Laura Toivonen1,2, Sinikka Karppinen2, Linnea Schuez-Havupalo2, Matti Waris3, Qiushui He4,5, Kristi L Hoffman6, Joseph F Petrosino6, Orianne Dumas7,8, Carlos A Camargo9, Kohei Hasegawa9, Ville Peltola2. 1. Department of Emergency Medicine, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts; laura.toivonen@utu.fi. 2. Department of Paediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland. 3. Virology Unit, Institute of Biomedicine and. 4. Department of Microbiology, Virology and Immunology and Institute of Biomedicine, University of Turku, Turku, Finland. 5. Department of Medical Microbiology, Capital Medical University, Beijing, China. 6. Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas. 7. INSERM U1168, VIMA: Aging and Chronic Diseases, Epidemiological and Public Health Approaches, Villejuif, France; and. 8. UMR-S 1168, Université de Versailles Saint-Quentin-en-Yvelines, Montigny-le-Bretonneux, France. 9. Department of Emergency Medicine, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts.
Abstract
OBJECTIVES: Although the airway microbiota is a highly dynamic ecology, the role of longitudinal changes in airway microbiota during early childhood in asthma development is unclear. We aimed to investigate the association of longitudinal changes in early nasal microbiota with the risk of developing asthma. METHODS: In this prospective, population-based birth cohort study, we followed children from birth to age 7 years. The nasal microbiota was tested by using 16S ribosomal RNA gene sequencing at ages 2, 13, and 24 months. We applied an unsupervised machine learning approach to identify longitudinal nasal microbiota profiles during age 2 to 13 months (the primary exposure) and during age 2 to 24 months (the secondary exposure) and examined the association of these profiles with the risk of physician-diagnosed asthma at age 7 years. RESULTS: Of the analytic cohort of 704 children, 57 (8%) later developed asthma. We identified 4 distinct longitudinal nasal microbiota profiles during age 2 to 13 months. In the multivariable analysis, compared with the persistent Moraxella dominance profile during age 2 to 13 months, the persistent Moraxella sparsity profile was associated with a significantly higher risk of asthma (adjusted odds ratio, 2.74; 95% confidence interval, 1.20-6.27). Similar associations were observed between the longitudinal changes in nasal microbiota during age 2 to 24 months and risk of asthma. CONCLUSIONS: Children with an altered longitudinal pattern in the nasal microbiota during early childhood had a high risk of developing asthma. Our data guide the development of primary prevention strategies (eg, early identification of children at high risk and modification of microbiota) for childhood asthma. These observations present a new avenue for risk modification for asthma (eg, microbiota modification).
OBJECTIVES: Although the airway microbiota is a highly dynamic ecology, the role of longitudinal changes in airway microbiota during early childhood in asthma development is unclear. We aimed to investigate the association of longitudinal changes in early nasal microbiota with the risk of developing asthma. METHODS: In this prospective, population-based birth cohort study, we followed children from birth to age 7 years. The nasal microbiota was tested by using 16S ribosomal RNA gene sequencing at ages 2, 13, and 24 months. We applied an unsupervised machine learning approach to identify longitudinal nasal microbiota profiles during age 2 to 13 months (the primary exposure) and during age 2 to 24 months (the secondary exposure) and examined the association of these profiles with the risk of physician-diagnosed asthma at age 7 years. RESULTS: Of the analytic cohort of 704 children, 57 (8%) later developed asthma. We identified 4 distinct longitudinal nasal microbiota profiles during age 2 to 13 months. In the multivariable analysis, compared with the persistent Moraxella dominance profile during age 2 to 13 months, the persistent Moraxella sparsity profile was associated with a significantly higher risk of asthma (adjusted odds ratio, 2.74; 95% confidence interval, 1.20-6.27). Similar associations were observed between the longitudinal changes in nasal microbiota during age 2 to 24 months and risk of asthma. CONCLUSIONS:Children with an altered longitudinal pattern in the nasal microbiota during early childhood had a high risk of developing asthma. Our data guide the development of primary prevention strategies (eg, early identification of children at high risk and modification of microbiota) for childhood asthma. These observations present a new avenue for risk modification for asthma (eg, microbiota modification).
Authors: Zhaozhong Zhu; Carlos A Camargo; Yoshihiko Raita; Robert J Freishtat; Michimasa Fujiogi; Andrea Hahn; Jonathan M Mansbach; Jonathan M Spergel; Marcos Pérez-Losada; Kohei Hasegawa Journal: J Allergy Clin Immunol Date: 2022-04-26 Impact factor: 14.290