Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Epigenetics. 2023 Dec;18(1):2257437. doi: 10.1080/15592294.2023.2257437. Epub 2023 Sep 20.
Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical power We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content. Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.
最近的研究已经确定了数千个 DNA 甲基化 CpG 与复杂疾病/特征之间的关联，强调了表观遗传学在理解疾病发病机制和识别生物标志物方面的关键作用。然而，基于甲基化阵列数据的关联分析容易受到批次/载玻片效应的影响，这可能导致虚报率升高或统计效力降低。我们使用多个基于流行的 Illumina Infinium MethylationEPIC BeadChip 阵列的 DNA 甲基化数据集来描述 CpG 跨越时载玻片效应的一致模式和联合分布，从而确认并扩展了以前的结果。易受影响的 CpG 与 Illumina Infinium HumanMethylation450 BeadChip 阵列内容重叠。我们的发现揭示了载玻片效应的系统模式。这些观察结果进一步深入了解了这些影响的特征，并可以改进现有的调整方法。
