The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Airway Microbiome Dynamics in Exacerbations of Chronic Obstructive Pulmonary Disease
Open accessAbstract
Specific bacterial species are implicated in the pathogenesis of exacerbations of chronic obstructive pulmonary disease (COPD). However, recent studies of clinically stable COPD patients have demonstrated a greater diversity of airway microbiota, whose role in acute exacerbations is unclear. In this study, temporal changes in the airway microbiome before, at the onset of, and after an acute exacerbation were examined in 60 sputum samples collected from subjects enrolled in a longitudinal study of bacterial infection in COPD. Microbiome composition and predicted functions were examined using 16S rRNA-based culture-independent profiling methods. Shifts in the abundance (≥ 2-fold, P < 0.05) of many taxa at exacerbation and after treatment were observed. Microbiota members that were increased at exacerbation were primarily of the Proteobacteria phylum, including nontypical COPD pathogens. Changes in the bacterial composition after treatment for an exacerbation differed significantly among the therapy regimens clinically prescribed (antibiotics only, oral corticosteroids only, or both). Treatment with antibiotics alone primarily decreased the abundance of Proteobacteria, with the prolonged suppression of some microbiota members being observed. In contrast, treatment with corticosteroids alone led to enrichment for Proteobacteria and members of other phyla. Predicted metagenomes of particular microbiota members involved in these compositional shifts indicated exacerbation-associated loss of functions involved in the synthesis of antimicrobial and anti-inflammatory products, alongside enrichment in functions related to pathogen-elicited inflammation. These trends reversed upon clinical recovery. Further larger studies will be necessary to determine whether specific compositional or functional changes detected in the airway microbiome could be useful indicators of exacerbation development or outcome.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“With remarkable consistency, all studies report no increase in bacterial burden and no decrease in community diversity during exacerbations.”
From The microbiome and critical illness (2016) · cites this paper as [132]
Citations
Cites
vegan: Community Ecology Package
Oksanen, J., Simpson, G. L., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O’Hara, R. B., Sólymos, P., Stevens, M. H. H., Szöcs, E., et al. (2001) · doi:10.32614/cran.package.vegan · Cited by 27,099
Vestbo, J., Hurd, S. S., Agustí, A. G., Jones, P. W., Vogelmeier, C., Anzueto, A., Barnes, P. J., Fabbri, L. M., Martinez, F. J., Nishimura, M., et al. (2013) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201204-0596pp · Cited by 15,983
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227
PAUWELS, R. A., Buist, A. S., CALVERLEY, P. M. A., Jenkins, C. R., & Hurd, S. S. (2001) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/ajrccm.163.5.2101039 · Cited by 6,578
Picante: R tools for integrating phylogenies and ecology
Kembel, S. W., Cowan, P. D., Helmus, M. R., Cornwell, W. K., Morlon, H., Ackerly, D. D., Blomberg, S. P., & Webb, C. O. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq166 · Cited by 6,192
Conservation evaluation and phylogenetic diversity
Faith, D. (1992) · Biological Conservation · doi:10.1016/0006-3207(92)91201-3 · Cited by 5,495
Cited by
Sorted by citations
Items 301–322 of 322
Guohui, J., Wu, K., Dong, T., Zhang, J., Liu, D., Dong, W., & Chen, J. (2022) · Health care science · doi:10.1002/hcs2.15
The Microbiome in Critically Ill Patients
Tulli, G., & Zuanetti, G. (2022) · Springer eBooks · doi:10.1007/978-3-031-14612-1_7
Pulmonary rehabilitation can alter the respiratory microbiome in patients with COPDPreprint
Ma, H., Wu, S., Zhang, Y., Xi Tao, X. U., Zhang, X., Zhao, F., Ti, X., & Qu, S. (2023) · Research Square · doi:10.21203/rs.3.rs-2576080/v1
Li, Y., Mao, X., Shi, P., Wan, Z., Yang, D., Wang, B., Wang, J., Wang, J. J., Zhu, R., & Ma, T. (2023) · Research Square · doi:10.21203/rs.3.rs-2977655/v1
Orlova, E. A., Petrov, V. I., Петровна, Д. И., Shatalova, O. V., & Орлов, М. А. (2023) · Clinical Microbiology and Antimicrobial Chemotherapy · doi:10.36488/cmac.2023.3.321-328
Obesity, the Microbiome, and Lung Disease
Ingram, J. L., & Huang, Y. J. (2024) · Respiratory medicine · doi:10.1007/978-3-031-52696-1_3
Lung Microbiome and Toxicology
Daniel, S., & Lund, A. K. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95488-4.00117-0
Rao, M. V., Messina, J. A., & Surana, N. K. (2023) · ClinMicroNow · doi:10.1002/9781683670438.mcm0017
Comparative metagenomic analysis of the sputum microbiome in different COPD clinical statesPreprint
Galal, L., Abostate, H. M., Omran, M. E., & Radwan, S. (2025) · Research Square · doi:10.21203/rs.3.rs-5921039/v1
Fedotov, V. D., Zhestkov, A. V., Lyamin, A. V., Lavrenyuk, N. A., Сергеевна, Д. И., & FALALEEVA, E. A. (2025) · Clinical Microbiology and Antimicrobial Chemotherapy · doi:10.36488/cmac.2025.1.111-120
Yang, C.-Y., Li, S.-W., Chin, C.-Y., Hsu, C.-W., Lee, C.-C., Yeh, Y.-M., & Wu, K.-A. (2021) · Figshare · doi:10.6084/m9.figshare.14274780
Sivapalan, P., Rutishauser, J., Ulrik, C. S., Leuppi, J. D., Pedersen, L., Mueller, B., Eklöf, J. V., Biering-Sørensen, T., Gottlieb, V., Armbruster, K., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14643038
Gonzales, G., Malka, R. E., Marinelli, L. M., Lee, C. M., Cook, S., Miar, S., Dion, G. R., & Guda, T. (2024) · Figshare · doi:10.6084/m9.figshare.27129494
Regard, L. (2019) · theses.fr (ABES) · doi:10.70675/0fc2d43fz2ce6z48b6za17bz193a5ee24f49
Feng, J., Li, S., Li, X. G., Li, H., Chen, H. Y., & Liu, X. (2026) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.6c02008
Comparative analysis of the sputum microbiota in different COPD clinical states
Galal, L., Eltokhy, M. A., Abostate, H. M., Omran, M. E., & Radwan, S. M. R. (2026) · Scientific Reports · doi:10.1038/s41598-026-53780-1
Yang, Y., Cui, J., Dong, X., Huang, Y., An, J., Cui, T., Ou, X., Liu, T., Gao, X., Zhang, H., et al. (2026) · Pathogens · doi:10.3390/pathogens15090883
Parolin, C., Gentile, E., Pellegrino, C., Spada, V., Bassi, C., Sabbioni, S., Vitali, B., Pinton, P., & Rimessi, A. (2026) · Biomedicines · doi:10.3390/biomedicines14091965
Llamosí, M., Sempere, J., Gómez‐López, A., Yuste, J., & Domenech, M. (2026) · Journal of Fungi · doi:10.3390/jof12090663
Metadata
- Authors
- Huang, Y. J., Sethi, S., Murphy, T., Nariya, S., Boushey, H. A., & Lynch, S. V.
- Affiliations
- University of California, San Francisco (US)
- Buffalo VA Medical Center (US)
- University at Buffalo, State University of New York (US)
- Venue
- Journal of Clinical Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2014-08
- Volume
- 52
- Issue
- 8
- Pages
- 2813-2823
- ISSN
- 0095-1137 (ISSN-L)
- 1098-660X
- PMC
- PMC4136157
- OpenAlex
- W2135623379
- Cited by
- 323
- References
- 48
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 25 · 2023: 25 · 2022: 30 · 2021: 33 · 2020: 35 · 2019: 28 · 2018: 24 · 2017: 38 · 2016: 27 · 2015: 29 · 2014: 6
- FWCI
- 26.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Microbiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Heart, Lung, and Blood Institute (K23HL105572, HL105572)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Chronic Obstructive Pulmonary Disease (COPD) Research
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Asthma and respiratory diseases
- Keywords
- chronic obstructive pulmonary disease, COPD exacerbations, airway microbiome, sputum microbiota, Proteobacteria, antibiotic therapy, oral corticosteroids, inflammation
- MeSH terms
- Aged, Aged, 80 and over, DNA, Bacterial, DNA, Ribosomal, Humans, Longitudinal Studies, Male, Middle Aged, Phylogeny, Respiratory System, RNA, Ribosomal, 16S, Sputum, Cluster Analysis, Sequence Analysis, DNA, Proteobacteria, Pulmonary Disease, Chronic Obstructive, Microbiota
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
