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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)

Mentioned by

news
2 news outlets
blogs
2 blogs
twitter
28 tweeters

Citations

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50 Dimensions

Readers on

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77 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.

Twitter Demographics

The data shown below were collected from the profiles of 28 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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 21%
Student > Master 11 14%
Student > Bachelor 10 13%
Student > Ph. D. Student 9 12%
Student > Postgraduate 6 8%
Other 11 14%
Unknown 14 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 22%
Biochemistry, Genetics and Molecular Biology 13 17%
Medicine and Dentistry 11 14%
Immunology and Microbiology 5 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Other 9 12%
Unknown 18 23%

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
#533,206
of 15,922,891 outputs
Outputs from Genome Medicine
#101
of 1,072 outputs
Outputs of similar age
#16,440
of 276,224 outputs
Outputs of similar age from Genome Medicine
#1
of 1 outputs
Altmetric has tracked 15,922,891 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 1,072 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one has done particularly well, scoring higher than 90% 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 276,224 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them