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