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Investigating potential causal relationships between SNPs, DNA methylation and HDL

机译:研究SNP,DNA甲基化和HDL之间的潜在因果关系

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Using data on 680 patients from the GAW20 real data set, we conducted Mendelian randomization (MR) studies to explore the causal relationships between methylation levels at selected probes (cytosine-phosphate-guanine sites [CpGs]) and high-density lipoprotein (HDL) changes (Δ HDL ) using single-nucleotide polymorphisms (SNPs) as instrumental variables. Several methods were used to estimate the causal effects at CpGs of interest on Δ HDL , including a newly developed method that we call constrained instrumental variables (CIV). CIV performs automatic SNP selection while providing estimates of causal effects adjusted for possible pleiotropy, when the potentially-pleiotropic phenotypes are measured. For CpGs in or near the 10 genes identified as associated with Δ HDL using a family-based VC-score test, we compared CIV to Egger regression and the two-stage least squares (TSLS) method. All 3 approaches selected at least 1CpG in 2 genes— RNMT;C18orf19 and C6orf141 —as showing a causal relationship with Δ HDL .
机译:利用来自GAW20真实数据集中的680位患者的数据,我们进行了孟德尔随机(MR)研究,以探讨所选探针(胞嘧啶-磷酸-鸟嘌呤位点[CpGs])的甲基化水平与高密度脂蛋白(HDL)之间的因果关系使用单核苷酸多态性(SNP)作为工具变量来改变(ΔHDL)。几种方法被用来估计感兴趣的CpG对ΔHDL的因果影响,包括一种新开发的方法,我们称为约束工具变量(CIV)。当测量潜在多效性表型时,CIV执行自动SNP选择,同时提供因可能的多效性而调整的因果效应估计值。对于使用基于家族的VC评分测试确定为与ΔHDL相关的10个基因中或附近的CpG,我们将CIV与Egger回归和两阶段最小二乘(TSLS)方法进行了比较。这三种方法均在RNMT; C18orf19和C6orf141这2个基因中选择了至少1CpG,这与ΔHDL具有因果关系。

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