CNV And Stroke (CaNVAS)

CNV 和中风 (CaVAS)

• 批准号: 10308412
• 负责人: JOHN W. COLE
• 金额: $ 50.73万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10308412
• 关键词: Address; Adult; Affect; African; Age; Bioinformatics; Biological; Biological Markers; Blood; Blood Pressure; Cardiovascular system; Cause of Death; Coagulation Process; Complex; Copy Number Polymorphism; Data; Data Set; Detection; Disease; Drug Targeting; Ethnic Origin; Etiology; European; Functional disorder; Genes; Genetic; Genetic study; Genotype; Heritability; Inflammation; Interdisciplinary Study; International; Ischemic Stroke; Leadership; London; Manuals; Measures; Messenger RNA; Methodology; Methylation; MicroRNAs; Morbidity - disease rate; Outcome; Pathway interactions; Phenotype; Population; Positioning Attribute; Predisposition; Prevention; Proteomics; RNA; Research; Research Personnel; Resources; Risk; Risk Factors; Role; Stroke; Stroke prevention; Susceptibility Gene; Sweden; Syndrome; Training; Trans-Omics for Precision Medicine; Treatment outcome; United States; Variant; Woman; base; case control; causal variant; circulating biomarkers; cost; cost efficient; disability; ethnic diversity; exome; experience; genome wide association study; genome-wide; improved; insight; men; metabolomics; mortality; novel; programs; sex; stroke outcome; stroke risk; tool

Ischemic stroke is the 4th leading cause of death in the U.S. and a major cause of disability. The etiology of stroke is multifactorial and poorly understood. Genetics is a potentially powerful tool for better understanding disease etiology as it can highlight biological mechanisms underlying disease and point the way to improved prevention, treatment, and outcome. Large genome-wide association studies (GWAS) of ischemic stroke (IS) populations have been successful at identifying stroke-risk-associated loci with small effect sizes, however, the role of copy number variation (CNV) variation in stroke susceptibility has yet to be explored, and is the premise of our proposal. Studying CNV has revealed important insights for numerous other complex diseases. Further, we recently demonstrated that a higher CNV burden genome-wide is associated with poorer stroke outcome at 3 months. We therefore hypothesize that CNV analyses of existing GWAS and exome data will be a highly effective and cost-efficient methodology to identify novel associations illuminating stroke mechanisms, treatment targets, and outcome drivers. We further speculate that these analyses will identify CNVs of large effect size in ischemic stroke, as suggested by the existence of numerous monogenic, syndromic and complex diseases associated with CNV and that CNV may help explain the ‘missing heritability’ known to exist in stroke. For this application, we have already assembled over 24,500 well-phenotyped IS cases, including IS subtypes, and over 43,500 controls, all with readily available genotyping on GWAS and exome arrays, with case measures of stroke outcome. To evaluate CNV-associated stroke risk and stroke outcome we will: 1) perform Risk Discovery using several analytic approaches to identify CNVs that are associated with the risk of IS and its subtypes, across the age-, sex- and ethnicity-spectrums; 2) perform Risk Replication and Extension to determine whether the identified stroke-associated CNVs replicate in the ethnically diverse TOPMed Consortia and then using existing TOPMed and GeneStroke Consortium biomarker data (e.g. methylation, proteomic, RNA, miRNA, etc.) evaluate how the identified CNVs exert their effects on stroke risk, and lastly; 3) perform outcome-based Replication and Extension analyses of our recent findings demonstrating an inverse relationship between CNV burden and stroke outcome at 3 months (mRS) in these additional datasets, and then determine the key CNV drivers responsible for these associations using existing biomarker data. Our study will leverage the numerous advantages of using existing case-control data sets, exploring the relationships between CNV and IS and its subtypes, and outcome at 3 months, across the sex-, age- and ethnicity-spectrums. The proposed study creates a new training network for junior investigators and establishes a unique resource for the continued study of the genetic basis of IS. The successful identification of novel genes, pathways and drug targets has the potential to transform our understanding of the stroke pathophysiology leading to more effective prevention, treatment and outcome strategies.

缺血性中风是美国第四大死亡原因，也是残疾的主要原因。病因 中风是多因素的，并且理解不佳。遗传学是一种可以更好地理解的潜在强大工具 疾病的病因可以强调疾病潜在的生物学机制，并指向改善的道路 预防，治疗和结果。全基因组的大型关联研究（GWAS）的缺血性中风（IS） 人群已经成功地识别与效应大小相关的中风风险相关基因座，但是 拷贝数变化（CNV）变化在中风易感性中的作用尚未探索，并且是 我们的提议的前提。研究CNV已经揭示了许多其他复杂疾病的重要见解。 此外，我们最近证明了较高的CNV Burnen基因组与中风较差有关 3个月的结果。因此，我们假设CNV对现有GWAS和外显图的分析将是 一种高效且具有成本效益的方法，以识别新型关联照明中风机制， 治疗目标和结果驱动因素。我们进一步推测这些分析将识别大型的CNV 缺血性中风的效应大小，如存在许多单基因，综合症和复杂的存在所暗示的那样 与CNV相关的疾病，CNV可能有助于解释中风中已知的“缺失遗传力”。 对于此应用程序，我们已经组装了24,500多个精心型的IS案例，包括IS 亚型和超过43,500个控件，所有对GWA和外显阵列上都有可用的基因分型，带有 中风结果的案例度量。为了评估CNV相关的中风风险和中风结果，我们将：1） 使用几种分析方法进行风险发现，以识别与风险相关的CNV IS及其亚型，跨年龄，性别和种族谱； 2）执行风险复制和扩展 确定已鉴定的中风相关的CNV是否在族裔多样性中复制 财团，然后使用现有的顶级和Genestroke Consortium生物标志物数据（例如甲基化， 蛋白质组学，RNA，miRNA等。 3）对我们最近发现的基于结果的复制和扩展分析，证明了反向 在这些其他数据集中，CNV Burnen与3个月（MRS）的中风结果之间的关系， 然后使用现有的生物标志物数据确定负责这些关联的关键CNV驱动程序。 我们的研究将利用使用现有的病例对照数据集的众多优势，探索 CNV与IS及其亚型之间的关系，以及在性别，年龄和年龄的3个月的结果 种族谱。拟议的研究为初级调查人员创建了一个新的培训网络，并建立了 继续研究IS遗传基础的独特资源。新颖的成功识别 基因，途径和药物靶标有可能改变我们对中风的理解 病理生理学导致更有效的预防，治疗和结果策略。