Transcriptomic signatures of airway inflammation in acute respiratory diseases

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PROJECT SUMMARY/ABSTRACT: Dysregulated inflammation is a potent driver of acute respiratory pathology, including acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and the acute respiratory distress syndrome (ARDS), two conditions with a heavy burden of morbidity, mortality, and healthcare costs. These conditions are diagnosed by clinical and physiologic criteria that include patients with heterogenous immune biology, which has resulted in imprecise therapy with limited efficacy. There is a critical need to understand the heterogeneous inflammatory dysregulation in the lung to develop precision diagnostics and therapies for these syndromes. This proposal builds on prior work by my mentors that identified specific inflammatory biomarkers that distinguish subgroups of patients with similar underlying biology, or “molecular phenotypes” in ARDS and COPD. My co-mentor, Dr. Christenson, identified two molecular phenotypes in stable COPD distinguished by increases in airway genomic signatures of either enhanced Type 2 (T2) or Type 17 (T17) inflammation. These subgroups exhibit distinct clinical differences, including response to treatment with steroids. My preliminary data suggest we can extend molecular phenotypes of polarized immune responses to patients with AECOPD. My primary mentor, Dr. Calfee, identified hyperinflammatory and hypoinflammatory molecular phenotypes in ARDS based on clinical data and plasma protein biomarkers. The phenotypes were associated with differences in mortality and response to treatments. The differences in inflammation in the lung between these molecular phenotypes is not known. Transcriptomic analysis of samples from the respiratory tract in these patients can identify the role of specific immune pathways in the pathophysiology that leads to such distinct hyperinflammatory and hypoinflammatory molecular phenotypes. The overall objective of this proposal is to examine the role of genomic markers of respiratory inflammation in distinguishing AECOPD and ARDS molecular phenotypes by using transcriptomic data from previously sequenced airway samples in well-phenotyped cohorts. In Aim 1, we will use sputum sequencing and clinical data from a cohort of patients with COPD to test for the presence of molecular phenotypes of AECOPD. I hypothesize there are of molecular phenotypes of AECOPD that are distinguished by expression of predefined gene signatures of T1, T2, or T17 inflammation during exacerbations. I further hypothesize that these same signatures in patients with stable COPD will be prognostic biomarkers for susceptibility to exacerbations in which these pathways are enriched. In Aim 2, I will test for the presence of molecular phenotypes of ARDS in using RNA sequencing data from tracheal aspirates from an observational cohort. I hypothesize respiratory tract transcriptional responses will provide insight into the role of the inflammation in the lung in the pathogenesis of previously described ARDS molecular phenotypes identified by plasma proteins.