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.

在美国，缺血性中风是第四大致死原因，也是致残的主要原因。病因学 卒中的病因是多因素的，人们对此知之甚少。遗传学是一种潜在的强大工具，可以更好地理解 疾病病因学，因为它可以突出疾病背后的生物机制，并指明改进的方向 预防、治疗和结果。缺血性卒中(IS)的大型全基因组关联研究 然而，人群已经成功地识别了效应大小较小的中风风险相关基因， 拷贝数变异(CNV)在卒中易感性中的作用还有待研究，这是 这是我们提案的前提。对CNV的研究揭示了对许多其他复杂疾病的重要见解。 此外，我们最近证明，全基因组范围内CNV负荷较高与较差的中风相关。 3个月后的结果。因此，我们假设对现有GWAS和Exome数据的CNV分析将是 一种高效且具有成本效益的方法，以确定启发中风机制的新关联， 治疗目标和结果驱动因素。我们进一步推测，这些分析将识别出大型CNV 缺血性卒中的效应大小--从众多单基因、综合征和复合体的存在来看 与CNV和CNV相关的疾病可能有助于解释已知存在于中风中的“缺失遗传性”。 对于这一应用程序，我们已经组装了超过24,500个表型良好的IS案例，包括IS 亚型，超过43,500个对照，所有这些都在GWAs和外显子组阵列上容易获得的基因分型， 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果，我们将：1) 使用多种分析方法执行风险发现，以确定与以下风险相关的CNV 不同年龄、性别和种族的IS及其亚型；2)进行风险复制和扩展 为了确定已识别的与中风相关的CNV是否在种族多样化的TOPMed中复制 然后使用现有的TOPMed和GeneStroke联盟生物标记物数据(例如甲基化， 蛋白质组、RNA、miRNA等)评估已识别的CNV如何在中风风险中发挥作用，最后； 3)对我们最近的发现执行基于结果的复制和扩展分析，证明 在这些额外的数据集中，CNV负荷与3个月的卒中预后(MRS)之间的关系，以及 然后使用现有的生物标记物数据确定对这些关联负责的关键CNV驱动因素。 我们的研究将利用使用现有病例对照数据集的众多优势，探索 不同性别、年龄和性别的CNV和IS及其亚型之间的关系以及3个月后的预后 种族--光谱。拟议的研究为初级调查员创建了一个新的培训网络，并建立了 为继续研究IS的遗传基础提供了独特的资源。小说的成功识别 基因、途径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。