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Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods

Overview of attention for article published in BMC Medical Genomics, January 2015
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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3 tweeters
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1 research highlight platform

Citations

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37 Dimensions

Readers on

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62 Mendeley
Title
Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
Published in
BMC Medical Genomics, January 2015
DOI 10.1186/s12920-014-0072-y
Pubmed ID
Authors

Jarrett D Morrow, Weiliang Qiu, Divya Chhabra, Stephen I Rennard, Paula Belloni, Anton Belousov, Sreekumar G Pillai, Craig P Hersh

Abstract

BackgroundExacerbations of chronic obstructive pulmonary disease (COPD), characterized by acute deterioration in symptoms, may be due to bacterial or viral infections, environmental exposures, or unknown factors. Exacerbation frequency may be a stable trait in COPD patients, which could imply genetic susceptibility. Observing the genes, networks, and pathways that are up- and down-regulated in COPD patients with differing susceptibility to exacerbations will help to elucidate the molecular signature and pathogenesis of COPD exacerbations.MethodsGene expression array and plasma biomarker data were obtained using whole-blood samples from subjects enrolled in the Treatment of Emphysema With a Gamma-Selective Retinoid Agonist (TESRA) study. Linear regression, weighted gene co-expression network analysis (WGCNA), and pathway analysis were used to identify signatures and network sub-modules associated with the number of exacerbations within the previous year; other COPD-related phenotypes were also investigated.ResultsIndividual genes were not found to be significantly associated with the number of exacerbations. However using network methods, a statistically significant gene module was identified, along with other modules showing moderate association. A diverse signature was observed across these modules using pathway analysis, marked by differences in B cell and NK cell activity, as well as cellular markers of viral infection. Within two modules, gene set enrichment analysis recapitulated the molecular signatures of two gene expression experiments; one involving sputum from asthma exacerbations and another involving viral lung infections. The plasma biomarker myeloperoxidase (MPO) was associated with the number of recent exacerbations.ConclusionA distinct signature of COPD exacerbations may be observed in peripheral blood months following the acute illness. While not predictive in this cross-sectional analysis, these results will be useful in uncovering the molecular pathogenesis of COPD exacerbations.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
United States 1 2%
Japan 1 2%
Colombia 1 2%
Canada 1 2%
Unknown 56 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 23%
Student > Ph. D. Student 13 21%
Student > Master 8 13%
Unspecified 6 10%
Student > Bachelor 5 8%
Other 16 26%
Readers by discipline Count As %
Medicine and Dentistry 14 23%
Agricultural and Biological Sciences 10 16%
Immunology and Microbiology 8 13%
Unspecified 8 13%
Biochemistry, Genetics and Molecular Biology 7 11%
Other 15 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 February 2015.
All research outputs
#1,827,420
of 4,760,832 outputs
Outputs from BMC Medical Genomics
#124
of 332 outputs
Outputs of similar age
#56,099
of 174,904 outputs
Outputs of similar age from BMC Medical Genomics
#13
of 21 outputs
Altmetric has tracked 4,760,832 research outputs across all sources so far. This one has received more attention than most of these and is in the 60th percentile.
So far Altmetric has tracked 332 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 174,904 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.