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Investigating potential causal relationships between SNPs, DNA methylation and HDL

机译:调查SNP,DNA甲基化和HDL之间的潜在因果关系

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Abstract 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 (ΔHDL) using single-nucleotide polymorphisms (SNPs) as instrumental variables. Several methods were used to estimate the causal effects at CpGs of interest on ΔHDL, 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 ΔHDL 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 ΔHDL.
机译:摘要在Gaw20真实数据集中使用680名患者的数据,我们进行了孟德利安随机化(MR)研究,探讨所选探针(胞嘧啶 - 磷酸胍网[CPGS])和高密度脂蛋白(HDL)甲基化水平之间的因果关系)使用单核苷酸多态性(SNP)作为仪器变量的变化(ΔHDL)。几种方法用于估计ΔHDL的兴趣点的因果效应,包括我们称之为受限制的仪器变量(CIV)的新开发的方法。 CIV在测量潜在渗透表型时,提供了用于可能的肺炎的因果效应的估计,同时提供了对可能的肺炎的因果效应的估计。对于使用基于家族的VC评分测试与ΔHDL相关的10个基因中的CPG,我们将CIV与Egger回归和两级最小二乘(TSL)方法进行比较。所有3种方法在2基因中选择至少1cpg; C18ORF19和C6ORF141--显示与ΔHDL的因果关系。

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