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DNA methylation differences in monozygotic twin pairs discordant for schizophrenia identifies psychosis related genes and networks

Overview of attention for article published in BMC Medical Genomics, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#34 of 1,223)
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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2 news outlets
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7 X users
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1 Facebook page

Citations

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53 Dimensions

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95 Mendeley
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1 CiteULike
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Title
DNA methylation differences in monozygotic twin pairs discordant for schizophrenia identifies psychosis related genes and networks
Published in
BMC Medical Genomics, May 2015
DOI 10.1186/s12920-015-0093-1
Pubmed ID
Authors

Christina A Castellani, Benjamin I Laufer, Melkaye G Melka, Eric J Diehl, Richard L O’Reilly, Shiva M Singh

Abstract

Despite their singular origin, monozygotic twin pairs often display discordance for complex disorders including schizophrenia. It is a common (1%) and often familial disease with a discordance rate of ~50% in monozygotic twins. This high discordance is often explained by the role of yet unknown environmental, random, and epigenetic factors. The involvement of DNA methylation in this disease appears logical, but remains to be established. We have used blood DNA from two pairs of monozygotic twins discordant for schizophrenia and their parents in order to assess genome-wide methylation using a NimbleGen Methylation Promoter Microarray. The genome-wide results show that differentially methylated regions (DMRs) exist between members representing discordant monozygotic twins. Some DMRs are shared with parent(s) and others appear to be de novo. We found twenty-seven genes affected by DMR changes that were shared in the affected member of two discordant monozygotic pairs from unrelated families. Interestingly, the genes affected by pair specific DMRs share specific networks. Specifically, this study has identified two networks; "cell death and survival" and a "cellular movement and immune cell trafficking". These two networks and the genes affected have been previously implicated in the aetiology of schizophrenia. The results are compatible with the suggestion that DNA methylation may contribute to the discordance of monozygotic twins for schizophrenia. Also, this may be accomplished by the direct effect of gene specific methylation changes on specific biological networks rather than individual genes. It supports the extensive genetic, epigenetic and phenotypic heterogeneity implicated in schizophrenia.

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X Demographics

The data shown below were collected from the profiles of 7 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 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Unknown 94 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 18 19%
Student > Ph. D. Student 16 17%
Student > Master 14 15%
Researcher 13 14%
Other 3 3%
Other 10 11%
Unknown 21 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 22%
Biochemistry, Genetics and Molecular Biology 19 20%
Psychology 10 11%
Neuroscience 8 8%
Medicine and Dentistry 5 5%
Other 7 7%
Unknown 25 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 18 October 2021.
All research outputs
#1,368,892
of 22,803,211 outputs
Outputs from BMC Medical Genomics
#34
of 1,223 outputs
Outputs of similar age
#18,750
of 264,554 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 23 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,223 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 264,554 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 92% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.