Rationale: Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asthma. Cluster analysis has been applied to explore novel phenotypes, which are not based on any a priori hypotheses.
Objectives: To explore novel severe asthma phenotypes by cluster analysis when including smoking patients with asthma.
Methods: We recruited a total of 127 subjects with severe asthma, including 59 current or ex-smokers, from our university hospital and its 29 affiliated hospitals/pulmonary clinics. Clinical variables obtained during a 2-day hospital stay were used for cluster analysis. After clustering using clinical variables, the sputum levels of 14 molecules were measured to biologically characterize the clinical clusters.
Results: Five clinical clusters, including two characterized by low forced expiratory volume in 1 second/forced vital capacity, were identified. When characteristics of smoking subjects in these two clusters were compared, there were marked differences between the two groups: one had high levels of circulating eosinophils, high immunoglobulin E levels, and a high sinus score, and the other was characterized by low levels of the same parameters. Sputum analysis revealed intriguing differences of cytokine/chemokine pattern in these two groups. The other three clusters were similar to those previously reported: young onset/atopic, nonsmoker/less eosinophilic, and female/obese. Key clinical variables were confirmed to be stable and consistent 3 years later.
Conclusions: This study reveals two distinct phenotypes with potentially different biological pathways contributing to fixed airflow limitation in cigarette smokers with severe asthma.
Keywords: cluster analysis; eosinophils; phenotypes; severe asthma; smoking.