ArticleRespiratory research2023
Respiratory microbiota and radiomics features in the stable COPD patients.
Article in Respiratory research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Development and validation of a multimodal clinical-radiomics-deep learning nomogram based on automated chest CT segmentation for classifying COPD severity: a multicenter study.Frontiers in medicine · 2026Article
- Nasal Microbiota Associated with the Lung Radiomic Features in Asthma.International journal of general medicine · 2026Article
- The Gut Microbiome and Metabolomics Profiles of Dust-exposed Rats.Combinatorial chemistry & high throughput screening · 2026Article
- Effects of Inhaled Corticosteroids/Long-Acting Beta-Agonists (ICS/LABA) on Airway Microbial Diversity and IL-8/IL-10 Cytokine Levels in Stable COPD.Combinatorial chemistry & high throughput screening · 2026Article
- Why the COPD Microbiome Matters: How Airway Microbes Shape Disease Severity and Treatment Response.International journal of chronic obstructive pulmonary disease · 2026Review
- Crosstalk between the microbiome and the mucosal immunoglobulin A system in the lung, in health and disease.Frontiers in cellular and infection microbiology · 2026Review
- The airway mycobiome in chronic respiratory diseases: current advances and future frontiers.Journal of translational medicine · 2025Review
- 16S rRNA sequencing-based analysis of sputum microbiome in patients with acute exacerbations of chronic obstructive pulmonary disease: retrospective cohort study.Journal of thoracic disease · 2025Article
- Lung Microbiota: From Healthy Lungs to Development of Chronic Obstructive Pulmonary Disease.International journal of molecular sciences · 2025Review
- Lung microbiota: a new hope for treating acute respiratory distress syndrome?Frontiers in microbiology · 2025Review
- Comparison of deep-learning and radiomics-based machine-learning methods for the identification of chronic obstructive pulmonary disease on low-dose computed tomography images.Quantitative imaging in medicine and surgery · 2024Article
- The application of multi-omics in the respiratory microbiome: Progresses, challenges and promises.Computational and structural biotechnology journal · 2023Review
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Authors and funding
12 authors.
Funding
Abstract
backgroundsThe respiratory microbiota and radiomics correlate with the disease severity and prognosis of chronic obstructive pulmonary disease (COPD). We aim to characterize the respiratory microbiota and radiomics features of COPD patients and explore the relationship between them.
methodsSputa from stable COPD patients were collected for bacterial 16 S rRNA gene sequencing and fungal Internal Transcribed Spacer (ITS) sequencing. Chest computed tomography (CT) and 3D-CT analysis were conducted for radiomics information, including the percentages of low attenuation area below - 950 Hounsfield Units (LAA%), wall thickness (WT), and intraluminal area (Ai). WT and Ai were adjusted by body surface area (BSA) to WT/[Formula: see text] and Ai/BSA, respectively. Some key pulmonary function indicators were collected, which included forced expiratory volume in one second (FEV1), forced vital capacity (FVC), diffusion lung carbon monoxide (DLco). Differences and correlations of microbiomics with radiomics and clinical indicators between different patient subgroups were assessed.
resultsTwo bacterial clusters dominated by Streptococcus and Rothia were identified. Chao and Shannon indices were higher in the Streptococcus cluster than that in the Rothia cluster. Principal Co-ordinates Analysis (PCoA) indicated significant differences between their community structures. Higher relative abundance of Actinobacteria was detected in the Rothia cluster. Some genera were more common in the Streptococcus cluster, mainly including Leptotrichia, Oribacterium, Peptostreptococcus. Peptostreptococcus was positively correlated with DLco per unit of alveolar volume as a percentage of predicted value (DLco/VA%pred). The patients with past-year exacerbations were more in the Streptococcus cluster. Fungal analysis revealed two clusters dominated by Aspergillus and Candida. Chao and Shannon indices of the Aspergillus cluster were higher than that in the Candida cluster. PCoA showed distinct community compositions between the two clusters. Greater abundance of Cladosporium and Penicillium was found in the Aspergillus cluster. The patients of the Candida cluster had upper FEV1 and FEV1/FVC levels. In radiomics, the patients of the Rothia cluster had higher LAA% and WT/[Formula: see text] than those of the Streptococcus cluster. Haemophilus, Neisseria and Cutaneotrichosporon positively correlated with Ai/BSA, but Cladosporium negatively correlated with Ai/BSA.
conclusionsAmong respiratory microbiota in stable COPD patients, Streptococcus dominance was associated with an increased risk of exacerbation, and Rothia dominance was relevant to worse emphysema and airway lesions. Peptostreptococcus, Haemophilus, Neisseria and Cutaneotrichosporon probably affected COPD progression and potentially could be disease prediction biomarkers.
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