Adjustment of Cell-Type Composition Minimizes Systematic Bias in Blood DNA Methylation Profiles Derived by DNA Collection Protocols.
Adjustment of Cell-Type Composition Minimizes Systematic Bias in Blood DNA Methylation Profiles Derived by DNA Collection Protocols.
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DOI：
10.1371/journal.pone.0147519
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Shimizu A
中科院分区：
文献类型：
--
作者：
Shiwa Y;Hachiya T;Furukawa R;Ohmomo H;Ono K;Kudo H;Hata J;Hozawa A;Iwasaki M;Matsuda K;Minegishi N;Satoh M;Tanno K;Yamaji T;Wakai K;Hitomi J;Kiyohara Y;Kubo M;Tanaka H;Tsugane S;Yamamoto M;Sobue K;Shimizu A
DNA 采集方案的差异可能是使用来自多个生物库和/或队列的大量血液样本进行全表观基因组关联研究 (EWAS) 的潜在混杂因素。在这里，我们表明，DNA 收集中涉及的预分析程序可能会导致血细胞 DNA 甲基化谱中的系统偏差，这些偏差可以通过细胞类型组成变量进行调整。在实验 1 中，收集了 16 名志愿者的全血，以检查 4°C 下 24 小时储存期对使用 Infinium HumanMmethylation450 BeadChip 阵列测量的 DNA 甲基化谱的影响。我们的统计分析表明，在比较两个对照重复时，超过 450,000 个 CpG 位点的 P 值分布与理论分布（在分位数-分位数图中，λ = 1.03）相似，而在比较对照和储存条件时，明显偏离理论分布（λ = 1.50）。然后，我们认为细胞类型组成是 DNA 甲基化谱中观察到的偏差的可能原因，并发现通过考虑细胞类型组成变量，与冷藏条件相关的偏差大大降低（λ adjustment = 1.14）。因此，我们比较了大型日本生物库或队列中使用的四种各自的样本收集方案以及两个对照重复。在对照方案和未调整细胞类型组成的四分之三方案之间观察到 DNA 甲基化谱的系统偏差 (λ = 1.12–1.45)，并且在所有四个方案中调整细胞类型组成后未发现显着偏差 (λ 调整 = 1.00–1.17)。这些结果揭示了比较不同来源的血液样本之间的 DNA 甲基化谱的重要意义，并可能导致疾病相关 DNA 甲基化标记的发现和基于 DNA 甲基化谱的预测风险模型的开发。
Differences in DNA collection protocols may be a potential confounder in epigenome-wide association studies (EWAS) using a large number of blood specimens from multiple biobanks and/or cohorts. Here we show that pre-analytical procedures involved in DNA collection can induce systematic bias in the DNA methylation profiles of blood cells that can be adjusted by cell-type composition variables. In Experiment 1, whole blood from 16 volunteers was collected to examine the effect of a 24 h storage period at 4°C on DNA methylation profiles as measured using the Infinium HumanMethylation450 BeadChip array. Our statistical analysis showed that the P-value distribution of more than 450,000 CpG sites was similar to the theoretical distribution (in quantile-quantile plot, λ = 1.03) when comparing two control replicates, which was remarkably deviated from the theoretical distribution (λ = 1.50) when comparing control and storage conditions. We then considered cell-type composition as a possible cause of the observed bias in DNA methylation profiles and found that the bias associated with the cold storage condition was largely decreased (λadjusted = 1.14) by taking into account a cell-type composition variable. As such, we compared four respective sample collection protocols used in large-scale Japanese biobanks or cohorts as well as two control replicates. Systematic biases in DNA methylation profiles were observed between control and three of four protocols without adjustment of cell-type composition (λ = 1.12–1.45) and no remarkable biases were seen after adjusting for cell-type composition in all four protocols (λadjusted = 1.00–1.17). These results revealed important implications for comparing DNA methylation profiles between blood specimens from different sources and may lead to discovery of disease-associated DNA methylation markers and the development of DNA methylation profile-based predictive risk models.