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Published on: August 7, 2017
Maturation of nasal microbiota and antibiotic exposures during early childhood: a population-based cohort study
Y Raita1, L Toivonen2, L Schuez-Havupalo3
1Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-1101, USA.
Insights
The nasal microbiota of healthy children matures in the first two years, with specific bacterial genera changing with age. Early antibiotic exposure alters this development, impacting the types of bacteria present.
Area of Science:
- Microbiology
- Pediatrics
- Computational Biology
Background:
- The development of the airway microbiota in early childhood is not well understood.
- Early-life antibiotic exposure may significantly impact microbial development.
Purpose of the Study:
- To investigate the maturation of the nasal microbiota in the first 24 months of life.
- To examine the influence of early-life antibiotic exposure on nasal microbiota development.
Main Methods:
- A population-based birth cohort of 902 healthy Finnish children was studied.
- Deep neural network models were used to analyze nasal microbiota composition (16S rRNA gene sequencing) in relation to child age.
- Stratified analyses were performed based on antibiotic exposure during the first two months of life.
Main Results:
- Deep neural networks successfully modeled the relationship between bacterial genera and child age.
- Specific genera like Staphylococcus and Corynebacteriaceae decreased with age, while Dolosigranulum and Moraxella increased.
- Early antibiotic exposure was associated with an increase in Haemophilus, whereas Dolosigranulum increased in unexposed children.
Conclusions:
- The study demonstrates significant maturation of the nasal microbiota in healthy children during the first two years of life.
- Early infant antibiotic exposure is linked to distinct age-discriminatory bacteria in the nasal microbiota.
Objectives:
Little is known about maturation of the airway microbiota during early childhood and the consequences of early-life antibiotic exposure.
Methods:
In a population-based birth cohort of 902 healthy Finnish children, we applied deep neural network models to investigate the relationship between the nasal microbiota (measured by 16S rRNA gene sequencing at up to three time points) and child age during the first 24 months. We also performed stratified analyses according to antibiotic exposure during the age period 0-2 months.
Results:
The dense deep neural network analysis successfully modelled the relationship between 232 bacterial genera and child age with a mean absolute error of 4.3 (95%CI 4.0-4.7) months. Similarly, the recurrent neural network analysis also successfully modelled the relationship between 215 genera and child age with a mean absolute error of 0.45 (95%CI 0.42-0.47) months. Among the genera, Staphylococcus spp. and members of the Corynebacteriaceae decreased with age, while Dolosigranulum and Moraxella increased with age in the first 2 years of life (all false discovery rate (FDR) = 0.001). In children without early-life antibiotic exposure, Dolosigranulum increased with age (FDR = 0.001). By contrast, in those with early-life antibiotic exposure, Haemophilus increased with age (FDR = 0.002).
Conclusions:
In this prospective birth cohort of healthy children, we demonstrated the development of the nasal microbiota, with shifts in specific genera constituting maturation, in the first 2 years of life. Antibiotic exposures during early infancy were related to different age-discriminatory bacteria.
