Frontiers in cellular and infection microbiology · 2026
Molecular insights into lower respiratory tract microbiota reveal disease-specific biomarkers and shared microbial networks in asthma and COPD.
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Huang Yuanping, Zhao Yanfei, Xin Xue, Lin Shan
Аннотация
BACKGROUND: Lower respiratory tract infections (LRTIs) exacerbate chronic airway diseases, yet phenotype-specific microbial signatures are poorly defined. We applied broncho-alveolar lavage fluid (BALF) genomic sequencing to identify biomarkers for asthma and chronic obstructive pulmonary disease (COPD).
METHODS: Between December 2023 and February 2025, 1-146 adults with suspected LRTI enrolled from the First Hospital of Jilin University underwent BALF next-generation sequencing. Patients were stratified by lung function, with the impaired pulmonary function group further divided into asthma, COPD-mild-moderate, and COPD-severe subgroups. Disease-specific key biomarkers were identified using machine learning algorithms and analyzed for co-occurrence.
RESULTS: Impaired pulmonary function was not only associated with pathogenic microorganisms and its higher microbial burden, but also associated with a distinct community structure. Random forest models revealed disease-specific biomarkers, with Prevotella intermedia, Finegoldia magna, and Human parvovirus enriched in asthma, Veillonella parvula, Human respiratory syncytial virus, and Haemophilus influenzae enriched in COPD-mild-moderate, and Human respiratory syncytial virus, Human coronavirus, and Human parainfluenza virus enriched in COPD-severe. Co-occurrence network identified hubs linking asthma-centric (Haemophilus parainfluenzae and Schaalia odontolytica) and COPD-centric (Klebsiella pneumoniae, Veillonella parvula, and Streptococcus constellatus) clusters, suggesting potential cross-phenotype microbial crosstalk.
CONCLUSIONS: Genomic sequencing profiling delineates distinct yet overlapping airway microbiota across separate pulmonary dysfunctional diseases - asthma and COPD. Compact biomarker panels classify each condition accurately and reveal shared microbial hubs that may drive chronic inflammation and exacerbations, supporting microbiome-guided precision diagnostics and therapy.
METHODS: Between December 2023 and February 2025, 1-146 adults with suspected LRTI enrolled from the First Hospital of Jilin University underwent BALF next-generation sequencing. Patients were stratified by lung function, with the impaired pulmonary function group further divided into asthma, COPD-mild-moderate, and COPD-severe subgroups. Disease-specific key biomarkers were identified using machine learning algorithms and analyzed for co-occurrence.
RESULTS: Impaired pulmonary function was not only associated with pathogenic microorganisms and its higher microbial burden, but also associated with a distinct community structure. Random forest models revealed disease-specific biomarkers, with Prevotella intermedia, Finegoldia magna, and Human parvovirus enriched in asthma, Veillonella parvula, Human respiratory syncytial virus, and Haemophilus influenzae enriched in COPD-mild-moderate, and Human respiratory syncytial virus, Human coronavirus, and Human parainfluenza virus enriched in COPD-severe. Co-occurrence network identified hubs linking asthma-centric (Haemophilus parainfluenzae and Schaalia odontolytica) and COPD-centric (Klebsiella pneumoniae, Veillonella parvula, and Streptococcus constellatus) clusters, suggesting potential cross-phenotype microbial crosstalk.
CONCLUSIONS: Genomic sequencing profiling delineates distinct yet overlapping airway microbiota across separate pulmonary dysfunctional diseases - asthma and COPD. Compact biomarker panels classify each condition accurately and reveal shared microbial hubs that may drive chronic inflammation and exacerbations, supporting microbiome-guided precision diagnostics and therapy.