Dataset Information

Application of the asthma phenotype algorithm from the Severe Asthma Research Program to an urban population.

ABSTRACT:

Rationale

Identification 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.

Methods

The 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.

Results

Asthma 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.

Conclusions

Application 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 registration

Clinicaltrials.gov NCT00212537.

SUBMITTER: Patrawalla P

PROVIDER: S-EPMC3441500 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Application of the asthma phenotype algorithm from the Severe Asthma Research Program to an urban population.

Patrawalla Paru P Kazeros Angeliki A Rogers Linda L Shao Yongzhao Y Liu Mengling M Fernandez-Beros Maria-Elena ME Shang Shulian S Reibman Joan J

PloS one 20120913 9

<h4>Rationale</h4>Identification 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.<h4>Methods</ ...[more]

PMID: 23028556

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Project description:RationaleSevere asthma (SA) remains poorly understood. Mast cells (MC) are implicated in asthma pathogenesis, but it remains unknown how their phenotype, location, and activation relate to asthma severity.ObjectivesTo compare MC-related markers measured in bronchoscopically obtained samples with clinically relevant parameters between normal subjects and subjects with asthma to clarify their pathobiologic importance.MethodsEndobronchial biopsies, epithelial brushings, and bronchoalveolar lavage were obtained from subjects with asthma and normal subjects from the Severe Asthma Research Program (N = 199). Tryptase, chymase, and carboxypeptidase A (CPA)3 were used to identify total MC (MC(Tot)) and the MC(TC) subset (MCs positive for both tryptase and chymase) using immunostaining and quantitative real-time polymerase chain reaction. Lavage was analyzed for tryptase and prostaglandin D2 (PGD2) by ELISA.Measurements and main resultsSubmucosal MC(Tot) (tryptase-positive by immunostaining) numbers were highest in "mild asthma/no inhaled corticosteroid (ICS) therapy" subjects and decreased with greater asthma severity (P = 0.002). In contrast, MC(TC) (chymase-positive by immunostaining) were the predominant (MC(TC)/MC(Tot) > 50%) MC phenotype in SA (overall P = 0.005). Epithelial MC(Tot) were also highest in mild asthma/no ICS, but were not lower in SA. Instead, they persisted and were predominantly MC(TC). Epithelial CPA3 and tryptase mRNA supported the immunostaining data (overall P = 0.008 and P = 0.02, respectively). Lavage PGD2 was higher in SA than in other steroid-treated groups (overall P = 0.02), whereas tryptase did not differentiate the groups. In statistical models, PGD2 and MC(TC)/MC(Tot) predicted SA.ConclusionsSevere asthma is associated with a predominance of MC(TC) in the airway submucosa and epithelium. Activation of those MC(TC) may contribute to the increases in PGD2 levels. The data suggest an altered and active MC population contributes to SA pathology.

Dataset Information

Application of the asthma phenotype algorithm from the Severe Asthma Research Program to an urban population.

Rationale

Methods

Results

Conclusions

Trial registration

Publications

Application of the asthma phenotype algorithm from the Severe Asthma Research Program to an urban population.

Similar Datasets

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