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Blood lipids influence DNA methylation in circulating cells

Overview of attention for article published in Genome Biology (Online Edition), June 2016
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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 (91st percentile)

Mentioned by

blogs
1 blog
twitter
33 tweeters

Citations

dimensions_citation
125 Dimensions

Readers on

mendeley
177 Mendeley
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Title
Blood lipids influence DNA methylation in circulating cells
Published in
Genome Biology (Online Edition), June 2016
DOI 10.1186/s13059-016-1000-6
Pubmed ID
Authors

Koen F. Dekkers, Maarten van Iterson, Roderick C. Slieker, Matthijs H. Moed, Marc Jan Bonder, Michiel van Galen, Hailiang Mei, Daria V. Zhernakova, Leonard H. van den Berg, Joris Deelen, Jenny van Dongen, Diana van Heemst, Albert Hofman, Jouke J. Hottenga, Carla J. H. van der Kallen, Casper G. Schalkwijk, Coen D. A. Stehouwer, Ettje F. Tigchelaar, André G. Uitterlinden, Gonneke Willemsen, Alexandra Zhernakova, Lude Franke, Peter A. C. ’t Hoen, Rick Jansen, Joyce van Meurs, Dorret I. Boomsma, Cornelia M. van Duijn, Marleen M. J. van Greevenbroek, Jan H. Veldink, Cisca Wijmenga, Erik W. van Zwet, P. Eline Slagboom, J. Wouter Jukema, Bastiaan T. Heijmans

Abstract

Cells can be primed by external stimuli to obtain a long-term epigenetic memory. We hypothesize that long-term exposure to elevated blood lipids can prime circulating immune cells through changes in DNA methylation, a process that may contribute to the development of atherosclerosis. To interrogate the causal relationship between triglyceride, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol levels and genome-wide DNA methylation while excluding confounding and pleiotropy, we perform a stepwise Mendelian randomization analysis in whole blood of 3296 individuals. This analysis shows that differential methylation is the consequence of inter-individual variation in blood lipid levels and not vice versa. Specifically, we observe an effect of triglycerides on DNA methylation at three CpGs, of LDL cholesterol at one CpG, and of HDL cholesterol at two CpGs using multivariable Mendelian randomization. Using RNA-seq data available for a large subset of individuals (N = 2044), DNA methylation of these six CpGs is associated with the expression of CPT1A and SREBF1 (for triglycerides), DHCR24 (for LDL cholesterol) and ABCG1 (for HDL cholesterol), which are all key regulators of lipid metabolism. Our analysis suggests a role for epigenetic priming in end-product feedback control of lipid metabolism and highlights Mendelian randomization as an effective tool to infer causal relationships in integrative genomics data.

Twitter Demographics

The data shown below were collected from the profiles of 33 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 177 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Spain 1 <1%
United Kingdom 1 <1%
Netherlands 1 <1%
Unknown 172 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 23%
Researcher 37 21%
Student > Master 19 11%
Student > Bachelor 14 8%
Student > Doctoral Student 13 7%
Other 32 18%
Unknown 21 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 57 32%
Agricultural and Biological Sciences 42 24%
Medicine and Dentistry 29 16%
Neuroscience 5 3%
Pharmacology, Toxicology and Pharmaceutical Science 4 2%
Other 10 6%
Unknown 30 17%

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 07 December 2018.
All research outputs
#1,099,617
of 18,997,895 outputs
Outputs from Genome Biology (Online Edition)
#1,024
of 3,792 outputs
Outputs of similar age
#21,838
of 271,026 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 18,997,895 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,792 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.9. This one has gotten more attention than average, scoring higher than 73% 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 271,026 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 91% 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