Bronchial epithelial cell transcriptional responses to inhaled corticosteroids dictate severe asthmatic outcomes.

BACKGROUND: Inhaled corticosteroids (CSs) are the backbone of asthma treatment, improving quality of life, exacerbation rates, and mortality. Although effective for most, a subset of patients with asthma experience CS-resistant disease despite receiving high-dose medication. OBJECTIVE: We sought to investigate the transcriptomic response of bronchial epithelial cells (BECs) to inhaled CSs. METHODS: Independent component analysis was performed on datasets, detailing the transcriptional response of BECs to CS treatment. The expression of these CS-response components was examined in 2 patient cohorts and investigated in relation to clinical parameters. Supervised learning was used to predict BEC CS responses using peripheral blood gene expression. RESULTS: We identified a signature of CS response that was closely correlated with CS use in patients with asthma. Participants could be separated on the basis of CS-response genes into groups with high and low signature expression. Patients with low expression of CS-response genes, particularly those with a severe asthma diagnosis, showed worse lung function and quality of life. These individuals demonstrated enrichment for T-lymphocyte infiltration in endobronchial brushings. Supervised machine learning identified a 7-gene signature from peripheral blood that reliably identified patients with poor CS-response expression in BECs. CONCLUSIONS: Loss of CS transcriptional responses within bronchial epithelium was related to impaired lung function and poor quality of life, particularly in patients with severe asthma. These individuals were identified using minimally invasive blood sampling, suggesting these findings may enable earlier triage to alternative treatments.

High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status.

Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, treatment-refractory disease. Applying mass cytometry and machine learning to bronchoalveolar lavage (BAL) cells, we find that corticosteroid-resistant asthma patients cluster largely into two groups: one enriched in interleukin (IL)-4+ innate immune cells and another dominated by interferon (IFN)-γ+ T cells, including tissue-resident memory cells. In contrast, BAL cells of a healthier population are enriched in IL-10+ macrophages. To better understand cellular mediators of severe asthma, we developed the Immune Cell Linkage through Exploratory Matrices (ICLite) algorithm to perform deconvolution of bulk RNA sequencing of mixed-cell populations. Signatures of mitosis and IL-7 signaling in CD206-FcεRI+CD127+IL-4+ innate cells in one patient group, contrasting with adaptive immune response in T cells in the other, are preserved across technologies. Transcriptional signatures uncovered by ICLite identify T-cell-high and T-cell-poor severe asthma patients in an independent cohort, suggesting broad applicability of our findings.