Evidence map›Paper›PMID 21925153›Full record

ArticleBiochemical and biophysical research communications2011

Pilot analysis of the plasma metabolite profiles associated with emphysematous Chronic Obstructive Pulmonary Disease phenotype.

Mikell Paige, Marie D Burdick, Suhyon Kim, Junrui Xu, Jae K Lee, Y Michael Shim

Open access · greenAbstract read
In one paragraph

Article in Biochemical and biophysical research communications, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

19 citing papers in PubMed, 39 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Role of medical and molecular imaging in COPD.Clinical and translational medicine · 2019
    Review
  10. Article
  11. Article
  12. Metabolic reprogramming in the pathogenesis of chronic lung diseases, including BPD, COPD, and pulmonary fibrosis.American journal of physiology. Lung cellular and molecular physiology · 2018
    Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Biomarkers in chronic obstructive pulmonary disease: confusing or useful?International journal of chronic obstructive pulmonary disease · 2014
    Review
  19. Fusion of theMetabolomics : Official journal of the Metabolomic Society
    Article
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

6 authors at 2 institutions in 1 country.

Mikell PaigeGeorgetown University, Drug Discovery Program, Lombardi Comprehensive Cancer Center, 3970 Reservoir Road, NW, NRB EP15, Washington, DC 20057, USA. map65@georgetown.edu
Marie D Burdick
Suhyon Kim
Junrui Xu
Jae K Lee
Y Michael Shim
University of Virginia · USGeorgetown University Medical Center · US

Funding

Tissue Culture Shared ResourceP30CA051008 · NCI · GEORGETOWN UNIVERSITY · PI Louis M Weiner · 1990 to 2026
$71.5M
Biology of Leukotrienes in the Pathogenesis of EmphysemaK08HL091127 · NHLBI · UNIVERSITY OF VIRGINIA · PI SHIM, YUN MICHAEL · 2008 to 2012
$643k
NCI NIH HHS P30 CA051008NCI NIH HHS P30-CA051008NHLBI NIH HHS K08 HL091127NHLBI NIH HHS K08HL091127
6 · The paper itself

Abstract

The current pilot study examined the hypothesis that cigarette smokers who developed an emphysematous phenotype of Chronic Obstructive Pulmonary Disease (COPD) were associated with distinctive patterns in their corresponding metabolomics profile as compared to those who did not. Peripheral blood plasma samples were collected from 38 subjects with different phenotypes of COPD. They were categorized into three groups: healthy non-smokers (n=16), smokers without emphysema (n=8), and smokers with emphysema (n=14). Ultra High Performance Liquid Chromatography/quadrupole-Time-of-Flight Mass Spectrometry techniques were used to identify a large number of metabolite markers (3534). Unsupervised clustering analysis accurately separated the smokers with emphysema from others without emphysema and demonstrated potentials of this metabolomics data. Subsequently predictive models were created with a supervised learning set, and these predictive models were found to be highly accurate in identifying the subjects with the emphysematous phenotype of COPD with excellent sensitivity and specificity. Our methodology provides a preliminary model that differentiates an emphysematous COPD phenotype from other COPD phenotypes on the basis of the metabolomics profiles. These results also suggest that the metabolomics profiling could potentially guide the characterization of relevant metabolites that leads to an emphysematous COPD phenotype.

Indexed as

MetabolomeBiomarkersChromatography, High Pressure LiquidFemaleHumansMaleMass SpectrometryMetabolomicsMiddle AgedPilot ProjectsPulmonary Disease, Chronic ObstructivePulmonary EmphysemaSmokingBiomarkers

Identifiers

PMID21925153
PMCPMC3199021
OpenAlexW2076316287

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

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.