Breathprint-Based Endotyping of COPD and Bronchiectasis COPD Overlap Using Electronic Nose Technology: A Prospective Observational Study
Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with multiple clinical and inflammatory phenotypes. The coexistence of bronchiectasis, known as bronchiectasis–COPD overlap (BCO), identifies a subgroup with increased morbidity and mortality. Non-invasive breath analysis using electronic noses (e-noses) has shown promise in identifying disease-specific volatile organic compound (VOC) patterns (“breathprints”). Our aim was to evaluate the ability of an e-nose to differentiate between COPD and BCO patients, and to assess its utility in detecting inflammatory endotypes (neutrophilic vs. eosinophilic). In a monocentric, prospective, real-life study, 98 patients were enrolled over nine months. Forty-two patients had radiologically confirmed BCO, while fifty-six had COPD without bronchiectasis. Exhaled breath samples were analyzed using the Cyranose 320 e-nose. Principal component analysis (PCA) and discriminant analysis were used to identify group-specific breathprints and inflammatory profiles. PCA revealed significant breathprint differences between BCO and COPD (p = 0.021). Discriminant analysis yielded an overall accuracy of 69.6% (AUC 0.768, p = 0.037). The highest classification performance (76.8%) was achieved when distinguishing eosinophilic COPD from neutrophilic BCO. These findings suggest distinct inflammatory profiles that may be captured non-invasively. E-nose technology holds potential for the non-invasive endotyping of COPD, especially in identifying neutrophilic BCO as a unique inflammatory entity. Breathomics may support early, personalized treatment strategies.
Authors
- Andrea Portacci (ORCID: https://orcid.org/0000-0002-6127-2486)
- Andrea Marinelli (ORCID: https://orcid.org/0009-0008-7779-7931)
- Maria Grimaldi (ORCID: https://orcid.org/0000-0002-5332-7969)
- Vitaliano Nicola Quaranta (ORCID: https://orcid.org/0000-0001-9920-780X)
- Giovanna Elisiana Carpagnano (ORCID: https://orcid.org/0000-0001-7931-4704)
- Silvano Dragonieri (ORCID: https://orcid.org/0000-0003-1563-6864)
- Maria Rosaria Vulpi
Institutions
- University of Bari Aldo Moro (IT)
Publication Details
- Journal
- Chemosensors
- Published
- 2025-08-16
- DOI
- https://doi.org/10.3390/chemosensors13080311
- Citations
- 2
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 1.35