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DNA methylation age of human tissues and cell types

Overview of attention for article published in Genome Biology (Online Edition), January 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 4,007)
  • High Attention Score compared to outputs of the same age (99th percentile)

Citations

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3347 Dimensions

Readers on

mendeley
3258 Mendeley
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19 CiteULike
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Title
DNA methylation age of human tissues and cell types
Published in
Genome Biology (Online Edition), January 2013
DOI 10.1186/gb-2013-14-10-r115
Pubmed ID
Authors

Steve Horvath

Abstract

It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results: I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance.

Twitter Demographics

The data shown below were collected from the profiles of 194 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 3,258 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 46 1%
United Kingdom 13 <1%
Germany 10 <1%
India 6 <1%
Netherlands 5 <1%
Brazil 3 <1%
Sweden 3 <1%
Russia 3 <1%
Japan 3 <1%
Other 29 <1%
Unknown 3137 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 687 21%
Researcher 626 19%
Student > Bachelor 382 12%
Student > Master 363 11%
Student > Doctoral Student 175 5%
Other 563 17%
Unknown 462 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 818 25%
Agricultural and Biological Sciences 786 24%
Medicine and Dentistry 326 10%
Neuroscience 154 5%
Psychology 88 3%
Other 483 15%
Unknown 603 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 1221. 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 14 August 2022.
All research outputs
#8,387
of 21,798,458 outputs
Outputs from Genome Biology (Online Edition)
#4
of 4,007 outputs
Outputs of similar age
#39
of 208,426 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 21,798,458 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,007 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one has done particularly well, scoring higher than 99% 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 208,426 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 99% 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