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Increased DNA methylation variability in rheumatoid arthritis-discordant monozygotic twins

Overview of attention for article published in Genome Medicine, September 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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2 news outlets
blogs
2 blogs
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27 X users

Citations

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63 Dimensions

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104 Mendeley
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Title
Increased DNA methylation variability in rheumatoid arthritis-discordant monozygotic twins
Published in
Genome Medicine, September 2018
DOI 10.1186/s13073-018-0575-9
Pubmed ID
Authors

Amy P. Webster, Darren Plant, Simone Ecker, Flore Zufferey, Jordana T. Bell, Andrew Feber, Dirk S. Paul, Stephan Beck, Anne Barton, Frances M. K. Williams, Jane Worthington

Abstract

Rheumatoid arthritis is a common autoimmune disorder influenced by both genetic and environmental factors. Epigenome-wide association studies can identify environmentally mediated epigenetic changes such as altered DNA methylation, which may also be influenced by genetic factors. To investigate possible contributions of DNA methylation to the aetiology of rheumatoid arthritis with minimum confounding genetic heterogeneity, we investigated genome-wide DNA methylation in disease-discordant monozygotic twin pairs. Genome-wide DNA methylation was assessed in 79 monozygotic twin pairs discordant for rheumatoid arthritis using the HumanMethylation450 BeadChip array (Illumina). Discordant twins were tested for both differential DNA methylation and methylation variability between rheumatoid arthritis and healthy twins. The methylation variability signature was then compared with methylation variants from studies of other autoimmune diseases and with an independent healthy population. We have identified a differentially variable DNA methylation signature that suggests multiple stress response pathways may be involved in the aetiology of the disease. This methylation variability signature also highlighted potential epigenetic disruption of multiple RUNX3 transcription factor binding sites as being associated with disease development. Comparison with previously performed epigenome-wide association studies of rheumatoid arthritis and type 1 diabetes identified shared pathways for autoimmune disorders, suggesting that epigenetics plays a role in autoimmunity and offering the possibility of identifying new targets for intervention. Through genome-wide analysis of DNA methylation in disease-discordant monozygotic twins, we have identified a differentially variable DNA methylation signature, in the absence of differential methylation in rheumatoid arthritis. This finding supports the importance of epigenetic variability as an emerging component in autoimmune disorders.

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X Demographics

The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 18%
Student > Master 12 12%
Student > Bachelor 12 12%
Student > Ph. D. Student 10 10%
Professor 7 7%
Other 18 17%
Unknown 26 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 16%
Biochemistry, Genetics and Molecular Biology 15 14%
Medicine and Dentistry 14 13%
Pharmacology, Toxicology and Pharmaceutical Science 7 7%
Immunology and Microbiology 6 6%
Other 13 13%
Unknown 32 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 09 November 2018.
All research outputs
#858,773
of 23,301,510 outputs
Outputs from Genome Medicine
#163
of 1,456 outputs
Outputs of similar age
#19,961
of 335,931 outputs
Outputs of similar age from Genome Medicine
#2
of 18 outputs
Altmetric has tracked 23,301,510 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,456 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has done well, scoring higher than 88% 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 335,931 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.