Moore WC, Meyers DA, Wenzel SE, Teague WG, Li H, Li X, D'Agostino Jr R, Castro M, Curran-Everett D, Fitzpatrick AM, Gaston B, Jarjour NN, Sorkness R, Calhoun WJ, Chung KF, Comhair SA, Dweik RA, Israel E, Peters SP, Busse WW, Erzurum SC, Bleecker ER
Identification of Asthma Phenotypes using Cluster Analysis in the Severe Asthma Research Program. [JOURNAL ARTICLE]
Am J Respir Crit Care Med 2009 Nov 5.
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.
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