All COPD patients consulting at the outpatient clinics of the Pulmonary Department of Saint George Hospital University Medical Center in Beirut, Lebanon between June 2011 and April 2013 were recruited in this case-control study. COPD diagnosis was defined as a post bronchodilator ratio of the forced expiratory volume in 1 sec (FEV₁)/forced vital capacity (FVC) of <70% (1). Ninety COPD patients were classified into categories based on Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) guidelines 2013 (1). There were 35 patients in group A, 38 in group B, 3 in group C, and 14 in group D. None of the patients had an exacerbation 1 month prior to inclusion. With regard to medication, COPD patients were classified as treated when they were receiving β2-agonists or anti-cholinergic agents (whether short-acting or long-acting) combined or not with inhaled corticosteroids (ICS), as suggested previously (16). A total of 46 COPD patients were found to be on regular medication. Patients with asthma (n=124) were defined according to Global Initiative for Asthma (GINA) guidelines 2012 (17). A clinical diagnosis based on symptoms (breathlessness, wheezing, cough and chest tightness), family history of asthma, worsening symptoms when exposed to various risk factors was performed and lung function measurements were assessed (17). Having another respiratory disease was the exclusion criterion for COPD or asthma patients. Healthy individuals from the general population (n=92) and outpatients consulting for a variety of non-respiratory problems in the same hospital (n=88) were recruited. Controls had normal lung function test results as defined by GOLD guidelines (1). The exclusion criteria were previous or current diagnosis of any respiratory disease such as asthma, COPD, chronic bronchitis, fibrosis, tuberculosis or lung cancer. Written informed consent was provided by all participants.

A standardized questionnaire, adapted to the local Arabic language, was filled out by all participants with the assistance of trained interviewers. The questionnaire included information on socio-demographic characteristics, exposure to disease risk factors, clinical assessment of the disease and its symptoms using the American Thoracic Society Questionnaire (18) and the Medical Research Council ‘MRC’ breathlessness scale (19), and smoking history.

Before conducting pulmonary function tests, venous blood samples were withdrawn from all participants, immediately transported at 4°C to the Immunology Laboratory of the Lebanese University (Fanar, Lebanon) and centrifuged at 4°C within 12 h after withdrawal. Plasma and serum were then aliquoted and stored frozen at −20°C until their analysis within 6 months.

All participants underwent baseline spirometry by a trained physician. Reversibility assessments (post-bronchodilator spirometry) were performed following the inhalation of two puffs of Ventolin (albuterol) with 30 min delay from the baseline spirometry.

Quantification of SP-D was performed by a five-layered enzyme-linked immunosorbent assay (ELISA) as previously described by Leth-Larsen et al (20). Briefly, microtiter plates were coated with polyclonal F(ab')₂ anti-human SP-D antibody [cat.no., K477; dilution, 1:1500; Grith Sorensen´s laboratory, Odense, Denmark (20)] in sodium carbonate buffer (pH 9.6). Following overnight incubation at 4°C, the plates were washed and left in contact with washing buffer (Tris-buffered saline, 0.05% Tween 20, 5 mM CaCl₂) for 1 h at room temperature. Calibrator, controls and samples were added at a dilution of 1:10 and incubated overnight at 4°C. This was followed by successive incubations with biotinylated monoclonal anti-human SP-D antibody [dilution, 1:2,000; Grith Sorensen´s laboratory (20)], horseradish peroxidase-conjugated streptavidin (cat.no., 43–4323; dilution, 1:20,000; Zymed; Thermo Fisher Scientific, Inc., Waltham, MA, USA) and o-phenylenediamine (Zymed; Thermo Fisher Scientific, Inc.) in citrate-phosphate buffer pH 5, containing 0.014% H₂O₂. Plates were read at 492 nm in a multichannel spectrophotometer (Bio-Tek ELx800 (BioTek instruments, Inc., Vermont, USA) after adding H₂SO₄. Serum CRP and plasma fibrinogen levels were measured using double antibody sandwich ELISA kits (Immunology Consultants Laboratory, Inc., Portland, OR, USA) according to the manufacturer's protocol. All samples were tested in duplicate. The coefficient of variation was 4.8% for SP-D, 2.7% for CRP, and 2% for fibrinogen.

Fibrinogen was normally distributed, whereas SP-D and CRP levels were not, even following log transformation. Results are expressed as the median (interquartile range). Differences between groups were tested using the t-test or Chi-square test when appropriate (non-parametric tests gave the same results). Associations between biomarkers and lung function tests were estimated using general linear models with adjustment for age, gender, body mass index (BMI) classes and smoking status. Three logistic regression models were used to evaluate the association between SP-D and COPD. In the first and second regressions, COPD patients vs. controls were used as the dependent variable. The independent variables were SP-D expressed as above/below the median value, and all potential confounding variables such as age, gender, BMI class, and smoking, and all the remaining socio-demographic characteristics and respiratory symptoms (cough, wheezing and expectoration) having P<0.2 in the bivariate analysis. As a sensitivity analysis, the second regression was performed in ever smokers (smokers and ex-smokers) only. Then, in order to confirm the ability of SP-D to differentiate patients with COPD from patients with asthma, a third regression including COPD vs. asthma patients as the dependent variable was performed. The adjusted odds ratios (aORs) obtained from the first and second regressions respectively were then rounded to the nearest unit and used as coefficients in the calculation of score 1 (for all COPD patients and controls) and score 2 (for ever-smoker COPD patients and controls) with the purpose of predicting COPD diagnosis. Receiver-operating characteristic (ROC) curves were then generated in order to determine the ability of the scores 1 and 2 to discriminate between patients with COPD and controls. P<0.05 was considered to indicate a statistically significant difference. All analyses were performed using SPSS software, version 17.0 (SPSS, Inc., Chicago, IL, USA).

According to a previous study on SP-D in COPD (21), the smallest difference that could exist between healthy individuals and COPD patients was 56.6 ng/ml, while the standard deviation was 80.2 ng/ml. With an α error of 5% and a power of 80%, a minimum of 32 patients and 46 controls was required for the study.

Characteristics of the COPD and asthma patients and controls are presented in Table I. The three groups were significantly different regarding age, gender, smoking, marital status and education. Compared with controls, patients with COPD were more frequently men, ever smokers and unmarried (all P≤0.003); while patients with asthma were younger, more often unmarried, non-smokers and were more likely to have a university degree (all P≤0.02). Compared with asthma patients, COPD patients were older, more frequently men, ever smokers and were less likely to have a university degree (all P≤0.001). No other significant associations were found.

The three groups were significantly different regarding SP-D levels only. Serum SP-D levels were significantly increased in COPD patients as compared with controls and with asthma patients. There were no significant differences in SP-D levels between asthma patients and controls. No other significant associations were observed (Table II).

SP-D levels were lower in the COPD patients that were receiving inhaled therapy (ICS and/or bronchodilators) compared with the COPD patients that were not, but the difference was not statistically significant [n=46 vs. 42; 1,507±868 vs. 1,830±971 ng/ml, respectively, P=0.1].

No significant associations were identified between biological markers and FEV1% predicted or FEV1/FVC following the administration of a bronchodilator to the COPD patients (data not shown).

Multivariate analyses performed on all COPD patients and controls showed that SP-D levels above the median value, male gender, being unmarried and symptoms such as having a morning cough, cough during the day and wheezing during the day were significantly and positively associated with COPD (Table IIIA). The same associations were observed in ever-smoker COPD patients and controls (Table IIIB).

In the third regression (Table IIIC) with COPD patients vs. asthma patients as the dependent variable, SP-D levels above the median value, older age, male gender and having a morning cough were significantly and positively associated with COPD.

Taking into account the aORs from the first regression (from Table IIIA) and rounding to the nearest unit, a first score (score 1) for COPD diagnosis was computed as follows: Score 1 = (SP-D above/below the median × 4) + (gender × 3) + (marital status × 3) + (cough in the morning × 39) + (cough during the day × 11) + (wheezing during the day × 65) + (smoking × 1).

In COPD patients, score 1 had a minimum of 6 and a maximum of 129. The mean was 47.2, the median was 49 and the standard deviation was 31.9. In controls, the minimum was 6 and the maximum was 75, with a mean of 12.6, a median of 10 and a standard deviation of 10.1.

The ROC curve generated for score 1 is shown in Fig. 1, for the comparison of COPD patients with controls. The area under the curve was 0.890 (0.841–0.940; P<0.001). The most optimal cut-off point was calculated to be 15.5 (Table IV) at which point the sensitivity, specificity, positive predictive value and negative predictive value were 76.4, 89.3, 81 and 74%, respectively.

A second score (score 2) was calculated from the second regression (from Table IIIB) for ever-smoker COPD patients and controls as follows: Score 2 = (SP-D above/below the median × 6) + (gender × 4) + (marital status × 3) + (cough in the morning × 54) + (cough during the day × 9) + (wheezing during the day × 36).

In ever-smoker COPD patients, score 2 had a minimum of 10 and a maximum of 116. The mean was 47.7, the median was 51 and the standard deviation of 28.5. In ever-smoker controls, the minimum was 7 and the maximum was 67, with a mean of 15, a median of 13 and a standard deviation of 11.4.

A ROC curve was generated from score 2 (Fig. 2). The area under the curve was at 0.895 (0.841–0.950; P<0.001). The most optimal cut-off point was 18.5 at which point the sensitivity, specificity, positive predictive value and negative predictive value were 77.8, 88.5, 70 and 82% respectively (Table V).