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：
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
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/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

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（由适用提供）：一起，肺肺气肿和慢性阻塞性肺疾病（COPD）是美国第三大死亡原因。尽管经常被认为是一种疾病，但计算机断层扫描（CT）上的肺气肿代表了某些COPD患者不存在的独特实体，并且在某些没有COPD中存在。间质性肺部疾病（ILD）是一类非感染，非恶性肺疾病，其特征是肺泡损伤，感染和纤维化。目前，很少有药物可以阻止这些疾病的进展，这反映了对基本分子机制的有限理解。我们最近在〜7,600名参与者的CT扫描中完成了全基因组关联研究（GWASS）的肺气肿百分比和亚临床ILD，该研究来自动脉粥样硬化研究（MESA）的7,600名参与者。我们的GWAS在识别SNRPF或附近的SNRPF和PPT2百分比百分比的SNP方面的总体成功，以及亚属性ILD特征的Anril和D21S2088E的总体成功反映了MESA中肺型表型的显着质量。尽管如此，GWAS方法仍然仍面临多个局限（b）缺乏将鉴定的SNP与特定基因联系起来的功能注释。为了解决这些局限性和其他局限性，我们建议采用一种新的基于基因的关联方法，称为predixcan，该方法直接测试了遗传变异影响表型的分子机制。该方法估计了由个体的遗传特征确定的基因表达的成分，并将“估算”的基因表达与投资下的表型相关联，以鉴定参与表型病因的基因。 predixcan的框架为MESA参与者“估算”组织特异性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，该数据集结合了CT扫描中的高质量表型与全血和肺特异性基因表达水平相结合。我们预计，通过预迪克斯can获得的基因表达性状的多次测试燃烧和增加的功能相关性将使我们能够鉴定出与肺气肿和ILD相关的新型基因和途径。因此，我们建议对MESA中肺气肿百分比（AIM 1A）和亚临床ILD（AIM 1B）的基因表达预测指标进行全转录组的研究。我们进一步使用模型选择框架来识别普通人群中肺气肿和亚临床ILD的基因的组合（AIM 2）。我们组建了一个高度协作和跨学科的研究人员，代表统计遗传学专业知识（Manichaikul）和IM），遗传流行病学（Manichaikul和Rich），肺部流行病学（Lederer和Barr），肺病理学（Borczuk）和系统遗传学（Farber）。提出的目标的完成将导致人们对与肺气肿和ILD相关的预测基因表达性状的了解，从而改善了针对性的预防和治疗这些疾病。