Project 1: Dynamic Host Responses During Resolution of HAP

项目 1：解决 HAP 期间的动态主机响应

基本信息

批准号：
10097983
负责人：
RICHARD G WUNDERINK
金额：
$ 45.98万
依托单位：
NORTHWESTERN UNIVERSITY AT CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-17 至 2022-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10097983
关键词：
Acinetobacter Alveolar Alveolar Macrophages Alveolus Antibiotic Resistance Antibiotic Therapy Antibiotics Biological Markers Cause of Death Cells Clinical Clinical Data Complex Computer Models Critical Illness Data Data Analyses Data Set Development Dose Ecosystem Electronic Health Record Equilibrium Failure Flow Cytometry Funding Opportunities Gene Expression Profile Goals Hospitals Human Immune Immune response Infection Inflammation Infrastructure Institution Instruction Irrigation Liquid substance Lung Lavage Fluid Lymphocyte Lymphocyte Subset Mechanical ventilation Metagenomics Modeling Nosocomial Infections Nosocomial pneumonia Pathway interactions Patients Phenotype Pneumonia Population Protocols documentation Pseudomonas Pseudomonas aeruginosa Regimen Regulatory T-Lymphocyte Research Research Project Grants Resolution Sampling Secondary to Shotguns Structure Systems Biology Testing Time Tissue-Specific Gene Expression Virulence Factors advanced system base biosignature clinical predictors cohort epigenomics genomic data humanized mouse macrophage microbial microbiome microbiome analysis mortality mouse model novel novel strategies outcome prediction pathogen peripheral blood phenomics pneumonia treatment predict clinical outcome predictive marker predictive tools prospective recruit response success therapeutic target transcriptomics

项目摘要

Project Summary Project 1: Dynamic Host Responses During Resolution of HAP Hospital-acquired pneumonia (HAP) is one of the leading causes of death from nosocomial infections, with high rates of associated mortality. HAP due to Pseudomonas aeruginosa and Acinetobacter spp. is substantially more difficult to treat than other pathogens, with clinical failure rates as high as 50%. These rates persist despite optimization of antibiotic regimens, suggesting factors beyond antibiotic resistance contribute. In this Project, we will examine the host response to pneumonia. We hypothesize that persistent inflammation in the alveolus after appropriate antibiotic treatment contributes to clinical failure in patients with P. aeruginosa or Acinetobacter spp. pneumonia. We will test this hypothesis in three interrelated Specific Aims. Aim 1. To determine whether pathogen-associated changes in the transcriptomic signatures of alveolar macrophages and lymphocyte subsets over time predict outcome of severe pneumonia. Aim 2. To prospectively validate predictive host responses identified using an ecosystem-based modeling approach in a separate cohort of patients with severe pneumonia. Aim 3. To determine whether validated host responses predictive of clinical outcome are related to pneumonia endpoints in murine models. We will combine clinical data from the Electronic Health Record and integrate these clinical data with transcriptomic and epigenomic data obtained from flow sorted alveolar macrophages and Treg cells isolated from serial samples of NBBAL over the course of the patient's illness. Through the development of these predictive tools, the SCRIPT Systems Biology Center offers the potential to discover novel pathways that drive pneumonia pathobiology for therapeutic targeting, and the ability to revise understanding of pneumonia as a complex interaction between the host, pathogen, and microbiome.

项目摘要项目1：HAP分辨率期间动态主机响应医院获得性肺炎（HAP）是院医院感染的主要死亡原因之一，较高相关死亡率的率。 HAP是由于铜绿假单胞菌和杆菌属引起的。更多比其他病原体难以治疗，临床衰竭率高达50％。这些费率持续了抗生素方案的优化，提示超出抗生素耐药性的因素会导致。在这个项目中，我们将检查宿主对肺炎的反应。我们假设肺泡持续的炎症之后适当的抗生素治疗会导致铜绿假单胞菌或动杆菌属患者的临床衰竭。肺炎。我们将以三个相互关联的特定目的来检验这一假设。目标1。确定是否病原体相关的肺泡巨噬细胞和淋巴细胞子集的转录组特征的变化随着时间的流逝，严重肺炎的预后。目标2。前瞻性验证预测主机响应使用基于生态系统的建模方法鉴定出严重的肺炎患者。目的3。确定验证的宿主反应是否可以预测临床结果与肺炎有关鼠模型中的终点。我们将结合电子健康记录中的临床数据并将其整合临床数据具有从流动的肺泡巨噬细胞和Treg获得的转录组和表观基因组数据在患者病的过程中，从NBBAL的系列样品中分离出来。通过发展这些预测工具，脚本系统生物学中心提供了发现新颖途径的潜力驱动肺炎病理生物学用于热靶向，以及逆转对肺炎的理解的能力宿主，病原体和微生物组之间的复杂相互作用。