↓ Skip to main content

Genome-wide DNA methylation analysis reveals loci that distinguish different types of adipose tissue in obese individuals

Overview of attention for article published in Clinical Epigenetics, May 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
35 Dimensions

Readers on

mendeley
70 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Genome-wide DNA methylation analysis reveals loci that distinguish different types of adipose tissue in obese individuals
Published in
Clinical Epigenetics, May 2017
DOI 10.1186/s13148-017-0344-4
Pubmed ID
Authors

Donia Macartney-Coxson, Miles C. Benton, Ray Blick, Richard S. Stubbs, Ronald D. Hagan, Michael A. Langston

Abstract

Epigenetic mechanisms provide an interface between environmental factors and the genome and are known to play a role in complex diseases such as obesity. These mechanisms, including DNA methylation, influence the regulation of development, differentiation and the establishment of cellular identity. Here we employ two approaches to identify differential methylation between two white adipose tissue depots in obese individuals before and after gastric bypass and significant weight loss. We analyse genome-wide DNA methylation data using (a) traditional paired t tests to identify significantly differentially methylated loci (Bonferroni-adjusted P ≤ 1 × 10(-7)) and (b) novel combinatorial algorithms to identify loci that differentiate between tissue types. Significant differential methylation was observed for 3239 and 7722 CpG sites, including 784 and 1129 extended regions, between adipose tissue types before and after significant weight loss, respectively. The vast majority of these extended differentially methylated regions (702) were consistent across both time points and enriched for genes with a role in transcriptional regulation and/or development (e.g. homeobox genes). Other differentially methylated loci were only observed at one time point and thus potentially highlight genes important to adipose tissue dysfunction observed in obesity. Strong correlations (r > 0.75, P ≤ 0.001) were observed between changes in DNA methylation (subcutaneous adipose vs omentum) and changes in clinical trait, in particular for CpG sites within PITX2 and fasting glucose and four CpG sites within ISL2 and HDL. A single CpG site (cg00838040, ATP2C2) gave strong tissue separation, with validation in independent subcutaneous (n = 681) and omental (n = 33) adipose samples. This is the first study to report a genome-wide DNA methylome comparison of subcutaneous abdominal and omental adipose before and after weight loss. The combinatorial approach we utilised is a powerful tool for the identification of methylation loci that strongly differentiate between these tissues. This study provides a solid basis for future research focused on the development of adipose tissue and its potential dysfunction in obesity, as well as the role DNA methylation plays in these processes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 1%
Unknown 69 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 16%
Researcher 10 14%
Student > Bachelor 9 13%
Student > Doctoral Student 5 7%
Student > Master 5 7%
Other 7 10%
Unknown 23 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 19%
Medicine and Dentistry 10 14%
Nursing and Health Professions 6 9%
Agricultural and Biological Sciences 6 9%
Unspecified 2 3%
Other 5 7%
Unknown 28 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 October 2017.
All research outputs
#13,936,858
of 24,049,457 outputs
Outputs from Clinical Epigenetics
#707
of 1,350 outputs
Outputs of similar age
#155,963
of 314,512 outputs
Outputs of similar age from Clinical Epigenetics
#15
of 36 outputs
Altmetric has tracked 24,049,457 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,350 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 314,512 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.