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捕捉功能性表观基因组以深入了解代谢疾病。

Capturing functional epigenomes for insight into metabolic diseases.

作者信息

Allum Fiona, Grundberg Elin

机构信息

Department of Human Genetics, McGill University, Montréal, Québec, H3A 0C7, Canada; McGill University and Genome Quebec Innovation Centre, Montréal, Québec, H3A 0G1, Canada.

Children's Mercy Kansas City, Kansas City, MO, 64108, United States.

出版信息

Mol Metab. 2020 Aug;38:100936. doi: 10.1016/j.molmet.2019.12.016. Epub 2020 Feb 14.

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.

摘要

背景

已知肥胖等代谢性疾病是由环境和遗传因素共同驱动的。尽管对常见变异及其对复杂性状影响的全基因组关联研究为疾病病因学提供了一些生物学见解,但已发现所识别的遗传变异仅占疾病遗传度的一小部分,并且主要定位于基因组的非编码区域。为了将变异与功能联系起来,通常会在疾病相关组织中进行细胞性状(如表观遗传标记)的关联研究。

综述范围

我们综述了生成全基因组协调表观遗传标记图谱的大规模努力及其在复杂疾病剖析中的应用,重点是DNA甲基化。我们对比了DNA甲基化分析方法,并讨论了使用靶向方法对组织特异性调控区域的甲基化水平进行单碱基分辨率评估的优势,以加深我们对导致复杂疾病的影响因素的理解。

主要结论

对代谢性疾病相关研究队列中的DNA甲基化模式进行大规模评估,有助于深入了解可变表观遗传变异在疾病病因学中的影响。对调控区域,特别是组织特异性元件处的表观遗传标记进行深入分析,将是剖析导致代谢性疾病发生和进展的遗传和环境因素的关键。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0db1/7300388/a0ca86905745/gr1.jpg

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