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Oral microbiome dysbiosis is associated with chronic respiratory diseases

Evidence from a population-based study and a hospital cohort

Bibliographic Data

ID22085536
AuthorsBaolin Jia (Suizhou Central Hospital), Xiaojuan Wu (0000-0002-9554-2034, Suizhou Central Hospital), Gaoyan He (0000-0001-5241-262X, Suizhou Central Hospital), Qiang Wang (0000-0003-3091-5503, Suizhou Central Hospital), Li Guan (0000-0002-3420-0110, Suizhou Central Hospital), Jun Ren (0000-0002-8056-9058, Suizhou Central Hospital), Guixin Li (0000-0001-9689-8705, Suizhou Central Hospital), Xianjie Zheng (Suizhou Central Hospital), Sen Yang (0000-0001-9953-4499, Suizhou Central Hospital, corresponding author)
Year2025
Volume13
Pages1696041-1696041
Publication date2025-10-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1696041
PMID41246092
OpenAlexW4415695386
LanguageEN
References cited45

Background The oral microbiome has been increasingly recognized for its role in systemic health through the oral–lung axis. However, population-level evidence linking oral microbial diversity and composition with chronic respiratory diseases (CRD) remains limited. Methods We analyzed data from 4,384 adults in the 2009–2012 National Health and Nutrition Examination Survey (NHANES), defining CRD by self-reported chronic obstructive pulmonary disease (COPD), asthma, emphysema, or chronic bronchitis. Oral rinse samples underwent 16S ribosomal RNA (16S rRNA) V1–V3 sequencing. Alpha diversity, including observed amplicon sequence variants (ASVs), Faith’s phylogenetic diversity (Faith’s PD), Shannon–Weiner index, and Simpson index, and beta diversity, including Bray–Curtis, weighted UniFrac, and unweighted UniFrac distances, were assessed. Associations with CRD were examined using weighted logistic regression and restricted cubic splines (RCS). Differential genus abundance was identified by Wilcoxon tests with false discovery rate correction. A random forest model integrated microbial and clinical features. An independent hospital cohort was additionally profiled by 16S rRNA sequencing, and genus-level differences were assessed with linear discriminant analysis effect size (LEfSe) to validate NHANES findings. Results Higher alpha diversity was inversely associated with CRD risk; each standard deviation increase in observed ASVs and Faith’s PD reduced CRD odds by 19 and 17%, respectively ( p < 0.05). Beta diversity showed significant community-level separation by CRD status ( p = 0.01). Several genera, including Rothia and Veillonella , were enriched in CRD, whereas Prevotella , Haemophilus , and Neisseria were more abundant in non-CRD individuals. The random forest model achieved an area under the curve (AUC) of 0.65. In the hospital cohort, compositional shifts were consistent with NHANES findings, and LEfSe confirmed the depletion of Alloprevotella and Peptostreptococcus in CRD patients. Conclusion Oral microbial diversity and composition were significantly associated with CRD across both a representative U. S. population and a hospital cohort. Select genera and diversity indices may serve as non-invasive biomarkers for respiratory health, warranting further validation in longitudinal and mechanistic studies

Cohort · Cohort study · Dysbiosis · Longitudinal study · Microbiome · Oral Microbiome · Population · Respiratory system · Respiratory tract infections · Gut microbiota and health · Oral health in cancer treatment · Oral microbiology and periodontitis research

  • Reproducible, interactive, scalable and extensible microbiome data science using Qiime 2

    Open Access•Evan Bolyen, Jai Ram Rideout et al.•Nature Biotechnology•2019

  • Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017

    Open Access•Joan B Soriano, Parkes J Kendrick et al.•The Lancet Respiratory Medicine•2020

  • The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement

    Open Access•Erik Von Elm, David G Altman et al.•The Lancet•2007

Citation velocityhistorical
Highly citedNo
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