Application of the Asthma Phenotype Algorithm from the Severe Asthma Research Program to an Urban Population

Paru Patrawalla,Linda Rogers,Joan Reibman,Yongzhao Shao,Maria-Elena Fernandez-Beros,Shulian Shang,Mengling Liu,Angeliki Kazeros,Christian Taube

doi:10.1371/journal.pone.0044540

Abstract

RationaleIdentification and characterization of asthma phenotypes are challenging due to disease complexity and heterogeneity. The Severe Asthma Research Program (SARP) used unsupervised cluster analysis to define 5 phenotypically distinct asthma clusters that they replicated using 3 variables in a simplified algorithm. We evaluated whether this simplified SARP algorithm could be used in a separate and diverse urban asthma population to recreate these 5 phenotypic clusters.MethodsThe SARP simplified algorithm was applied to adults with asthma recruited to the New York University/Bellevue Asthma Registry (NYUBAR) to classify patients into five groups. The clinical phenotypes were summarized and compared.ResultsAsthma subjects in NYUBAR (n = 471) were predominantly women (70%) and Hispanic (57%), which were demographically different from the SARP population. The clinical phenotypes of the five groups generated by the simplified SARP algorithm were distinct across groups and distributed similarly to those described for the SARP population. Groups 1 and 2 (6 and 63%, respectively) had predominantly childhood onset atopic asthma. Groups 4 and 5 (20%) were older, with the longest duration of asthma, increased symptoms and exacerbations. Group 4 subjects were the most atopic and had the highest peripheral eosinophils. Group 3 (10%) had the least atopy, but included older obese women with adult-onset asthma, and increased exacerbations.ConclusionsApplication of the simplified SARP algorithm to the NYUBAR yielded groups that were phenotypically distinct and useful to characterize disease heterogeneity. Differences across NYUBAR groups support phenotypic variation and support the use of the simplified SARP algorithm for classification of asthma phenotypes in future prospective studies to investigate treatment and outcome differences between these distinct groups.Trial RegistrationClinicaltrials.gov NCT00212537

Highlights

Asthma affects more than 17 million American adults, and is estimated to cost $20.7 billion [1,2]
We report that application of the simplified Severe Asthma Research Program (SARP) algorithm to an urban population reproduced groups with similar phenotypic characteristics to those reported for the SARP population
We evaluated whether a separate cluster analysis of the diverse New York University/Bellevue Asthma Registry (NYUBAR) urban population would result in clusters that were similar to those in SARP

Summary

Introduction

Asthma affects more than 17 million American adults, and is estimated to cost $20.7 billion [1,2]. Despite guideline-recommended treatment strategies, asthma morbidity remains high, with almost 50% of adults reporting an exacerbation in the previous year [3]. Asthma is characterized by chronic inflammation, variable symptoms and airflow limitation [4]. Asthma is heterogeneous and appropriate classification of asthma phenotypes using clinical characteristics and immunologic biomarkers can improve our understanding of asthma pathogenesis, therapeutics and targeted management. Cluster analysis, incorporating demographic, clinical and biologic variables, has recently been used to identify distinct asthma phenotype groups [5,6].

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