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

慢性阻塞性肺疾病(COPD)是美国第四大死因。 COPD的定义是通过肺功能测试(PFT)测量的肺功能下降，即 1秒用力呼气量(FEV1)及其与用力肺活量(FEV1/FVC)的比值。而主要的 COPD的危险因素是吸烟，COPD的风险也随着年龄的增长而增加，COPD可以进展 尽管戒烟了。目前还没有延缓COPD进展的药物疗法或 影响死亡率。对PFT和COPD的大规模全基因组关联研究(GWAS)已经确定&GT； 200个相关遗传基因座。然而，COPD和PFT Gwas一直受到不完美匹配和 参考小组的样本大小(例如，HapMap或1000个基因组)和下游解释 受限于非洲疾病和组织特异性eQTL和pQTL资源的缺乏和表达不足 美国人和西班牙裔/拉丁裔研究对象包括常见和罕见的变异。此外，所有研究都用于 到目前为止，进行的GWA对罕见和不常见的风险相关变异的代表性有限。这个 NHLBI TOPMed计划现在正在为数千个TOPMed生成RNA-Seq和蛋白质组学数据 参与者拥有全基因组序列(WGS)数据。TOPMed特别增强了非 欧洲血统人口，从而增加了种族多样性，并包括来自 基于人群的动脉粥样硬化多种族研究[MESA]，COPD富集型COPD基因研究，以及 肺组织研究联盟[LTRC])。我们假设多组数据与 通过TOPMed发现的新的罕见/罕见变异关联将加速发现和验证 新的生物标记物，COPD发病机制的分子机制的定义和构建 针对不同血统人群的改进遗传风险模型。为了解决这些最重要的假设， 我们提出了两个具体目标。在目标1中，我们将确定潜在的罕见/罕见和常见的变异 通过TOPMed中扩展的WGS分析，进行PFT和COPD，进行多祖先精细绘图，以及 构建适合非洲血统和多血统的新遗传风险预测模型 申请。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。 已知的和新的与PFT/COPD的遗传关联通过综合的多基因组和 功能研究。为了实现这些目标，我们将结合最新的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和蛋白质组资源。 我们已经组建了一个代表统计遗传学专业知识的跨学科协作小组， 肺部流行病学、综合基因组学、蛋白质组学和肺部医学。完成这些工作 AIMS将建立罕见和常见的遗传变异及其下游分子的扩展视图 来自人群和慢性阻塞性肺病患者队列的多种族样本中的靶标。

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.