imputation in up to ~77,000 additional ischemic stroke cases (and controls) obtained through UKBiobank, Million Veteran Program, and the SiGN and METASTROKE stroke genomics consortia. To assess the biologic mechanism of stroke-associated genetic loci, we will further test any newly identified stroke loci for association with: (1) a rich set of CVD risk factors and ~40 plasma biomarkers related to atherosclerosis, thrombosis, inflammation, and hormones available in WHI; (2) a new, commercial panel of 184 emerging biomarkers related to neurovascular disease and CVD in 2000 WHI TOPMed samples selected on the basis of genotype. Using casual inference methodology, we will perform mediation analyses to determine mechanistic relationships between genotype, intermediate biomarker phenotype, and stroke outcome.