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Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways

Overview of attention for article published in BMC Medical Genomics, October 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
5 tweeters
patent
2 patents

Citations

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58 Dimensions

Readers on

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80 Mendeley
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Title
Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways
Published in
BMC Medical Genomics, October 2015
DOI 10.1186/s12920-015-0133-x
Pubmed ID
Authors

David A. Ewald, Dana Malajian, James G. Krueger, Christopher T. Workman, Tianjiao Wang, Suyan Tian, Thomas Litman, Emma Guttman-Yassky, Mayte Suárez-Fariñas

Abstract

Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies. We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome. This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD "classifier genes" discriminate lesional from nonlesional skin, and may evaluate therapeutic responses. Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Germany 1 1%
Brazil 1 1%
Unknown 77 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 21%
Student > Ph. D. Student 14 18%
Student > Master 11 14%
Student > Bachelor 8 10%
Professor > Associate Professor 5 6%
Other 14 18%
Unknown 11 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 18%
Biochemistry, Genetics and Molecular Biology 14 18%
Medicine and Dentistry 13 16%
Immunology and Microbiology 8 10%
Chemistry 3 4%
Other 10 13%
Unknown 18 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 20 November 2019.
All research outputs
#2,337,984
of 15,055,678 outputs
Outputs from BMC Medical Genomics
#128
of 795 outputs
Outputs of similar age
#45,019
of 253,969 outputs
Outputs of similar age from BMC Medical Genomics
#2
of 15 outputs
Altmetric has tracked 15,055,678 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 795 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 83% 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 253,969 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.