免疫学
维管菌
肺炎链球菌
哮喘
副流感嗜血杆菌
流感嗜血杆菌
呼吸道感染
博卡病毒
支气管肺泡灌洗
微生物群
偏肺病毒
普雷沃菌属
生物
慢性阻塞性肺病
医学
微生物学
鼻病毒
呼吸道
生物标志物
卡他莫拉菌
下呼吸道感染
肺
人体微生物群
人巨细胞病毒
嗜血杆菌
节点2
毛细支气管炎
病毒学
呼吸系统
医学微生物学
呼吸道疾病
支气管扩张
痰
作者
Yuanping Huang,Yanfei Zhao,Xue Xin,Shan Lin
标识
DOI:10.3389/fcimb.2026.1840378
摘要
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.
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