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Published ahead of print on November 5, 2009
Am. J. Respir. Crit. Care Med. 2009, doi:10.1164/rccm.200906-0896OC
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Submitted on June 15, 2009
Accepted on November 5, 2009

Identification of Asthma Phenotypes using Cluster Analysis in the Severe Asthma Research Program

Wendy C Moore1*, Deborah A Meyers1, Sally E Wenzel2, W Gerald Teague3, Huashi Li4, Xingnan Li4, Ralph D'Agostino, Jr.5, Mario Castro6, Douglas Curran-Everett7, Anne M Fitzpatrick8, Benjamin Gaston3, Nizar N Jarjour9, Ronald Sorkness9, William J Calhoun10, Kian Fan Chung11, Suzy AA Comhair12, Raed A Dweik12, Elliot Israel13, Stephen P Peters1, William W Busse9, Serpil C Erzurum12, and Eugene R Bleecker1

1 Center for Human Genomics, Wake Forest University School of Medicine, Winston Salem, North Carolina, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 2 University of Pittsburgh, Pittsburgh, Pennsylvania, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 3 University of Virginia, Charlottesville, Virginia, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 4 Center for Human Genomics, Wake Forest University School of Medicine, Winston Salem, North Carolina, United States, 5 Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, North Carolina, United States, 6 Washington University in St. Louis, St. Louis, Missouri, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 7 Data Coordinating Center, Denver, Colorado, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 8 Emory University, Atlanta, Georgia, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 9 University of Wisconsin, Madison, Wisconsin, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 10 University of Texas-Medical Branch, Galveston, Texas, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 11 Imperial College School of Medicine, London, United Kingdom; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 12 Cleveland Clinic, Cleveland, Ohio, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States, 13 Brigham and Women's Hospital, Boston, Massachusetts, United States; The Severe Asthma Research Program (SARP), NHLBI, Bethesda, Maryland, United States

* To whom correspondence should be addressed. E-mail: wmoore{at}wfubmc.edu.

Rationale: The Severe Asthma Research Program cohort includes subjects with persistent asthma who have undergone detailed phenotypic characterization. Previous univariate methods compared features of mild, moderate and severe asthma. Objective: Identify novel asthma phenotypes using an unsupervised hierarchical cluster analysis. Methods: Reduction of the initial 628 variables to 34 core variables was achieved by elimination of redundant data and transformation of categorical variables into ranked ordinal composite variables. Cluster analysis was performed on 726 subjects. Measurements and Main Results: Five groups were identified. Subjects in Cluster 1 (n=110) have early onset atopic asthma with normal lung function treated with ≤ 2 controller medications (82%) and minimal health care utilization. Cluster 2 (n=321) consists of subjects with early onset atopic asthma and preserved lung function, but increased medication requirements (29% on ≥ 3) and health care utilization. Cluster 3 (n=59) is a unique group of mostly older obese women with late onset nonatopic asthma, moderate reductions in FEV1 and frequent oral corticosteroid use to manage exacerbations. Subjects in Clusters 4 (n=120) and 5 (n=116) have severe airflow obstruction with bronchodilator responsiveness, but differ with regards to their ability to attain normal lung function, age of asthma onset, atopic status, and use of oral corticosteroids. Conclusions: Five distinct clinical phenotypes of asthma have been identified using unsupervised hierarchical cluster analysis. All clusters contain subjects who meet the ATS definition of severe asthma, which supports clinical heterogeneity in asthma and the need for new approaches for the classification of disease severity in asthma.
Key words: asthma phenotypes • definition • cluster analysis • severe asthma






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