Distinct Nasal Microbiome Profiles and Prediction Model for Allergic Rhinitis, Nonallergic Rhinitis, and Healthy Children

Abstract

Objectives: Adult studies reported differences in nasal microbiota composition among patients with allergic rhinitis (AR), nonallergic rhinitis (NAR), and healthy controls (HCs), whereas pediatric data remain limited. This study compared the nasal microbiomes of children with AR, NAR, and HC, investigated factors influencing these microbiomes, and developed a predictive model to differentiate these conditions based on microbiome data. Methods: Nasal swab samples were collected from children with AR, NAR, and HC. Microbial characterization was performed using 16S rDNA sequencing to analyze bacterial composition. Relevant demographic data and influencing factors were collected. Results: Sixty participants (median age 6.3 [4.3–8.4] years, 51.6% males) were categorized into AR (n = 24), NAR (n = 14), and HC (n = 22). Significant differences in alpha and beta diversity were observed among groups (p < 0.01 and p < 0.05, respectively). The AR and NAR groups exhibited lower Pielou's evenness than HC (FDR-adjusted p < 0.01 and p = 0.02, respectively). Compared to HC, the AR group showed a higher abundance of Escherichia-Shigella, Negativicoccus, and Campylobacter. In contrast, Dolosigranulum was enriched while the Enterobacteriaceae family was depleted in the NAR group. Household pets and breastfeeding duration significantly influenced nasal microbiome diversity regardless of the disease groups. A prediction model of nasal microbial distribution for AR, NAR, and HC identified 14 taxa critical for distinguishing these groups (accuracy of 0.83). Conclusion: This pilot study identified preliminary differences in nasal microbiome diversity and composition among children with AR, NAR, and HC. Differential microbial abundances may reflect distinct rhinitis phenotypes. However, these findings are hypothesis-generating and require validation in larger, independent cohorts.