ArticleNature medicine2021
Integrative microbiomics in bronchiectasis exacerbations.
Article in Nature medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 119 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
119 citing papers in PubMed, 5 syntheses or guidelines pooled it, 223 citations in OpenAlex.
- Management of Adult Bronchiectasis: Consensus-Based Guidelines of the German Respiratory Society.Respiration; international review of thoracic diseases · 2026Guideline
- Bronchiectasis in children: a systematic review of cytokine profile, immune cell phenotypes and microbiota in bronchoalveolar lavage fluid.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Pulmonary microbiology and microbiota in adults with non-cystic fibrosis bronchiectasis: a systematic review and meta-analysis.Respiratory research · 2025Pooled it
- The respiratory microbiota alpha-diversity in chronic lung diseases: first systematic review and meta-analysis.Respiratory research · 2022Pooled it
- Pooled it
- Endotypes ofAmerican journal of respiratory and critical care medicine · 2025Trial
- Characterization of the Human Oropharyngeal Microbiomes in SARS-CoV-2 Infection and Recovery Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Trial
- Review
- Targeting Inflammation in Bronchiectasis.Drugs · 2026Review
- Lower airway dysbiosis in nontuberculous mycobacteria-positive bronchiectasis is associated with neutrophil extracellular trap-predominant severe phenotypes.American journal of respiratory and critical care medicine · 2026Article
- Mycobacterium tuberculosis infection disrupts gut and respiratory microbial communities and networks with incomplete restoration after two months of treatment.Gut pathogens · 2026Article
- Article
- Article
- Multidrug-resistantERJ open research · 2026Article
- MDPD reveals specific microbial signatures in human pulmonary diseases.Briefings in bioinformatics · 2026Article
- Candida in the lung: Fact, fiction, friend or foe?PLoS pathogens · 2026Article
- Fungal-Associated Endotypes as a Treatable Trait in Bronchiectasis.Pulmonary therapy · 2026Review
- Radiological Phenotypes of Bronchiectasis Based on Airway Generation.Biomedicines · 2026Article
- Crosstalk between the microbiome and the mucosal immunoglobulin A system in the lung, in health and disease.Frontiers in cellular and infection microbiology · 2026Review
- Gut-Lung Axis Microbiome Dysbiosis and Cross-Domain Network Analysis in Bronchiectasis Complicated by Invasive Pulmonary Aspergillosis.Infection and drug resistance · 2026Article
59 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors at 9 institutions in 5 countries.
Funding
Abstract
Bronchiectasis, a progressive chronic airway disease, is characterized by microbial colonization and infection. We present an approach to the multi-biome that integrates bacterial, viral and fungal communities in bronchiectasis through weighted similarity network fusion ( https://integrative-microbiomics.ntu.edu.sg ). Patients at greatest risk of exacerbation have less complex microbial co-occurrence networks, reduced diversity and a higher degree of antagonistic interactions in their airway microbiome. Furthermore, longitudinal interactome dynamics reveals microbial antagonism during exacerbation, which resolves following treatment in an otherwise stable multi-biome. Assessment of the Pseudomonas interactome shows that interaction networks, rather than abundance alone, are associated with exacerbation risk, and that incorporation of microbial interaction data improves clinical prediction models. Shotgun metagenomic sequencing of an independent cohort validated the multi-biome interactions detected in targeted analysis and confirmed the association with exacerbation. Integrative microbiomics captures microbial interactions to determine exacerbation risk, which cannot be appreciated by the study of a single microbial group. Antibiotic strategies probably target the interaction networks rather than individual microbes, providing a fresh approach to the understanding of respiratory infection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.