Relationship of Airway Microbiota, Endotype and Phenotype in Adult Asthma

Increasing evidence supports that the respiratory microbiota, including viral and bacterial microorganisms, play important roles in respiratory health and disease. Microbial patterns in airways may induce distinctive endotypes of asthma. Previous studies suggest host-microbiota interactions in children may account for the heterogeneity of endotypes and clinical presentations. However, information on such relationship is limited in adults. Furthermore, how the upper airway microbiome is related to asthma endotype and phenotype is not well understood. Knowledge of microbiota in the airway allows exploration of therapeutic manipulation of the microbiome and targeting the development of asthma prevention strategies and the optimization of asthma treatment.

This study plans to assess microbes in nasopharyngeal flock swab of asthma subjects. The swabs will be subjected to sequence analysis of 16S rRNA. Endotypes (e.g. TH1 vs TH2 inflammation) and phenotypes of the subjects (e.g. severity, exacerbation, lung function, etc.) will be assessed. The planned sample size is 140 adult asthma subjects. Patients will have nasopharyngeal swabs taken at baseline, 3 months (after optimization of asthma treatment at baseline) and at 1 year. They will undergo assessments, including clinical course, lung function, exhaled nitric oxide, skin test, and blood test (including eosinophils and immunoglobulin E levels). All subjects will be followed up for 2 years to assess subsequent exacerbations and levels of asthma control. The 16S data retrieved from the official website of HMP (http://www.hmpdacc.org/) will be used as the geographic reference for this study. Sequences assigned to different taxonomic levels, from phylum to genus using the RDP (ribosomal database project) database, will be clustered into operating taxonomic units (OTUs). Bioinformatic tools will be used to assess the relations of microbiota, asthma endotypes and phenotypes and change of microbiota pattern upon optimization of asthma drug treatment.