Document Type

Article

Publication Date

8-2020

Identifier

DOI: 10.1016/j.molmet.2019.12.016; PMCID: PMC7300388

Abstract

BACKGROUND: Metabolic diseases such as obesity are known to be driven by both environmental and genetic factors. Although genome-wide association studies of common variants and their impact on complex traits have provided some biological insight into disease etiology, identified genetic variants have been found to contribute only a small proportion to disease heritability, and to map mainly to non-coding regions of the genome. To link variants to function, association studies of cellular traits, such as epigenetic marks, in disease-relevant tissues are commonly applied.

SCOPE OF THE REVIEW: We review large-scale efforts to generate genome-wide maps of coordinated epigenetic marks and their utility in complex disease dissection with a focus on DNA methylation. We contrast DNA methylation profiling methods and discuss the advantages of using targeted methods for single-base resolution assessments of methylation levels across tissue-specific regulatory regions to deepen our understanding of contributing factors leading to complex diseases.

MAJOR CONCLUSIONS: Large-scale assessments of DNA methylation patterns in metabolic disease-linked study cohorts have provided insight into the impact of variable epigenetic variants in disease etiology. In-depth profiling of epigenetic marks at regulatory regions, particularly at tissue-specific elements, will be key to dissect the genetic and environmental components contributing to metabolic disease onset and progression.

Journal Title

Mol Metab

Volume

38

First Page

100936

Last Page

100936

Keywords

Adipose tissue; DNA methylation; Epigenomics; Metabolic diseases; Next-generation sequencing; Regulatory elements

Comments

This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.

Publisher's Link: https://doi.org/10.1016/j.molmet.2019.12.016

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