Gaps in current methods to detect polymorphic CpGs from Illumina Infinium human methylation microarrays and exploring their potential impact in multi-EWAS analyses

DNA methylation (DNAm) epigenome-wide association studies (EWAS) have been performed on diverse ethnicities to discover novel biomarkers associated with various diseases, such as cancers, autoimmune diseases, and neurological disorders. However, genetic polymorphisms can influence DNAm levels resulting in methylation quantitative trait loci (meQTL). These can be either direct effects, by altering the sequence of the methylation (CpG) site itself, or, in the case of array-based measures, indirectly altering the detection probe-binding site interaction. Given that genetic variant frequencies associated with meQTL can differ between population groups, these have the potential to confound EWAS observations, particularly in multi-ethnic populations. In this study, we analysed publicly available DNA methylation profiles (450K array), consisting of 1342 individuals from 6 distinct ancestral groups. We investigate two distinct tools (GapHunter and MethylToSNP) specifically designed to identify CpG sites that may be influenced by genetic variation. Results from this aggregated trans-ancestral epigenome-wide dataset suggest that both tools fail to consistently identify not only rarer (MAF < 0.05) genetic variant effects but also more than half of sites predicted to be associated with variants with much higher allele frequencies (MAF >0.2). In addition, there is a relatively low concordance in the detection of polymorphic CpGs between GapHunter and MethylToSNP. Screening of CpG site associations from EWAS using either of these tools is unlikely to be a robust or comprehensive means of identifying all genetic variant confounding effects.

全基因组DNA甲基化（DNAm）表观遗传组关联研究（EWAS）已在不同民族群体中开展，旨在发现与多种疾病相关的新的生物标志物，如癌症、自身免疫性疾病和神经系统疾病。然而，遗传多态性可能影响DNAm水平，导致甲基化数量性状位点（meQTL）。这些影响可以是直接的，通过改变甲基化（CpG）位点的序列本身实现，或者，在基于阵列的测量中，通过间接改变检测探针结合位点的相互作用实现。鉴于与meQTL相关的遗传变异频率在不同种群群体中可能存在差异，这些变异有潜在的可能性干扰EWAS的观察结果，尤其是在多民族群体中。在本研究中，我们分析了公开可用的DNA甲基化轮廓（450K阵列），其中包括来自6个不同祖先群体的1342个个体。我们研究了两种专门设计的工具（GapHunter和MethylToSNP），旨在识别可能受遗传变异影响的CpG位点。从这一聚合的跨祖先表观遗传组全基因组数据集中获得的结果表明，这两种工具均未能一致地识别出罕见的（MAF < 0.05）遗传变异效应，甚至也未能识别出超过一半预测与具有更高等位基因频率变异（MAF > 0.2）相关的位点。此外，GapHunter和MethylToSNP在检测多态性CpG位点方面的吻合度相对较低。使用这些工具中的任何一个从EWAS中筛选CpG位点关联，不太可能成为一种稳健或全面的识别所有遗传变异干扰效应的手段。