Genomic and Transcriptomic Analysis of Emphysema and Subclinical ILD

肺气肿和亚临床 ILD 的基因组和转录组分析

• 批准号: 9076283
• 负责人: ANI Wang MANICHAIKUL
• 金额: $ 44.4万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-15 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9076283
• 关键词: Address; Affect; African American; Air; Alveolar; Atherosclerosis; Biopsy; Bronchodilator Agents; Carbohydrates; Catabolism; Cause of Death; Chinese People; Chronic; Chronic Obstructive Airway Disease; Collection; Complex; DNA; Data; Data Set; Diagnosis; Disease; Disease Progression; Epidemiology; Ethnic Origin; Ethnic group; Etiology; European; Face; Fibrosis; Framingham Heart Study; Gene Combinations; Gene Expression; General Population; Genes; Genetic; Genetic Variation; Genomics; Glycoproteins; Hamman-Rich syndrome; Hispanics; Human; Individual; Inflammation; Injury; Interstitial Lung Diseases; Investigation; Joints; Lead; Link; Lung; Lung Transplantation; Lung diseases; Methods; Modeling; Molecular; Molecular Profiling; Nature; Non-Malignant; Oxygen Therapy Care; Participant; Pathogenesis; Pathology; Pathway interactions; Patients; Pharmaceutical Preparations; Phenotype; Prevention; Pulmonary Emphysema; Pulmonary Pathology; Race; Reporting; Research; Research Design; Research Personnel; SNRPF gene; Scanning; Site; Smoking History; Steroids; Structure of parenchyma of lung; System; Testing; Time; Tissue Banking; Tissue Banks; Tissue Sample; Tissues; Training; United States; Universities; Validation; Variant; Whole Blood; X-Ray Computed Tomography; alveolar destruction; base; gene interaction; genetic epidemiology; genetic profiling; genetic variant; genome wide association study; genome-wide; genome-wide analysis; improved; interest; novel; population based; public health relevance; research study; smoking cessation; success; trait; transcriptome; transcriptome sequencing; transcriptomics; whole genome

 DESCRIPTION (provided by applicant): Together, pulmonary emphysema and chronic obstructive pulmonary disease (COPD) are the third leading cause of death in the United States. Although often considered one disease, emphysema on computed tomography (CT) represents a distinct entity that is absent in some patients with COPD and present in some without COPD. The interstitial lung diseases (ILDs) are a class of non-infectious, non-malignant lung diseases characterized by alveolar injury, inflammation, and fibrosis. There are currently few medications available to stop the progression of these diseases, reflecting a limited understanding of the underlying molecular mechanisms. We recently completed genome-wide association studies (GWASs) of percent emphysema and subclinical ILD on CT scan in ~7,600 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). The overall success of our GWAS efforts in identifying SNPs at genome-wide significance in or near SNRPF and PPT2 for percent emphysema, and ANRIL and D21S2088E for subclinical ILD traits reflect the notable quality of the pulmonary phenotypes in MESA. Still, GWAS approaches continue to face multiple limitations including (a) large multiple testing burden from considering millions of SNPs, and (b) lack of functional annotation to connect identified SNPs with specific genes. To address these and other limitations, we propose to apply a new gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual's genetic profile and correlates the "imputed" gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. The framework of PrediXcan opens the possibility to "impute" tissue-specific genome-wide gene expression levels for the MESA participants, thereby creating a population-based data set that combines both high quality phenotypes for percent emphysema on CT scan with whole blood and lung-specific gene expression levels. We expect that reduced multiple testing burden and increased functional relevance of gene expression traits obtained through PrediXcan will allow us to identify novel genes and pathways related to emphysema and ILD. Therefore, we propose to carry out transcriptome-wide studies of gene expression predictors for percent emphysema (Aim 1a) and subclinical ILD (Aim 1b) traits in MESA. We further use a model selection framework to identify combinations of genes underlying pathogenesis of emphysema and subclinical ILD in the general population (Aim 2). We have assembled a highly collaborative and interdisciplinary team of investigators representing expertise in statistical genetics (Manichaikul and Im), genetic epidemiology (Manichaikul and Rich), pulmonary epidemiology (Lederer and Barr), lung pathology (Borczuk) and systems genetics (Farber). Completion of the proposed Aims would result in improved understanding of predicted gene expression traits in relation to emphysema and ILD, leading to improved targeted prevention and treatment of these diseases.

 描述（由申请人提供）：肺气肿和慢性阻塞性肺病（COPD）是美国第三大死亡原因。虽然通常被认为是一种疾病，但计算机断层扫描（CT）显示的肺气肿是一种不同的实体，在一些COPD患者中不存在，而在一些非COPD患者中存在。间质性肺病（ILD）是一类以肺泡损伤、炎症和纤维化为特征的非感染性、非恶性肺部疾病。目前几乎没有药物可以阻止这些疾病的进展，这反映了对潜在分子机制的理解有限。我们最近在多种族动脉粥样硬化研究（梅萨）的约7,600名参与者中完成了CT扫描肺气肿和亚临床ILD百分比的全基因组关联研究（GWAS）。我们的GWAS在识别SNRPF和PPT 2中或其附近的全基因组显著性SNP（用于肺气肿百分比）以及ANRIL和D21 S2088 E（用于亚临床ILD性状）方面的总体成功反映了梅萨中肺表型的显著质量。尽管如此，GWAS方法仍然面临多重限制，包括（a）考虑数百万个SNP的大量多重测试负担， 和（B）缺乏将鉴定的SNP与特定基因连接的功能注释。为了解决这些和其他限制，我们建议应用一种新的基于基因的关联方法，称为PrediXcan，直接测试遗传变异影响表型的分子机制。该方法估计由个体的遗传特征决定的基因表达的组分，并将“估算的”基因表达与正在研究的表型相关联，以鉴定参与表型病因学的基因。PrediXcan的框架为梅萨参与者提供了“估算”组织特异性全基因组基因表达水平的可能性，从而创建了一个基于人群的数据集，该数据集将CT扫描上肺气肿百分比的高质量表型与全血和肺特异性基因表达水平相结合。我们期望通过PrediXcan获得的减少的多重检测负担和增加的基因表达特征的功能相关性将使我们能够鉴定与肺气肿和ILD相关的新基因和途径。因此，我们建议在梅萨中对肺气肿百分比（Aim 1a）和亚临床ILD（Aim 1b）性状的基因表达预测因子进行全转录组研究。我们进一步使用模型选择框架来确定一般人群中肺气肿和亚临床ILD发病机制的基因组合（目的2）。我们已经组建了一个高度合作和跨学科的研究团队，代表了统计遗传学的专业知识（Manichaikul 和Im）、遗传流行病学（Manichaikul和Rich）、肺流行病学（Lederer和巴尔）、肺病理学（Borczuk）和系统遗传学（Farber）。完成拟议的目标将导致更好地了解与肺气肿和ILD相关的预测基因表达特征，从而改善这些疾病的靶向预防和治疗。