当前位置: X-MOL 学术bioRxiv. Genom. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A region-based method for causal mediation analysis of DNA methylation data
bioRxiv - Genomics Pub Date : 2021-01-18 , DOI: 10.1101/2020.11.03.366989
Qi Yan , Erick Forno , Juan C. Celedón , Wei Chen

Exposure to environmental factors can affect DNA methylation at a CpG site or a genomic region, which can then affect an outcome. In other words, environmental effects on an outcome could be mediated by DNA methylation. To date, single CpG site-based mediation analysis has been employed extensively. More recently, however, there has been considerable interest on studying differentially methylated regions (DMRs), both because DMRs are more likely to have functional effects than single CpG sites and because testing DMRs reduces multiple testing. In this report, we propose a novel causal mediation approach under the counterfactual framework to test the significance of total, direct and indirect effects of predictors on response variable with a methylated region (MR) as the mediator (denoted as MR-Mediation). Functional linear transformation is used to reduce the possible high dimension of the CpG sites in a predefined methylated region and to account for their location information. In our simulation studies, MR-Mediation retained the desired Type I error rates for total, direct and indirect effect tests, for both continuous and binary outcomes. Furthermore, MR-Mediation had better power performance than testing mean methylation level as the mediator in most considered scenarios, especially for indirect effect (i.e., mediated effect) test, which could be more interesting than the other two effect tests. We further illustrate our proposed method by analyzing the methylation mediated effect of exposure to gun violence on total immunoglobulin E (IgE) or atopic asthma among participants in the Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR) study.

中文翻译:

基于区域的DNA甲基化数据因果关系分析方法

暴露于环境因素会影响CpG位点或基因组区域的DNA甲基化,进而影响结果。换句话说,对结果的环境影响可以由DNA甲基化介导。迄今为止,单个基于CpG网站的中介分析已被广泛采用。然而,最近,研究差异甲基化区域(DMR)引起了极大的兴趣,这是因为DMR比单个CpG位点更可能具有功能作用,并且因为测试DMR减少了多次测试。在本报告中,我们提出了一种在反事实框架下的新颖因果中介方法,以检验预测因子对响应变量的总体,直接和间接影响的重要性,其中甲基化区域(MR)作为中介(表示为MR中介)。功能性线性转化用于减少预定义甲基化区域中CpG位点的可能高维,并考虑其位置信息。在我们的模拟研究中,MR-Mediation保留了期望的I类错误率,以进行连续,二进制结果的全部,直接和间接效果测试。此外,在大多数考虑的情况下,特别是对于间接效应(即介导效应)测试,MR-Mediation具有比测试平均甲基化水平作为介体更好的功率性能,这可能比其他两种效应测试更有趣。
更新日期:2021-01-19
down
wechat
bug