Epigenome-wide cross-tissue predictive modeling and comparison of cord blood and placental methylation in a birth cohort. (March 2017)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Epigenomics. Volume 9:Number 3(2017)
• Page Start: 231
• Page End: 240
• Publication Date: 2017-03
• Subjects: 450k arrays -- cord blood -- DNA methylation -- epigenetics -- methylation prediction -- placenta -- support vector machine; Epigenesis -- Periodicals; Genomics -- Periodicals; Chromatin -- Periodicals; DNA -- Periodicals; 572.87
• DOI: 10.2217/epi-2016-0109
• Languages: English
• ISSNs: 1750-1911

Abstract

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 2 ≥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.