Wouters, Emiel F.�M.

Abstract Lung tissue remodeling in chronic obstructive pulmonary disease (COPD) is characterized by airway wall thickening and/or emphysema. Although the bronchial and alveolar compartments are functionally independent entities, we recently showed comparable alterations in matrix composition comprised of decreased elastin content and increased collagen and hyaluronan contents of alveolar and small airway walls. Out of several animal models tested, surfactant protein C (SPC)-TNF-α mice showed remodeling in alveolar and airway walls similar to what we observed in patients with COPD. Epithelial cells are able to undergo a phenotypic shift, gaining mesenchymal properties, a process in which c-Jun N-terminal kinase (JNK) signaling is involved. Therefore, we hypothesized that TNF-α induces JNK-dependent epithelial plasticity, which contributes to lung matrix remodeling. To this end, the ability of TNF-α to induce a phenotypic shift was assessed in A549, BEAS2B, and primary bronchial epithelial cells, and phenotypic markers were studied in SPC–TNF-α mice. Phenotypic markers of mesenchymal cells were elevated both in vitro and in vivo, as shown by the expression of vimentin, plasminogen activator inhibitor-1, collagen, and matrix metalloproteinases. Concurrently, the expression of the epithelial markers, E-cadherin and keratin 7 and 18, was attenuated. A pharmacological inhibitor of JNK attenuated this phenotypic shift in vitro, demonstrating involvement of JNK signaling in this process. Interestingly, activation of JNK signaling was also clearly present in lungs of SPC–TNF-α mice and patients with COPD. Together, these data show a role for TNF-α in the induction of a phenotypic shift in vitro, resulting in increased collagen production and the expression of elastin-degrading matrix metalloproteinases, and provide evidence for involvement of the TNF-α–JNK axis in extracellular matrix remodeling.

We described physical activity measures and hourly patterns in patients with chronic obstructive pulmonary disease (COPD) after stratification for generic and COPD-specific characteristics and, based on multiple physical activity measures, we identified clusters of patients. In total, 1001 patients with COPD (65% men; age, 67 years; forced expiratory volume in the first second [FEV 1 ], 49% predicted) were studied cross-sectionally. Demographics, anthropometrics, lung function and clinical data were assessed. Daily physical activity measures and hourly patterns were analysed based on data from a multisensor armband. Principal component analysis (PCA) and cluster analysis were applied to physical activity measures to identify clusters. Age, body mass index (BMI), dyspnoea grade and ADO index (including age, dyspnoea and airflow obstruction) were associated with physical activity measures and hourly patterns. Five clusters were identified based on three PCA components, which accounted for 60% of variance of the data. Importantly, couch potatoes (i.e. the most inactive cluster) were characterised by higher BMI, lower FEV 1 , worse dyspnoea and higher ADO index compared to other clusters ( p < 0.05 for all). Daily physical activity measures and hourly patterns are heterogeneous in COPD. Clusters of patients were identified solely based on physical activity data. These findings may be useful to develop interventions aiming to promote physical activity in COPD.