Systems Biology Modeling of Severe Hospital-Acquired Pneumonia

严重医院获得性肺炎的系统生物学模型

• 批准号: 10551467
• 负责人: ALAN R HAUSER
• 金额: $ 43.35万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-17 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10551467
• 关键词: Age; Antibiotics; Bacteria; Biological Assay; Bronchoalveolar Lavage; Bronchoalveolar Lavage Fluid; Clinical; Communities; Complication; Computer Models; Data; Dedications; Deterioration; Development; Disease; Disease Outcome; Enrollment; Failure; Flow Cytometry; Funding; Future; Genetic; Genome; Goals; Hospitalization; Hospitals; Immune response; Immunosuppression; Infection; Inflammatory Response; Intervention; Intervention Studies; Klebsiella; Knowledge; Lung; Mechanical ventilation; Metadata; Modeling; Morbidity - disease rate; Multi-Drug Resistance; Multiomic Data; Nosocomial pneumonia; Outcome; Pathogenesis; Pathogenicity; Patient-Focused Outcomes; Patients; Pattern; Pneumonia; Pseudomonas aeruginosa; Research; Research Project Grants; Resources; Respiratory Failure; Ribosomal RNA; Sampling; Shotguns; Staphylococcus aureus; Systems Biology; Techniques; Testing; Therapeutic Intervention; Unfavorable Clinical Outcome; Validation; Work; biobank; biomarker identification; biosignature; clinical predictors; cohort; community acquired pneumonia; cytokine; humanized mouse; improved; insight; lung microbiome; metagenomic sequencing; microbiome; microbiota; mortality; mouse model; multiple omics; novel; novel therapeutic intervention; outcome prediction; pathogen; pathogenic bacteria; pneumonia model; pneumonia treatment; predict clinical outcome; predictive modeling; predictive test; response; single-cell RNA sequencing; transcriptome; transcriptomics; ventilator-associated pneumonia

PROJECT SUMMARY/ABSTRACT – Project 2 Mechanical ventilation has saved the lives of countless patients with respiratory failure but may lead to the dreaded complication of ventilator-associated pneumonia (VAP), a form of hospital-acquired pneumonia (HAP). HAP/VAP are associated with particularly high mortality rates despite the administration of appropriate and highly potent antibiotics. Recent work suggests that the host inflammatory response, the specific pathogenic strain causing the infection, and the pulmonary microbiome all contribute to the pathogenesis of HAP/VAP. However, to our knowledge these three contributing factors have not been comprehensively examined together. To better understand HAP/VAP, we established the Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center to enroll pneumonia patients, collect bronchoalveolar lavage samples from them, and apply multi-omic approaches to these samples. We hypothesize that these approaches will identify specific host response patterns, pathogen genetic biosignatures, and pulmonary microbiome consortia that define and predict the clinical trajectory of patients with HAP/VAP and define the pathogenesis of these infections. To test this hypothesis, we will perform the following aims: (1) Identify host response biosignatures, (2) features of bacterial pathogens, and (3) patterns of pulmonary microbiome consortia that inform pathogenesis and are associated with clinical improvement or deterioration in HAP/VAP. (4) Integrate host response, pathogen, and microbiome features with clinical metadata to generate a comprehensive computational model that predicts clinical outcomes and favorable/unfavorable transitions in HAP/VAP. The data we generate will be useful clinically in identifying those patients who require aggressive management and scientifically in providing a deeper understanding of the pathogenesis of HAP/VAP.

专题摘要/摘要-专题二