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

Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study
Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study
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.
1465-9921
1-21
Loza, Matthew
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Djukanovic, Ratko
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Chung, Kian
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Horrowitz, Daniel
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Ma, Keying
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Branigan, Patrick
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Bamathan, Elliott
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Susulic, Vedrana
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Silkoff, Philip
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Sterk, Peter
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Baribaud, Fredereric
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Loza, Matthew
5b72e3d3-c7ee-4b77-91a6-406fb0e90063
Djukanovic, Ratko
d9a45ee7-6a80-4d84-a0ed-10962660a98d
Chung, Kian
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Horrowitz, Daniel
1f5da508-8e4e-4842-bda2-2cccfdad4f44
Ma, Keying
577c2c44-77f7-4951-b410-9dd022ab73d6
Branigan, Patrick
193f0c9b-0910-4500-a244-445acce12aa9
Bamathan, Elliott
4c4cb653-a8e9-4626-a09e-23655f7c8566
Susulic, Vedrana
0ae757bb-7e20-4864-b282-4f20b32b457d
Silkoff, Philip
36c5662c-a1db-4a97-a2f0-b354a93b33fa
Sterk, Peter
c337e5c5-bd25-4556-9273-7a0504a4014d
Baribaud, Fredereric
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Loza, Matthew, Djukanovic, Ratko, Chung, Kian, Horrowitz, Daniel, Ma, Keying, Branigan, Patrick, Bamathan, Elliott, Susulic, Vedrana, Silkoff, Philip, Sterk, Peter and Baribaud, Fredereric (2016) Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study. Respiratory Research, 17 (165), 1-21. (doi:10.1186/s12931-016-0482-9).

Record type: Article

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.

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More information

Accepted/In Press date: 1 December 2016
e-pub ahead of print date: 15 December 2016
Published date: 15 December 2016
Additional Information: For the ADEPT (Airways Disease Endotyping for Personalized Therapeutics) and U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcome Consortium) investigators
Organisations: Clinical & Experimental Sciences

Identifiers

Local EPrints ID: 404786
URI: https://eprints.soton.ac.uk/id/eprint/404786
ISSN: 1465-9921
PURE UUID: f16c1633-04f5-435e-8226-0cc60e7220c5
ORCID for Ratko Djukanovic: ORCID iD orcid.org/0000-0001-6039-5612

Catalogue record

Date deposited: 23 Jan 2017 14:27
Last modified: 10 Dec 2019 01:58

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Contributors

Author: Matthew Loza
Author: Kian Chung
Author: Daniel Horrowitz
Author: Keying Ma
Author: Patrick Branigan
Author: Elliott Bamathan
Author: Vedrana Susulic
Author: Philip Silkoff
Author: Peter Sterk
Author: Fredereric Baribaud

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