出生队列中全表观基因组跨组织预测建模及脐血与胎盘甲基化比较
Epigenome-wide cross-tissue predictive modeling and comparison of cord blood and placental methylation in a birth cohort.
作者信息
De Carli Margherita M, Baccarelli Andrea A, Trevisi Letizia, Pantic Ivan, Brennan Kasey Jm, Hacker Michele R, Loudon Holly, Brunst Kelly J, Wright Robert O, Wright Rosalind J, Just Allan C
机构信息
Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
出版信息
Epigenomics. 2017 Mar;9(3):231-240. doi: 10.2217/epi-2016-0109. Epub 2017 Feb 17.
AIM
We compared predictive modeling approaches to estimate placental methylation using cord blood methylation.
MATERIALS & METHODS: We performed locus-specific methylation prediction using both linear regression and support vector machine models with 174 matched pairs of 450k arrays.
RESULTS
At most CpG sites, both approaches gave poor predictions in spite of a misleading improvement in array-wide correlation. CpG islands and gene promoters, but not enhancers, were the genomic contexts where the correlation between measured and predicted placental methylation levels achieved higher values. We provide a list of 714 sites where both models achieved an R ≥0.75.
CONCLUSION
The present study indicates the need for caution in interpreting cross-tissue predictions. Few methylation sites can be predicted between cord blood and placenta.
目的
我们比较了使用脐带血甲基化来估计胎盘甲基化的预测建模方法。
材料与方法
我们使用线性回归和支持向量机模型，对174对匹配的450k阵列进行了位点特异性甲基化预测。
结果
尽管全阵列相关性有误导性的提高，但在大多数CpG位点，两种方法的预测效果都很差。CpG岛和基因启动子（而非增强子）是测量的和预测的胎盘甲基化水平之间相关性达到较高值的基因组背景。我们提供了一个列表，其中包含714个位点，两种模型在这些位点的R≥0.75。
结论
本研究表明在解释跨组织预测时需要谨慎。脐带血和胎盘之间可预测的甲基化位点很少。
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