Distinct Phenotypes of Smokers with Fixed Airflow Limitation Identified by Cluster Analysis of Severe Asthma
Description
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.
Journal
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- Annals of the American Thoracic Society
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Annals of the American Thoracic Society 15 (1), 33-41, 2018-01
American Thoracic Society
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Details 詳細情報について
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- CRID
- 1050282814001090560
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- NII Article ID
- 120006416016
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- HANDLE
- 2115/68597
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- ISSN
- 15463222
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- Text Lang
- en
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- Article Type
- journal article
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- Data Source
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- IRDB
- CiNii Articles