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A large lung gene expression study identifying IL1B as a novel player in airway inflammation in COPD airway epithelial cells

Overview of attention for article published in Inflammation Research, April 2018
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Title
A large lung gene expression study identifying IL1B as a novel player in airway inflammation in COPD airway epithelial cells
Published in
Inflammation Research, April 2018
DOI 10.1007/s00011-018-1145-8
Pubmed ID
Authors

Gao Yi, Min Liang, Ming Li, Xiangming Fang, Jifang Liu, Yuxiong Lai, Jitao Chen, Wenxia Yao, Xiao Feng, La Hu, Chunyi Lin, Xinke Zhou, Zhaoyu Liu

Abstract

Chronic obstructive pulmonary disease (COPD) is a chronic and progressive lung disease characterized by a mixture of small airway disease and lung tissue parenchymal destruction. Abnormal inflammatory responses to cigarette smoking and other noxious particles are generally thought to be responsible for causing of COPD. Since airway inflammation is a key factor in COPD progress, it is crucial to unravel its underlying molecular mechanisms. Unbiased analysis of genome-wide gene expression profiles in lung small airway epithelial cells provides a powerful tool to investigate this. Gene expression data of GSE611906, GSE20257, GSE8545 were downloaded from GEO database. All 288 lung small airway samples in these cohorts, including donors with (n = 61) and without (n = 227) COPD, were chosen for differential gene expression analysis. The gene ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses, gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were performed. Subsequently, the analyses of IL1B expression level, the Pearson correlation between IL1B and several COPD biomarkers were performed using other cohorts to validate our main findings. With a change ≥ twofold and P value < 0.05 cutoff, we found 38 genes were up-regulated and 114 genes were down-regulated in patients with COPD compared with health controls, while using cutoff fold change 1.5 and P value < 0.05, there were 318 genes up-regulated and 333 genes down-regulated. Among the most up-regulated genes were IL1B, CCL2, CCL23, and CXCL14, all implicated in inflammation triggering. GO, KEGG and WGCNA analysis all disclosed IL1B was highly correlated to COPD disease trait. The expression profile of IL1B was further validated using independent cohorts from COPD airway epithelium, lung tissue, sputum, and blood. We demonstrated higher IL1B gene expression in COPD small airway epithelial cells, but not in COPD lung tissue, sputum, and blood. Strong co-expression of IL1B with COPD biomarkers, such as DUOX2, MMP12, CCL2, and CXCL14, were validated in silico analysis. Finally, PPI network analysis using enriched data showed IL1B, CCL2, CCL7 and BMP7 were in the same hub node with high degrees. We identified IL1B was significantly up-regulated in COPD small airway epithelial cells and propose IL1B as a novel player in airway inflammation in COPD.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 25%
Student > Master 7 15%
Researcher 5 10%
Student > Postgraduate 4 8%
Student > Bachelor 3 6%
Other 5 10%
Unknown 12 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 23%
Medicine and Dentistry 7 15%
Agricultural and Biological Sciences 6 13%
Immunology and Microbiology 2 4%
Nursing and Health Professions 1 2%
Other 7 15%
Unknown 14 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 11 April 2018.
All research outputs
#18,601,965
of 23,041,514 outputs
Outputs from Inflammation Research
#704
of 960 outputs
Outputs of similar age
#255,657
of 329,118 outputs
Outputs of similar age from Inflammation Research
#8
of 11 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 960 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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