A genome-wide methylation study on obesity: Differential variability and differential methylation
Besides differential methylation, DNA methylation variation has recently been proposed and demonstrated to be a potential contributing factor to cancer risk. Here we aim to examine whether differential variability in methylation is also an important feature of obesity, a typical non-malignant common...
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pubmed-37412222013-08-28 A genome-wide methylation study on obesity: Differential variability and differential methylation Xu, Xiaojing Su, Shaoyong Barnes, Vernon A. De Miguel, Carmen Pollock, Jennifer Ownby, Dennis Shi, Huidong Zhu, Haidong Snieder, Harold Wang, Xiaoling Research Paper Besides differential methylation, DNA methylation variation has recently been proposed and demonstrated to be a potential contributing factor to cancer risk. Here we aim to examine whether differential variability in methylation is also an important feature of obesity, a typical non-malignant common complex disease. We analyzed genome-wide methylation profiles of over 470,000 CpGs in peripheral blood samples from 48 obese and 48 lean African-American youth aged 14–20 y old. A substantial number of differentially variable CpG sites (DVCs), using statistics based on variances, as well as a substantial number of differentially methylated CpG sites (DMCs), using statistics based on means, were identified. Similar to the findings in cancers, DVCs generally exhibited an outlier structure and were more variable in cases than in controls. By randomly splitting the current sample into a discovery and validation set, we observed that both the DVCs and DMCs identified from the first set could independently predict obesity status in the second set. Furthermore, both the genes harboring DMCs and the genes harboring DVCs showed significant enrichment of genes identified by genome-wide association studies on obesity and related diseases, such as hypertension, dyslipidemia, type 2 diabetes and certain types of cancers, supporting their roles in the etiology and pathogenesis of obesity. We generalized the recent finding on methylation variability in cancer research to obesity and demonstrated that differential variability is also an important feature of obesity-related methylation changes. Future studies on the epigenetics of obesity will benefit from both statistics based on means and statistics based on variances. Landes Bioscience 2013-05-01 2013-04-17 /pmc/articles/PMC3741222/ /pubmed/23644594 http://dx.doi.org/10.4161/epi.24506 Text en Copyright © 2013 Landes Bioscience http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited. |
repository_type |
Open Access Journal |
institution_category |
Foreign Institution |
institution |
US National Center for Biotechnology Information |
building |
NCBI PubMed |
collection |
Online Access |
language |
English |
format |
Online |
author |
Xu, Xiaojing Su, Shaoyong Barnes, Vernon A. De Miguel, Carmen Pollock, Jennifer Ownby, Dennis Shi, Huidong Zhu, Haidong Snieder, Harold Wang, Xiaoling |
spellingShingle |
Xu, Xiaojing Su, Shaoyong Barnes, Vernon A. De Miguel, Carmen Pollock, Jennifer Ownby, Dennis Shi, Huidong Zhu, Haidong Snieder, Harold Wang, Xiaoling A genome-wide methylation study on obesity: Differential variability and differential methylation |
author_facet |
Xu, Xiaojing Su, Shaoyong Barnes, Vernon A. De Miguel, Carmen Pollock, Jennifer Ownby, Dennis Shi, Huidong Zhu, Haidong Snieder, Harold Wang, Xiaoling |
author_sort |
Xu, Xiaojing |
title |
A genome-wide methylation study on obesity: Differential variability and differential methylation |
title_short |
A genome-wide methylation study on obesity: Differential variability and differential methylation |
title_full |
A genome-wide methylation study on obesity: Differential variability and differential methylation |
title_fullStr |
A genome-wide methylation study on obesity: Differential variability and differential methylation |
title_full_unstemmed |
A genome-wide methylation study on obesity: Differential variability and differential methylation |
title_sort |
genome-wide methylation study on obesity: differential variability and differential methylation |
description |
Besides differential methylation, DNA methylation variation has recently been proposed and demonstrated to be a potential contributing factor to cancer risk. Here we aim to examine whether differential variability in methylation is also an important feature of obesity, a typical non-malignant common complex disease. We analyzed genome-wide methylation profiles of over 470,000 CpGs in peripheral blood samples from 48 obese and 48 lean African-American youth aged 14–20 y old. A substantial number of differentially variable CpG sites (DVCs), using statistics based on variances, as well as a substantial number of differentially methylated CpG sites (DMCs), using statistics based on means, were identified. Similar to the findings in cancers, DVCs generally exhibited an outlier structure and were more variable in cases than in controls. By randomly splitting the current sample into a discovery and validation set, we observed that both the DVCs and DMCs identified from the first set could independently predict obesity status in the second set. Furthermore, both the genes harboring DMCs and the genes harboring DVCs showed significant enrichment of genes identified by genome-wide association studies on obesity and related diseases, such as hypertension, dyslipidemia, type 2 diabetes and certain types of cancers, supporting their roles in the etiology and pathogenesis of obesity. We generalized the recent finding on methylation variability in cancer research to obesity and demonstrated that differential variability is also an important feature of obesity-related methylation changes. Future studies on the epigenetics of obesity will benefit from both statistics based on means and statistics based on variances. |
publisher |
Landes Bioscience |
publishDate |
2013 |
url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741222/ |
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1612002445663141888 |