Cluster Analysis of Inhalant Allergens in South Korea: A Computational Model of Allergic Sensitization

Abstract

Objectives. Sensitization to specific inhalant allergens is a major risk factor for the development of atopic diseases, which impose a major socioeconomic burden and significantly diminish quality of life. However, patterns of inhalant allergic sensitization have yet to be precisely described. Therefore, to enhance the understanding of aeroallergens, we performed a cluster analysis of inhalant allergic sensitization using a computational model. Methods. Skin prick data were collected from 7,504 individuals. A positive skin prick response was defined as an allergento-histamine wheal ratio ≥1. To identify the clustering of inhalant allergic sensitization, we performed computational analysis using the four-parameter unified-Richards model. Results. Hierarchical cluster analysis grouped inhalant allergens into three clusters based on the Davies-Bouldin index (0.528): cluster 1 (Dermatophagoides pteronyssinus and Dermatophagoides farinae), cluster 2 (mugwort, cockroach, oak, birch, cat, and dog), and cluster 3 (Alternaria tenus, ragweed, Candida albicans, Kentucky grass, and meadow grass). Computational modeling revealed that each allergen cluster had a different trajectory over the lifespan. Cluster 1 showed a high level (>50%) of sensitization at an early age (before 19 years), followed by a sharp decrease in sensitization. Cluster 2 showed a moderate level (10%-20%) of sensitization before 29 years of age, followed by a steady decrease in sensitization. However, cluster 3 revealed a low level (<10%) of sensitization at all ages. Conclusion. Computational modeling suggests that allergic sensitization consists of three clusters with distinct patterns at different ages. The results of this study will be helpful to allergists in managing patients with atopic diseases.

Sensitisation to Imbrasia belina (mopane worm) and other local allergens in rural Gwanda district of Zimbabwe

“…Cluster analysis is exploratory in nature and there are several different clustering algorithms to choose from. We selected Ward’s method of hierarchical clustering as it has been used in other studies assessing allergen clusters in different populations [ 62 ]. Agglomerative hierarchical clustering includes all observations into a cluster and even though three clusters were optimally selected, there are likely smaller, but important, sub clusters within the main clusters [ 63 ].…”

Aeroallergen Sensitization Status in South Korea From 2018 to 2021

“…Many studies have been conducted on the status of aeroallergen sensitization in Koreans [9][10][11][12][13][14][15][16][17][18][19][20]. However, many of these studies are old, and it is difficult to consider them representative of the national situation as only a limited number of aeroallergens were investigated, or relatively few patients were enrolled at a single institution.…”

Understanding the Patterns and Clustering of Inhalant Allergic Sensitization

“…In that study, hierarchical cluster analysis identified seven clusters: plants (grass, tree, weed, and peanut), dust mites (Dermatophagoides farina, Dermatophagoides pteronyssinus), pets (dog/cat), cockroach/shrimp, molds (Alternaria alternata, Aspergillus fumigatus), foods (egg white/cow's milk), and rodents (mouse/rat). In another study, medical records of 4,360 patients with multiple allergen simultaneous test results at a dermatology clinic in South Korea were retrospectively reviewed and a cluster analysis was performed to elucidate the allergen-specific IgE cluster pattern [5]. In total, 39 items were grouped into eight clusters and each cluster had characteristic features.…”

“…In the current issue of Clinical and Experimental Otorhino-laryngology, Kim et al [5] investigated patterns of sensitization to inhalant allergens through a computational analysis using a four-parameter unified Richards model to identify the clustering of inhalant allergic sensitization. In total, 7,504 individuals' skin prick data were collected and analyzed.…”

“…As allergic sensitization is a significant risk factor for atopic diseases, monitoring the prevalence and patterns of IgE-mediated sensitization in populations over time is important for the control and prevention of allergic diseases. The authors [5] found that inhalant allergens in the South Korea consisted of three hierarchical clusters and that these three clusters had distinct sensitization-desensitization patterns according to age. These findings could help us understand the characteristics and behavior of inhalant allergens, which may influence the diagnosis and treatment algorithms of allergic diseases.…”