Integrative genomic, transcriptomic and proteomic studies of pulmonary function and COPD

慢性阻塞性肺疾病（COPD）是美国第四大死亡原因。 COPD定义为肺功能测试（PFT）测量的肺功能降低，即 1秒用力呼气量（FEV 1）及其与用力肺活量的比值（FEV 1/FVC）。而主 COPD的危险因素是吸烟，COPD的风险也随着年龄的增长而增加，并且COPD可以进展 尽管戒烟了。目前没有减缓COPD进展的药物治疗， 影响死亡率。PFT和COPD的大规模全基因组关联研究（GWAS）已经确定> 200个相关基因位点。然而，COPD和PFT GWAS受到不完全匹配的限制， 参考组的样本量（例如HapMap或1000个基因组），以及下游的解释已经 由于缺乏疾病和组织特异性eQTL和pQTL资源以及在非洲的代表性不足， 常见和罕见变异的美国和西班牙裔/拉丁裔受试者。此外，所有用于 迄今为止进行的GWAS对罕见和不常见的风险相关变异的代表性有限。的 NHLBI TOPMed项目现在正在为数千个TOPMed项目生成RNA-seq和蛋白质组学数据。 全基因组序列（WGS）数据。TOPMed特别是加强与非主题- 欧洲血统人口，从而增加种族多样性并包括来自欧洲的参与者 基于人群的多种族动脉粥样硬化研究[梅萨]，COPD富集的COPD基因研究，以及 肺组织研究联盟[LTRC]）。我们假设多组学数据的系统整合， 通过TOPMed确定的新的罕见/罕见变异关联将加速发现和验证， 新的生物标志物，COPD发病机制的分子机制的定义， 改进的遗传风险模型，为不同的祖先群体。为了解决这些首要的假设， 我们提出两个具体目标。在目标1中，我们将识别潜在的罕见/罕见和常见变异， 通过TOPMed中的扩展WGS分析PFT和COPD，执行多祖先精细映射， 构建适合非洲血统和多血统的新遗传风险预测模型 应用.在目标2中，我们将识别和验证候选基因和潜在的分子靶点， 通过全面的多组学研究， 功能研究。为了实现这些目标，我们将联合收割机结合最新的WGS分析方法 利用新的多组学方法来利用我们的大规模高质量RNA-seq和蛋白质组学资源。 我们组建了一个跨学科的合作小组，代表统计遗传学方面的专业知识， 肺流行病学、整合基因组学、蛋白质组学和肺医学。完成这些 目的将建立一个扩展的观点罕见和常见的遗传变异及其下游分子 在基于人群和COPD富集队列的多种族样本中的靶点。

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States. COPD is defined by a decrease in lung function as measured by pulmonary function testing (PFT), namely forced expiratory volume in one second (FEV1) and its ratio to forced vital capacity (FEV1/FVC). While the main risk factor for COPD is cigarette smoking, the risk of COPD also increases with age, and COPD can progress despite smoking cessation. There are no current pharmacologic therapies that slow progression of COPD or affect mortality. Large-scale genome-wide association studies (GWAS) of PFT and COPD have identified > 200 associated genetic loci. However, COPD and PFT GWAS have been limited by imperfect matching and sample sizes of reference panels (e.g. HapMap or 1000 Genomes), and downstream interpretation has been limited by lack of disease- and tissue-specific eQTL and pQTL resources and under-represention in African American and Hispanic/Latino subjects for both common and rare variants. In addition, all studies used for GWAS performed to date have limited representation of rare and infrequent risk-associated variants. The NHLBI TOPMed program is now generating RNA-seq and proteomics data for thousands of TOPMed participants with whole genome sequence (WGS) data. TOPMed specifically is enhanced with subjects of non- European ancestry populations, thereby increasing ethnic diversity and including participants from the population-based Multi-Ethnic Study of Atherosclerosis [MESA], the COPD-enriched COPDGene study, and the Lung Tissue Research Consortium [LTRC]). We hypothesize systematic integration of multi-omic data with novel rare/infrequent variant associations identified through TOPMed will accelerate discovery and validation of novel biomarkers, definition of the molecular mechanisms underlying pathogenesis of COPD, and construction of improved genetic risk models for diverse ancestry populations. To address these overarching hypotheses, we propose two Specific Aims. In Aim 1, we will identify rare/infrequent and common variation underlying PFT and COPD through expanded WGS analysis in TOPMed, perform multi-ancestry fine mapping, and construct new genetic risk prediction models tailored to African ancestry and multi-ancestry applications. In Aim 2, we will identify and validate candidate genes and molecular targets underlying known and novel genetic associations for PFT / COPD through comprehensive multi-omic and functional studies. To accomplish these Aims, we will combine the most current methods for WGS analysis with novel multi-omics approaches to leverage our large-scale high quality RNA-seq and proteomic resources. We have assembled an interdisciplinary collaborative group representing expertise in statistical genetics, pulmonary epidemiology, integrative genomics, proteomics, and pulmonary medicine. Completion of these Aims will establish an expanded view of rare and common genetic variation and their downstream molecular targets in multi-ethnic samples from population-based and COPD-enriched cohorts.