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Emphysema is characterised by a loss of alveolar structure, as reflected in elastic recoil and gas exchange. As fibroblasts play a key role in the maintenance of structure, the current authors hypothesised that their proliferation might be constitutively impaired in lung emphysema.Using explant cultures, lung fibroblasts were obtained from resected lungs of 10 patients with emphysema (median forced expiratory volume in one second (FEV1) 40% predicted) and 10 control patients (FEV1, 95% pred). The doubling time (DT) was measured over 4 days under standard conditions (10% foetal calf serum) prior and after cryopreservation. Additionally, in seven samples per group the total population doubling level (PDL) was determined.In emphysema, mean¡SEM DT was 33.6¡2.8 h compared with 24.8¡1.4 h in controls. The differences in DT were preserved after cryopreservation. Groups also differed in the initial slope of the PDL plot during long-term culture (up to 35 days). However, the median (range) maximum PDL did not differ significantly between groups (13.8 (7.4-22.6) versus 20.2 (11.2-25.5)).The current authors, therefore, suggest that the reduced proliferation rate in vitro of lung fibroblasts from patients with emphysema reflects a persistent, intrinsic failure of cellular replacement and maintenance in this disease, possibly in relation to pre-term aging.

The identification and validation of biomarkers to support the assessment of novel therapeutics for COPD continues to be an important area of research. The aim of the current study was to identify systemic protein biomarkers correlated with measures of COPD severity, as well as specific protein signatures associated with comorbidities such as metabolic syndrome. 142 protein analytes were measured in serum of 140 patients with stable COPD, 15 smokers without COPD and 30 non-smoking controls. Seven analytes (sRAGE, EN-RAGE, NGAL, Fibrinogen, MPO, TGF-α and HB-EGF) showed significant differences between severe/very severe COPD, mild/moderate COPD, smoking and non-smoking control groups. Within the COPD subjects, univariate and multivariate analyses identified analytes significantly associated with FEV1, FEV1/FVC and DLCO. Most notably, a set of 5 analytes (HB-EGF, Fibrinogen, MCP-4, sRAGE and Sortilin) predicted 21% of the variability in DLCO values. To determine common functions/pathways, analytes were clustered in a correlation network by similarity of expression profile. While analytes related to neutrophil function (EN-RAGE, NGAL, MPO) grouped together to form a cluster associated with FEV1 related parameters, analytes related to the EGFR pathway (HB-EGF, TGF-α) formed another cluster associated with both DLCO and FEV1 related parameters. Associations of Fibrinogen with DLCO and MPO with FEV1/FVC were stronger in patients without metabolic syndrome (r  =  −0.52, p  = 0.005 and r  =  −0.61, p  = 0.023, respectively) compared to patients with coexisting metabolic syndrome (r  =  −0.25, p  = 0.47 and r  =  −0.15, p  = 0.96, respectively), and may be driving overall associations in the general cohort. In summary, our study has identified known and novel serum protein biomarkers and has demonstrated specific associations with COPD disease severity, FEV1, FEV1/FVC and DLCO. These data highlight systemic inflammatory pathways, neutrophil activation and epithelial tissue injury/repair processes as key pathways associated with COPD.

Currently no published data are available concerning the comparability of different types of NO analysers, making inter-laboratory comparisons difficult. In two sets of experiments we compared 4 and 5 NO analysers, respectively, from 3 different manufacturers using different calibration regimes: calibration with (1) a separate recommended calibration gas for each analyser, (2) a single low concentration for all (394 ppb), and (3) a single high concentration (12.8 ppm). We measured three subjects with known low (L), moderate (M) and high (H) bronchial exhaled nitric oxide concentrations as well as standard gases (SG). In the first set of experiments, calibration regime 1 resulted in the largest differences between analysers (coefficient of variation (CV) for L, M, H, SG: 0.42, 0.22, 0.20, 0.14). The lowest CV between analysers was observed after calibration 2 (0.34, 0.19, 0.12, 0.02). Very similar results were obtained in the second set of comparisons. Thus, differences between analysers existed, but were mainly due to differences in recommended calibration gases/procedures. Only a small part was explainable by deviations from target flow. These differences need to be taken into account when comparing data between laboratories or replacing the calibration gas of an analyser, as well as for the establishment and interpretation of normal values.