Integrative Genomics of Stroke

中风综合基因组学

• 批准号: 8321586
• 负责人: Rose Du
• 金额: $ 19.37万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8321586
• 关键词: Adult; Affect; Atherosclerosis; Bioinformatics; Candidate Disease Gene; Cause of Death; Cerebral Infarction; Cerebral Ischemia; Cerebrovascular Disorders; Cerebrum; Cessation of life; Code; Comparative Genomic Analysis; Complex; Computer Simulation; DNA; Databases; Dementia; Disease; Ensure; Environment; Environmental Risk Factor; Feasibility Studies; Gene Expression; Gene Expression Microarray Analysis; Genes; Genetic; Genetic Polymorphism; Genetic Recombination; Genomics; Goals; Haplotypes; Health Care Costs; Hospitals; Human; Hypertension; Inbred Strain; Inbred Strains Mice; Individual; Infarction; Ischemia; Lead; Maps; Methods; Middle Cerebral Artery Occlusion; Modeling; Monozygotic Twinning; Monozygotic twins; Mouse Strains; Mus; Mutation; Pathogenesis; Pathologic; Patients; Phenotype; Predisposition; Public Health; Quantitative Trait Loci; Research; Resolution; Resources; Rodent Model; Sequence Analysis; Single Nucleotide Polymorphism Map; Slide; Stroke; Surveys; Susceptibility Gene; Techniques; Testing; Therapeutic; Time; Tissue-Specific Gene Expression; Twin Studies; United States; Variant; Western Blotting; Woman; base; comparative genomics; computer based statistical methods; cost effective; disability; experience; genetic linkage analysis; genetic resource; genome sequencing; medical schools; middle cerebral artery; mortality; mouse genome; mouse model; network models; protein expression; public health relevance; response; success; tool; trait

DESCRIPTION (provided by applicant): Stroke is the third leading cause of mortality and the leading cause of severe disability worldwide. It is a complex disease that results from many different pathologic conditions including atherosclerosis and hypertension and is therefore affected by multiple genetic and environmental factors. Understanding the genetic basis of stroke will allow us to gain a deeper understanding of the mechanisms behind its pathogenesis. As a complex disease trait, the genetic basis of stroke susceptibility can be studied by using quantitative trait loci analysis to identify regions of DNA that are associated with it. In this proposal, we aim to study the susceptibility to cerebral infarction in the presence of focal cerebral ischemia in mice via an integrative strain survey. We hypothesize that susceptibility to cerebral infarction in the presence of ischemia vary among inbred strains of mice and that this phenotypic variability across strains has a genetic basis. We will perform in silico QTL mapping (haplotype association mapping) for inbred strain phenotypes to identify potential chromosomal regions with stroke susceptibility genes. We will integrate the QTL results with that of microarray gene expression analysis and other bioinformatics tools to narrow down the QTL regions for selection of candidate genes causing stroke susceptibility. The single gene analysis will be extended to incorporate probabilistic gene networks. The candidate genes which affect the vulnerability to stroke as predicted by the QTL mapping can be applied to human studies and ultimately lead to therapeutic and predictive tools for cerebral protection in patients with a variety of cerebrovascular diseases. PUBLIC HEALTH RELEVANCE: Stroke is a major public health burden. This project uses a mouse model of stroke to examine the genetic basis of stroke susceptibility. This will be accomplished via computational and bioinformatics tools together with the emerging genetics resources.

描述（由申请人提供）： 中风是全球第三大死亡原因，也是导致严重残疾的主要原因。它是一种复杂的疾病，由许多不同的病理状况（包括动脉粥样硬化和高血压）引起，因此受到多种遗传和环境因素的影响。了解中风的遗传基础将使我们能够更深入地了解其发病机制背后的机制。作为一种复杂的疾病特征，中风易感性的遗传基础可以通过使用数量性状基因座分析来识别与其相关的 DNA 区域来研究。在本提案中，我们的目的是通过综合应变调查来研究小鼠局灶性脑缺血情况下对脑梗塞的易感性。我们假设，近交系小鼠在存在缺血的情况下对脑梗塞的易感性有所不同，并且不同品系之间的这种表型变异具有遗传基础。我们将对近交系表型进行计算机 QTL 作图（单倍型关联作图），以识别具有中风易感基因的潜在染色体区域。我们将把QTL结果与微阵列基因表达分析和其他生物信息学工具相结合，以缩小QTL区域的范围，从而选择导致中风易感性的候选基因。单基因分析将扩展到纳入概率基因网络。通过QTL作图预测的影响中风易感性的候选基因可应用于人体研究，并最终为多种脑血管疾病患者提供脑保护的治疗和预测工具。 公共卫生相关性： 中风是一项重大的公共卫生负担。该项目使用中风小鼠模型来检查中风易感性的遗传基础。这将通过计算和生物信息学工具以及新兴的遗传资源来实现。