A Systemic Inflammatory Endotype of Asthma With More Severe Disease Identified by Unbiased Clustering of the Serum Cytokine Profile

Abstract

Asthma is considered as a clinical and molecularly heterogeneous disorder. Systemic inflammation is suggested to play an important role in a group of asthma patients. We hypothesized that there is a subgroup of patients with asthma characterized by systemic inflammation. In this study, we aimed to discriminate asthma subtypes based on circulating biomarkers and to determine whether a systemic inflammatory endotype of asthma could be identified. In the present cross-sectional study, 50 patients with untreated asthma were prospectively recruited from a single academic outpatient clinic, and characterized with respect to clinical, functional, and inflammatory parameters. The expression profiles of 20 serum cytokines were assessed by anti-human cytokine antibody array. Then, hierarchical clustering analysis was performed based on principal component analysis (PCA)-transformed data to classify the clinical groups. PCA showed that 6 independent components accounted for 80.113% of the variance, and PCA-based hierarchical clustering identified 3 endotypes. One of the endotypes was evidenced by elevated systemic inflammation markers such as leptin, vascular endothelial growth factor (VEGF), and reduced levels of soluble receptor for advanced glycation end products (sRAGE), an anti-inflammatory molecule. More female patients were included, with higher circulating neutrophil counts and more severe symptoms. In conclusion, we identified an endotype of asthma characterized by systemic inflammation and severe symptoms. Increased levels of VEGF, leptin and decreased level of sRAGE may contribute to the systemic inflammation of this asthma endotype.

FIGURE 1

Screeplot of principal component analysis. Six components had eigen values ≥1 (dotted line, and because 0.981 is approximately equal to 1, we also captured the sixth component)) and explained 80.113% of the variance.

FIGURE 2

Hierarchical clustering based on PCA. Each column is a component, and each row is an individual patient. Numbers at the right side of the heat map are the patient numbers. Left, dendrogram showing similarity of groups. Right, 3 endotypes are indicated by vertical bars.

FIGURE 3

Pairwise comparisons of serum cytokine concentrations between endotypes. Data were analyzed with 1-way analysis of variance with the least significant difference post hoc test. E = endotype, EGF = epidermal growth factor, GM-CSF = Granulocyte-macroprhage colony-stimulating factor, IFN = interferon, IL = interleukin, sRAGE = soluble receptor for advanced glycation end products, TGF-β1 = transforming growth factor-beta 1, TNF = tumor necrosis factor, VEGF = vascular endothelial growth factor.

FIGURE 4

Pairwise comparisons of clinical parameters between endotypes. Data were analyzed with one-way analysis of variance with the least significant difference post hoc test. ACQ-5 = 5-item Asthma Control Questionnaire, FEV1 = forced expiratory volume in 1 second, FVC = forced vital capacity