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: 8913766
• 负责人: Peter Castaldi
• 金额: $ 86.88万
• 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/8913766
• 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; Genomic Segment; 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）是主要的公共卫生负担，这是美国第三大死亡原因。 COPD中全基因组关联研究（GWAS）已成功鉴定出与疾病相关的遗传基因座，但是大多数对这种疾病的遗传敏感性尚未解释。 GWAS发现为新的疾病改良治疗的翻译需要持续的发现和功能表征。显然，许多GWAS基因座是基因表达定量性状基因座（即EQTL），并且基因表达模式的精细调制是包括COPD在内的复杂疾病遗传结构的关键组成部分。 COPD是一种复杂的临床综合征，可能包括不同的生物学过程。这种复杂性的一种富有成果的方法是确定具有强大的GWAS信号和独特的生物学的COPD相关表型，例如肺气肿。肺气肿是一种可遗传的表型。但是，很少有研究能够在足够大的足够大的样品中产生肺气肿表型，并且现有的定量肺气肿测量具有已知的局限性。使用基于局部直方图的肺计算层析成像扫描中的新颖的肺气肿定量方法，我们在COPDGENE研究中对9,000多名受试者进行了详细的定量肺气肿测量，这些测量比传统的肺气肿测量更具信息性。该建议基于两个假设-1）局部直方图肺气肿模式的GWA将鉴定出新型肺气肿相关的遗传变异和2）基因表达的遗传控制是一种重要机制，遗传变异会影响孔隙症表型。为了研究这些假设，我们提出了以下特定目标。在AIM 1中，将在Copdgene和Eclipse研究中产生更新的LHE表型，并将进行GWAS以鉴定与肺气肿相关的遗传变异。在AIM 2中，将在支气管上皮细胞（BEC）中进行使用RNA-Seq数据的EQTL分析，以及来自具有一系列肺气肿范围的COPDGENE受试者的全血样品。这些EQTL和GWAS结果将集成以识别与肺气肿相关的新基因座，并将这些基因座与它们发挥表型作用的基因联系起来。在AIM 3A中，我们将通过一种创新的方法来确定可能与GWAS，EQTL和功能调节数据相结合的基因组区域，这些方法可能与eNcode和Roadmap表观基因组学项目相结合。在AIM 3B中，这些基因组区域的功能相关性将在BEC细胞系的基于细胞的功能测定中进行检查。这项工作以强大的初步数据为基础，研究团队在对该项目至关重要的领域中具有密切合作和多学科专业知识的历史。