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Updated: Sep 19, 2025

Methodology for Sputum Induction and Laboratory Processing
Published on: December 17, 2017
Distinct Airway Microbiome and Metabolite Profiles in Eosinophilic and Neutrophilic Asthma
Shuang Liu1, Zhiwei Lin1,2, Jiayong Zhou3
1Department of Clinical Laboratory, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Laboratory, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China.
Background:
Asthma is a chronic, heterogeneous disease driven by inflammatory phenotypes, primarily eosinophilic asthma (EA) and neutrophilic asthma (NEA). While allergen triggers are well-known, the role of the airway microbiome and metabolites in asthma exacerbations remains poorly understood.
Methods:
We recruited 64 participants (24 EA, 20 NEA, 20 healthy controls [HC]) for the discovery cohort, with validation in an external cohort (10 EA, 8 NEA, 8 HC). Induced sputum samples were analyzed using 16S rRNA sequencing to profile bacterial composition and non-targeted metabolomics to assess airway metabolites. Random forest models identified diagnostic markers, validated in the external cohort.
Results:
Significant shifts in airway microbiota were observed, particularly between NEA and HC, and between EA and NEA. Four bacterial general-Stenotrophomonas, Streptococcus, Achromobacter, and Neisseria-were consistently identified across groups. Veillonella was more abundant in NEA vs HC, while Achromobacter was enriched in NEA vs EA, indicating distinct microbial signatures. Metabolomic profiling revealed distinct pathways: pyrimidine metabolism (EA vs HC), tryptophan metabolism (NEA vs HC), and arachidonic acid metabolism (EA vs NEA). Microbial-metabolite correlations indicated microbiota-driven metabolic activity. Biomarker candidates were validated in the external cohort.
Conclusion:
The airway microbiota and metabolites are intricately linked to asthma exacerbations, with distinct patterns between EA and NEA. These findings highlight their potential as diagnostic biomarkers and therapeutic targets for personalized asthma management.
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