Discriminative potential of exhaled breath condensate biomarkers with respect to chronic obstructive pulmonary disease

Abstract

Background: Chronic obstructive pulmonary disease (COPD) affecting 334 million people in the world remains a major cause of morbidity and mortality. Proper diagnosis of COPD is still a challenge and largely solely based on spirometric criteria. We aimed to investigate the potential of nitrosative/oxidative stress and related metabolic biomarkers in exhaled breath condensate (EBC) to discriminate COPD patients.

Methods: Three hundred three participants were randomly selected from a 15,000-transit worker cohort within the Respiratory disease Occupational Biomonitoring Collaborative Project (ROBoCoP). COPD was defined using the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria as post-bronchodilator ratio of Forced Expiratory Volume in 1st second to Forced Vital Capacity < 0.7 in spirometry validated by an experienced pulmonologist. Discriminative power of biomarker profiles in EBC was analyzed using linear discriminant analyses.

Results: Amongst 300 participants with validated spirometry, 50.3% were female, 52.3 years old in average, 36.0% were current smokers, 12.7% ex-smokers with mean tobacco exposure of 15.4 pack-years. Twenty-one participants (7.0%) were diagnosed as COPD, including 19 new diagnoses, 12 of which with a mild COPD stage (GOLD 1). Amongst 8 biomarkers measured in EBC, combination of 2 biomarkers, Lactate and Malondialdehyde (MDA) significantly discriminated COPD subjects from non-COPD, with a 71%-accuracy, area under the receiver curve of 0.78 (p-value < 0.001), and a negative predictive value of 96%.

Conclusions: These findings support the potential of biomarkers in EBC, in particular lactate and MDA, to discriminate COPD patients even at a mild or moderate stage. These EBC biomarkers present a non-invasive and drugless technique, which can improve COPD diagnosis in the future.

Keywords: Biomarker; COPD; Exhaled breath condensate; Oxidative stress; Respiratory.

Fig. 1

Receiver operating characteristic curve of the two-biomarker model. Notes: Linear discriminant analysis; Abbreviations: AUC Area Under the Curve, MDA Malondialdehyde