Analysis of volatile organic compounds (VOCs): an innovative approach to disease characterization in elderly patients

Background and aim. Chronic heart failure (CHF) and chronic obstructive pulmonary disease (COPD) are two of the leading causes of disability and death worldwide in the elderly. The differential diagnosis between the two is important for the correct therapeutic management, given the side-effects that cardiac medications may have in patients with lung disease and vice versa. The atypical clinical presentation, the lower reliability of laboratory tests and the difficulty to perform some instrumental tests, common in aged patients, limit the diagnostic accuracy, as well as the disease severity stratification and the prognostic assessment of these diseases. Therefore, the development of new, safe, non-invasive, repeatable and reproducible technologies are warranted. Human breath contains thousands of molecules of different size, chemical structure and concentration, known as volatile organic compounds (VOCs), which can potentially carry information on the physiologic and pathologic processes related to respiratory and non-respiratory diseases. This thesis aimed at investigating the role that VOC analysis using an electronic-nose (BIONOTE®) may have in the diagnosis, disease severity stratification and prognosis of COPD and CHF patients. Materials and methods. Firstly, a computerized literature search was performed to identify relevant articles reporting original data on the clinical use of breath analysis in respiratory diseases and heart failure. We recruited 89 subjects admitted to an acute care ward with acutely decompensated CHF, 117 healthy controls and 103 COPD patients and partial least square (PLS) analysis was used to evaluate discriminative capacity of VOCs. PLS analysis was also used to evaluate VOC ability to predict COPD patients’ functional status and its variation over time in a sample of 63 COPD patients with a one-year follow-up. Furthermore, VOC ability to characterize newly diagnosed COPD patients and changes in response to inhaled therapy was assessed on 50 newly diagnosed COPD patients grouped using K-mean cluster analysis on BIONOTE responses. All patients were recruited among those attending the "Campus Bio-Medico" University Hospital. VOCs were collected using the Pneumopipe® and analyzed with the BIONOTE® electronic nose, an array of seven quartium-microbalances which provides a comprehensive and often peculiar VOC pattern named 'breath-fingerprint'. Results. Analysis of exhaled VOCs discriminates CHF from healthy controls and COPD patients with an accuracy of 81% and 69%, respectively. In CHF patients VOC pattern poorly predicts ejection fraction and systolic pulmonary arterial pressure. Three well distinguished groups of naïve COPD patients may be recognized basing on their breath-fingerprint: a) without remarkable comorbidities; b) with air trapping and higher BODE index score (mean 1.2); c) without air trapping and with a lower BODE index. Inhaled bronchodilators produce a quantitative reduction in VOCs amount, while inhaled steroids provides a qualitative modification of the breath profile. Furthermore, exhaled VOC analysis discriminates baseline functional status, assessed using the 6-minute walking distance normalized per squared height – n6MWD – (79% of accuracy) and BODE classes (86% of accuracy), and is able to predict 6MWD variation over one-year of follow-up with an accuracy of 86%, better than the GOLD classes (accuracy of 52%). Conclusion. Breath-fingerprint discriminates elderly people affected by CHF and COPD from healthy controls and, even with a lower accuracy, it discriminates CHF from COPD. It does not correlate with the severity of CHF, but is able to identify COPD patients with similar characteristics (phenotype), and predicts functional status and prognosis of COPD patients. Breath-fingerprints change in distinctive ways depending upon whether the COPD patients has been prescribed inhaled bronchodilators alone or any combinations of inhaled drugs including inhaled corticosteroids.