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

基本信息

批准号：
9271241
负责人：
ANI Wang MANICHAIKUL
金额：
$ 40.05万
依托单位：
UNIVERSITY OF VIRGINIA
依托单位国家：
美国
项目类别：
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/9271241
关键词：
Address Affect African American Air Alveolar 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 Components Gene Expression General Population Genes Genetic Genetic Variation Genomics Glycoproteins Hamman-Rich syndrome Hispanics Human Individual Inflammation Injury Interstitial Lung Diseases Investigation Joints Link Lung Lung Transplantation Lung diseases Methods Modeling Molecular Molecular Profiling Multi-Ethnic Study of Atherosclerosis 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 Banks Tissue Sample Tissues Training United States Universities Validation Variant Whole Blood X-Ray Computed Tomography alveolar destruction base experimental study gene interaction genetic epidemiology genetic profiling genetic variant genome wide association study genome-wide genome-wide analysis improved novel population based public health relevance smoking cessation success trait transcriptome transcriptome sequencing transcriptomics whole genome

项目摘要

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（由申请人证明）：肺肺气肿和慢性阻塞性肺疾病（COPD）在联合静脉中的DEA经常被视为一种疾病，在计算机断层扫描（CT）上渗透了某些患者，这是一种独特的实体COPD和以肺泡损伤，炎症和纤维化为特征的UNG疾病。动脉粥样硬化的多种族研究（MESA）。尽管如此，GWAS仍面临多个限制（b）缺乏与特定基因的连接SNP的功能注释。并与表型相关的表型与表型有关。肺特异性基因表达水平。（AIM 1A）台面中的无数特征（AIM 1B）。调查人员团队压抑SE统计遗传学（Manichaikul） Andetic流行病学（Manichaikul和Rich），肺部流行病学（LEDER和BARR），肺病理学（Borczuk）和系统遗传学RBER）。，导致靶向释放和治疗这些疾病的改善。