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棘手问题:表观基因组关联研究中的细胞异质性及其他混杂因素

Grasping nettles: cellular heterogeneity and other confounders in epigenome-wide association studies.

作者信息

Liang Liming, Cookson William O C

机构信息

Department of Epidemiology and Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA and.

National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK

出版信息

Hum Mol Genet. 2014 Sep 15;23(R1):R83-8. doi: 10.1093/hmg/ddu284. Epub 2014 Jun 13.

Abstract

Platform technologies for measurement of CpG methylation at multiple loci across the genome have made ambitious epigenome-wide association studies affordable and practicable. In contrast to genetic studies, which estimate the effects of structural changes in DNA, and transcriptomic studies, which measure genomic outputs, epigenetic studies can access states of regulation of genome function in particular cells and in response to specific stimuli. Although many factors complicate the interpretation of epigenetic variation in human disease, cell-specific methylation patterns and the cellular heterogeneity present in peripheral blood and tissue biopsies are anticipated to cause the most problems. In this review, we suggest that the difficulties may be exaggerated and we explore how cellular heterogeneity may be embraced with appropriate study designs and analytical tools. We further suggest that systematic mapping of the loci influenced by age, sex and genetic polymorphisms will bring important biological insights as well as improved control of epigenome-wide association studies.

摘要

用于全基因组多个位点CpG甲基化测量的平台技术,已使雄心勃勃的全表观基因组关联研究变得经济可行。与估计DNA结构变化影响的基因研究以及测量基因组输出的转录组学研究不同,表观遗传学研究能够探究特定细胞中基因组功能的调控状态以及对特定刺激的反应。尽管许多因素使人类疾病中表观遗传变异的解释变得复杂,但外周血和组织活检中存在的细胞特异性甲基化模式和细胞异质性预计会带来最多问题。在本综述中,我们认为这些困难可能被夸大了,并探讨如何通过适当的研究设计和分析工具来应对细胞异质性。我们还认为,对受年龄、性别和基因多态性影响的位点进行系统定位,将带来重要的生物学见解,并改善对全表观基因组关联研究的控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b09/4170720/d1438905e79d/ddu28401.jpg

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