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

摘要 卒中是研究不足的疾病之一，尽管其在美国的发病率和死亡率较高。 由于脑血管闭塞而导致的缺血性中风占病例的80%。缺血性中风是一种 复杂的多因素疾病，具有年龄、性别和卒中亚型的异质性。相当大比例 中风风险仍然无法解释。迄今为止，中风遗传学研究的相对低产量可能反映了 各种亚型的异质性原因和临床表现。参与的许多研究 GWAS纳入的中风数据很少或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）和多组学整合生物学研究为生物技术的发展提供了新的机遇。 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 功能性非编码变体，需要鉴定不常见变体的全部贡献谱 中风风险。目前正在通过WHI的11，000多名参与者生成深度WGS数据， NHLBI TOPMed项目，包括4,000多例缺血性卒中病例。在这里，我们建议采用创新的 采用统计方法进行有效分析，以发现、复制和功能表征 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体）（和 其亚型）使用WGS和插补。将在约4，000例缺血性卒中病例中进行发现 以及超过5，000个来自WHI和WGS的控件。单一变异和基于基因的测试将是 根据先前的GWAS和当前的表观基因组学和蛋白质组学， 分析。将通过最先进的基于WGS的外显子组和GWAS插补进行复制， 通过UKBiobank，Million Veteran获得的多达约77，000例额外缺血性卒中病例（和对照） 计划，以及SIGN和METASTRKE中风基因组学联盟。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的关联：（1）丰富的 一组CVD风险因素和约40种与动脉粥样硬化、血栓形成、炎症和 WHI中可用的激素;（2）一个新的，商业化的184种与神经血管相关的生物标志物 疾病和心血管疾病在2000年WHI TOPM的样本选择的基因型的基础上。使用因果推理 方法，我们将进行中介分析，以确定基因型， 中间生物标志物表型和中风结果。

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.