A Multi-Compartment Cytological Approach to Severe Asthma Phenotyping: The BRISA Study (Biomedical Research in Severe Asthma).

BACKGROUND

Accurate inflammatory phenotyping in asthma remains challenging. Nasal cytology has emerged as a potential non-invasive tool to assess airway inflammation in asthma. However, its relationship with lower airway inflammation and systemic biomarkers remains unclear, particularly in severe asthma (SA).

OBJECTIVE

To evaluate whether a multi-compartment approach could improve the characterisation of type 2 inflammation and the relationship between nasal cytology, induced sputum, and systemic inflammatory biomarkers in patients with severe asthma.

METHODS

In this cross-sectional exploratory BRISA study, twenty-two patients with SA underwent nasal cytology by mucosal scraping, induced sputum analysis, and serum biomarker assessment (periostin, eosinophil cationic protein, thymic stromal lymphopoietin, dipeptidyl peptidase-4, and total IgE). Patients were stratified according to blood eosinophil count (BEC <300 vs ≥300 cells/µL). Correlations between compartments and associations with clinical and inflammatory variables were analysed.

RESULTS

Higher blood eosinophil counts were associated with worse lung function, increased exacerbations, and higher serum periostin levels. Valid induced sputum samples were obtained in 16 patients: 7 eosinophilic, 3 neutrophilic, 2 mixed eosinophilic-neutrophilic and 4 paucigranulocytic. Nasal cytology predominantly showed limited agreement with induced sputum inflammatory phenotypes. Serum TSLP, DPP4, and IgE also showed an upward trend in patients with higher blood eosinophil counts, although these differences were not statistically significant. Correlation analysis demonstrated a significant positive association between sputum and blood eosinophils, as well as between blood eosinophils and serum periostin. A strong positive correlation was also observed between serum eotaxin and TSLP.

CONCLUSION

Nasal cytology alone cannot replace induced sputum for inflammatory phenotyping in SA, although it may provide complementary information on upper airway inflammation. Among the evaluated systemic biomarkers, periostin emerged as the most consistent marker associated with blood eosinophilia, while other biomarkers showed only non-significant trends. Further studies are needed to validate the role of combined biomarkers in predicting airway inflammation.