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 R2 ≥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.
Keywords: 450k arrays; DNA methylation; cord blood; epigenetics; methylation prediction; placenta; support vector machine.