Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL

使用综合基因组学来识别和表征肺气肿相关的 eQTL

• 批准号: 8762578
• 负责人: Peter Castaldi
• 金额: $ 87.32万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8762578
• 关键词: Affect; Alleles; Architecture; Area; Binding; Bioinformatics; Biological Assay; Biological Process; Biology; Blood specimen; Cause of Death; Cell Line; Cells; Characteristics; Chromosomes; Chronic Obstructive Airway Disease; Clinical; Collaborations; Complex; Computer Simulation; Data; Development; Disease; Disease susceptibility; Epithelial Cells; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Genetic Variation; Genomics; Goals; Health; Image; Individual; Interdisciplinary Study; Investigation; Lead; Link; Lung; Measures; Meta-Analysis; Molecular Biology; Mutation; Nucleic Acid Regulatory Sequences; Pattern; Phenotype; Predisposition; Protein Isoforms; Public Health; Pulmonary Emphysema; Quantitative Trait Loci; RNA Sequences; Recording of previous events; Reporter; Research; Risk; Sampling; Scanning; Signal Transduction; Smoker; Specificity; Syndrome; Tissues; Update; Variant; Whole Blood; Work; X-Ray Computed Tomography; base; density; epigenomics; genetic association; genetic risk factor; genetic variant; genome wide association study; genome-wide; improved; innovation; lung acinus structure; lymphoblastoid cell line; novel; novel strategies; public health relevance; research study; small airways disease; standard measure; transcription factor; transcriptome sequencing

DESCRIPTION (provided by applicant): Chronic obstructive pulmonary disease (COPD) is a major public health burden, and it is the third leading cause of death in the US. Genome-wide association studies (GWAS) in COPD have successfully identified disease-associated genetic loci, but most of the genetic susceptibility to this disease has yet to be explained. The translatin of GWAS discoveries into new disease-modifying treatments requires the continued discovery and functional characterization of GWAS-identified loci. It is clear that many GWAS loci are gene expression quantitative trait loci (i.e. eQTLs) and that fine modulation of gene expression patterns is a key component of the genetic architecture of complex diseases, including COPD. COPD is a complex clinical syndrome that may consist of distinct biological processes. One fruitful approach to this complexity is to identify COPD-associated phenotypes, such as emphysema, that have their own strong GWAS signals and distinct biology. Emphysema is a heritable phenotype. However, few studies have been able to generate emphysema phenotypes in samples large enough for adequately-powered GWAS, and existing quantitative emphysema measures have known limitations. Using a novel, approach for emphysema quantification from lung computed tomography scans based on local histograms, we have generated detailed quantitative emphysema measures on over 9,000 subjects in the COPDGene Study that are more informative than traditional emphysema measures. This proposal is based on two hypotheses - 1) GWAS of local histogram emphysema patterns will identify novel emphysema-associated genetic variants and 2) genetic control of gene expression is an important mechanism by which genetic variation impacts the emphysema phenotype. To investigate these hypotheses, we propose the following specific aims. In Aim 1, updated LHE phenotypes will be generated in the COPDGene and ECLIPSE studies, and GWAS will be performed to identify emphysema-associated genetic variants. In Aim 2, eQTL analysis using RNA-Seq data will be performed in bronchial epithelial cells (BECs) and whole blood samples from COPDGene subjects with a range of emphysema. These eQTL and GWAS results will be integrated to identify novel emphysema-associated loci and link these loci to the genes through which they exert their phenotypic effects. In Aim 3a, we will identify genomic regions that are likely to be causally-linked to emphysema susceptibility through an innovative approach integrating GWAS, eQTL, and functional regulatory data from the ENCODE and Roadmap Epigenomics projects. In Aim 3b, the functional relevance of these genomic regions will be examined in cell-based functional assays in BEC cell lines. This work builds on strong preliminary data, and the research team has a history of close collaboration and multidisciplinary expertise in areas critical for this project.

描述（由申请人提供）：慢性阻塞性肺疾病（COPD）是一个主要的公共卫生负担，是美国第三大死因。慢性阻塞性肺病的全基因组关联研究（GWAS）已成功识别出与疾病相关的基因位点，但对该疾病的大部分遗传易感性仍有待解释。将 GWAS 发现转化为新的疾病缓解疗法需要持续发现 GWAS 识别的位点并对其进行功能表征。很明显，许多 GWAS 基因座是基因表达数量性状基因座（即 eQTL），基因表达模式的精细调节是包括 COPD 在内的复杂疾病遗传结构的关键组成部分。慢性阻塞性肺病是一种复杂的临床综合征，可能由不同的生物过程组成。解决这种复杂性的一种有效方法是识别与 COPD 相关的表型，例如肺气肿，它们有自己强大的 GWAS 信号和独特的生物学特性。肺气肿是一种可遗传的表型。然而，很少有研究能够在足够大的样本中生成肺气肿表型，以进行充分动力的 GWAS，并且现有的定量肺气肿测量方法具有已知的局限性。使用基于局部直方图的肺部计算机断层扫描进行肺气肿量化的新颖方法，我们在 COPDGene 研究中对 9,000 多名受试者生成了详细的定量肺气肿测量值，这些测量值比传统的肺气肿测量值更丰富。该提议基于两个假设 - 1）局部直方图肺气肿模式的 GWAS 将识别新的肺气肿相关遗传变异，2）基因表达的遗传控制是遗传变异影响肺气肿表型的重要机制。为了研究这些假设，我们提出以下具体目标。在目标 1 中，将在 COPDGene 和 ECLIPSE 研究中生成更新的 LHE 表型，并将进行 GWAS 来识别与肺气肿相关的遗传变异。在目标 2 中，将使用 RNA-Seq 数据对患有一系列肺气肿的 COPDGene 受试者的支气管上皮细胞 (BEC) 和全血样本进行 eQTL 分析。这些 eQTL 和 GWAS 结果将被整合，以识别新的肺气肿相关基因座，并将这些基因座与它们发挥表型效应的基因联系起来。在目标 3a 中，我们将通过整合 GWAS、eQTL 以及来自 ENCODE 和 Roadmap Epigenomics 项目的功能调控数据的创新方法，识别可能与肺气肿易感性存在因果关系的基因组区域。在目标 3b 中，将在 BEC 细胞系中通过基于细胞的功能测定来检查这些基因组区域的功能相关性。这项工作建立在强有力的初步数据的基础上，研究团队在该项目的关键领域有着密切合作的历史和多学科的专业知识。