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Abstract
Bisphenol A (BPA), a high production volume chemical widely used in consumer products, is an endocrine active compound associated with complex epigenetic responses in animal models and humans. Developmental BPA exposure in mice previously revealed widespread changes in the mouse liver methylome. Here, we undertake the first epigenome-wide analysis of the effect of BPA concentration on human fetal liver DNA methylation. Enzymatic enrichment of genomic DNA for high CG density and methylation followed by next-generation sequencing yielded data for positional methylation across the genome. Comparing three groups of BPA-exposed subjects (n = 18; 6 per group), high (35.44–96.76 ng/g), low (3.50 to 5.79 ng/g), and non-detect (<0.83 ng/g), revealed regions of altered methylation. Similar numbers of regions of altered methylations were detected in pairwise comparisons; however, their genomic locations were distinct between the non-detect and low or high BPA groups. In general, BPA levels were positively associated with methylation in CpG islands and negatively associated with methylation in CpG shores, shelves, and repetitive regions. DNA methylation at the SNORD imprinted cluster (15q11q13) illustrated both linear and non-monotonic associations with BPA levels. Integrated methylation and RNA-sequencing gene expression analysis revealed differential regulation of transcription at low BPA levels, as well as expression changes in RNA for ligand-binding proteins as BPA levels increase. BPA levels in human fetal liver tissue are associated with complex linear and non-monotonic as well as sequence-dependent alterations in DNA methylation. Future longitudinal studies are needed to link these changes with altered health risks.
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1 Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA 48109;; Department of Animal Science, University of Minnesota, Minneapolis, MN, USA 55108;
2 Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA 48109;; Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA 48109;
3 Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA 48109;
4 Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA 48109;
5 Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA 48109;; Department of Nutritional Sciences, University of Michigan, Ann Arbor, MI 48109, USA