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Genome-wide epigenetic signatures of childhood adversity in early life: Opportunities and challenges

  • Aya Sasaki (a1) and Stephen G. Matthews (a1) (a2) (a3)


Maternal adversity and fetal glucocorticoid exposure has long-term effects on cardiovascular, metabolic and behavioral systems in offspring that can persist throughout the lifespan. These data, along with other environmental exposure data, implicate epigenetic modifications as potential mechanisms for long-term effects of maternal exposures on adverse health outcomes in offspring. Advances in microarray, sequencing and bioinformatic approaches have enabled recent studies to examine the genome-wide epigenetic response to maternal adversity. Studies of maternal exposures to xenobiotics such as arsenic and smoking have been performed at birth to examine fetal epigenomic signatures in cord blood relating to adult health outcomes. However, there have been no epigenomic studies examining these effects in animal models. On the other hand, to date, only a few studies of the effects of maternal psychosocial stress have been performed in human infants, and the majority of animal studies have examined epigenomic outcomes in adulthood. In terms of maternal exposure to excess glucocorticoids by synthetic glucocorticoid treatment, there has been no epigenetic study performed in humans and only a few studies undertaken in animal models. This review emphasizes the importance of examining biomarkers of exposure to adversity throughout development to identify individuals at risk and to target interventions. Thus, research performed at birth will be reviewed. In addition, potential subject characteristics associated with epigenetic modifications, technical considerations, the selection of target tissues and combining human studies with animal models will be discussed in relation to the design of experiments in this field of study.


Corresponding author

*Address of Correspondence: Stephen Matthews, Department of Physiology, University of Toronto, Toronto, ON, Canada, M5S 1A8 E-mail:


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1. Gillman, MW. Developmental origins of health and disease. The New England journal of medicine. 2005; 353, 18481850.10.1056/NEJMe058187
2. Gluckman, PD, Hanson, MA. Evolution, development and timing of puberty. Trends in endocrinology and metabolism: TEM. 2006; 17, 712.10.1016/j.tem.2005.11.006
3. Barker, DJ. The developmental origins of chronic adult disease. Acta paediatrica. 2004; 93, 2633.10.1111/j.1651-2227.2004.tb00236.x
4. Bird, A. Perceptions of epigenetics. Nature. 2007; 447, 396398.10.1038/nature05913
5. Huyck, KL, Kile, ML, Mahiuddin, G, et al. Maternal arsenic exposure associated with low birth weight in Bangladesh. Journal of occupational and environmental medicine. 2007; 49, 10971104.10.1097/JOM.0b013e3181566ba0
6. Rahman, A, Vahter, M, Ekstrom, EC, et al. Association of arsenic exposure during pregnancy with fetal loss and infant death: a cohort study in Bangladesh. American journal of epidemiology. 2007; 165, 13891396.10.1093/aje/kwm025
7. Rodriguez-Barranco, M, Lacasana, M, Aguilar-Garduno, C, et al. Association of arsenic, cadmium and manganese exposure with neurodevelopment and behavioural disorders in children: a systematic review and meta-analysis. The Science of the total environment. 2013; 454-455, 562577.
8. Broberg, K, Ahmed, S, Engstrom, K, et al. Arsenic exposure in early pregnancy alters genome-wide DNA methylation in cord blood, particularly in boys. Journal of developmental origins of health and disease. 2014; 5, 288298.10.1017/S2040174414000221
9. Kile, ML, Houseman, EA, Baccarelli, AA, et al. Effect of prenatal arsenic exposure on DNA methylation and leukocyte subpopulations in cord blood. Epigenetics. 2014; 9, 774782.
10. Koestler, DC, Avissar-Whiting, M, Houseman, EA, Karagas, MR, Marsit, CJ. Differential DNA methylation in umbilical cord blood of infants exposed to low levels of arsenic in utero. Environmental health perspectives. 2013; 121, 971977.10.1289/ehp.1205925
11. Rager, JE, Bailey, KA, Smeester, L, et al. Prenatal arsenic exposure and the epigenome: altered microRNAs associated with innate and adaptive immune signaling in newborn cord blood. Environmental and molecular mutagenesis. 2014; 55, 196208.10.1002/em.21842
12. Houseman, EA, Accomando, WP, Koestler, DC, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics. 2012; 13, 86.10.1186/1471-2105-13-86
13. Waalkes, MP, Ward, JM, Liu, J, Diwan, BA. Transplacental carcinogenicity of inorganic arsenic in the drinking water: induction of hepatic, ovarian, pulmonary, and adrenal tumors in mice. Toxicology and applied pharmacology. 2003; 186, 717.10.1016/S0041-008X(02)00022-4
14. Tokar, EJ, Diwan, BA, Ward, JM, Delker, DA, Waalkes, MP. Carcinogenic effects of “whole-life” exposure to inorganic arsenic in CD1 mice. Toxicological sciences : an official journal of the Society of Toxicology. 2011; 119, 7383.10.1093/toxsci/kfq315
15. Tong, VT, Jones, JR, Dietz, PM, et al. Trends in smoking before, during, and after pregnancy - Pregnancy Risk Assessment Monitoring System (PRAMS), United States, 31 sites, 2000-2005. Morbidity and mortality weekly report Surveillance summaries. 2009; 58, 129.
16. Magnus, MC, Haberg, SE, Karlstad, O, et al. Grandmother’s smoking when pregnant with the mother and asthma in the grandchild: the Norwegian Mother and Child Cohort Study. Thorax. 2015; 70, 237243.10.1136/thoraxjnl-2014-206438
17. Breton, CV, Byun, HM, Wenten, M, et al. Prenatal tobacco smoke exposure affects global and gene-specific DNA methylation. American journal of respiratory and critical care medicine. 2009; 180, 462467.10.1164/rccm.200901-0135OC
18. Guerrero-Preston, R, Goldman, LR, Brebi-Mieville, P, et al. Global DNA hypomethylation is associated with in utero exposure to cotinine and perfluorinated alkyl compounds. Epigenetics. 2010; 5, 539546.10.4161/epi.5.6.12378
19. Murphy, SK, Adigun, A, Huang, Z, et al. Gender-specific methylation differences in relation to prenatal exposure to cigarette smoke. Gene. 2012; 494, 3643.10.1016/j.gene.2011.11.062
20. Suter, M, Abramovici, A, Aagaard-Tillery, K. Genetic and epigenetic influences associated with intrauterine growth restriction due to in utero tobacco exposure. Pediatric endocrinology reviews : PER. 2010; 8, 94102.
21. Suter, M, Ma, J, Harris, A, et al. Maternal tobacco use modestly alters correlated epigenome-wide placental DNA methylation and gene expression. Epigenetics. 2011; 6, 12841294.
22. Joubert, BR, Haberg, SE, Nilsen, RM, et al. 450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environmental health perspectives. 2012; 120, 14251431.10.1289/ehp.1205412
23. Markunas, CA, Xu, Z, Harlid, S, et al. Identification of DNA methylation changes in newborns related to maternal smoking during pregnancy. Environmental health perspectives. 2014; 122, 11471153.10.1289/ehp.1307892
24. Adkins, RM, Tylavsky, FA, Krushkal, J. Newborn umbilical cord blood DNA methylation and gene expression levels exhibit limited association with birth weight. Chemistry & biodiversity. 2012; 9, 888899.
25. Engel, SM, Joubert, BR, Wu, MC, et al. Neonatal genome-wide methylation patterns in relation to birth weight in the Norwegian Mother and Child Cohort. American journal of epidemiology. 2014; 179, 834842.10.1093/aje/kwt433
26. Kupers, LK, Xu, X, Jankipersadsing, SA, et al. DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring. International journal of epidemiology. 2015; 44, 12241237.10.1093/ije/dyv048
27. Rehan, VK, Liu, J, Naeem, E, et al. Perinatal nicotine exposure induces asthma in second generation offspring. BMC medicine. 2012; 10, 129.10.1186/1741-7015-10-129
28. Johns, JM, Louis, TM, Becker, RF, Means, LW. Behavioral effects of prenatal exposure to nicotine in guinea pigs. Neurobehavioral toxicology and teratology. 1982; 4, 365369.
29. Levin, ED, Briggs, SJ, Christopher, NC, Rose, JE. Prenatal nicotine exposure and cognitive performance in rats. Neurotoxicology and teratology. 1993; 15, 251260.10.1016/0892-0362(93)90006-A
30. Sorenson, CA, Raskin, LA, Suh, Y. The effects of prenatal nicotine on radial-arm maze performance in rats. Pharmacology, biochemistry, and behavior. 1991; 40, 991993.10.1016/0091-3057(91)90117-K
31. Yanai, J, Pick, CG, Rogel-Fuchs, Y, Zahalka, EA. Alterations in hippocampal cholinergic receptors and hippocampal behaviors after early exposure to nicotine. Brain research bulletin. 1992; 29, 363368.
32. Zahalka, EA, Seidler, FJ, Lappi, SE, et al. Deficits in development of central cholinergic pathways caused by fetal nicotine exposure: differential effects on choline acetyltransferase activity and [3H]hemicholinium-3 binding. Neurotoxicology and teratology. 1992; 14, 375382.10.1016/0892-0362(92)90047-E
33. Moisiadis, VG, Matthews, SG. Glucocorticoids and fetal programming part 2: Mechanisms. Nature reviews Endocrinology. 2014a; 10, 403411.10.1038/nrendo.2014.74
34. Moisiadis, VG, Matthews, SG. Glucocorticoids and fetal programming part 1: Outcomes. Nature reviews Endocrinology. 2014b; 10, 391402.
35. Murphy, KE, Hannah, ME, Willan, AR, et al. Multiple courses of antenatal corticosteroids for preterm birth (MACS): a randomised controlled trial. Lancet. 2008; 372, 21432151.
36. Wapner, RJ, et al. Single versus weekly courses of antenatal corticosteroids: evaluation of safety and efficacy. American journal of obstetrics and gynecology. 2006; 195, 633642.
37. Wapner, RJ, Sorokin, Y, Mele, L, et al. Long-term outcomes after repeat doses of antenatal corticosteroids. The New England journal of medicine. 2007; 357, 11901198.
38. Asztalos, E, Willan, A, Murphy, K, et al. Association between gestational age at birth, antenatal corticosteroids, and outcomes at 5 years: multiple courses of antenatal corticosteroids for preterm birth study at 5 years of age (MACS-5). BMC pregnancy and childbirth. 2014; 14, 272.
39. Asztalos, EV, Murphy, KE, Willan, AR, et al. Multiple courses of antenatal corticosteroids for preterm birth study: outcomes in children at 5 years of age (MACS-5). JAMA pediatrics. 2013; 167, 11021110.
40. Newnham, JP, Evans, SF, Godfrey, M, et al. Maternal, but not fetal, administration of corticosteroids restricts fetal growth. The Journal of maternal-fetal medicine. 1999; 8, 8187.
41. Drake, AJ, Walker, BR, Seckl, JR. Intergenerational consequences of fetal programming by in utero exposure to glucocorticoids in rats. Am J Physiol Regul Integr Comp Physiol. 2005; 288, R3438.
42. Levitt, NS, Lindsay, RS, Holmes, MC, Seckl, JR. Dexamethasone in the last week of pregnancy attenuates hippocampal glucocorticoid receptor gene expression and elevates blood pressure in the adult offspring in the rat. Neuroendocrinology. 1996; 64, 412418.
43. Liu, L, Li, A, Matthews, SG. Maternal glucocorticoid treatment programs HPA regulation in adult offspring: sex-specific effects. American journal of physiology Endocrinology and metabolism. 2001; 280, E729739.
44. Sloboda, DM, Moss, TJ, Gurrin, LC, Newnham, JP, Challis, JR. The effect of prenatal betamethasone administration on postnatal ovine hypothalamic-pituitary-adrenal function. J Endocrinol. 2002; 172, 7181.
45. Uno, H, Eisele, S, Sakai, A, et al. Neurotoxicity of glucocorticoids in the primate brain. Hormones and behavior. 1994; 28, 336348.
46. Crudo, A, Petropoulos, S, Moisiadis, VG, et al. Prenatal synthetic glucocorticoid treatment changes DNA methylation states in male organ systems: multigenerational effects. Endocrinology. 2012; 153, 32693283.
47. Crudo, A, Petropoulos, S, Suderman, M, et al. Effects of antenatal synthetic glucocorticoid on glucocorticoid receptor binding, DNA methylation, and genome-wide mRNA levels in the fetal male hippocampus. Endocrinology. 2013a; 154, 41704181.
48. Crudo, A, Suderman, M, Moisiadis, VG, et al. Glucocorticoid programming of the fetal male hippocampal epigenome. Endocrinology. 2013b; 154, 11681180.
49. Hompes, T, Izzi, B, Gellens, E, et al. Investigating the influence of maternal cortisol and emotional state during pregnancy on the DNA methylation status of the glucocorticoid receptor gene (NR3C1) promoter region in cord blood. Journal of psychiatric research. 2013; 47, 880891.
50. Mulligan, CJ, D’Errico, NC, Stees, J, Hughes, DA. Methylation changes at NR3C1 in newborns associate with maternal prenatal stress exposure and newborn birth weight. Epigenetics. 2012; 7, 853857.
51. Oberlander, TF, Weinberg, J, Papsdorf, M, et al. Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3C1) and infant cortisol stress responses. Epigenetics. 2008; 3, 97106.
52. Gurnot, C, Martin-Subero, I, Mah, SM, et al. Prenatal antidepressant exposure associated with CYP2E1 DNA methylation change in neonates. Epigenetics. 2015; 10, 361372.
53. Non, AL, Binder, AM, Kubzansky, LD, Michels, KB. Genome-wide DNA methylation in neonates exposed to maternal depression, anxiety, or SSRI medication during pregnancy. Epigenetics. 2014; 9, 964972.
54. Nemoda, Z, Massart, R, Suderman, M, et al. Maternal depression is associated with DNA methylation changes in cord blood T lymphocytes and adult hippocampi. Translational psychiatry. 2015; 5, e545.
55. Champagne, FA, Francis, DD, Mar, A, Meaney, MJ. Variations in maternal care in the rat as a mediating influence for the effects of environment on development. Physiology & behavior. 2003; 79, 359371.
56. Francis, D, Diorio, J, Liu, D, Meaney, MJ. Nongenomic transmission across generations of maternal behavior and stress responses in the rat. Science. 1999; 286, 11551158.
57. Weaver, IC, Cervoni, N, Champagne, FA, et al. Epigenetic programming by maternal behavior. Nature neuroscience. 2004; 7, 847854.
58. Weaver, IC, Meaney, MJ, Szyf, M. Maternal care effects on the hippocampal transcriptome and anxiety-mediated behaviors in the offspring that are reversible in adulthood. Proceedings of the National Academy of Sciences of the United States of America. 2006; 103, 34803485.
59. McGowan, PO, Suderman, M, Sasaki, A, et al. Broad epigenetic signature of maternal care in the brain of adult rats. PloS one. 2011; 6, e14739.
60. Mueller, BR, Bale, TL. Sex-specific programming of offspring emotionality after stress early in pregnancy. The Journal of neuroscience : the official journal of the Society for Neuroscience. 2008; 28, 90559065.
61. St-Cyr, S, McGowan, PO. Programming of stress-related behavior and epigenetic neural gene regulation in mice offspring through maternal exposure to predator odor. Frontiers in behavioral neuroscience. 2015; 9, 145.
62. St-Cyr, S, Abuaish, S, Sivanathan, S, McGowan, PO. Maternal programming of sex-specific responses to predator odor stress in adult rats. Hormones and behavior. 2017; 94, 112.
63. Rassoulzadegan, M, Grandjean, V, Gounon, P, et al. RNA-mediated non-mendelian inheritance of an epigenetic change in the mouse. Nature. 2006; 441, 469474.
64. Rodgers, AB, Morgan, CP, Bronson, SL, Revello, S, Bale, TL. Paternal stress exposure alters sperm microRNA content and reprograms offspring HPA stress axis regulation. The. Journal of neuroscience : the official journal of the Society for Neuroscience. 2013; 33, 90039012.
65. Rodgers, AB, Morgan, CP, Leu, NA, Bale, TL. Transgenerational epigenetic programming via sperm microRNA recapitulates effects of paternal stress. Proceedings of the National Academy of Sciences of the United States of America. 2015; 112, 1369913704.
66. Reinius, LE, Acevedo, N, Joerink, M, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PloS one. 2012; 7, e41361.
67. Bakulski, KM, Feinberg, JI, Andrews, SV, et al. DNA methylation of cord blood cell types: Applications for mixed cell birth studies. Epigenetics. 2016; 11, 354362.
68. Jaffe, AE, Irizarry, RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome biology. 2014; 15, R31.
69. Debey, S, Schoenbeck, U, Hellmich, M, et al. Comparison of different isolation techniques prior gene expression profiling of blood derived cells: impact on physiological responses, on overall expression and the role of different cell types. The pharmacogenomics journal. 2004; 4, 193207.
70. Baechler, EC, Batliwalla, FM, Karypis, G, et al. Expression levels for many genes in human peripheral blood cells are highly sensitive to ex vivo incubation. Genes and immunity. 2004; 5, 347353.
71. Guthrie, R, Susi, A. A Simple Phenylalanine Method for Detecting Phenylketonuria in Large Populations of Newborn Infants. Pediatrics. 1963; 32, 338343.
72. Aberg, KA, Xie, LY, Nerella, S, et al. High quality methylome-wide investigations through next-generation sequencing of DNA from a single archived dry blood spot. Epigenetics. 2013; 8, 542547.
73. Ghantous, A, Saffery, R, Cros, MP, et al. Optimized DNA extraction from neonatal dried blood spots: application in methylome profiling. BMC biotechnology. 2014; 14, 60.
74. Hardin, J, Finnell, RH, Wong, D, et al. Whole genome microarray analysis, from neonatal blood cards. BMC genetics. 2009; 10, 38.
75. Hollegaard, MV, Grauholm, J, Nielsen, R, et al. Archived neonatal dried blood spot samples can be used for accurate whole genome and exome-targeted next-generation sequencing. Molecular genetics and metabolism. 2013; 110, 6572.
76. Joo, JE, Wong, EM, Baglietto, L, et al. The use of DNA from archival dried blood spots with the Infinium HumanMethylation450 array. BMC biotechnology. 2013; 13, 23.
77. Michels, KB, Binder, AM, Dedeurwaerder, S, et al. Recommendations for the design and analysis of epigenome-wide association studies. Nature methods. 2013; 10, 949955.
78. Plongthongkum, N, Diep, DH, Zhang, K. Advances in the profiling of DNA modifications: cytosine methylation and beyond. Nature reviews Genetics. 2014; 15, 647661.
79. Chen, YA, Lemire, M, Choufani, S, et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics. 2013; 8, 203209.
80. Dedeurwaerder, S, Defrance, M, Calonne, E, et al. Evaluation of the Infinium Methylation 450K technology. Epigenomics. 2011; 3, 771784.
81. Pidsley, R, Zotenko, E, Peters, TJ, et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome biology. 2016; 17, 208.
82. Bock, C. Analysing and interpreting DNA methylation data. Nature reviews Genetics. 2012; 13, 705719.
83. Liu, Y, Siegmund, KD, Laird, PW, Berman, BP. Bis-SNP: combined DNA methylation and SNP calling for Bisulfite-seq data. Genome biology. 2012; 13, R61.
84. Guo, JU, Su, Y, Zhong, C, Ming, GL, Song, H. Hydroxylation of 5-methylcytosine by TET1 promotes active DNA demethylation in the adult brain. Cell. 2011a; 145, 423434.
85. Guo, JU, Su, Y, Zhong, C, Ming, GL, Song, H. Emerging roles of TET proteins and 5-hydroxymethylcytosines in active DNA demethylation and beyond. Cell cycle. 2011b; 10, 26622668.
86. Booij, L, Szyf, M, Carballedo, A, et al. DNA methylation of the serotonin transporter gene in peripheral cells and stress-related changes in hippocampal volume: a study in depressed patients and healthy controls. PloS one. 2015; 10, e0119061.
87. Liu, XS, Wu, H, Ji, X, et al. Editing DNA Methylation in the Mammalian Genome. Cell. 2016; 167(233-247), e217.


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Genome-wide epigenetic signatures of childhood adversity in early life: Opportunities and challenges

  • Aya Sasaki (a1) and Stephen G. Matthews (a1) (a2) (a3)


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