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Vol. 61. Issue 7.
Pages 417-426 (July 2025)
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Vol. 61. Issue 7.
Pages 417-426 (July 2025)
Original Article
Sputum Microbiota Correlates With Metabolome and Clinical Outcomes in Asthma–Bronchiectasis Overlap
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Xiao-xian Zhanga,1, Zhen-feng Hea,1, Jia-hui Hea,1, Zhao-ming Chena,1, Cui-xia Pana, Zhen-hong Lina, Lai-jian Cena, Hui-min Lia, Yan Huangb, Ming-xin Shia, Wei-jie Guana,c,
Corresponding author
battery203@163.com

Corresponding author.
a Department of Allergy and Clinical Immunology, Department of Respiratory and Critical Care Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
b Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
c Guangzhou National Laboratory, Guangzhou, Guangdong, China
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Table 1. Baseline Characteristics of Patients With ABO, Asthma and Bronchiectasis.
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Abstract
Objectives

To investigate the microbiota and metabolome of patients with ABO compared with bronchiectasis and asthma, and determine the relevance with clinical characteristics, inflammatory endotype and exacerbation risks.

Methods

In this prospective cohort study, patients underwent comprehensive assessments, including sputum differential cell count, and sputum collection at baseline. Sputum microbiota was profiled via 16S rRNA gene sequencing and metabolome via liquid chromatography/mass spectrometry. Shannon-Wiener Diversity Index (SWDI) was used to reflect dysbiosis. Patients were followed-up to record exacerbations. ABO patients were stratified by the SWDI and sputum eosinophilia to determine the exacerbation risks.

Results

Two hundred forty-seven patients were recruited, including 99 ABO (median age: 53.2 years, 65.7% female), 61 asthma (median age: 39.5 years, 50.8% female) and 87 bronchiectasis patients (median age: 52.3 years, 55.2% female). Both microbiota compositions and metabolites differed among asthma, ABO and bronchiectasis, and between eosinophilic and non-eosinophilic ABO at steady-state. Baseline SWDI of microbiota was highest in asthma, followed by ABO. Both Pseudomonadaceae and Rothia most effectively discriminated ABO from asthma and bronchiectasis. Pseudomonas exhibited a more pronounced negative correlation with other taxa in nonEos-ABO. ABO patients with low SWDI with sputum eosinophilia, or those with high SWDI without sputum eosinophilia, had a shorter time to the first exacerbation. Metabolomic compositions in Eos-ABO separated from nonEos-ABO. The relative abundance of Enterobacteriaceae correlated negatively with 15-hydroxylated eicosatetraenoic acid, whose concentrations were higher in Eos-ABO.

Conclusions

Integrating microbiota and metabolome profiles, together with eosinophilic inflammatory endotyping, can inform exacerbation risk and personalized management of ABO.

Keywords:
Asthma–bronchiectasis overlap
Eosinophil
Exacerbation
Metabolome
Microbiota
Abbreviations:
ABO
AE
ASVs
BSI
CRDs
Eos-ABO
FDR
FEV1
HR
HRCT
IgE
IQR
LDA
LEfSe
nonEos-ABO
PCA
SWDI
PERMANOVA
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