Identification of immune cell-cell communication networks and inflammatory pulmonary microenvironments associated with the progression of COPD

项目摘要 慢性阻塞性肺疾病（COPD）是一种致命的肺部疾病，是第四大死亡原因 在美国，尽管每年的医疗费用估计为500亿美元，但目前还没有治愈方法，只有姑息疗法， 提供治疗。慢性阻塞性肺病的明显特征是慢性肺部炎症，这可能是由于调节异常引起的。 免疫因子和细胞的复杂网络跨越多个组织隔室的离子。虽然多个 个体基因和蛋白质与COPD风险和进展相关， 缺乏对其病理生理学的了解，特别是关于COPD的显著异质性 表型我们研究的总体目标是从系统水平深入了解复杂的炎症和 COPD潜在的免疫机制，通过应用数据驱动（也称为“机器学习”）建模 从人肺微环境和匹配的免疫细胞收集的临床样品的方法 来自外周血的网络。我们的中心假设是，免疫网络将更能预测 COPD表型、进展和加重比为个体因素。我们将在三个方面来检验这个假设。 特定目的，使用匹配的支气管肺泡灌洗（BAL）和在SPIROMICS I和 II临床试验。目标1将通过高通量的方法识别免疫细胞间通讯网络的变化 来自吸烟者的外周血免疫细胞的刺激系统的细胞因子测量， 无COPD和从不吸烟的对照组（从即将到来的SPIROMICS II访视中收集; n=150）。目的2 将使用高通量技术确定炎症肺微环境中发生的系统级变化， BAL样品中的细胞因子测量（均来自SPIROMICS I存档，n=200，并且在2010年期间收集）。 即将进行的SPIROMICS II支气管镜检查）。 我们将确定与纵向临床进展和加重频率相关的网络。目标3 将整合肺和血液组织区室的测量，以定义关键的组合 与进展和加重事件相关的关系。总的来说，该项目将提供系统- 深入了解COPD的发病机制和进展，并为其他疾病的研究创造新的范式。 涉及慢性炎症的肺部疾病，包括特发性肺纤维化、哮喘和肺 移植结果将有助于未来开发新的非侵入性诊断检测方法，并将指导 系统水平的机制研究，可能导致新的组合疗法。

PROJECT SUMMARY Chronic obstructive pulmonary disease (COPD) is a fatal lung disease that is the fourth leading cause of death in the U.S. Despite an estimated $50 billion in yearly healthcare costs, it has no current cure and only palliat- ive treatments. COPD is clearly characterized by chronic lung inflammation that likely arises from dysregulat- ion of complex networks of immune factors and cells across multiple tissue compartments. Although multiple individual genes and proteins have been associated with COPD risk and progression, global mechanistic understanding of its pathophysiology is lacking, particularly regarding the marked heterogeneity in COPD phenotypes. The overall objective of our study is to gain systems-level insight into complex inflammatory and immune mechanisms underlying COPD, by applying data-driven (also called ‘machine learning’) modeling approaches to clinical samples collected from human pulmonary microenvironments and matched immune cell networks from peripheral blood. Our central hypothesis is that immune networks will be more predictive of COPD phenotype, progression, and exacerbation than individual factors. We will test this hypothesis in three Specific Aims, using matched brochoalveolar lavage (BAL) and blood samples collected in SPIROMICS I and II clinical trials. Aim 1 will identify changes in immune cell-cell communication networks, by high-throughput cytokine measurements from stimulated systems of peripheral blood immune cells from smokers with and without COPD and never-smoking controls (collected from the upcoming SPIROMICS II visit; n=150). Aim 2 will determine systems-level changes that occur in the inflamed lung microenvironment, using high-throughput cytokine measurements in BAL samples (both archival from SPIROMICS I, n=200, and collected during upcoming SPIROMICS II bronchoscopies) from smokers with and without COPD and never-smoking controls. We will identify networks associated with longitudinal clinical progression and exacerbation frequency. Aim 3 will integrate measurements across lung and blood tissue compartments to define key combinatorial relationships associated with progression and exacerbation events. Overall, this project will provide systems- level insight into COPD pathogenesis and progression, and create a new paradigm for the study of other pulmonary conditions involving chronic inflammation, including idiopathic pulmonary fibrosis, asthma, and lung transplant. Results will aid in the future development of new non-invasive diagnostic assays and will guide systems-level mechanistic studies that could result in new combinatorial therapies.