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Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Czamara D 1 , Eraslan G 2 , Page CM 3 , Lahti J 4 , Lahti-Pulkkinen M 4 , Hämäläinen E 5 Show all authors , Kajantie E 6 , Laivuori H 7 , Villa PM 7 , Reynolds RM 8 , Nystad W 9 , Håberg SE 10 , London SJ 11 , O'Donnell KJ 12 , Garg E 12 , Meaney MJ 12 , Entringer S 13 , Wadhwa PD 14 , Buss C 13 , Jones MJ 15 , Lin DTS 15 , MacIsaac JL 15 , Kobor MS 15 , Koen N 16 , Zar HJ 17 , Koenen KC 18 , Dalvie S 16 , Stein DJ 16 , Kondofersky I 2 , Müller NS 2 , Theis FJ 2 , Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium , Räikkönen K 4 , Binder EB 19

Affiliations 

  • 1 Max-Planck-Institute of Psychiatry, Department of Translational Research in Psychiatry, Munich, 80804, Germany
  • 2 Institute of Computational Biology, Helmholtz-Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
  • 3 Oslo Centre for Biostatistics and Epidemiology, Research Support Unit, Oslo University Hospital, Oslo, 0372, Norway
  • 4 Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland
  • 5 HUSLAB and Department of Clinical Chemistry, Helsinki University, Helsinki, 00290, Finland
  • 6 Oulu University Hospital and University of Oulu, PEDEGO Research Unit, MRC Oulu, 90014, Finland
  • 7 Medical and Clinical Genetics and Obstetrics and Gynaecology University of Helsinki and Helsinki University Central Hospital, Helsinki, 00014, Finland
  • 8 British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
  • 9 Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, 0213, Norway
  • 10 Center for Fertility and Health, Norwegian Institute of Public Health, Oslo, 0213, Norway
  • 11 Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, U.S. Department of Health and Human Services, Research Triangle Park, North Carolina, 20814, USA
  • 12 Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, H3A 2B4, QC, Canada
  • 13 Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), Institute of Medical Psychology, Berlin, 10117, Germany
  • 14 University of California, Irvine, Development, Health, and Disease Research Program, Orange, CA, 92697, USA
  • 15 Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia and the BC Children's Hospital Research Institute, Vancouver, V5Z 4H4, BC, Canada
  • 16 Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, 7925, South Africa
  • 17 Department of Paediatrics & Child Health and SAMRC Unit on Child and Adolescent Health, University of Cape Town, Cape Town, 7505, South Africa
  • 18 Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
  • 19 Max-Planck-Institute of Psychiatry, Department of Translational Research in Psychiatry, Munich, 80804, Germany. binder@psych.mpg.de
Nat Commun, 2019 06 11;10(1):2548.
PMID: 31186427 DOI: 10.1038/s41467-019-10461-0

Abstract

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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