Gene Signature Linked to ICS-Induced Lung Function Improvement in COPD: Insights from the GLUCOLD Study

Rationale Chronic obstructive pulmonary disease (COPD) is characterized by chronic airflow limitation and persistent inflammation. Inhaled corticosteroids (ICS) are often used to reduce airway inflammation in patients. However, the response to ICS treatment varies among patients and blood eosinophils may not fully reflect treatment effectiveness. In this study, we aim to identify gene modules associated with ICS responsiveness and assess the underlying biological pathways. Methods We included 55 patients from the GLUCOLD study with mild-moderate COPD treated with ICS for 6 months with available gene expression data from biopsies. Treatment response was defined as changes in post-bronchodilator FEV 1 %predicted, post-bronchodilator FEV 1 /FVC and RV/TLC. To identify gene modules significantly correlated with ICS treatment responsiveness, we applied Weighted Gene Co-Expression Network Analysis (WGCNA). To explore the biological relevance of these modules, functional enrichment analysis was conducted using the STRING database, and key genes were identified through Gene Network Inference using the Ensemble of Trees (GENIE3) approach. Results We identified four gene modules associated to ICS-induced improvement in FEV 1 %predicted. Pathway enrichment analysis revealed key biological pathways including cilium function, positive regulation of various metabolic processes and inflammation. These pathways were also reflected by key genes including LRRC6 , IFT46 , AKT2 , and PIK3C3 . Conclusion This study identified gene modules and pathways associated with ICS responsiveness in COPD, providing a potential mechanistic explanation for the variability in ICS treatment responsiveness in COPD.