Distinct Endotypes of Pediatric Rhinitis Based on Cluster Analysis

Abstract

Purpose: Despite the wide spectrum of pediatric rhinitis, endotyping of rhinitis based on type 2 inflammation and bronchial hyper-responsiveness (BHR) is lacking. This study aimed to investigate endotypes of pediatric rhinitis using cluster analysis.

Methods: Cluster analysis was performed on data from 241 children with rhinitis by using 12 variables reflecting clinical characteristics of skin prick, laboratory, and pulmonary function tests. After extracting clusters, between-cluster differences in clinical features, such as nasal symptom scores and asthma comorbidity, were assessed to investigate the association between the endotypes and clinical features.

Results: Four clusters were extracted by hierarchical cluster analysis. Cluster 1 (n = 32 [13.3%]) was the non-allergic rhinitis dominant cluster with low type 2 inflammation and the lowest rate of BHR. Patients in cluster 1 had the mildest nasal symptoms and no asthma comorbidity. Cluster 2 (n = 114 [47.3%]) was the largest cluster and exhibited intermediate type 2 inflammation and low BHR. Cluster 3 (n = 65 [27.0%]) showed high type 2 inflammation and intermediate BHR. However, the severity of nasal symptoms and asthma comorbidity in this cluster were comparable with those in cluster 2. Cluster 4 (n = 30 [12.4%]) revealed high type 2 inflammation and BHR with potential functional airway impairment. Additionally, cluster 4 displayed the most severe nasal symptoms and frequent asthma comorbidity.

Conclusions: Four distinct endotypes of pediatric rhinitis based on allergen sensitization, type 2 inflammation, and BHR correlate to symptoms and asthma comorbidity. These endotypes may aid clinicians in understanding the wide spectrum of pediatric rhinitis.

Keywords: Allergic rhinitis; asthma; bronchial hyper-responsiveness; bronchial hyperreactivity; child; cluster analysis; pediatric rhinitis; rhinitis; type 2 inflammation.

Fig. 1. Heatmap of the hierarchical clustering. The dendrogram on the left side shows cluster variables, and that on the bottom shows the 241 pediatric patients in this study. A total of 4 clusters of pediatric patients were obtained as illustrated on the top of dendrogram.

FEV1, forced expiratory volume in one second; FVC, forced vital capacity; PC20, provocative concentration < 16 mg/mL that caused a 20% decrease in forced expiratory volume in one second; IgE, immunoglobulin E; HDM, house dust mite.

Fig. 2. Exploratory factor analysis based on principal component analysis and multiple correspondence analysis. The first and second principal components accounted for 21.9% and 15.6% of the total variance, respectively. (A) Cluster variables including age, type 2 inflammatory markers, parameters for bronchial hyper-responsiveness, and sensitization to allergens against the first 2 principal components. Arrows are displayed for cluster variables against the first 2 principal components. (B) Individual patients were categorized by the cluster against first 2 principal components. The dots are displayed for individual patients, and they are divided into 4 colors based on the cluster.

FAMD, factor analysis of mixed data; FEV1, forced expiratory volume in one second; FVC, forced vital capacity; PC20, provocative concentration < 16 mg/mL that caused a 20% decrease in forced expiratory volume in one second; IgE, immunoglobulin E; HDM, house dust mite.

Fig. 3. Modified heat map of clinical and immunological parameters according to clusters. Rows consists of clinical and immunological parameters including variables used for cluster analysis, and columns define clusters of children with AR. Median values for each parameter are provided for each cluster. FEV1, FVC, FEV1/FVC, FEF25%–75% were adjusted for age, sex, height, and weight and presented as percent predicted values. For characterization of clusters, multiple group comparison for between-cluster differences is visualized with a color code, as shown in the legend. Because low values of FEV1, FVC, FEV1/FVC, FEF25%–75%, and PC20 indicate bronchial hyper-responsiveness and impaired lung function, the lower values of these parameters were colored for readability.

FEV1, forced expiratory volume in one second; FVC, forced vital capacity; FEF25%–75%, forced mid-expiratory flow; HDM, house dust mite; PC20, provocative concentration < 16 mg/mL that caused a 20% decrease in forced expiratory volume in one second. ^*The variables including in the clustering analysis.

Fig. 4. Total nasal VAS score in each cluster. Total nasal VAS score was significantly different across all clusters (P = 0.016), and cluster 4 had the highest total nasal VAS score among all clusters.

VAS, visual analog scale. ^*P < 0.05; ^†P < 0.10.

Fig. 5. Kaplan-Meier plot for asthma morbidity according to clusters. Twenty-four patients (11.6%) had been diagnosed with asthma prior to time of enrollment (cluster 1: 0%, cluster 2: 14%, cluster 3: 10.8%, and cluster 4: 16.6%). During the follow-up periods, 13 (5.4%) patients were additionally diagnosed with asthma (cluster 1: 0%, cluster 2: 2.6%, cluster 3: 7.7%, and cluster 4: 16.6%). Clusters 2, 3, and 4 had higher asthma comorbidity compared with cluster 1 (cluster 2: HR of 11.71 with 95% CI [1.61–inf], cluster 3: HR of 13.21 with 95% CI [1.74–inf], and cluster 4: HR of 25.21 with 95% CI [3.25–inf]). In addition, cluster 4 tended to have higher asthma comorbidity compared with cluster 2 (HR of 2.13 with 95% CI [0.99–4.58]).

HR, hazard ratio; CI, confidence interval.