Distinct Air Pollutant Exposures in Patients With Bronchiectasis Are Associated With Differences in Airway Microbiome

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Abstract Rationale: Recent data from patients with chronic respiratory diseases such as COPD suggest that air pollution is associated with changes in the airway microbiome, and lower airway dysbiosis has been linked to the severity of bronchiectasis. Here we examine whether distinct air pollution exposure patterns are associated with the composition of the lung microbiome in a bronchiectasis cohort. Method: Lower airway samples were obtained from 200 patients undergoing clinically indicated bronchoscopies. Outdoor air pollution exposure data was derived from the Chemical Speciation Network, and was available for 96 participants. Chi-square tests were used for categorical variables, reported as frequency/percentage, while continuous variables were analyzed using the Kruskal-Wallis test and reported as median/interquartile range. Hierarchical clustering (complete linkage) with Euclidean distance identified three clusters based on air pollutant levels. Using 16S rRNA gene sequencing data from lower airway samples, beta diversity was assessed using the Bray-Curtis dissimilarity index. Differential enrichment analysis across clusters was performed using LEfSe (LDA score: 2). Result: Clustering analysis revealed three distinct environmental exposure profiles (Figure 1A). Cluster 1 had elevated exposure to biomass and potassium with lower levels of traffic-related pollutants. Cluster 2 had high levels of traffic-related pollutants, including elemental carbon, nickel, and oil, along with PM2.5, soil, and silicon. Cluster 3 exhibited high sulfur and coal exposure with lower levels of soil and silicon. Beta diversity analysis showed significant differences in microbial composition between clusters (p = 0.006, Figure 1B). Genus-level analysis identified multiple taxa differentially enriched across all three clusters (Figure 1C). Differential enrichment analyses using LEfSe showed that 23 taxa at genus level were significantly enriched in the lower airways comparing the three environmental clusters. Among the top differentially enriched taxa, the lower airways of patients exposed to Cluster 1 air pollutants with Halomonas (LDA score = 3.95, p < 0.006), the lower airways of patients exposed to Cluster 2 air pollutants with Flavobacterium (LDA score = 4.6, p < 0.017), while the lower airways of patients exposed to Cluster 3 air pollutants were enriched with Haemophilus (LDA score = 4.89, p < 0.005). Conclusion: Distinct environmental exposure profiles in bronchiectasis are associated with specific shifts in lower airway microbiota, highlighting potential impacts of pollutants on microbial dysbiosis. These findings emphasize the potential role of environmental factors in the pathogenesis of bronchiectasis. Further investigation is needed to clarify the mechanisms by which these pollutants may contribute to disease progression and exacerbation risk.

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