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. 2011 Apr 19:11:19.
doi: 10.1186/1471-2466-11-19.

Ageing and smoking contribute to plasma surfactant proteins and protease imbalance with correlations to airway obstruction

Helen Ilumets  1 , Witold Mazur, Tuula Toljamo, Noora Louhelainen, Pentti Nieminen, Hideo Kobayashi, Nobuhisa Ishikawa, Vuokko L Kinnula
Affiliations

Ageing and smoking contribute to plasma surfactant proteins and protease imbalance with correlations to airway obstruction

Helen Ilumets et al. BMC Pulm Med. .

Abstract

Background: A significant number of young people start smoking at an age of 13-15, which means that serious smoking-evoked changes may have been occurred by their twenties. Surfactant proteins (SP) and matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been linked to cigarette smoke induced lung remodelling and chronic obstructive pulmonary disease (COPD). However, the level of these proteins has not been examined during ageing or in young individuals with short smoking histories.

Methods: Plasma levels of SP-A, SP-D, MMP-9, and TIMP-1 were measured by EIA/ELISA from young (18-23 years) non-smoking controls (YNS) (n = 36), smokers (YS) (n = 51), middle aged/elderly (37-77 years) non-smoking controls (ONS) (n = 40), smokers (OS) (n = 64) (FEV1/FVC >0.7 in all subjects) and patients with COPD (n = 44, 35-79 years).

Results: Plasma levels of SP-A increased with age and in the older group in relation to smoking and COPD. Plasma SP-D and MMP-9 levels did not change with age but were elevated in OS and COPD as compared to ONS. The TIMP-1 level declined with age but increased in chronic smokers when compared to ONS. The clearest correlations could be detected between plasma SP-A vs. age, pack years and FEV1/FVC. The receiver operating characteristic (ROC) curve analysis revealed SP-A to be the best marker for discriminating between patients with COPD and the controls (area under ROC curve of 0.842; 95% confidence interval, 0.785-0.899; p < 0.001).

Conclusions: Age has a significant contribution to potential markers related to smoking and COPD; SP-A seems to be the best factor in differentiating COPD from the controls.

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Figures

Figure 1
Figure 1
Box-and-whisker plots of SP-A, SP-D, MMP-9 and TIMP-1 in plasma (A, B, C and D, respectively). The boxes represent the 25th to 75th percentiles, the solid lines within the boxes show the median values, the whiskers are the 10th and 90th percentiles, and the points represent outliers. *: p < 0.05; **: p < 0.01; ***: p < 0.001 (between two groups, t-test).
Figure 2
Figure 2
Relationship between plasma SP-A levels and the demographic parameters, age (A), BMI (B), pack-years (C) and FEV1/FVC% of predicted (D), in all of the subjects. ○ = young non-smokers; ● = young smokers; ◊ = middle aged/elderly non-smokers; ♦ = middle aged/elderly smokers; ■ = COPD patients.
Figure 3
Figure 3
Relationship between plasma SP-D levels and the demographic parameters, age (A), BMI (B), pack-years (C) and FEV1/FVC% of predicted (D), in all of the subjects. ○ = young non-smokers; ● = young smokers; ◊ = middle aged/elderly non-smokers; ♦ = middle aged/elderly smokers; ■ = COPD patients.
Figure 4
Figure 4
Relationship between plasma MMP-9 levels and the demographic parameters, age (A), BMI (B), pack-years (C) and FEV1/FVC% of predicted (D), in all of the subjects. ○ = young non-smokers; ● = young smokers; ◊ = middle aged/elderly non-smokers; ♦ = middle aged/elderly smokers; ■ = COPD patients.
Figure 5
Figure 5
Receiver operating characteristic curves of SP-A, SP-D, MMP-9 and TIMP-1 in plasma (A, B, C and D, respectively) obtained from patients with COPD, young and middle aged/elderly smokers and the controls. Values in parentheses indicate 95% confidence intervals for the area under the curve (AUC).
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