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 中风的发生是多因素的，而且人们对此知之甚少。遗传学是一个潜在的强大工具， 疾病病因学，因为它可以突出疾病的生物学机制，并指出改善 预防、治疗和结果。缺血性卒中（IS）的大型全基因组关联研究（GWAS） 人群已经成功地鉴定了具有小效应大小的中风风险相关基因座，然而， 拷贝数变异（CNV）变异在中风易感性中的作用还有待研究， 我们提案的前提。研究CNV揭示了许多其他复杂疾病的重要见解。 此外，我们最近证实，较高的CNV基因组负荷与较差的中风有关 3个月的结果。因此，我们假设，现有的GWAS和外显子组数据的CNV分析将是一个新的研究方向。 一种高度有效和成本有效的方法来识别阐明中风机制的新关联， 治疗目标和结果驱动因素。我们进一步推测，这些分析将确定大的CNVs。 缺血性卒中的效应量，如存在许多单基因、综合征和复杂的 CNV可能有助于解释已知存在于中风中的“缺失遗传性”。 对于这个应用，我们已经收集了超过24，500个表型良好的IS病例，包括IS 亚型和超过43，500个对照，所有这些都在GWAS和外显子组阵列上进行了基因分型， 卒中结局的病例测量。为了评估CNV相关的卒中风险和卒中结局，我们将：1） 使用几种分析方法进行风险发现，以识别与以下风险相关的CNV IS及其亚型，跨越年龄、性别和种族谱; 2）进行风险复制和扩展 为了确定所鉴定的中风相关CNV是否在种族多样性TOPM中复制， Consortia，然后使用现有的TOPMed和GeneStroke Consortia生物标志物数据（例如甲基化， 蛋白质组学、RNA、miRNA等）评估所识别的CNV如何对中风风险产生影响，最后; 3)对我们最近的研究结果进行基于结果的复制和扩展分析，证明了 在这些额外数据集中，CNV负荷与3个月时卒中结局（mRS）之间的关系，以及 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驱动因素。 我们的研究将利用现有病例对照数据集的众多优势，探索 CNV和IS及其亚型之间的关系，以及3个月时的结果，跨性别，年龄和 种族光谱拟议的研究为初级调查员建立了一个新的培训网络， 一个独特的资源，为继续研究遗传基础的IS。小说的成功鉴定 基因、通路和药物靶点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。