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DNA methylation analysis on purified neurons and glia dissects age and Alzheimer’s disease-specific changes in the human cortex

Overview of attention for article published in Epigenetics & Chromatin, July 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#28 of 568)
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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1 news outlet
blogs
1 blog
twitter
9 X users
patent
1 patent

Citations

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170 Dimensions

Readers on

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184 Mendeley
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Title
DNA methylation analysis on purified neurons and glia dissects age and Alzheimer’s disease-specific changes in the human cortex
Published in
Epigenetics & Chromatin, July 2018
DOI 10.1186/s13072-018-0211-3
Pubmed ID
Authors

Gilles Gasparoni, Sebastian Bultmann, Pavlo Lutsik, Theo F. J. Kraus, Sabrina Sordon, Julia Vlcek, Vanessa Dietinger, Martina Steinmaurer, Melanie Haider, Christopher B. Mulholland, Thomas Arzberger, Sigrun Roeber, Matthias Riemenschneider, Hans A. Kretzschmar, Armin Giese, Heinrich Leonhardt, Jörn Walter

Abstract

Epigenome-wide association studies (EWAS) based on human brain samples allow a deep and direct understanding of epigenetic dysregulation in Alzheimer's disease (AD). However, strong variation of cell-type proportions across brain tissue samples represents a significant source of data noise. Here, we report the first EWAS based on sorted neuronal and non-neuronal (mostly glia) nuclei from postmortem human brain tissues. We show that cell sorting strongly enhances the robust detection of disease-related DNA methylation changes even in a relatively small cohort. We identify numerous genes with cell-type-specific methylation signatures and document differential methylation dynamics associated with aging specifically in neurons such as CLU, SYNJ2 and NCOR2 or in glia RAI1,CXXC5 and INPP5A. Further, we found neuron or glia-specific associations with AD Braak stage progression at genes such as MCF2L, ANK1, MAP2, LRRC8B, STK32C and S100B. A comparison of our study with previous tissue-based EWAS validates multiple AD-associated DNA methylation signals and additionally specifies their origin to neuron, e.g., HOXA3 or glia (ANK1). In a meta-analysis, we reveal two novel previously unrecognized methylation changes at the key AD risk genes APP and ADAM17. Our data highlight the complex interplay between disease, age and cell-type-specific methylation changes in AD risk genes thus offering new perspectives for the validation and interpretation of large EWAS results.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 184 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 22%
Researcher 26 14%
Student > Master 20 11%
Student > Bachelor 18 10%
Student > Doctoral Student 12 7%
Other 29 16%
Unknown 39 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 46 25%
Neuroscience 35 19%
Medicine and Dentistry 17 9%
Agricultural and Biological Sciences 15 8%
Pharmacology, Toxicology and Pharmaceutical Science 5 3%
Other 18 10%
Unknown 48 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 02 September 2021.
All research outputs
#1,474,797
of 23,098,660 outputs
Outputs from Epigenetics & Chromatin
#28
of 568 outputs
Outputs of similar age
#33,149
of 330,303 outputs
Outputs of similar age from Epigenetics & Chromatin
#2
of 18 outputs
Altmetric has tracked 23,098,660 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 568 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 95% 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 330,303 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 89% 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.