The goal of this study is to iteratively identify, validate and refine biomarkers to predict clinical failure, and identify novel targets for therapy beyond traditional antibiotics for patients with severe pneumonia requiring intubation, including severe community-acquired pneumonia (CAP), hospital-acquired pneumonia, and ventilator-associated pneumonia (HAP/VAP). We hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution. Pneumonia - encompassing both CAP and HAP/VAP - accounts for nearly 80% of infection-related deaths in the United States. The COVID-19 pandemic further underscores the significant morbidity and mortality associated with severe pneumonia. Our U19 Systems Biology Center, Successful Clinical Response In Pneumonia Therapy (SCRIPT), renamed Super-SCRIPT (SCRIPT²) for the renewal, integrates bronchoalveolar lavage (BAL), nasal curettage, and blood sampling with advanced multi-omics approaches. These include multiparameter BAL flow cytometry, single-cell RNA sequencing of alveolar cells, deep pathogen sequencing, DNA metagenomic sequencing of alveolar fluid, and extensive clinical phenotyping to build comprehensive models of pneumonia pathogenesis. In the original SCRIPT project, we developed a systems biology model of SARS-CoV-2 pathobiology that informed a novel therapy for severe COVID-19 pneumonia, which showed efficacy in a Phase II clinical trial. In SCRIPT², we aim to determine whether high-dimensional, longitudinal data describing host responses, pathogens, microbiomes, and clinical phenotypes in patients with severe CAP (Project 1) and HAP/VAP (Project 2) can be used to predict favorable or unfavorable clinical trajectories during the course of illness. This will be achieved by employing longitudinal samples, specifically from the distal lung and nasopharynx for CAP patients, and from the distal lung for HAP/VAP patients. We hypothesize that these integrated multi-omics datasets will yield predictive models capable of identifying actionable biomarkers and informing outcomes for both severe CAP and HAP/VAP. To achieve these goals, we have assembled a talented group of investigators in the SCRIPT² Systems Biology Center, We will leverage our routine clinical practice of safe alveolar sampling in mechanically ventilated patients with pneumonia with initial and repeated bronchoscopic BAL or non-bronchoscopic alveolar lavage (NBBAL) sampling over the course of pneumonia. From this fluid, we will combine flow cytometry with multi-omic technologies (cell population-specific transcriptomics, epigenomics, shotgun microbiome sequencing, and pathogen-specific sequencing). Our systems scientists integrate these multi-omic data with robust clinical data with the goal of identifying biomarkers that can be prospectively tested in patients and causally evaluated in mouse models.

Successful Clinical Response in Pneumonia Therapy (SCRIPT)

19 variables across Anthropometry, Demographics

Successful Clinical Response in Pneumonia Therapy (SCRIPT)

Anthropometry (1)

Demographics (3)

Other (15)