RESUMEN
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.