A clustering approach to identify and characterize the asthma and chronic obstructive pulmonary disease overlap phenotype

Abstract

Background

Asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous diseases. The phenotypes that have clinical features of both asthma and COPD are still incompletely understood.

Objective

To clarify the best discriminators of the asthma-COPD overlap phenotype from asthma and COPD subgroups using a clustering approach.

Methods

This study assessed pathophysiological parameters, including mRNA expression levels of T helper cell-related transcription factors, namely, TBX21 (Th1), GATA3 (Th2), RORC (Th17), and FOXP3 (Treg), in peripheral blood mononuclear cells in asthma patients (n = 152) and in COPD patients (n = 50). Clusters were determined using k-means clustering. Exacerbations of asthma and COPD were recorded during the 1-year follow-up period.

Results

The cluster analysis revealed four biological clusters: cluster 1, predominantly patients with COPD; cluster 2, patients with an asthma-COPD overlap phenotype; cluster 3, patients with non-atopic and late-onset asthma; and cluster 4, patients with early-onset atopic asthma. Hazard ratios for exacerbation were 2.5 (95% confidence interval [CI], 1.1–5.6) in cluster 1 and 2.3 (95% CI, 1.0–5.0) in cluster 2 compared with patients in other clusters. Cluster 2 was discriminated from other clusters by total serum IgE level ≥ 310 IU/mL, blood eosinophil counts ≥ 280 cells/μL, a higher ratio of TBX21/GATA3, FEV₁/FVC ratio < 0.67, and smoking ≥ 10 pack-years with an area under the curve of 0.94 (95% CI, 0.90–0.98) in the receiver operating characteristic analysis.

Conclusions & Clinical Relevance

The asthma-COPD overlap phenotype was characterized by peripheral blood eosinophilia and higher levels of IgE despite the Th2-low endotype.

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