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Network-based analysis reveals novel gene signatures in peripheral blood of patients with chronic obstructive pulmonary disease

Overview of attention for article published in Respiratory Research, April 2017
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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7 tweeters

Citations

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16 Dimensions

Readers on

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45 Mendeley
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Title
Network-based analysis reveals novel gene signatures in peripheral blood of patients with chronic obstructive pulmonary disease
Published in
Respiratory Research, April 2017
DOI 10.1186/s12931-017-0558-1
Pubmed ID
Authors

Ma’en Obeidat, Yunlong Nie, Virginia Chen, Casey P. Shannon, Anand Kumar Andiappan, Bernett Lee, Olaf Rotzschke, Peter J. Castaldi, Craig P. Hersh, Nick Fishbane, Raymond T. Ng, Bruce McManus, Bruce E. Miller, Stephen Rennard, Peter D. Paré, Don D. Sin

Abstract

Chronic obstructive pulmonary disease (COPD) is currently the third leading cause of death and there is a huge unmet clinical need to identify disease biomarkers in peripheral blood. Compared to gene level differential expression approaches to identify gene signatures, network analyses provide a biologically intuitive approach which leverages the co-expression patterns in the transcriptome to identify modules of co-expressed genes. A weighted gene co-expression network analysis (WGCNA) was applied to peripheral blood transcriptome from 238 COPD subjects to discover co-expressed gene modules. We then determined the relationship between these modules and forced expiratory volume in 1 s (FEV1). In a second, independent cohort of 381 subjects, we determined the preservation of these modules and their relationship with FEV1. For those modules that were significantly related to FEV1, we determined the biological processes as well as the blood cell-specific gene expression that were over-represented using additional external datasets. Using WGCNA, we identified 17 modules of co-expressed genes in the discovery cohort. Three of these modules were significantly correlated with FEV1 (FDR < 0.1). In the replication cohort, these modules were highly preserved and their FEV1 associations were reproducible (P < 0.05). Two of the three modules were negatively related to FEV1 and were enriched in IL8 and IL10 pathways and correlated with neutrophil-specific gene expression. The positively related module, on the other hand, was enriched in DNA transcription and translation and was strongly correlated to CD4+, CD8+ T cell-specific gene expression. Network based approaches are promising tools to identify potential biomarkers for COPD. The ECLIPSE study was funded by GlaxoSmithKline, under ClinicalTrials.gov identifier NCT00292552 and GSK No. SCO104960.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 27%
Student > Ph. D. Student 9 20%
Student > Bachelor 6 13%
Other 4 9%
Lecturer 2 4%
Other 5 11%
Unknown 7 16%
Readers by discipline Count As %
Medicine and Dentistry 8 18%
Biochemistry, Genetics and Molecular Biology 6 13%
Agricultural and Biological Sciences 5 11%
Computer Science 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Other 11 24%
Unknown 9 20%

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 May 2017.
All research outputs
#4,704,328
of 10,263,476 outputs
Outputs from Respiratory Research
#486
of 1,234 outputs
Outputs of similar age
#96,225
of 262,379 outputs
Outputs of similar age from Respiratory Research
#32
of 70 outputs
Altmetric has tracked 10,263,476 research outputs across all sources so far. This one has received more attention than most of these and is in the 53rd percentile.
So far Altmetric has tracked 1,234 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 58% 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 262,379 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 62% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.