Abstract
Chronic obstructive pulmonary disease (COPD) is an etiologically complex disease characterized by acute exacerbations and stable phases. We aimed to identify biological functions modulated in specific COPD conditions, using whole blood samples collected in the AERIS clinical study (NCT01360398). Considered conditions were exacerbation onset, severity of airway obstruction, and presence of respiratory pathogens in sputum samples. With an integrative multi-network gene community detection (MNGCD) approach, we analyzed expression profiles to identify communities of correlated genes. The approach combined different layers of gene interactions for each explored condition/subset of samples: gene expression similarity, protein-protein interactions, transcription factors, and microRNAs validated regulons. Heme metabolism, interferon-alpha, and interferon-gamma pathways were modulated in patients at both exacerbation and stable-state visits, but with the involvement of distinct sets of genes. An important gene community was enriched with G2M checkpoint, E2F targets, and mitotic spindle pathways during exacerbation. Targets of TAL1 regulator and hsa-let-7b - 5p microRNA were modulated with increasing severity of airway obstruction. Bacterial infections with Moraxella catarrhalis and, particularly, Haemophilus influenzae triggered a specific cellular and inflammatory response in acute exacerbations, indicating an active reaction of the host to infections. In conclusion, COPD is a complex multifactorial disease that requires in-depth investigations of its causes and features during its evolution and whole blood transcriptome profiling can contribute to capturing some relevant regulatory mechanisms associated with this disease. In this work, we explored multi-network modeling that integrated diverse layers of regulatory gene networks and enhanced our comprehension of the biological functions implicated in the COPD pathogenesis.