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Research Article

Prenatal maternal stress is associated with site-specific and age acceleration changes in maternal and newborn DNA methylation

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Article: 2222473 | Received 17 Feb 2023, Accepted 01 Jun 2023, Published online: 10 Jun 2023

References

  • Coussons-Read ME. Effects of prenatal stress on pregnancy and human development: mechanisms and pathways. Obstet Med. 2013;6(2):52–16. doi:10.1177/1753495x12473751
  • Entringer S, Wüst S, Kumsta R, et al. Prenatal psychosocial stress exposure is associated with insulin resistance in young adults. Am J Obstet Gynecol. 2008;199:498.e1–7. doi:10.1016/j.ajog.2008.03.006
  • Bianco-Miotto T, Craig JM, Gasser YP, et al. Epigenetics and DOHaD: from basics to birth and beyond. J Dev Orig Health Dis. 2017;8:513–519. doi:10.1017/S2040174417000733
  • Bussières E-L, Tarabulsy GM, Pearson J, et al. Maternal prenatal stress and infant birth weight and gestational age: a meta-analysis of prospective studies. Developmental Review. 2015;36:179–199. doi:10.1016/j.dr.2015.04.001
  • Belbasis L, Savvidou MD, Kanu C, et al. Birth weight in relation to health and disease in later life: an umbrella review of systematic reviews and meta-analyses. BMC Med. 2016;14(1):147. doi:10.1186/s12916-016-0692-5
  • Laplante DP, Brunet A, Schmitz N, et al. Project ice storm: prenatal maternal stress affects cognitive and linguistic functioning in 5 1/2-year-old children. J Am Acad Child Adolesc Psychiatry. 2008;47:1063–1072. doi:10.1097/CHI.0b013e31817eec80
  • O’Connor TG, Heron J, Golding J, et al. ALSPAC study team. Maternal antenatal anxiety and behavioural/emotional problems in children: a test of a programming hypothesis. J Child Psychol Psychiatr. 2003;44(7):1025–1036. doi:10.1111/1469-7610.00187
  • Cusick SE, Georgieff MK. The role of nutrition in brain development: the golden opportunity of the “first 1000 days”. J Pediatr. 2016;175:16–21. doi:10.1016/j.jpeds.2016.05.013
  • Aristizabal MJ, Anreiter I, Halldorsdottir T, et al. Biological embedding of experience: a primer on epigenetics. Proc Natl Acad Sci, USA. 2020;117(38):23261–23269. doi:10.1073/pnas.1820838116
  • Greenberg MVC, Bourc’his D. The diverse roles of DNA methylation in mammalian development and disease. Nat Rev Mol Cell Biol. 2019;20(10):590–607. doi:10.1038/s41580-019-0159-6
  • Klengel T, Mehta D, Anacker C, et al. Allele-specific FKBP5 DNA demethylation mediates gene-childhood trauma interactions. Nat Neurosci. 2013;16:33–41. doi:10.1038/nn.3275
  • Mulligan CJ. Early environments, stress, and the epigenetics of human health. Annu Rev Anthropol. 2016;45(1):233–249. doi:10.1146/annurev-anthro-102215-095954
  • Mulligan CJ. Insights from epigenetic studies on human health and evolution. Curr Opin Genet Dev. 2018;53:36–42. doi:10.1016/j.gde.2018.06.008
  • Sharma R, Frasch MG, Zelgert C, et al. Maternal-fetal stress and DNA methylation signatures in neonatal saliva: an epigenome-wide association study. Clin Epigenetics. 2022;14:87. doi:10.1186/s13148-022-01310-x
  • Viuff AC, Sharp GC, Rai D, et al. Maternal depression during pregnancy and cord blood DNA methylation: findings from the avon longitudinal study of parents and children. Transl Psychiatry. 2018;8(1):244. doi:10.1038/s41398-018-0286-4
  • Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:R115. doi:10.1186/gb-2013-14-10-r115
  • Palma-Gudiel H, Fañanás L, Horvath S, et al. Psychosocial stress and epigenetic aging. Int Rev Neurobiol. 2020;150:107–128 doi:10.1016/bs.irn.2019.10.020.
  • Zannas AS, Arloth J, Carrillo-Roa T, et al. Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling. Genome Biol. 2015;16(1):1–12. doi:10.1186/s13059-015-0828-5
  • Jovanovic T, Vance LA, Cross D, et al. Exposure to violence accelerates epigenetic aging in children. Sci Rep. 2017;7(1):8962. doi:10.1038/s41598-017-09235-9
  • McGill MG, Pokhvisneva I, Clappison AS, et al. Maternal prenatal anxiety and the fetal origins of epigenetic aging. Biol Psychiatry. 2022;91(3):303–312. doi:10.1016/j.biopsych.2021.07.025
  • Oblak L, van der Zaag J, Higgins-Chen AT, et al. A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration. Ageing Res Rev. 2021;69:101348. doi:10.1016/j.arr.2021.101348
  • Rodney NC, Mulligan CJ. A biocultural study of the effects of maternal stress on mother and newborn health in the Democratic Republic of Congo. Am J Phys Anthropol. 2014;155:200–209. doi:10.1002/ajpa.22568
  • Clukay CJ, Hughes DA, Kertes DA, et al. Associations between maternal psychosocial stress, DNA methylation, and newborn birth weight identified by investigating methylation at individual, regional, and genome levels. Hum Biol. 2019;91:117–131. doi:10.13110/humanbiology.91.2.04
  • Mulligan CJ, D’Errico NC, Stees J, et al. Methylation changes at NR3C1 in newborns associate with maternal prenatal stress exposure and newborn birth weight. Epigenetics. 2012;7(8):853–857. doi:10.4161/epi.21180
  • Kertes DA, Kamin HS, Hughes DA, et al. Prenatal maternal stress predicts methylation of genes regulating the hypothalamic-pituitary-adrenocortical system in mothers and newborns in the Democratic Republic of Congo. Child Dev. 2016;87:61–72. doi:10.1111/cdev.12487
  • Kertes DA, Bhatt SS, Kamin HS, et al. BNDF methylation in mothers and newborns is associated with maternal exposure to war trauma. Clin Epigenetics. 2017;9(1):68. doi:10.1186/s13148-017-0367-x
  • Montoya-Williams D, Quinlan J, Clukay C, et al. Associations between maternal prenatal stress, methylation changes in IGF1 and IGF2, and birth weight. J Dev Orig Health Dis. 2018;9(2):215–222. doi:10.1017/S2040174417000800
  • Clukay CJ, Hughes DA, Rodney NC, et al. DNA methylation of methylation complex genes in relation to stress and genome-wide methylation in mother-newborn dyads. Am J Phys Anthropol. 2018;165:173–182. doi:10.1002/ajpa.23341
  • Bremner JD, Bolus R, Mayer EA. Psychometric properties of the early trauma inventory-self report. J Nerv Ment Dis. 2007;195:211–218. doi:10.1097/01.nmd.0000243824.84651.6c
  • Hooper LM, Stockton P, Krupnick JL, et al. Development, use, and psychometric properties of the trauma history questionnaire. J Loss Trauma. 2011;16(3):258–283. doi:10.1080/15325024.2011.572035
  • Kanner AD, Coyne JC, Schaefer C, et al. Comparison of two modes of stress measurement: daily hassles and uplifts versus major life events. J Behav Med. 1981;4(1):1–39. doi:10.1007/BF00844845
  • Haftorn KL, Lee Y, Denault WRP, et al. An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies. Clin Epigenetics. 2021;13(1):82. doi:10.1186/s13148-021-01055-z
  • Green MR, Sambrook J. Precipitation of DNA with Ethanol. Cold Spring Harb Protoc. 2016;2016:pdb.prot093377. doi:10.1101/pdb.prot093377
  • R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2021.
  • Min JL, Hemani G, Davey Smith G, et al. Meffil: efficient normalization and analysis of very large DNA methylation datasets. Bioinformatics. 2018;34(23):3983–3989. doi:10.1093/bioinformatics/bty476
  • Heiss JA, Just AC. Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO. Clin Epigenetics. 2018;10(1):73. doi:10.1186/s13148-018-0504-1
  • Salas LA, Koestler DC, Butler RA, et al. An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome Biol. 2018;19(1):64. doi:10.1186/s13059-018-1448-7
  • Gervin K, Salas LA, Bakulski KM, et al. Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data. Clin Epigenetics. 2019;11(1):125. doi:10.1186/s13148-019-0717-y
  • Zhou W, Triche TJ, Laird PW, et al. SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions. Nucleic Acids Res. 2018;46:e123. doi:10.1093/nar/gky691
  • Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8(1):118–127. doi:10.1093/biostatistics/kxj037
  • Leek JT, Johnson WE, Parker HS, et al. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28(6):882–883. doi:10.1093/bioinformatics/bts034
  • Zhou W, Laird PW, Shen H. Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes. Nucleic Acids Res. 2017;45:e22. doi:10.1093/nar/gkw967
  • Sharp GC, Salas LA, Monnereau C, et al. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium. Hum Mol Genet. 2017;26(20):4067–4085. doi:10.1093/hmg/ddx290
  • Liu C, Marioni RE, Hedman ÅK, et al. A DNA methylation biomarker of alcohol consumption. Mol Psychiatry. 2018;23(2):422–433. doi:10.1038/mp.2016.192
  • Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15(2):R31. doi:10.1186/gb-2014-15-2-r31
  • Ryan CP, Hayes MG, Lee NR, et al. Reproduction predicts shorter telomeres and epigenetic age acceleration among young adult women. Sci Rep. 2018;8(1):11100. doi:10.1038/s41598-018-29486-4
  • Jones MJ, Goodman SJ, Kobor MS. DNA methylation and healthy human aging. Aging Cell. 2015;14(6):924–932. doi:10.1111/acel.12349
  • Schlinzig T, Johansson S, Gunnar A, et al. Epigenetic modulation at birth - altered DNA-methylation in white blood cells after Caesarean section. Acta Paediatr. 2009;98:1096–1099. doi:10.1111/j.1651-2227.2009.01371.x
  • Horvath S, Gurven M, Levine ME, et al. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol. 2016;17(1):1–22. doi:10.1186/s13059-016-1030-0
  • Lu AT, Seeboth A, Tsai P-C, et al. DNA methylation-based estimator of telomere length. Aging. 2019;11(16):5895–5923. doi:10.18632/aging.102173
  • Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging. 2018;10(4):573–591. doi:10.18632/aging.101414
  • Lu AT, Quach A, Wilson JG, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging. 2019;11(2):303–327. doi:10.18632/aging.101684
  • Breeze CE, Reynolds AP, van Dongen J, et al. eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data. Bioinformatics. 2019;35(22):4767–4769. doi:10.1093/bioinformatics/btz456
  • Breeze CE. Cell type-specific signal analysis in epigenome-wide association studies. Methods Mol Biol. 2022;2432:57–71.
  • Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847–2849. doi:10.1093/bioinformatics/btw313
  • Hammes SR, Levin ER. Impact of estrogens in males and androgens in females. J Clin Invest. 2019;129(5):1818–1826. doi:10.1172/JCI125755
  • Alameda F, Mejías-Luque R, Garrido M, et al. Mucin genes (MUC2, MUC4, MUC5AC, and MUC6) detection in normal and pathological endometrial tissues. Int J Gynecol Pathol. 2007;26:61–65. doi:10.1097/01.pgp.0000225837.32719.c1
  • Dharmaraj N, Chapela PJ, Morgado M, et al. Expression of the transmembrane mucins, MUC1, MUC4 and MUC16, in normal endometrium and in endometriosis. Hum Reprod. 2014;29(8):1730–1738. doi:10.1093/humrep/deu146
  • Chang C-Y, Chang H-W, Chen C-M, et al. MUC4 gene polymorphisms associate with endometriosis development and endometriosis-related infertility. BMC Med. 2011;9:19. doi:10.1186/1741-7015-9-19
  • Kim J-H, Park H-S, Lee J-Y, et al. Association study between Mucin 4 (MUC4) polymorphisms and idiopathic recurrent pregnancy loss in a Korean population. Genes (Basel). 2022;13(6):937. doi:10.3390/genes13060937
  • Harris HR, Wieser F, Vitonis AF, et al. Early life abuse and risk of endometriosis. Hum Reprod. 2018;33(9):1657–1668. doi:10.1093/humrep/dey248
  • Wang L, Zhang J, Xia M, et al. High mobility group A1 (HMGA1): structure, biological function, and therapeutic potential. Int J Biol Sci. 2022;18(11):4414–4431. doi:10.7150/ijbs.72952
  • Bamberger A-M, Makrigiannakis A, Röser K, et al. Expression of the high-mobility group protein HMGI(Y) in human trophoblast: potential role in trophoblast invasion of maternal tissue. Virchows Arch. 2003;443:649–654. doi:10.1007/s00428-003-0892-1
  • Matsubara K, Matsubara Y, Uchikura Y, et al. HMGA1 is a potential driver of preeclampsia pathogenesis by interference with extravillous trophoblasts invasion. Biomolecules. 2021;11(6):11. doi:10.3390/biom11060822
  • Zhang D, Penttila TL, Morris PL, et al. Spermiogenesis deficiency in mice lacking the Trf2 gene. Science. 2001;292(5519):1153–1155. doi:10.1126/science.1059188
  • Kuzmin A, Jarvi K, Lo K, et al. Identification of potentially damaging amino acid substitutions leading to human male infertility. Biol Reprod. 2009;81(2):319–326. doi:10.1095/biolreprod.109.076000
  • Balakrishnan MP, Cilenti L, Ambivero C, et al. THAP5 is a DNA-binding transcriptional repressor that is regulated in melanoma cells during DNA damage-induced cell death. Biochem Biophys Res Commun. 2011;404(1):195–200. doi:10.1016/j.bbrc.2010.11.092
  • Balakrishnan MP, Cilenti L, Mashak Z, et al. THAP5 is a human cardiac-specific inhibitor of cell cycle that is cleaved by the proapoptotic Omi/HtrA2 protease during cell death. Am J Physiol Heart Circ Physiol. 2009;297(2):H643–53. doi:10.1152/ajpheart.00234.2009
  • Barker DJ, Gluckman PD, Godfrey KM, et al. Fetal nutrition and cardiovascular disease in adult life. Lancet. 1993;341:938–941. doi:10.1016/0140-6736(93)91224-A
  • McColl ER, Piquette-Miller M. Poly(i: c) alters placental and fetal brain amino acid transport in a rat model of maternal immune activation. Am J Reprod Immunol. 2019;81:e13115. doi:10.1111/aji.13115
  • Rakers F, Rupprecht S, Dreiling M, et al. Transfer of maternal psychosocial stress to the fetus. Neurosci Biobehav Rev. 2017. doi:10.1016/j.neubiorev.2017.02.019
  • Yim IS, Kofman YB. The psychobiology of stress and intimate partner violence. Psychoneuroendocrinology. 2019;105:9–24. doi:10.1016/j.psyneuen.2018.08.017
  • Rentscher KE, Carroll JE, Mitchell C. Psychosocial stressors and telomere length: a current review of the science. Annu Rev Public Health. 2020;41(1):223–245. doi:10.1146/annurev-publhealth-040119-094239
  • Danese A, Baldwin JR. Hidden wounds? inflammatory links between childhood trauma and psychopathology. Annu Rev Psychol. 2017;68:517–544. doi:10.1146/annurev-psych-010416-044208
  • van den Oord CLJD, Copeland WE, Zhao M, et al. DNA methylation signatures of childhood trauma predict psychiatric disorders and other adverse outcomes 17 years after exposure. Mol Psychiatry. 2022;27:3367–3373. doi:10.1038/s41380-022-01597-5
  • Zhang X, Lin P-Y, Liakath-Ali K, et al. Teneurins assemble into presynaptic nanoclusters that promote synapse formation via postsynaptic non-teneurin ligands. Nat Commun. 2022;13(1):2297. doi:10.1038/s41467-022-29751-1
  • Breeze CE, Wong JYY, Beck S, et al. Diversity in EWAS: current state, challenges, and solutions. Genome Med. 2022;14(1):71. doi:10.1186/s13073-022-01065-3
  • Non AL. Social epigenomics: are we at an impasse? Epigenomics. 2021;13(21):1747–1759. doi:10.2217/epi-2020-0136
  • D’Errico NC, Wake CM, Wake RM. Healing Africa? Reflections on the peace-building role of a health-based non governmental organization operating in eastern Democratic Republic of Congo. Med Confl Surviv. 2010;26(2):145–159. doi:10.1080/13623699.2010.491390
  • Bakulski KM, Halladay A, Hu VW, et al. Epigenetic research in neuropsychiatric disorders: the “tissue issue”. Curr Behav Neurosci Rep. 2016;3(3):264–274. doi:10.1007/s40473-016-0083-4