Pneumonia, including both community-acquired pneumonia (CAP) and hospital/ventilator-acquired pneumonia (HAP/VAP), causes almost 80% of deaths from infections in the US. As evidenced by the ongoing COVID-19 pandemic, severe pneumonia represents an important cause of morbidity and mortality. Our U19 Systems Biology Center, Successful Clinical Response In Pneumonia Therapy (SCRIPT), which we rename Super-SCRIPT (SCRIPT2) for this renewal, leverages bronchoalveolar lavage (BAL), nasal curettage, and blood sampling paired with cutting-edge multi-omics technologies—including multiparameter flow cytometry, single-cell RNA-sequencing, deep pathogen sequencing, DNA metagenomics, and deep clinical phenotyping—to develop models of pneumonia pathogenesis. In SCRIPT, we generated a detailed systems biology model of SARS-CoV-2 pathobiology that supported a novel therapy for severe SARS-CoV-2 pneumonia that was effective in a phase II clinical trial. In SCRIPT2, we will determine whether models generated using high-dimension longitudinal data describing the host response, pathogen, microbiome, and clinical phenome in patients with severe CAP (Project 1) and HAP/VAP (Project 2) can predict favorable or unfavorable clinical transitions over the course of a pneumonia episode. We test the hypothesis that multi-omics inputs will create models that identify determinants of clinical outcome for both early severe CAP as well as for subsequent and primary HAP/VAP. A corollary hypothesis is that perturbations of these determinants during controlled clinical trials of pharmacologic interventions will allow iteration of the models’ predictive capabilities. Aim 1/Project 1. To ascertain models of early severe CAP, including co-infections, which identify targetable determinants of clinical outcome. Aim 2/Project 2. To ascertain models of HAP/VAP (post-viral and primary) that identify targetable determinants of clinical outcome. Three scientific cores support the projects. The Technology Core developed cutting edge multi-omics approaches for the analysis of bronchoalveolar lavage samples collected as part of clinical care. The Bioinformatics and Data Management Core weaves together clinical data extracted from our own EHR and those from other centers. The Modeling Core works seamlessly with the projects and cores to integrate, validate and iteratively improve latent space models of disease. Clinician scholars who provide direct care to patients with pneumonia lead or contribute to each project and core, enhancing the translational impact of our findings.
|Effective start/end date||1/1/23 → 12/31/27|
- National Institute of Allergy and Infectious Diseases (2U19AI135964-06)
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