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Dynamic DNA methylation changes in early versus late adulthood suggest nondeterministic effects of childhood adversity: a meta-analysis

Published online by Cambridge University Press:  14 December 2020

Rocio Artigas ,
Fabián Vega-Tapia ,
James Hamilton  and
Bernardo J. Krause Open the ORCID record for Bernardo J. Krause [Opens in a new window]
Rocio Artigas
Affiliation:
CUIDA – Centro de Investigación del Abuso y la Adversidad Temprana, Pontificia Universidad Católica de Chile, Avenida Libertador Bernardo O’Higgins 340, Santiago, Chile Instituto de Ingeniería Biológica y Médica, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Macul, Santiago, Chile
Fabián Vega-Tapia
Affiliation:
Instituto de Ciencias de la Salud, Universidad de O’Higgins, Avenida Libertador Bernardo O’Higgins 611, Rancagua, Chile
James Hamilton
Affiliation:
CUIDA – Centro de Investigación del Abuso y la Adversidad Temprana, Pontificia Universidad Católica de Chile, Avenida Libertador Bernardo O’Higgins 340, Santiago, Chile Fundación Para la Confianza, Pérez Valenzuela 1264, Providencia, Santiago, Chile
Bernardo J. Krause*
Affiliation:
CUIDA – Centro de Investigación del Abuso y la Adversidad Temprana, Pontificia Universidad Católica de Chile, Avenida Libertador Bernardo O’Higgins 340, Santiago, Chile Instituto de Ciencias de la Salud, Universidad de O’Higgins, Avenida Libertador Bernardo O’Higgins 611, Rancagua, Chile
*
Address for correspondence: Bernardo J. Krause, Avenida Libertador Bernardo O’Higgins 611, Rancagua, Chile. Email: bjkrause@gmail.com
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Abstract

Adverse childhood experiences (ACEs) are associated with a high risk of developing chronic diseases and decreased life expectancy, but no ACE epigenetic biomarkers have been identified until now. The latter may result from the interaction of multiple factors such as age, sex, degree of adversity, and lack of transcriptional effects of DNA methylation changes. We hypothesize that DNA methylation changes are related to childhood adversity levels and current age, and these markers evolve as aging proceeds. Two Gene Expression Omnibus datasets, regarding ACE, were selected (GSE72680 and GSE70603), considering raw- and meta-data availability, including validated ACE index (Childhood Trauma Questionnaire (CTQ) score). For DNA methylation, analyzed probes were restricted to those laying within promoters and first exons, and samples were grouped by CTQ scores terciles, to compare highly (ACE) with non-abused (control) cases. Comparison of control and ACE methylome profile did not retrieve differentially methylated CpG sites (DMCs) after correcting by false discovery rate < 0.05, and this was also observed when samples were separated by sex. In contrast, grouping by decade age ranges (i.e., the 20s, 30s, 40s, and 50s) showed a progressive increase in the number of DMCs and the intensity of changes, mainly related with hypomethylation. Comparison with transcriptome data for ACE subjects in the 40s, and 50s showed a similar age-dependent effect. This study provides evidence that epigenetic markers of ACE are age-dependent, but not defined in the long term. These differences among early, middle, and late adulthood epigenomic profiles suggest a window for interventions aimed to prevent the detrimental effects of ACE.

Keywords

Adverse childhood experiencesepigeneticsagingDNA methylation
Type
Original Article
Information
Journal of Developmental Origins of Health and Disease , Volume 12 , Issue 5 , October 2021 , pp. 768 - 779
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Copyright
© The Author(s), 2020. Published by Cambridge University Press in association with International Society for Developmental Origins of Health and Disease

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References

Anda, RF, Butchart, A, Felitti, VJ, Brown, DW. Building a framework for global surveillance of the public health implications of adverse childhood experiences. Am J Prev Med. 2010; 39(1), 93–98.CrossRefGoogle ScholarPubMed
Felitti, VJ, Anda, RF, Nordenberg, D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998; 14(4), 245–258.CrossRefGoogle ScholarPubMed
Brown, DW, Anda, RF, Tiemeier, H, et al. Adverse childhood experiences and the risk of premature mortality. Am J Prev Med. 2009; 37(5), 389–396.CrossRefGoogle ScholarPubMed
Dong, M, Giles, WH, Felitti, VJ, et al. Insights into causal pathways for ischemic heart disease: adverse childhood experiences study. Circulation. 2004; 110(13), 1761–1766.CrossRefGoogle ScholarPubMed
Ridout, KK, Coe, JL, Parade, SH, et al. Molecular markers of neuroendocrine function and mitochondrial biogenesis associated with early life stress. Psychoneuroendocrinology. 2020; 116, 104632.CrossRefGoogle ScholarPubMed
Ridout, KK, Khan, M, Ridout, SJ. Adverse childhood experiences run deep: toxic early life stress, telomeres, and mitochondrial DNA copy number, the biological markers of cumulative stress. Bioessays. 2018; 40(9), e1800077.CrossRefGoogle ScholarPubMed
Oh, DL, Jerman, P, Silverio Marques, S, et al. Systematic review of pediatric health outcomes associated with childhood adversity. BMC Pediatr. 2018; 18(1), 83.CrossRefGoogle ScholarPubMed
Lang, J, McKie, J, Smith, H, et al. Adverse childhood experiences, epigenetics and telomere length variation in childhood and beyond: a systematic review of the literature. Eur Child Adolesc Psychiatry. 2019; 29(10), 1329–1338. doi: 10.1007/s00787-019-01329-1.CrossRefGoogle ScholarPubMed
Weaver, IC, Cervoni, N, Champagne, FA, et al. Epigenetic programming by maternal behavior. Nat Neurosci. 2004; 7(8), 847–854.CrossRefGoogle ScholarPubMed
Krause, BJ, Artigas, R, Sciolla, AF, Hamilton, J. Epigenetic mechanisms activated by childhood adversity Epigenomics. 2020; 12(14), 1239–1255. doi: 10.2217/epi-2020-0042.CrossRefGoogle ScholarPubMed
Walsh, ND, Dalgleish, T, Lombardo, MV, et al. General and specific effects of early-life psychosocial adversities on adolescent grey matter volume. Neuroimage Clin. 2014; 4, 308–318.CrossRefGoogle ScholarPubMed
Narita, K, Fujihara, K, Takei, Y, et al. Associations among parenting experiences during childhood and adolescence, hypothalamus-pituitary-adrenal axis hypoactivity, and hippocampal gray matter volume reduction in young adults. Hum Brain Mapp. 2012; 33(9), 2211–2223.CrossRefGoogle ScholarPubMed
Nemeroff, CB. Paradise Lost: The Neurobiological and Clinical Consequences of Child Abuse and Neglect. Neuron. 2016; 89(5), 892–909.CrossRefGoogle ScholarPubMed
Jiang, S, Postovit, L, Cattaneo, A, Binder, EB, Aitchison, KJ. Epigenetic modifications in stress response genes associated with childhood trauma. Front Psychiatry. 2019; 10, 808.CrossRefGoogle ScholarPubMed
Oh, DL, Jerman, P, Purewal Boparai, SK, et al. Review of tools for measuring exposure to adversity in children and adolescents. J Pediatr Health Care. 2018; 32(6), 564–583.CrossRefGoogle ScholarPubMed
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, 266.CrossRefGoogle Scholar
Schwaiger, M, Grinberg, M, Moser, D, et al. Altered stress-induced regulation of genes in monocytes in adults with a history of childhood adversity. Neuropsychopharmacology. 2016; 41(10), 2530–2540.CrossRefGoogle ScholarPubMed
Luo, R, Bai, C, Yang, L, et al. DNA methylation subpatterns at distinct regulatory regions in human early embryos. Open Biol. 2018; 8(10), 180131.CrossRefGoogle ScholarPubMed
Ringner, M. What is principal component analysis? Nat Biotechnol. 2008; 26(3), 303–304.CrossRefGoogle ScholarPubMed
Ritchie, ME, Phipson, B, Wu, D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015; 43(7), e47.CrossRefGoogle ScholarPubMed
Liu, X, Li, N, Liu, S, et al. Normalization methods for the analysis of unbalanced transcriptome data: a review. Front Bioeng Biotechnol. 2019; 7, 358.CrossRefGoogle ScholarPubMed
Krzywinski, M, Schein, J, Birol, I, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009; 19(9), 1639–1645.CrossRefGoogle ScholarPubMed
Palma-Gudiel, H, Cordova-Palomera, A, Leza, JC, Fananas, L. Glucocorticoid receptor gene (NR3C1) methylation processes as mediators of early adversity in stress-related disorders causality: a critical review. Neurosci Biobehav Rev. 2015; 55, 520–535.CrossRefGoogle ScholarPubMed
Jones, PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet. 2012; 13(7), 484–492.CrossRefGoogle ScholarPubMed
Luo, C, Hajkova, P, Ecker, JR. Dynamic DNA methylation: in the right place at the right time. Science. 2018; 361(6409), 1336–1340.CrossRefGoogle Scholar
Teschendorff, AE, Relton, CL. Statistical and integrative system-level analysis of DNA methylation data. Nat Rev Genet. 2018; 19(3), 129–147.CrossRefGoogle ScholarPubMed
Chatterjee, A, Rodger, EJ, Morison, IM, Eccles, MR, Stockwell, PA. Tools and strategies for analysis of genome-wide and gene-specific DNA methylation patterns. Methods Mol Biol. 2017; 1537, 249–277.CrossRefGoogle ScholarPubMed
Clive, ML, Boks, MP, Vinkers, CH, et al. Discovery and replication of a peripheral tissue DNA methylation biosignature to augment a suicide prediction model. Clin Epigenetics. 2016; 8, 113.CrossRefGoogle ScholarPubMed
Rosen, AD, Robertson, KD, Hlady, RA, et al. DNA methylation age is accelerated in alcohol dependence. Transl Psychiatry. 2018; 8(1), 182.CrossRefGoogle ScholarPubMed
Houtepen, LC, Hardy, R, Maddock, J, et al. Childhood adversity and DNA methylation in two population-based cohorts. Transl Psychiatry. 2018; 8(1), 266.CrossRefGoogle ScholarPubMed
Guillemin, C, Provencal, N, Suderman, M, et al. DNA methylation signature of childhood chronic physical aggression in T cells of both men and women. PLoS One. 2014; 9(1), e86822.CrossRefGoogle Scholar
Suderman, M, Borghol, N, Pappas, JJ, et al. Childhood abuse is associated with methylation of multiple loci in adult DNA. BMC Med Genomics. 2014; 7, 13.CrossRefGoogle ScholarPubMed
Roberts, AL, Gladish, N, Gatev, E, et al. Exposure to childhood abuse is associated with human sperm DNA methylation. Transl Psychiatry. 2018; 8(1), 194.CrossRefGoogle ScholarPubMed
Provencal, N, Suderman, MJ, Guillemin, C, et al. Association of childhood chronic physical aggression with a DNA methylation signature in adult human T cells. PLoS One. 2014; 9(4), e89839.CrossRefGoogle ScholarPubMed
Prados, J, Stenz, L, Courtet, P, et al. Borderline personality disorder and childhood maltreatment: a genome-wide methylation analysis. Genes Brain Behav. 2015; 14(2), 177–188.CrossRefGoogle ScholarPubMed
Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 2013; 14(10), R115.CrossRefGoogle ScholarPubMed
Naumova, OY, Hein, S, Suderman, M, et al. Epigenetic patterns modulate the connection between developmental dynamics of parenting and offspring psychosocial adjustment. Child Dev. 2016; 87(1), 98–110.CrossRefGoogle ScholarPubMed
Houtepen, LC, Vinkers, CH, Carrillo-Roa, T, et al. Genome-wide DNA methylation levels and altered cortisol stress reactivity following childhood trauma in humans. Nat Commun. 2016; 7, 10967.CrossRefGoogle ScholarPubMed
Suderman, M, Pappas, JJ, Borghol, N, et al. Lymphoblastoid cell lines reveal associations of adult DNA methylation with childhood and current adversity that are distinct from whole blood associations. Int J Epidemiol. 2015; 44(4), 1331–1340.CrossRefGoogle ScholarPubMed
Marinova, Z, Maercker, A, Kuffer, A, et al. DNA methylation profiles of elderly individuals subjected to indentured childhood labor and trauma. BMC Med Genet. 2017; 18(1), 21.CrossRefGoogle ScholarPubMed
Austin, MK, Chen, E, Ross, KM, et al. Early-life socioeconomic disadvantage, not current, predicts accelerated epigenetic aging of monocytes. Psychoneuroendocrinology. 2018; 97, 131–134.CrossRefGoogle Scholar
Fiorito, G, Polidoro, S, Dugue, PA, et al. Social adversity and epigenetic aging: a multi-cohort study on socioeconomic differences in peripheral blood DNA methylation. Sci Rep. 2017; 7(1), 16266.CrossRefGoogle Scholar
Lawn, RB, Anderson, EL, Suderman, M, et al. Psychosocial adversity and socioeconomic position during childhood and epigenetic age: analysis of two prospective cohort studies. Hum Mol Genet. 2018; 27(7), 1301–1308.CrossRefGoogle ScholarPubMed
Jovanovic, T, Vance, LA, Cross, D, et al. Exposure to violence accelerates epigenetic aging in children. Sci Rep. 2017; 7(1), 8962.CrossRefGoogle ScholarPubMed
Marini, S, Davis, KA, Soare, TW, et al. Adversity exposure during sensitive periods predicts accelerated epigenetic aging in children. Psychoneuroendocrinology. 2020; 113, 104484.CrossRefGoogle ScholarPubMed
Mehta, D, Klengel, T, Conneely, KN, et al. Childhood maltreatment is associated with distinct genomic and epigenetic profiles in posttraumatic stress disorder. Proc Natl Acad Sci U S A. 2013; 110(20), 8302–8307.CrossRefGoogle ScholarPubMed
Kennedy, EM, Goehring, GN, Nichols, MH, et al. An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells. BMC Genomics. 2018; 19(1), 476.CrossRefGoogle ScholarPubMed
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