TY - JOUR
T1 - Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study
AU - For the ADEPT (Airways Disease Endotyping for Personalized Therapeutics)
AU - U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcome Consortium) investigators
AU - Loza, Matthew J.
AU - Djukanovic, Ratko
AU - Chung, Kian Fan
AU - Horowitz, Daniel
AU - Ma, Keying
AU - Branigan, Patrick
AU - Barnathan, Elliot S.
AU - Susulic, Vedrana S.
AU - Silkoff, Philip E.
AU - Sterk, Peter J.
AU - Baribaud, Frédéric
AU - Strambu, I.
AU - Laviolette, M.
AU - Singh, D.
AU - FitzGerald, J. M.
AU - Lam, S.
AU - Kelsen, S.
AU - Eich, A.
AU - Ludwig-Sengpiel, A.
AU - hupp, G. C.
AU - Backer, V.
AU - Porsbjerg, C.
AU - Girodet, P. O.
AU - Berger, P.
AU - Leigh, R.
AU - Kline, J.
AU - Dransfield, M.
AU - Calhoun, W.
AU - Hussaini, A.
AU - Khatri, S.
AU - Chanez, P.
AU - Ian, Adcock
AU - Fleming Louis, J.
AU - David, Gibeon
AU - Sile, Hu
AU - Scott, Kuo
AU - Sally, Meah
AU - Andrea, Meiser
AU - Stelios, Pavlidis
AU - Christos, Rossios
AU - Kirsty, Russell
AU - Kai, Sun
AU - Coen, Wiegman
AU - Xian, Yang
AU - Nora, Adriaens
AU - Ariane, Wagener
AU - Kees, van Drunen
AU - Marianne, van de Pol
AU - Wim, van Aalderen
AU - Amphun, Chaiboonchoe
N1 - Publisher Copyright:
© 2016 The Author(s).
PY - 2016/12/15
Y1 - 2016/12/15
N2 - 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.
AB - 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.
KW - Biological markers
KW - Cluster analysis
KW - Observational study
UR - https://www.scopus.com/pages/publications/85006434882
U2 - 10.1186/s12931-016-0482-9
DO - 10.1186/s12931-016-0482-9
M3 - Article
C2 - 27978840
AN - SCOPUS:85006434882
SN - 1465-9921
VL - 17
JO - Respiratory Research
JF - Respiratory Research
IS - 1
M1 - 165
ER -
SDG 3 Good Health and Well-being