Transcriptomic signatures of airway inflammation in acute respiratory diseases

急性呼吸道疾病气道炎症的转录组特征

• 批准号: 9911601
• 负责人: Aartik Sarma
• 金额: $ 8.74万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9911601
• 关键词: Acute; Acute respiratory failure; Address; Adult Respiratory Distress Syndrome; Aspirate substance; Biological Markers; Biology; Blood specimen; Budesonide; Chronic; Chronic Obstructive Airway Disease; Clinical; Clinical Data; Clinical Research; Computational Biology; Coughing; Data; Diagnostic radiologic examination; Disease; Dyspnea; Exhibits; Functional disorder; Genetic Transcription; Goals; Health Care Costs; Heterogeneity; Hypoxemia; Immune; Immune response; Inflammation; Inflammatory; Injury; K-Series Research Career Programs; Lung; Lung Inflammation; Lung diseases; Mentors; Molecular; Morality; Morbidity - disease rate; National Heart, Lung, and Blood Institute; Pathogenesis; Pathology; Pathway interactions; Patients; Phenotype; Physiological; Plasma Proteins; Precision therapeutics; Predisposition; Prognostic Marker; Research; Research Priority; Respiratory Failure; Respiratory Process; Respiratory Signs and Symptoms; Respiratory System; Role; Sampling; Site; Sputum; Steroids; Subgroup; Syndrome; Testing; Vision; Work; airway inflammation; base; clinical Diagnosis; clinical biomarkers; cohort; differential expression; disorder subtype; formoterol; genetic signature; genomic biomarker; genomic signature; health care service utilization; insight; molecular phenotype; mortality; non cardiogenic pulmonary edema; outcome prediction; patient subsets; personalized diagnostics; prospective; protein biomarkers; respiratory; response; skills; tool; transcriptome sequencing; transcriptomics; treatment response

PROJECT SUMMARY/ABSTRACT: Dysregulated inflammation is a potent driver of acute respiratory pathology, including acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and the acute respiratory distress syndrome (ARDS), two conditions with a heavy burden of morbidity, mortality, and healthcare costs. These conditions are diagnosed by clinical and physiologic criteria that include patients with heterogenous immune biology, which has resulted in imprecise therapy with limited efficacy. There is a critical need to understand the heterogeneous inflammatory dysregulation in the lung to develop precision diagnostics and therapies for these syndromes. This proposal builds on prior work by my mentors that identified specific inflammatory biomarkers that distinguish subgroups of patients with similar underlying biology, or “molecular phenotypes” in ARDS and COPD. My co-mentor, Dr. Christenson, identified two molecular phenotypes in stable COPD distinguished by increases in airway genomic signatures of either enhanced Type 2 (T2) or Type 17 (T17) inflammation. These subgroups exhibit distinct clinical differences, including response to treatment with steroids. My preliminary data suggest we can extend molecular phenotypes of polarized immune responses to patients with AECOPD. My primary mentor, Dr. Calfee, identified hyperinflammatory and hypoinflammatory molecular phenotypes in ARDS based on clinical data and plasma protein biomarkers. The phenotypes were associated with differences in mortality and response to treatments. The differences in inflammation in the lung between these molecular phenotypes is not known. Transcriptomic analysis of samples from the respiratory tract in these patients can identify the role of specific immune pathways in the pathophysiology that leads to such distinct hyperinflammatory and hypoinflammatory molecular phenotypes. The overall objective of this proposal is to examine the role of genomic markers of respiratory inflammation in distinguishing AECOPD and ARDS molecular phenotypes by using transcriptomic data from previously sequenced airway samples in well-phenotyped cohorts. In Aim 1, we will use sputum sequencing and clinical data from a cohort of patients with COPD to test for the presence of molecular phenotypes of AECOPD. I hypothesize there are of molecular phenotypes of AECOPD that are distinguished by expression of predefined gene signatures of T1, T2, or T17 inflammation during exacerbations. I further hypothesize that these same signatures in patients with stable COPD will be prognostic biomarkers for susceptibility to exacerbations in which these pathways are enriched. In Aim 2, I will test for the presence of molecular phenotypes of ARDS in using RNA sequencing data from tracheal aspirates from an observational cohort. I hypothesize respiratory tract transcriptional responses will provide insight into the role of the inflammation in the lung in the pathogenesis of previously described ARDS molecular phenotypes identified by plasma proteins.

项目摘要/摘要：炎症失调是急性呼吸道疾病的潜在驱动因素 病理学，包括慢性阻塞性肺疾病急性加重（AECOPD）和急性发作 呼吸窘迫综合征（ARDS），这两种疾病具有沉重的发病率、死亡率和 这些疾病是根据临床和生理标准来诊断的，其中包括患有以下疾病的患者： 异质免疫生物学导致治疗不精确且疗效有限。 需要了解肺部的异质炎症失调以开发精确的诊断 该建议建立在我的导师之前的工作基础上，这些工作确定了具体的方法。 区分具有相似基础生物学或“分子生物学”的患者亚组的炎症生物标志物 我的合作导师 Christenson 博士发现了 ARDS 和 COPD 的两种分子表型。 稳定型 COPD 的特征是增强型 2 型 (T2) 或 2 型气道基因组特征增加 17 (T17) 炎症这些亚组表现出明显的临床差异，包括对治疗的反应。 我的初步数据表明我们可以扩展极化免疫的分子表型。 我的主要导师 Calfee 博士确定了对 AECOPD 患者的反应。 基于临床数据和血浆蛋白生物标志物的 ARDS 低炎症分子表型。 表型与死亡率和治疗反应的差异相关。 这些分子表型之间的肺部炎症尚不清楚。 来自这些患者呼吸道的样本可以识别特定免疫途径在疾病中的作用。 导致这种独特的高炎症和低炎症分子表型的病理生理学。 该提案的总体目标是检查呼吸道炎症基因组标记物在 使用先前的转录组数据区分 AECOPD 和 ARDS 分子表型 在目标 1 中，我们将使用痰测序和临床技术对表型良好的气道样本进行测序。 来自 COPD 患者队列的数据，用于测试 AECOPD I 分子表型的存在。 AECOPD 有多种分子表型，其特征是表达 恶化期间 T1、T2 或 T17 炎症的预定义基因特征。 稳定期 COPD 患者的这些相同特征将成为易感性的预后生物标志物 在目标 2 中，我将测试分子的存在。 使用来自观察队列 I 的气管抽吸物的 RNA 测序数据来分析 ARDS 的表型。 发展呼吸道转录反应将有助于深入了解炎症在 先前描述的通过血浆鉴定的 ARDS 分子表型的发病机制中的肺 蛋白质。