C15-01 Nasal Microbiome and Nasal Epithelial Transcriptomic and DNA Methylation Profiles in Puerto Rican Youth

Background The airway microbiome may influence airway inflammation and asthma pathogenesis in youth, yet the relationships between nasal microbiome community structure and nasal epithelial transcriptomic profiles (T2HIGH, T17HIGH, and T2/T17LOW) and DNA methylation markers remains undefined. This study aims to address (i) whether the nasal microbiome maps onto nasal transcriptomic profiles and (ii) whether nasal microbiome community structure is linked to nasal epithelial DNA methylation in children and adolescents. Methods We analyzed 478 nasal meta-transcriptomic microbiome profiles from youth with (cases, n = 234) and without (controls, n = 244) asthma aged 9-20 years who participated in EVA-PR (the Epigenetic Variation and Childhood Asthma in Puerto Ricans Study). After prevalence filtering, we quantified ɑ- and β-diversity to assess global and pairwise differences across nasal epithelial transcriptomic profiles, adjusting for age, sex, BMI z-score, secondhand smoke exposure, asthma status, and batch effects. Partitioning around medoids (PAM) clustering defined data-driven nasal “community types,” which were then tested for associations with host nasal epithelial transcriptomic profiles and DNA methylation. Genus-level differential abundance and CpG-level differential methylation were evaluated using covariate-adjusted models with false discovery rate (FDR) control and Bonferroni sensitivity thresholds for stringency. Results Airway epithelial transcriptomic profile was significantly associated with nasal microbiome composition (overall p < 0.001), explaining 3.1% of between-sample variation. Pairwise comparisons showed that T2HIGH samples were compositionally distinct from both T17HIGH and T2/T17LOW groups. Unsupervised clustering identified three stable nasal community types dominated by Mycobacterium (n = 310), Corynebacterium (n = 138), and Moraxella (n = 30). These clusters differed by age, sex, BMI z-score, total IgE, eosinophils, and transcriptomic profiles (all at p < 0.001). In adjusted models, T2HIGH profiles were more likely to be enriched for Mycobacterium-enriched communities (FDR = 0.020), whereas T17HIGH profiles were enriched for Moraxella-enriched communities (FDR ≤ 0.023). At the taxon level, multiple genera showed profile-specific enrichment after FDR correction (Figure). Finally, microbiome community type was also associated with nasal epithelial DNA methylation markers. Compared with cluster 1, cluster 2 showed 197 differentially methylated CpGs (FDR < 0.05; 18 Bonferroni-filtered) and cluster 3 showed 58,661 differentially methylated CpGs (FDR < 0.05; 76 Bonferroni-filtered). Conclusion In this study of a high-risk population for asthma, nasal microbiome community structure was strongly associated with specific airway transcriptomic profiles and DNA methylation markers in nasal epithelium. These findings support a microbiome-epithelium-epigenome axis in airway inflammation that may play a role in asthma pathogenesis. This abstract is funded by: NIH