Science Advances | 03-01-2018
Although it is assumed that epigenetic mechanisms, such as changes in DNA methylation (DNAm), underlie the relationship between adverse intrauterine conditions and adult metabolic health, evidence from human studies remains scarce. Therefore, we evaluated whether DNAm in whole blood mediated the association between prenatal famine exposure and metabolic health in 422 individuals exposed to famine in utero and 463 (sibling) controls. We implemented a two-step analysis, namely, a genome-wide exploration across 342,596 cytosine-phosphate-guanine dinucleotides (CpGs) for potential mediators of the association between prenatal famine exposure and adult body mass index (BMI), serum triglycerides (TG), or glucose concentrations, which was followed by formal mediation analysis. DNAm mediated the association of prenatal famine exposure with adult BMI and TG but not with glucose. DNAm at PIM3 (cg09349128), a gene involved in energy metabolism, mediated 13.4% [95% confidence interval (CI), 5 to 28%] of the association between famine exposure and BMI. DNAm at six CpGs, including TXNIP (cg19693031), influencing β cell function, and ABCG1 (cg07397296), affecting lipid metabolism, together mediated 80% (95% CI, 38.5 to 100%) of the association between famine exposure and TG. Analyses restricted to those exposed to famine during early gestation identified additional CpGs mediating the relationship with TG near PFKFB3 (glycolysis) and METTL8 (adipogenesis). DNAm at the CpGs involved was associated with gene expression in an external data set and correlated with DNAm levels in fat depots in additional postmortem data. Our data are consistent with the hypothesis that epigenetic mechanisms mediate the influence of transient adverse environmental factors in early life on long-term metabolic health. The specific mechanism awaits elucidation.
Auteurs: Elmar W. Tobi1,2,Roderick C. Slieker1,René Luijk1,3,Koen F. Dekkers1,Aryeh D. Stein4,Kate M. Xu3,5,Biobank-based Integrative Omics Studies consortium*,P. Eline Slagboom1,Erik W. van Zwet3,L. H. Lumey1,6,† and Bastiaan T. Heijmans1,†,‡
Affiliaties: 1Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands. 2Division of Human Nutrition, Wageningen University and Research, 6708 WE Wageningen, Netherlands. 3Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands. 4Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA. 5Faculty of Psychology and Educational Sciences, Welten Institute, Open University of the Netherlands, 6419 AT Heerlen, Netherlands. 6Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
↵‡Corresponding author. Email: email@example.com
↵* The consortium member names are listed in the acknowledgments.
↵† These authors contributed equally to this work.
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