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

To identify novel asthma phenotypes using an unsupervised hierarchical cluster analysis.

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 two or fewer 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 three or more medications) 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 FEV(1), 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 in to their ability to attain normal lung function, age of asthma onset, atopic status, and use of oral corticosteroids.