Genome-wide DNA promoter methylation and transcriptome analysis in human adipose tissue unravels novel candidate genes for obesity.

Abstract:

OBJECTIVE/METHODS: DNA methylation plays an important role in obesity and related metabolic complications. We examined genome-wide DNA promoter methylation along with mRNA profiles in paired samples of human subcutaneous adipose tissue (SAT) and omental visceral adipose tissue (OVAT) from non-obese vs. obese individuals. RESULTS: We identified negatively correlated methylation and expression of several obesity-associated genes in our discovery dataset and in silico replicated ETV6 in two independent cohorts. Further, we identified six adipose tissue depot-specific genes (HAND2, HOXC6, PPARG, SORBS2, CD36, and CLDN1). The effects were further supported in additional independent cohorts. Our top hits might play a role in adipogenesis and differentiation, obesity, lipid metabolism, and adipose tissue expandability. Finally, we show that in vitro methylation of SORBS2 directly represses gene expression. CONCLUSIONS: Taken together, our data show distinct tissue specific epigenetic alterations which associate with obesity.

PubMed ID: 28123940

Projects: LHA - Leipzig Health Atlas

Publication type: Not specified

Journal: Mol Metab

Human Diseases: Obesity

Citation: Mol Metab. 2016 Nov 16;6(1):86-100. doi: 10.1016/j.molmet.2016.11.003. eCollection 2017 Jan.

Date Published: 27th Jan 2017

Registered Mode: by PubMed ID

Authors: M. Keller, L. Hopp, X. Liu, T. Wohland, K. Rohde, R. Cancello, M. Klos, K. Bacos, M. Kern, F. Eichelmann, A. Dietrich, M. R. Schon, D. Gartner, T. Lohmann, M. Dressler, M. Stumvoll, P. Kovacs, A. M. DiBlasio, C. Ling, H. Binder, M. Bluher, Y. Bottcher

Help
help Submitter
Activity

Views: 1979

Created: 22nd Apr 2020 at 13:11

Last updated: 7th Dec 2021 at 17:58

help Tags

This item has not yet been tagged.

help Attributions

None

Related items

Powered by
(v.1.13.0-master)
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies