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Differential allelic expression of IL13 and CSF2 genes associated with asthma

Overview of attention for article published in Genetics and Molecular Biology, August 2012
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Title
Differential allelic expression of IL13 and CSF2 genes associated with asthma
Published in
Genetics and Molecular Biology, August 2012
DOI 10.1590/s1415-47572012005000055
Pubmed ID
Authors

Jana Burkhardt, Holger Kirsten, Grit Wolfram, Elfi Quente, Peter Ahnert

Abstract

An important area of genetic research is the identification of functional mechanisms in polymorphisms associated with diseases. A highly relevant functional mechanism is the influence of polymorphisms on gene expression levels (differential allelic expression, DAE). The coding single nucleotide polymorphisms (SNPs) CSF2(rs25882) and IL13(rs20541) have been associated with asthma. In this work, we investigated whether the mRNA expression levels of CSF2 or IL13 were correlated with these SNPs. Samples were analyzed by mass spectrometry-based quantification of gene expression. Both SNPs influenced gene expression levels (CSF2(rs25882): p(overall) = 0.008 and p(DAE samples) = 0.00006; IL13(rs20541): p(overall) = 0.059 and p(DAE samples) = 0.036). For CSF2, the expression level was increased by 27.4% (95% CI: 18.5%-35.4%) in samples with significant DAE in the presence of one copy of risk variant CSF2(rs25882-T). The average expression level of IL13 was increased by 29.8% (95% CI: 3.1%-63.4%) in samples with significant DAE in the presence of one copy of risk variant IL13(rs20541-A). Enhanced expression of CSF2 could stimulate macrophages and neutrophils during inflammation and may be related to the etiology of asthma. For IL-13, higher expression could enhance the functional activity of the asthma-associated isoform. Overall, the analysis of DAE provides an efficient approach for identifying possible functional mechanisms that link disease-associated variants with altered gene expression levels.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 24%
Student > Ph. D. Student 5 24%
Student > Master 4 19%
Student > Doctoral Student 2 10%
Unspecified 1 5%
Other 1 5%
Unknown 3 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 43%
Medicine and Dentistry 3 14%
Computer Science 1 5%
Immunology and Microbiology 1 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Other 0 0%
Unknown 6 29%

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 19 August 2012.
All research outputs
#17,664,478
of 22,675,759 outputs
Outputs from Genetics and Molecular Biology
#466
of 705 outputs
Outputs of similar age
#121,666
of 164,815 outputs
Outputs of similar age from Genetics and Molecular Biology
#8
of 10 outputs
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