Antibiotic Treatments During Infancy, Changes in Nasal Microbiota, and Asthma Development: Population-based Cohort Study

Abstract

Background: Early-life exposures to antibiotics may increase the risk of developing childhood asthma. However, little is known about the mechanisms linking antibiotic exposures to asthma. We hypothesized that changes in the nasal airway microbiota serve as a causal mediator in the antibiotics-asthma link.

Methods: In a population-based birth-cohort study in Finland, we identified longitudinal nasal microbiota profiles during age 2-24 months using 16S rRNA gene sequencing and an unsupervised machine learning approach. We performed a causal mediation analysis to estimate the natural direct effect of systemic antibiotic treatments during age 0-11 months on risks of developing physician-diagnosed asthma by age 7 years and the natural indirect (causal mediation) effect through longitudinal changes in nasal microbiota.

Results: In our birth cohort of 697 children, 8.0% later developed asthma. Exposure to ≥2 antibiotic treatments during age 0-11 months was associated with a 4.0% increase in the absolute risk of developing asthma (absolute increase, 95% CI, .9-7.2%; P = .006). The unsupervised clustering approach identified 6 longitudinal nasal microbiota profiles. Infants with a larger number of antibiotic treatments had a higher risk of having a profile with early Moraxella sparsity (per each antibiotic treatment, adjusted RRR, 1.38; 95% CI, 1.15-1.66; P < .001). This effect of antibiotics on asthma was partly mediated by longitudinal changes in the nasal microbiota (natural indirect effect, P = .008), accounting for 16% of the total effect.

Conclusions: Early exposures to antibiotics were associated with increased risk of asthma; the effect was mediated, in part, by longitudinal changes in the nasal airway microbiota.

Keywords: airway microbiota; antibiotics; asthma; causal mediation; children.

Figure 1.

Causal DAG of the proposed mediation model. Abbreviations: ARI, acute respiratory infection; DAG, directed acyclic graph.

Figure 2.

Exposure to antibiotic treatments during age 0–11 months in 697 children enrolled in the STEPS cohort. Narrow-spectrum antibiotics are presented in blue and broad-spectrum antibiotics in red. Abbreviation: STEPS, Steps to the Healthy Development and Well-being of Children.

Figure 3.

Longitudinal nasal microbiota profiles during age 2–24 months in 697 children enrolled in the STEPS cohort. A, Six longitudinal nasal microbiota profiles were identified using the k-means clustering method: (1) profile A (reference) with persistent Moraxella dominance with high Dolosigranulum as well as low Streptococcus and Staphylococcus abundances, n = 279 (40%); (2) profile B with Streptococcus-to-Moraxella transition, n = 84 (12%); (3) profile C with early Dolosigranulum/Corynebacteriaceae dominance, n = 139 (20%); (4) profile D with early Moraxella sparsity with its subsequent increase as well as persistently high Streptococcus abundance, n = 100 (14%); (5) profile E with mixed longitudinal patterns, n = 92 (13%); (6) profile F, n = 3 (0.4%). Relative abundances of the 15 most abundant genera are shown with the other genera categorized into the 5 most abundant phylum groups. Color codes of genera are based on taxonomic annotation at the phylum level: red, Proteobacteria; blue, Firmicutes; yellow, Actinobacteria; and green, Bacteroidetes. B, For the mediation analysis, longitudinal nasal microbiota profiles were dichotomized to (1) low-risk profile with persistent Moraxella dominance, early high Dolosigranulum as well as low Streptococcus and Staphylococcus abundances (reference, profile A), n = 279 (40%) and (2) high-risk profile with early Moraxella sparsity, early low Dolosigranulum as well as high Streptococcus and Staphylococcus abundances (profiles B–F), n = 418 (60%). Abbreviation: STEPS, Steps to the Healthy Development and Well-being of Children.