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Clinical Trial
. 2021 Aug;148(2):407-419.
doi: 10.1016/j.jaci.2020.12.652. Epub 2021 Feb 3.

Lung function fluctuation patterns unveil asthma and COPD phenotypes unrelated to type 2 inflammation

Edgar Delgado-Eckert  1 , Anna James  2 , Delphine Meier-Girard  1 , Maciej Kupczyk  3 , Lars I Andersson  2 , Apostolos Bossios  4 , Maria Mikus  2 , Junya Ono  5 , Kenji Izuhara  6 , Roelinde Middelveld  2 , Barbro Dahlén  4 , Mina Gaga  7 , Nikos M Siafakas  8 , Alberto Papi  9 , Bianca Beghe  10 , Guy Joos  11 , Klaus F Rabe  12 , Peter J Sterk  13 , Elisabeth H Bel  13 , Sebastian L Johnston  14 , Pascal Chanez  15 , Mark Gjomarkaj  16 , Peter H Howarth  17 , Ewa Niżankowska-Mogilnicka  18 , Sven-Erik Dahlén  19 , Urs Frey  1
Affiliations
Clinical Trial

Lung function fluctuation patterns unveil asthma and COPD phenotypes unrelated to type 2 inflammation

Edgar Delgado-Eckert et al. J Allergy Clin Immunol. 2021 Aug.

Abstract

Background: In all chronic airway diseases, the dynamics of airway function are influenced by underlying airway inflammation and bronchial hyperresponsiveness along with limitations in reversibility owing to airway and lung remodeling as well as mucous plugging. The relative contribution of each component translates into specific clinical patterns of symptoms, quality of life, exacerbation risk, and treatment success.

Objective: We aimed to evaluate whether subgrouping of patients with obstructive airway diseases according to patterns of fluctuation in lung function allows identification of specific phenotypes with distinct clinical characteristics.

Methods: We applied the novel method of fluctuation-based clustering (FBC) to twice-daily FEV1 measurements recorded over a 1-year period in a mixed group of 134 adults with mild-to-moderate asthma, severe asthma, or chronic obstructive pulmonary disease from the European BIOAIR cohort.

Results: Independently of clinical diagnosis, FBC divided patients into 4 fluctuation-based clusters with progressively increasing alterations in lung function that corresponded to patterns of increasing clinical severity, risk of exacerbation, and lower quality of life. Clusters of patients with airway disease with significantly elevated levels of biomarkers relating to remodeling (osteonectin) and cellular senescence (plasminogen activator inhibitor-1), accompanied by a loss of airway reversibility, pulmonary hyperinflation, and loss of diffusion capacity, were identified. The 4 clusters generated were stable over time and revealed no differences in levels of markers of type 2 inflammation (blood eosinophils and periostin).

Conclusion: FBC-based phenotyping provides another level of information that is complementary to clinical diagnosis and unrelated to eosinophilic inflammation, which could identify patients who may benefit from specific treatment strategies or closer monitoring.

Keywords: Asthma; chronic obstructive pulmonary disease; cluster analysis; phenotyping; remodeling.

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