Evidence map›Paper›PMID 31335912›Full record

ArticlePloS one2019

Chronic obstructive pulmonary disease upper airway microbiome is associated with select clinical characteristics.

Alexa A Pragman, Katherine A Knutson, Trevor J Gould, Shane W Hodgson, Richard E Isaacson, Cavan S Reilly, Chris H Wendt

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Why the COPD Microbiome Matters: How Airway Microbes Shape Disease Severity and Treatment Response.International journal of chronic obstructive pulmonary disease · 2026
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Balancing Benefits and Risks: Do Inhaled Corticosteroids Modify the Lung Microbiome?American journal of respiratory and critical care medicine · 2021
    Article
  13. Article
  14. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Alexa A PragmanDepartment of Medicine, Minneapolis Veterans Affairs Medical Center and University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID 0000-0001-8152-3951
Katherine A KnutsonDivision of Biostatistics, University of Minnesota, Minneapolis, Minnesota, United States of America.
Trevor J GouldUniversity of Minnesota Informatics Institute, University of Minnesota, St. Paul, Minnesota, United States of America.
Shane W HodgsonResearch Service, Minneapolis Veterans Affairs Medical Center, Minneapolis, Minnesota, United States of America.ORCID 0000-0002-1552-9359
Richard E IsaacsonDepartment of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, Minnesota, United States of America.
Cavan S ReillyDivision of Biostatistics, University of Minnesota, Minneapolis, Minnesota, United States of America.
Chris H WendtDepartment of Medicine, Minneapolis Veterans Affairs Medical Center and University of Minnesota, Minneapolis, Minnesota, United States of America.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR000114 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$35.0M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Institutional Career Development CoreKL2TR002492 · NCATS · UNIVERSITY OF MINNESOTA · PI INGBAR, DAVID H · 2018 to 2022
$6.3M
Infectious Disease Training in Clinical InvestigationT32AI055433 · NIAID · UNIVERSITY OF MINNESOTA TWIN CITIES · PI David R Boulware · 2003 to 2026
$6.1M
Biostatistics in Genetics and Genomics Training ProgramT32GM108557 · NIGMS · UNIVERSITY OF MINNESOTA · PI PAN, WEI · 2014 to 2018
$583k
Evaluation of the Oral and Lung Microbiota and Inflammation in Chronic Obstructive Pulmonary Disease Frequent ExacerbatorsIK2CX001095 · VA · MINNEAPOLIS VA MEDICAL CENTER · PI PRAGMAN, ALEXA A · 2016 to 2021
–
CSRD VA IK2 CX001095NCATS NIH HHS KL2 TR002492NCATS NIH HHS UL1 TR000114NCATS NIH HHS UL1 TR002494NIAID NIH HHS T32 AI055433NIGMS NIH HHS T32 GM108557
6 · The paper itself

Abstract

backgroundChronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder associated with lung microbiome dysbiosis. Although the upper airway microbiome is the source of the lung microbiome, the relationships between the oral, nasal, and sputum microbiota are incompletely understood. Our objective was to determine features that differentiate the oral, nasal, and sputum microbiome among subjects with stable COPD.

methodsWe recruited 15 current or former smokers to provide oral and sputum samples on day 1. On day 2, another oral sample and a nasal sample were obtained. Each sample and control underwent DNA extraction, 16S V4 rRNA amplification, 16S V4 sequencing, and qPCR of 16S rRNA. Data were analyzed using dada2 and R.

resultsMost (14 of 15) subjects were male with a mean age of 65.2. One subject had no pulmonary obstruction, while 5 had mild COPD, 7 had moderate COPD, and 2 had severe COPD. Three subjects (20%) were current tobacco users and 2 subjects (13%) used inhaled corticosteroids (ICS). Subjects had a mean of 49.1 pack-years of tobacco exposure. Bacterial biomass was associated with anatomic site, but no differences in biomass were observed with age, FEV1 percent predicted (FEV1pp), ICS use, smoking status, or edentulous state. Shannon index was associated with site (lower nasal diversity than oral and sputum diversity, p<0.001), but not age, ICS use, FEV1pp, tobacco use, or edentulous state. β-diversity was illustrated by principal coordinate analysis using Bray-Curtis dissimilarity and PERMANOVA analyses, showing sample clustering by anatomic site (p = 0.001) with nasal samples forming a cluster separate from the combined oral wash samples and sputum samples. Clustering was also observed with ICS use (p = 0.029) and edentulous state (p = 0.019), while FEV1pp and current tobacco use were not significant. In an amplicon sequencing variant (ASV)-level analysis of oral samples using a linear regression model with Benjamini-Hochberg correction at an FDR<0.10, 10 ASVs were associated with age while no ASVs were associated with FEV1pp or smoking status. Sputum sample analysis demonstrated that 51 ASVs (25 unique genera) were associated with age, 61 ASVs (32 genera) were associated with FEV1pp, and no ASVs were associated with smoking status. In a combined dataset, the frequent exacerbator phenotype, rather than ICS use, was associated with decreased sputum Shannon diversity.

conclusionsAmong the upper airway microbiota of COPD subjects, anatomic site was associated with bacterial biomass, Shannon diversity, and β-diversity. ICS use and edentulous state were both associated with β-diversity. Age was associated with taxa relative abundance in oral and sputum samples, while FEV1pp was associated with taxa relative abundance in sputum samples only.

Indexed as

MicrobiotaAgedFemaleHumansLaryngeal MucosaMaleMetagenomeMiddle AgedNasal MucosaPulmonary Disease, Chronic ObstructiveSmokingSputum

Identifiers

PMID31335912
PMCPMC6650084

What OpenQuestion holds

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Registered trials

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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.