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Disentangling associations between DNA methylation and blood lipids: a Mendelian randomization approach

机译:DNA甲基化与血脂之间的关系解开:孟德尔随机化方法

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BackgroundDNA methylation is an epigenetic mechanism that has been proposed as a possible link between genetic and environmental determinants of disease. Prior studies reported robust associations between the methylation of specific cytosine-phosphate-guanine (CpG) sites and plasma lipids, namely triglycerides (TGs) and high-density lipoprotein cholesterol (HDL-C). However, the causality of the observed association remains elusive, hampered by weak instrumental variables for methylation status. AimWe present a novel application of the elastic net approach to implement a bidirectional Mendelian randomization approach to inferring causal relationships between candidate CpGs and plasma lipids in GAW20 data. MethodsWe used DNA methylation, TGs, and HDL-C measured during the visit 2. Based on prior findings, we selected 5 methylation markers (cg00574958, cg07504977, cg06690548, cg19693031, and cg03717755) related to TGs, 2 markers (cg09572125 and cg02650017) related to HDL-C, and 2 markers (cg06500161 and cg11024682) related to both traits. We implemented an elastic net approach to improve the selection of the genetic instrument for the methylation markers, followed by bidirectional Mendelian randomization 2-stage least-squares regression. ResultsWe observed causal effects of blood fasting TGs on the methylation levels of cg00574958 ( CPT1A ) and cg06690548 ( SLC7A11 ). For cg00574958, our findings were also consistent with the reverse direction of association, that is, from CPT1A methylation to TGs. ConclusionsCurrent evidence does not rule out either direction of association between the methylation of the cg00574958 CPT1A locus and plasma TGs, highlighting the complexity of lipid homeostasis. We also demonstrated a novel approach to improve instrument selection in DNA methylation studies.
机译:背景技术DNA甲基化是一种表观遗传机制,已被提议作为疾病的遗传和环境决定因素之间的可能联系。先前的研究报道了特定胞嘧啶-磷酸-鸟嘌呤(CpG)位点的甲基化与血浆脂质,即甘油三酸酯(TGs)和高密度脂蛋白胆固醇(HDL-C)之间的密切关联。但是,所观察到的关联的因果关系仍然难以捉摸,并由于甲基化状态的弱仪器变量而受阻。 AimWe提出了一种弹性网络方法的新应用,该方法可实现双向孟德尔随机方法来推断GAW20数据中候选CpGs与血浆脂质之间的因果关系。方法我们使用了访问2期间测量的DNA甲基化,TG和HDL-C。基于先前的发现,我们选择了5个与TG相关的甲基化标记(cg00574958,cg07504977,cg06690548,cg19693031和cg03717755),2个标记(cg09572125和cg02650017)与HDL-C相关的标记,以及与这两个性状相关的2个标记(cg06500161和cg11024682)。我们实施了一种弹性网方法,以改善甲基化标记的遗传工具选择,然后进行双向孟德尔随机化2阶段最小二乘回归。结果我们观察到空腹TGs对cg00574958(CPT1A)和cg06690548(SLC7A11)甲基化水平的因果关系。对于cg00574958,我们的发现也与缔合的相反方向一致,即从CPT1A甲基化至TG。结论目前的证据并不能排除cg00574958 CPT1A基因座的甲基化与血浆TG之间的任何关联,这突出了脂质稳态的复杂性。我们还展示了一种新颖的方法来改善DNA甲基化研究中的仪器选择。

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