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Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program
Wendy C Moore1, Deborah A Meyers, Sally E Wenzel
1Center for Human Genomics, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA. wmoore@wfubmc.edu
American Journal of Respiratory and Critical Care Medicine
|November 7, 2009
Summary
This study identified five distinct asthma phenotypes using cluster analysis. These findings highlight the clinical diversity of severe asthma and suggest new classification approaches are needed.
Area of Science:
- Pulmonology and Respiratory Medicine
- Clinical Phenotyping
- Asthma Research
Background:
- The Severe Asthma Research Program (SARP) cohort comprises individuals with persistent asthma, extensively phenotyped.
- Previous studies utilized univariate methods to compare mild, moderate, and severe asthma characteristics.
Purpose of the Study:
- To discover novel asthma phenotypes through unsupervised hierarchical cluster analysis.
- To better understand the heterogeneity within severe asthma classifications.
Main Methods:
- Reduced 628 variables to 34 core variables by data transformation and elimination.
- Applied hierarchical cluster analysis to a cohort of 726 asthma subjects.
Main Results:
- Identified five distinct asthma phenotypes.
- Phenotypes varied in age of onset, atopic status, lung function, medication needs, and oral corticosteroid use.
- One cluster comprised older, obese women with late-onset nonatopic asthma and frequent exacerbations.
Conclusions:
- Unsupervised hierarchical cluster analysis revealed five distinct clinical asthma phenotypes.
- All identified clusters included subjects meeting the definition of severe asthma.
- Findings underscore asthma's clinical heterogeneity, necessitating advanced disease severity classification methods.
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