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全基因组甲基化研究鉴定出与肥胖风险相关的甲基化位点。

Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity.

机构信息

Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, 40 Ruskin St-H4208, Ottawa, ON K1Y 4W7, Canada.

Plastenor Technologies Company, Montreal, QC H2P 2G4, Canada.

出版信息

Nutrients. 2021 Jun 9;13(6):1984. doi: 10.3390/nu13061984.

Abstract

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of , whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of . Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of , and . In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.

摘要

在这里,我们进行了全基因组范围内的甲基化位点搜索,以寻找导致肥胖风险的甲基化位点。我们通过基于 SNP 的多组学方法将甲基化数量性状基因座 (mQTL) 数据与 BMI GWAS 信息整合,以识别与肥胖风险 SNP 共定位的 mQTL 所在的基因组区域。然后,我们通过孟德尔随机化测试确定的位点是否对 BMI 有影响。我们确定了多个导致肥胖风险的甲基化位点。我们通过复制阶段验证了这些发现。通过整合表达数量性状基因座 (eQTL) 数据,我们注意到位于 上游的 cg21178254 位点的低甲基化通过增加该基因的表达导致肥胖。cg02814054 位点的高甲基化通过降低 的表达增加肥胖的风险,而 cg06028605 位点的低甲基化通过降低 的表达导致肥胖。最后,我们注意到 2p23.3 内的稀有变异通过使 cg01884057 位点更容易发生甲基化来影响肥胖,从而降低 的表达 , 以及 。在这项研究中,我们确定了与肥胖风险相关的甲基化位点,并揭示了这些位点发挥作用的机制。该研究为表型进行全组学关联研究提供了框架,并有助于理解罕见变异导致疾病的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56a5/8229089/a113e36bfd06/nutrients-13-01984-g001.jpg

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