title: Epigenome-wide cross-tissue predictive modeling and comparison of cord blood and placental methylation in a birth cohort.
abstract: We compared predictive modeling approaches to estimate placental methylation using cord blood methylation.
  
  
  
  We performed locus-specific methylation prediction using both linear regression and support vector machine models with 174 matched pairs of 450k arrays.
  
  
  
  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.
  
  
  
  The present study indicates the need for caution in interpreting cross-tissue predictions. Few methylation sites can be predicted between cord blood and placenta.
authors.affiliation: Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Margherita M
authors.initials: MM
authors.lastname: De Carli
authors.affiliation: Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
authors.forename: Andrea A
authors.initials: AA
authors.lastname: Baccarelli
authors.affiliation: Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, USA.
authors.forename: Letizia
authors.initials: L
authors.lastname: Trevisi
authors.affiliation: Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, USA.|Department of Developmental Neurobiology, National Institute of Perinatology, Mexico City, Mexico.
authors.forename: Ivan
authors.initials: I
authors.lastname: Pantic
authors.affiliation: Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
authors.forename: Kasey Jm
authors.initials: KJ
authors.lastname: Brennan
authors.affiliation: Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.|Department of Obstetrics & Gynecology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
authors.forename: Michele R
authors.initials: MR
authors.lastname: Hacker
authors.affiliation: Department of Obstetrics & Gynecology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Holly
authors.initials: H
authors.lastname: Loudon
authors.affiliation: Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Kelly J
authors.initials: KJ
authors.lastname: Brunst
authors.affiliation: Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.|Mindich Child Health & Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Robert O
authors.initials: RO
authors.lastname: Wright
authors.affiliation: Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.|Mindich Child Health & Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Rosalind J
authors.initials: RJ
authors.lastname: Wright
authors.affiliation: Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.|Mindich Child Health & Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Allan C
authors.initials: AC
authors.lastname: Just
mesh_terms: D018899:CpG Islands; D019175:DNA Methylation; D004742:Enhancer Elements, Genetic; D044127:Epigenesis, Genetic; D005260:Female; D005312:Fetal Blood / Q000378:metabolism*; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D010920:Placenta / Q000378:metabolism*; D011247:Pregnancy; D011401:Promoter Regions, Genetic; D060388:Support Vector Machine
keywords: 450k arrays; DNA methylation; cord blood; epigenetics; methylation prediction; placenta; support vector machine