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Maturation of nasal microbiota and antibiotic exposures during early childhood: a population-based cohort study.
Metadata
Journalclinical microbiology and infection7.117Date
2020 Jun 04
4 months ago
Type
Journal Article
Volume
2020-Jun-04 / :
Author
Raita Y 1, Toivonen L 2, Schuez-Havupalo L 3, Karppinen S 3, Waris M 4, Hoffman KL 5, Camargo CA 6, Peltola V 3, Hasegawa K 6
Affiliation
  • 2. Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-1101, USA; Department of Paediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, 20520, Finland.
  • 3. Department of Paediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, 20520, Finland.
  • 4. Virology Unit, Institute of Biomedicine, University of Turku, Turku, 20520, Finland.
  • 5. Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA.
  • 6. Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-1101, USA.
Doi
PMIDMESH
Abstract
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.
Keywords: Airway Antibiotics Children Deep neural network model Infant Nasal microbiota STEPS study
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Clin Microbiol Infectclinical microbiology and infection
Metadata
LocationEngland
FromELSEVIER SCI LTD

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