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Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.

ABSTRACT: BACKGROUND:Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED. METHODS:Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants (n?=?156) and independently on data from a subset of U-BIOPRED asthma participants (n?=?82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset (n?=?397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13. RESULTS:Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was "mild, good lung function, early onset", with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a "moderate, hyper-responsive, eosinophilic" phenotype, with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a "mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic" phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a "severe uncontrolled, severe reversible obstruction, mixed granulocytic" phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort. CONCLUSIONS:Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies. TRIAL REGISTRATION:NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013.

SUBMITTER: Loza MJ

PROVIDER: S-EPMC5159977 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.

Loza Matthew J MJ Djukanovic Ratko R Chung Kian Fan KF Horowitz Daniel D Ma Keying K Branigan Patrick P Barnathan Elliot S ES Susulic Vedrana S VS Silkoff Philip E PE Sterk Peter J PJ Baribaud Frédéric F

Respiratory research 20161215 1

<h4>Background</h4>Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED.<h4>Methods</h4>Fuzzy parti ...[more]

PMID: 27978840

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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:Asthma is a biologically heterogeneous disease and development of novel therapeutics requires understanding of pathophysiologic phenotypes. There is uncertainty regarding the stability of clinical characteristics and biomarkers in asthma over time. This report presents the longitudinal stability over 12 months of clinical characteristics and clinically accessible biomarkers from ADEPT.Mild, moderate, and severe asthma subjects were assessed at 5 visits over 12 months. Assessments included patient questionnaires, spirometry, bronchodilator reversibility, fractional exhaled nitric oxide (FENO), and biomarkers measured in induced sputum.Mild (n?=?52), moderate (n?=?55), and severe (n?=?51) asthma cohorts were enrolled from North America and Western Europe. For all clinical characteristics and biomarkers, group mean data showed no significant change from visit to visit. However, individual data showed considerable variability. FEV1/FVC ratio showed excellent reproducibility while pre-bronchodilator FEV1 and FVC were only moderately reproducible. Of note bronchodilator FEV1 reversibility showed low reproducibility, with the nonreversible phenotype much more reproducible than the reversible phenotype. The 7-item asthma control questionnaire (ACQ7) demonstrated moderate reproducibility for the combined asthma cohorts, but the uncontrolled asthma phenotype (ACQ7?>?1.5) was inconstant in mild and moderate asthma but stable in severe asthma. FENO demonstrated good reproducibility, with the FENO-low phenotype (FENO?<?35 ppb) more stable than the FENO-high phenotype (FENO???35 ppb). Induced sputum inflammatory phenotypes showed marked variability across the 3 sputum samples taken over 6 months.The ADEPT cohort showed group stability, individual stability in some parameters e.g. low FEV1/FVC ratio, and low FENO, but marked individual variability in other clinical characteristics and biomarkers e.g. type-2 biomarkers over 12 months. This variability is possibly related to seasonal variations in climate and allergen exposure, medication changes and acute exacerbations. The implications for patient selection strategies based on clinical biomarkers may be considerable.

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Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.

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Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.

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