Volume 74, Issue 5 pp. 953-963
ORIGINAL ARTICLE

Data-driven adult asthma phenotypes based on clinical characteristics are associated with asthma outcomes twenty years later

Anne Boudier

Anne Boudier

IAB, Team of Environmental Epidemiology Applied To Reproduction and Respiratory Health, INSERM, Université Grenoble Alpes, CNRS, Grenoble, France

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Sébastien Chanoine

Sébastien Chanoine

IAB, Team of Environmental Epidemiology Applied To Reproduction and Respiratory Health, INSERM, Université Grenoble Alpes, CNRS, Grenoble, France

Faculté de Pharmacie, Université Grenoble Alpes, Grenoble, France

Pôle Pharmacie, CHU Grenoble Alpes, Grenoble, France

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Simone Accordini

Simone Accordini

Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy

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Josep M. Anto

Josep M. Anto

ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain

Universitat Pompeu Fabra (UPF), Barcelona, Spain

CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

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Xavier Basagaña

Xavier Basagaña

ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain

Universitat Pompeu Fabra (UPF), Barcelona, Spain

CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

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Jean Bousquet

Jean Bousquet

Epidemiological and Public Health Approaches, INSERM, U1168: Aging and Chronic Diseases, Villejuif, France

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Pascal Demoly

Pascal Demoly

Pneumology Department, CHU Montpellier, Montpellier, France

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Judith Garcia-Aymerich

Judith Garcia-Aymerich

ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain

Universitat Pompeu Fabra (UPF), Barcelona, Spain

CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

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Frédéric Gormand

Frédéric Gormand

Pneumology Department, CHU de Lyon, Lyon, France

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Joachim Heinrich

Joachim Heinrich

Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital of Ludwig Maximilians University, Comprehensive Pneumology Centre Munich, German Centre for Lung Research, Muenchen, Germany

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Christer Janson

Christer Janson

Department of Medical Sciences: Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden

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Nino Künzli

Nino Künzli

Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland

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Régis Matran

Régis Matran

CHU, Université de Lille, Lille, France

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Christophe Pison

Christophe Pison

Clinique Universitaire de Pneumologie, Pôle Thorax et Vaisseaux, CHU de Grenoble, INSERM U1055, Université Grenoble Alpes, Grenoble, France

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Chantal Raherison

Chantal Raherison

INSERM Bordeaux Population Health Research Center, Team EPICENE, UMR 1219, Université Bordeaux, Bordeaux, France

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Jordi Sunyer

Jordi Sunyer

ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain

Universitat Pompeu Fabra (UPF), Barcelona, Spain

CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

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Raphaëlle Varraso

Raphaëlle Varraso

Epidemiological and Public Health Approaches, INSERM, U1168: Aging and Chronic Diseases, Villejuif, France

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Deborah Jarvis

Deborah Jarvis

National Heart and Lung Institute, Imperial College, London, UK

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Bénédicte Leynaert

Bénédicte Leynaert

Unit 1152, Team of Epidemiology, INSERM, University Paris-Diderot, Paris, France

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Isabelle Pin

Isabelle Pin

IAB, Team of Environmental Epidemiology Applied To Reproduction and Respiratory Health, INSERM, Université Grenoble Alpes, CNRS, Grenoble, France

Pediatric Department, CHU Grenoble, Grenoble, France

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Valérie Siroux

Corresponding Author

Valérie Siroux

IAB, Team of Environmental Epidemiology Applied To Reproduction and Respiratory Health, INSERM, Université Grenoble Alpes, CNRS, Grenoble, France

Correspondence

Valérie Siroux, Institute for Advanced Biosciences, Inserm U1209 /CNRS UMR5309, Université Grenoble-Alpes, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France.

Email: [email protected]

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First published: 13 December 2018
Citations: 21

Funding information

The present analysis was funded by National PHRC 2012, the scientific committee “AGIR pour les Maladies Chroniques.” EGEA data collection was funded in part by Hospital program of clinical research (PHRC), Paris, PHRC-Grenoble, national PHRC 2012, Scientific committee “AGIR pour les Maladies Chroniques,” Merck Sharp & Dohme (MSD), and the GA2LEN project (Global Allergy and Asthma European Network). The ECRHS data collection has had multiple funding sources within each center (listed in the Appendix  S1). The coordination of ECRHS3 was funded by the Medical Research Council (Grant Number 92091).

Abstract

Background

Research based on cluster analyses led to the identification of particular phenotypes confirming phenotypic heterogeneity of asthma. The long-term clinical course of asthma phenotypes defined by clustering analysis remains unknown, although it is a key aspect to underpin their clinical relevance. We aimed to estimate risk of poor asthma events between asthma clusters identified 20 years earlier.

Methods

The study relied on two cohorts of adults with asthma with 20-year follow-up, ECRHS (European Community Respiratory Health Survey) and EGEA (Epidemiological study on Genetics and Environment of Asthma). Regression models were used to compare asthma characteristics (current asthma, asthma exacerbations, asthma control, quality of life, and FEV1) at follow-up and the course of FEV1 between seven cluster-based asthma phenotypes identified 20 years earlier.

Results

The analysis included 1325 adults with ever asthma. For each asthma characteristic assessed at follow-up, the risk for adverse outcomes differed significantly between the seven asthma clusters identified at baseline. As compared with the mildest asthma phenotype, ORs (95% CI) for asthma exacerbations varied from 0.9 (0.4 to 2.0) to 4.0 (2.0 to 7.8) and the regression estimates (95% CI) for FEV1% predicted varied from 0.6 (−3.5 to 4.6) to −9.9 (−14.2 to −5.5) between clusters. Change in FEV1 over time did not differ significantly across clusters.

Conclusion

Our findings show that the long-term risk for poor asthma outcomes differed between comprehensive adult asthma phenotypes identified 20 years earlier, and suggest a strong tracking of asthma activity and impaired lung function over time.

Graphical Abstract

Risk for poor asthma outcomes varied between cluster-based asthma phenotypes defined 20 years earlier. The clinical prognosis of the cluster-based asthma phenotypes was stronger as compared to classical phenotypes. There was a tracking of asthma activity and lung function over the life course for each asthma cluster.

CONFLICT OF INTEREST

DJ reports grants from MRC, grants from EU, grants from Asthma UK, during the conduct of the study. IP reports other from Astra Zeneca, other from Novartis, other from GSK, outside the submitted work. PD reports personal fees from ALK, personal fees from Stallergènes Greer, personal fees from MEDA-MYLAN, personal fees from Chiesi, personal fees from Thermo Fisher Scientific, personal fees from Menarini, personal fees from AstraZeneca, personal fees from ASIT Biotech, outside the submitted work. CP reports grants, personal fees, and nonfinancial support from GSK France, grants, personal fees and nonfinancial support from Novartis France, grants, personal fees, and nonfinancial support from Actélion France, grants, personal fees, and nonfinancial support from BIF France, outside the submitted work. JB reports personal fees and other from Chiesi, Cipla, Hikma, Menarini, Mundipharma, Mylan, Novartis, Sanofi-Aventis, Takeda, Teva, Uriach, other from Kyomed, from null, outside the submitted work. SC reports personal fees from AstraZeneca, non-financial support from Boehringer Ingelheim, nonfinancial support from Actelion Pharmaceuticals, nonfinancial support from MSD, outside the submitted work. VS reports personal fees from TEVA, AstraZeneca and Novartis France, outside the submitted work. All other authors declare no conflicts of interests.

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