Satoshi Konno1, Natsuko Taniguchi1, Hironi Makita1, Yuji Nakamaru2, Kaoruko Shimizu1, Noriharu Shijubo3, Satoshi Fuke4, Kimihiro Takeyabu5, Mitsuru Oguri6, Hirokazu Kimura1, Yukiko Maeda1, Masaru Suzuki1, Katsura Nagai1, Yoichi M Ito7, Sally E Wenzel8, Masaharu Nishimura1. 1. 1 First Department of Medicine and. 2. 2 Department of Otolaryngology-Head and Neck Surgery, Hokkaido University School of Medicine, Sapporo, Japan. 3. 3 Department of Respiratory Medicine, Japan Railways Sapporo Hospital, Sapporo, Japan. 4. 4 Department of Respiratory Medicine, KKR Sapporo Medical Center, Sapporo, Japan. 5. 5 Department of Respiratory Medicine, Otaru Kyokai Hospital, Otaru, Japan. 6. 6 Department of Respiratory Medicine, Oji General Hospital, Tomakomai, Japan. 7. 7 Department of Biostatistics, Hokkaido University Graduate School of Medicine, Sapporo, Japan; and. 8. 8 University of Pittsburgh Asthma Institute at University of Pittsburgh Medial Center/University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Abstract
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.
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.
Entities:
Keywords:
cluster analysis; eosinophils; phenotypes; severe asthma; smoking
Authors: Ankura Singh; Charles Liu; Barbara Putman; Rachel Zeig-Owens; Charles B Hall; Theresa Schwartz; Mayris P Webber; Hillel W Cohen; Kenneth I Berger; Anna Nolan; David J Prezant; Michael D Weiden Journal: Chest Date: 2018-07-17 Impact factor: 9.410
Authors: Maria Cristina Vazquez Guilamet; Michael Bernauer; Scott T Micek; Marin H Kollef Journal: Medicine (Baltimore) Date: 2019-04 Impact factor: 1.817