Epigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.

中文翻译：

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在全基因组表观遗传学研究中测试细胞类型特异性介导效应。

表观基因组范围的中介分析旨在识别 DNA 甲基化 CpG 位点，该位点介导遗传/环境暴露对健康结果的因果影响。然而，外周血组织中的 DNA 甲基化通常是根据白细胞的异质群体在总体水平上进行测量的。在中介分析中使用大量 DNA 甲基化数据可能会导致混杂偏差并降低研究功效。因此，通过以细胞类型特异性的方式检测介导 CpG 位点来获得细粒度的结果至关重要。然而，目前缺乏实现这一目标的方法和软件。我们提出了一种新方法（细胞类型特异性介导，MICS），仅使用批量水平的 DNA 甲基化数据来识别全基因组表观遗传学研究中细胞类型特异性介导效应。MICS 遵循标准中介分析范式，由三个关键步骤组成。在步骤 1 中，我们评估每种细胞类型的暴露-介体关联；在步骤 2 中，我们评估每种细胞类型的中介-结果关联；在步骤 3 中，我们使用名为 MultiMed 的多重测试程序将细胞类型特异性暴露介体和介体结果关联结合起来 [Sampson JN、Boca SM、Moore SC等人。测试多个中介时的 FWER 和 FDR 控制。Bioinformatics 2018;34:2418–24] 识别具有细胞类型特异性介导作用的显着 CpG。我们进行模拟研究来证明我们的方法具有正确的 FDR 控制。我们还将 MICS 程序应用于规范衰老研究，并确定了淋巴细胞中的 9 个 DNA 甲基化 CpG 位点，这些位点可能介导吸烟对肺功能的影响。