Evolution and resolution of ARDS molecular phenotypes

ARDS 分子表型的进化和解析

• 批准号: 10592022
• 负责人: Aartik Sarma
• 金额: $ 18.87万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-05 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10592022
• 关键词: Acute Respiratory Distress Syndrome; Airway Disease; Automobile Driving; Biological; Biological Markers; Biology; COVID-19 patient; COVID-19/ARDS; Candida; Cell Proliferation; Cell model; Clinical; Complement; Complex; Computer Analysis; Data; Disease; Enterobacteriaceae; Epidemiologic Methods; Evolution; Family; Foundations; Future; Gene Expression; Gene Expression Profiling; Genes; Genomic approach; Goals; Grant; Health Care Costs; Immune; Inflammation; Inflammatory; Interferons; Interleukin-1; Interleukin-4; Knowledge; Learning; Liquid substance; Longitudinal Studies; Lower respiratory tract structure; Lung; Lung diseases; Macrophage; Mechanical ventilation; Medicine; Mentored Patient-Oriented Research Career Development Award; Mentorship; Methods; Morbidity - disease rate; National Heart, Lung, and Blood Institute; Pathway Analysis; Pathway interactions; Patient Recruitments; Patients; Phenotype; Plasma; Positive-Pressure Respiration; Pre-Clinical Model; Precision therapeutics; Pulmonary Inflammation; Randomized, Controlled Trials; Reporting; Research; Research Personnel; Resolution; Respiratory System; Risk; STAT6 gene; Sampling; Signal Transduction; Simvastatin; T-Cell Activation; T-Lymphocyte; Taxon; Testing; Time Series Analysis; Trachea; Training; Transforming Growth Factor beta; Trauma patient; Uncertainty; Virulence Factors; aspirate; bioinformatics tool; biological adaptation to stress; career development; cohort; cytokine; design; dimensional analysis; drug candidate; dysbiosis; experience; fungus; high dimensionality; insight; large datasets; lung injury; metatranscriptome; metatranscriptomics; microbial; microbial community; microbiome; molecular phenotype; mortality; novel; polarized cell; repaired; respiratory microbiome; response; secondary analysis; single-cell RNA sequencing; skill acquisition; skills; systemic inflammatory response; transcriptome sequencing; transcriptomics; treatment response; ventilation

ABSTRACT. The acute respiratory distress syndrome (ARDS) is associated with high mortality, morbidity, and health care costs (Bellani 2016). Dozens of candidate drugs for ARDS have been identified in preclinical models, but none consistently reduced mortality in randomized controlled trials (RCTs). This dismal record is likely driven in part by the heterogenous biology encompassed within the definition of ARDS (Rubenfeld 2015). Unsupervised clustering of plasma biomarkers and clinical variables recently identified two molecular phenotypes of ARDS (Calfee 2014) which may enable predictive enrichment in future RCTs. Uncertainty about the key biologic mechanisms that distinguish these two phenotypes from each other remains a critical knowledge gap. The overall objective of this proposal is to recruit patients to an established cohort of mechanically ventilated patients and identify distinct mechanisms of lung injury in ARDS molecular phenotypes. The central hypothesis of this proposal is that ARDS phenotypes are driven by different dysregulated pathways that result in distinct clinical trajectories and responses to treatment. In Aim 1, I will use single cell RNA sequencing to study tracheal aspirates and develop a model of cell signaling in the lung of each molecular phenotype. I hypothesize hyperinflammatory ARDS is associated with increased Type 1 T-cell polarization and a diminished response to interferons in macrophages. In Aim 2, I will use metatranscriptomic sequencing to characterize differences in the tracheal aspirate microbiome in each phenotype. I hypothesize TA metatranscriptomes will have distinct microbial community composition in each phenotype, which will be characterized by increased burden of enteric bacteria in the hypoinflammatory phenotype and an increased burden of fungi in the hyperinflammatory phenotype. In Aim 3, I will collect longitudinal tracheal aspirate and plasma samples to study the evolution of pro-inflammatory, pro-resolution, and pro-fibrotic pathways in each ARDS phenotype. I hypothesize ARDS phenotypes have distinct trajectories of inflammation and repair pathways in the first week of mechanical ventilation. I will address a critical gap in knowledge required to develop phenotype-specific precision treatments. This K23 award is sponsored by Dr. Carolyn Calfee, an experienced ARDS researcher whose group has pioneered analyses of ARDS molecular phenotypes, and Dr. Stephanie Christenson, a computational biologist with expertise in the transcriptomics of airway diseases. Their mentorship and the research and training plan in this K23 will support my continued career development and allow me to learn essential skills I require to be an independent investigator, including advanced computational analyses, epidemiological methods, and management of a research cohort. Developing these skills will be essential to achieve my long-term goal of understanding the mechanistic pathways distinguishing ARDS phenotypes to identify novel potential therapies. The proposed aims lay the foundation for a R01 proposal to study the interaction of pulmonary and systemic inflammation in ARDS phenotypes.

摘要。急性呼吸窘迫综合征（ARDS）与高死亡率、高发病率和高并发症相关。 医疗费用（Bellani 2016）。临床前研究已经确定了数十种治疗ARDS的候选药物， 模型，但在随机对照试验（RCT）中没有一致降低死亡率。这一令人沮丧的记录是 可能部分由ARDS定义中包含的异质生物学驱动（Rubenfeld 2015）。 血浆生物标志物和临床变量的无监督聚类最近确定了两种分子 ARDS表型（Calfee 2014），这可能有助于在未来的RCT中进行预测性富集。不确定性 区分这两种表型的关键生物学机制仍然是一个关键的 知识差距。该提案的总体目标是招募患者到一个已建立的队列， 机械通气患者，并确定ARDS分子肺损伤的不同机制 表型该建议的中心假设是ARDS表型是由不同的基因驱动的。 失调的途径导致不同的临床轨迹和对治疗的反应。在目标1中，我将使用 单细胞RNA测序，以研究气管吸出物，并建立肺细胞信号传导模型， 每个分子表型。我假设炎症性ARDS与1型T细胞增多有关， 极化和减弱的反应，干扰素在巨噬细胞。在目标2中，我将使用元转录组 测序以表征每种表型中气管抽吸物微生物组的差异。我假设 TA元转录组在每种表型中将具有不同的微生物群落组成，这将是 其特征在于低炎性表型中肠细菌负荷增加， 真菌在高度炎症表型中的负荷。在目标3中，我将收集纵向气管抽吸物， 血浆样本，以研究每个组织中促炎、促消退和促纤维化途径的演变 ARDS表型。我假设ARDS表型有不同的炎症和修复轨迹 在机械通气的第一个星期。我将解决所需知识的关键差距， 开发针对特定表型的精确治疗方法。K23奖由Carolyn Calfee博士赞助， 经验丰富的ARDS研究者，他的小组率先分析了ARDS分子表型， Stephanie Christenson是一位计算生物学家，擅长气道疾病的转录组学。 他们的指导以及K23的研究和培训计划将支持我的持续职业发展 并让我学习成为一名独立调查员所需的基本技能，包括高级 计算分析、流行病学方法和研究队列的管理。开发这些 技能将是必不可少的，以实现我的长期目标，了解机械途径区分 ARDS表型，以确定新的潜在治疗方法。提出的目标为R01奠定了基础 建议研究ARDS表型中肺部和全身炎症的相互作用。