Back to Search
Start Over
The respiratory microbiota alpha-diversity in chronic lung diseases: first systematic review and meta-analysis
- Source :
- Respiratory Research, Respiratory Research, 2022, 23 (214), ⟨10.1186/s12931-022-02132-4⟩, Respiratory Research, BioMed Central, 2022, 23 (214), ⟨10.1186/s12931-022-02132-4⟩
- Publication Year :
- 2022
- Publisher :
- HAL CCSD, 2022.
-
Abstract
- Background While there seems to be a consensus that a decrease in gut microbiome diversity is related to a decline in health status, the associations between respiratory microbiome diversity and chronic lung disease remain a matter of debate. We provide a systematic review and meta-analysis of studies examining lung microbiota alpha-diversity in patients with asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF) or bronchiectasis (NCFB), in which a control group based on disease status or healthy subjects is provided for comparison. Results We reviewed 351 articles on title and abstract, of which 27 met our inclusion criteria for systematic review. Data from 24 of these studies were used in the meta-analysis. We observed a trend that CF patients have a less diverse respiratory microbiota than healthy individuals. However, substantial heterogeneity was present and detailed using random-effects models, which limits the comparison between studies. Conclusions Knowledge on respiratory microbiota is under construction, and for the moment, it seems that alpha-diversity measurements are not enough documented to fully understand the link between microbiota and health, excepted in CF context which represents the most studied chronic respiratory disease with consistent published data to link alpha-diversity and lung function. Whether differences in respiratory microbiota profiles have an impact on chronic respiratory disease symptoms and/or evolution deserves further exploration.
- Subjects :
- Non-cystic fibrosis bronchiectasis
Factor Analysis of Mixed Data
Human lung bacteriome
Chronic respiratory diseases
[STAT.CO] Statistics [stat]/Computation [stat.CO]
Cystic fibrosis
Random effects models
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]
[STAT.AP] Statistics [stat]/Applications [stat.AP]
Human lung microbiome
Humans
[STAT.CO]Statistics [stat]/Computation [stat.CO]
Lung
[STAT.AP]Statistics [stat]/Applications [stat.AP]
[STAT.ME] Statistics [stat]/Methodology [stat.ME]
Microbiota
[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG]
Respiration Disorders
Asthma
[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]
Bronchiectasis
Gastrointestinal Microbiome
Chronic obstructive respiratory disease
Alpha-diversity
Meta-analysis
[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
[STAT.ME]Statistics [stat]/Methodology [stat.ME]
Subjects
Details
- Language :
- English
- ISSN :
- 14659921
- Database :
- OpenAIRE
- Journal :
- Respiratory Research, Respiratory Research, 2022, 23 (214), ⟨10.1186/s12931-022-02132-4⟩, Respiratory Research, BioMed Central, 2022, 23 (214), ⟨10.1186/s12931-022-02132-4⟩
- Accession number :
- edsair.doi.dedup.....93c301e83a2e5f4a0f252aa520180a93