Dataset Information

Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.

ABSTRACT:

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.

Objectives

To 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 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.

Conclusions

Five distinct clinical phenotypes of asthma have been identified using unsupervised hierarchical cluster analysis. All clusters contain subjects who meet the American Thoracic Society definition of severe asthma, which supports clinical heterogeneity in asthma and the need for new approaches for the classification of disease severity in asthma.

SUBMITTER: Moore WC

PROVIDER: S-EPMC2822971 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4; P < .001). Lower whole-lung Jacobian and ADI values were associated with greater cluster severity. Compared to cluster 1, cluster 5 lung expansion was 31% smaller (Jacobian in SARP III cohort: 2.31 ± 0.6 vs 1.61 ± 0.3, respectively, P < .001) and 34% more isotropic (ADI in SARP III cohort: 0.40 ± 0.1 vs 0.61 ± 0.2, P < .001). Within-lung Jacobian and ADI SDs decreased as severity worsened (Jacobian SD in SARP III cohort: 0.90 ± 0.4 for cluster 1; 0.79 ± 0.3 for cluster 2; 0.62 ± 0.2 for cluster 3; 0.63 ± 0.2 for cluster 4; and 0.41 ± 0.2 for cluster 5; P < .001). Conclusion Quantitative CT assessments of the degree and intraindividual regional variability of lung expansion distinguished between well-established clinical phenotypes among participants with asthma from the Severe Asthma Research Program study. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Verschakelen in this issue.

Project description:BackgroundAsthma is a heterogeneous disease with variability among patients in characteristics such as lung function, symptoms and control, body weight, markers of inflammation, and responsiveness to glucocorticoids (GC). Cluster analysis of well-characterized cohorts can advance understanding of disease subgroups in asthma and point to unsuspected disease mechanisms. We utilized an hypothesis-free cluster analytical approach to define the contribution of obesity and related variables to asthma phenotype.Methodology and principal findingsIn a cohort of clinical trial participants (n = 250), minimum-variance hierarchical clustering was used to identify clinical and inflammatory biomarkers important in determining disease cluster membership in mild and moderate persistent asthmatics. In a subset of participants, GC sensitivity was assessed via expression of GC receptor alpha (GCRα) and induction of MAP kinase phosphatase-1 (MKP-1) expression by dexamethasone. Four asthma clusters were identified, with body mass index (BMI, kg/m(2)) and severity of asthma symptoms (AEQ score) the most significant determinants of cluster membership (F = 57.1, p<0.0001 and F = 44.8, p<0.0001, respectively). Two clusters were composed of predominantly obese individuals; these two obese asthma clusters differed from one another with regard to age of asthma onset, measures of asthma symptoms (AEQ) and control (ACQ), exhaled nitric oxide concentration (F(E)NO) and airway hyperresponsiveness (methacholine PC(20)) but were similar with regard to measures of lung function (FEV(1) (%) and FEV(1)/FVC), airway eosinophilia, IgE, leptin, adiponectin and C-reactive protein (hsCRP). Members of obese clusters demonstrated evidence of reduced expression of GCRα, a finding which was correlated with a reduced induction of MKP-1 expression by dexamethasoneConclusions and significanceObesity is an important determinant of asthma phenotype in adults. There is heterogeneity in expression of clinical and inflammatory biomarkers of asthma across obese individuals. Reduced expression of the dominant functional isoform of the GCR may mediate GC insensitivity in obese asthmatics.

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.