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Epigenome-wide associations between observed maternal sensitivity and offspring DNA methylation: a population-based prospective study in children

Published online by Cambridge University Press:  03 December 2020

Lorenza Dall’ Aglio
Affiliation:
Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, The Netherlands The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
Jolien Rijlaarsdam
Affiliation:
Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, The Netherlands The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
Rosa H. Mulder
Affiliation:
Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, The Netherlands The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
Alexander Neumann
Affiliation:
Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, The Netherlands The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
Janine F. Felix
Affiliation:
The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
Rianne Kok
Affiliation:
Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
Marian J. Bakermans-Kranenburg
Affiliation:
Clinical Child and Family Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
Marinus H. van Ijzendoorn
Affiliation:
Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands Primary Care Unit School of Clinical Medicine, University of Cambridge, UK
Henning Tiemeier
Affiliation:
Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, The Netherlands Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, USA
Charlotte A.M. Cecil*
Affiliation:
Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, The Netherlands Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
*
Author for correspondence: Charlotte A.M. Cecil, E-mail: [email protected]

Abstract

Background

Experimental work in animals has shown that DNA methylation (DNAm), an epigenetic mechanism regulating gene expression, is influenced by typical variation in maternal care. While emerging research in humans supports a similar association, studies to date have been limited to candidate gene and cross-sectional approaches, with a focus on extreme deviations in the caregiving environment.

Methods

Here, we explored the prospective association between typical variation in maternal sensitivity and offspring epigenome-wide DNAm, in a population-based cohort of children (N = 235). Maternal sensitivity was observed when children were 3- and 4-years-old. DNAm, quantified with the Infinium 450 K array, was extracted at age 6 (whole blood). The influence of methylation quantitative trait loci (mQTLs), DNAm at birth (cord blood), and confounders (socioeconomic status, maternal psychopathology) was considered in follow-up analyses.

Results

Genome-wide significant associations between maternal sensitivity and offspring DNAm were observed at 13 regions (p < 1.06 × 10−07), but not at single sites. Follow-up analyses indicated that associations at these regions were in part related to genetic factors, confounders, and baseline DNAm levels at birth, as evidenced by the presence of mQTLs at five regions and estimate attenuations. Robust associations with maternal sensitivity were found at four regions, annotated to ZBTB22, TAPBP, ZBTB12, and DOCK4.

Conclusions

These findings provide novel leads into the relationship between typical variation in maternal caregiving and offspring DNAm in humans, highlighting robust regions of associations, previously implicated in psychological and developmental problems, immune functioning, and stress responses.

Type
Original Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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Footnotes

*

Authors contributed equally.

References

Agapite, J., Albou, L.-P., Aleksander, S., Argasinska, J., Arnaboldi, V., Attrill, H., … Yook, K. (2020). Alliance of genome resources portal: Unified model organism research platform. Nucleic Acids Research, 48(D1), D650D658. https://doi.org/10.1093/nar/gkz813.Google Scholar
Alkelai, A., Lupoli, S., Greenbaum, L., Kohn, Y., Kanyas-Sarner, K., Ben-Asher, E., … Lerer, B. (2012). DOCK4 And CEACAM21 as novel schizophrenia candidate genes in the Jewish population. International Journal of Neuropsychopharmacology, 15(4), 459469. https://doi.org/10.1017/S1461145711000903.CrossRefGoogle ScholarPubMed
Aryee, M. J., Jaffe, A. E., Corrada-Bravo, H., Ladd-Acosta, C., Feinberg, A. P., Hansen, K. D., & Irizarry, R. A. (2014). Minfi: A flexible and comprehensive bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics (Oxford, England), 30(10), 13631369. https://doi.org/10.1093/bioinformatics/btu049.CrossRefGoogle ScholarPubMed
Baldwin, J. R., Reuben, A., Newbury, J. B., & Danese, A. (2019). Agreement between prospective and retrospective measures of childhood maltreatment: A systematic review and meta-analysis. JAMA Psychiatry, 76(6), 584593. https://doi.org/10.1001/jamapsychiatry.2019.0097.CrossRefGoogle ScholarPubMed
Barfield, R. T., Kilaru, V., Smith, A. K., & Conneely, K. N. (2012). Cpgassoc: An R function for analysis of DNA methylation microarray data. Bioinformatics (Oxford, England), 28(9), 12801281. https://doi.org/10.1093/bioinformatics/bts124.CrossRefGoogle Scholar
Beery, A. K., McEwen, L. M., MacIsaac, J. L., Francis, D. D., & Kobor, M. S. (2016). Natural variation in maternal care and cross-tissue patterns of oxytocin receptor gene methylation in rats. Hormones and Behavior, 77, 4252. https://doi.org/10.1016/j.yhbeh.2015.05.022.CrossRefGoogle ScholarPubMed
Bernier, A., Carlson, S. M., Deschênes, M., & Matte-Gagné, C. (2012). Social factors in the development of early executive functioning: A closer look at the caregiving environment. Developmental Science, 15(1), 1224. https://doi.org/10.1111/j.1467-7687.2011.01093.x.CrossRefGoogle Scholar
Birney, E., Smith, G. D., & Greally, J. M. (2016). Epigenome-wide association studies and the interpretation of disease -omics. PLoS Genetics, 12, e1006105. https://doi.org/10.1371/journal.pgen.1006105 PGENETICS-D-16-00215 [pii].CrossRefGoogle ScholarPubMed
Blaze, J., Asok, A., Borrelli, K., Tulbert, C., Bollinger, J., Ronca, A. E., & Roth, T. L. (2017). Intrauterine exposure to maternal stress alters Bdnf IV DNA methylation and telomere length in the brain of adult rat offspring. International Journal of Developmental Neuroscience, 62, 5662. https://doi.org/10.1016/j.ijdevneu.2017.03.007.CrossRefGoogle ScholarPubMed
Bosmans, G., Young, J. F., & Hankin, B. L. (2018). NR3C1 Methylation as a moderator of the effects of maternal support and stress on insecure attachment development. Developmental Psychology, 54(1), 2938. https://doi.org/10.1037/dev0000422.CrossRefGoogle ScholarPubMed
Breton, C. V., Byun, H.-M., Wenten, M., Pan, F., Yang, A., & Gilliland, F. D. (2009). Prenatal tobacco smoke exposure affects global and gene-specific DNA methylation. American Journal of Respiratory and Critical Care Medicine, 180(5), 462467. https://doi.org/10.1164/rccm.200901-0135OC.CrossRefGoogle ScholarPubMed
Carey, N. (2012). Life as we know it now. In The epigenetics revolution (pp. 7273). London: Icon Books Ltd.Google Scholar
Cecil, C. A. M., Smith, R. G., Walton, E., Mill, J., McCrory, E. J., & Viding, E. (2016). Epigenetic signatures of childhood abuse and neglect: Implications for psychiatric vulnerability. Journal of Psychiatric Research, 83, 184194. https://doi.org/10.1016/j.jpsychires.2016.09.010.CrossRefGoogle ScholarPubMed
Cecil, C. A. M., Walton, E., Jaffee, S. R., O'Connor, T., Maughan, B., Relton, C. L., … Barker, E. D. (2017). Neonatal DNA methylation and early-onset conduct problems: A genome-wide, prospective study. Development and Psychopathology, 30(2), 383397. https://doi.org/10.1111/jcpp.12782.CrossRefGoogle ScholarPubMed
Cecil, C. A. M., Walton, E., Pingault, J.-B., Provençal, N., Pappa, I., Vitaro, F., … McCrory, E. J. (2018). DRD4 Methylation as a potential biomarker for physical aggression: An epigenome-wide, cross-tissue investigation. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 177(8), 746764. https://doi.org/10.1002/ajmg.b.32689.CrossRefGoogle ScholarPubMed
Cents, R. A. M., Kok, R., Tiemeier, H., Lucassen, N., Székely, E., Bakermans-Kranenburg, M. J., … Berg, M. P. L. den. (2014). Variations in maternal 5-HTTLPR affect observed sensitive parenting. Journal of Child Psychology and Psychiatry, 55(9), 10251032. https://doi.org/10.1111/jcpp.12205.CrossRefGoogle ScholarPubMed
Colquhoun, D. (2014). An investigation of the false discovery rate and the misinterpretation of p-values. Royal Society Open Science, 1(3), 140216. https://doi.org/10.1098/rsos.140216.CrossRefGoogle ScholarPubMed
Conradt, E., Hawes, K., Guerin, D., Armstrong, D. A., Marsit, C. J., Tronick, E., & Lester, B. M. (2016). The contributions of maternal sensitivity and maternal depressive symptoms to epigenetic processes and neuroendocrine functioning. Child Development, 87(1), 7385. https://doi.org/10.1111/cdev.12483.CrossRefGoogle ScholarPubMed
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98104. https://doi.org/10.1037/0021-9010.78.1.98.CrossRefGoogle Scholar
Czamara, D., Eraslan, G., Page, C. M., Lahti, J., Lahti-Pulkkinen, M., Hämäläinen, E., … Binder, E. B. (2019). Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns. Nature Communications, 10(1), 118. https://doi.org/10.1038/s41467-019-10461-0.CrossRefGoogle ScholarPubMed
Daskalakis, N. P., & Yehuda, R. (2014). Site-specific methylation changes in the glucocorticoid receptor exon 1F promoter in relation to life adversity: Systematic review of contributing factors. Frontiers in Neuroscience, 8, 369. https://doi.org/10.3389/fnins.2014.00369.CrossRefGoogle ScholarPubMed
Doherty, T. S., Forster, A., & Roth, T. L. (2016). Global and gene-specific DNA methylation alterations in the adolescent amygdala and hippocampus in an animal model of caregiver maltreatment. Behavioural Brain Research, 298(Pt A), 5561. https://doi.org/10.1016/j.bbr.2015.05.028.CrossRefGoogle Scholar
Edgar, R. D., Jones, M. J., Meaney, M. J., Turecki, G., & Kobor, M. S. (2017). BECon: A tool for interpreting DNA methylation findings from blood in the context of brain. Translational Psychiatry, 7(8), e1187. https://doi.org/10.1038/tp.2017.171.CrossRefGoogle ScholarPubMed
Egeland, B., Erickson, M. F., Clemenhagen-Moon, J., Hiester, M. K., & Korfmacher, J. (1990). 24 months tools coding manual. Project STEEP-revised, 1990, from Mother-Child project scales.Google Scholar
Feldman, R. (2016). The neurobiology of mammalian parenting and the biosocial context of human caregiving. Hormones and Behavior, 77, 317. https://doi.org/10.1016/j.yhbeh.2015.10.001.CrossRefGoogle ScholarPubMed
Gaunt, T. R., Shihab, H. A., Hemani, G., Min, J. L., Woodward, G., Lyttleton, O., … Relton, C. L. (2016). Systematic identification of genetic influences on methylation across the human life course. Genome Biology, 17, 61. https://doi.org/10.1186/s13059-016-0926-z 10.1186/s13059-016-0926-z [pii].CrossRefGoogle ScholarPubMed
Geer, L. Y., Marchler-Bauer, A., Geer, R. C., Han, L., He, J., He, S., … Bryant, S. H. (2010). The NCBI BioSystems database. Nucleic Acids Research, 38, D492D496. https://doi.org/10.1093/nar/gkp858.CrossRefGoogle ScholarPubMed
Glad, C. A. M., Andersson-Assarsson, J. C., Berglund, P., Bergthorsdottir, R., Ragnarsson, O., & Johannsson, G. (2017). Reduced DNA methylation and psychopathology following endogenous hypercortisolism – a genome-wide study. Scientific Reports, 7, 44445. https://doi.org/10.1038/srep44445.CrossRefGoogle ScholarPubMed
Glynn, L. M., & Baram, T. Z. (2019). The influence of unpredictable, fragmented parental signals on the developing brain. Frontiers in Neuroendocrinology, 53, 100736. https://doi.org/10.1016/j.yfrne.2019.01.002.CrossRefGoogle ScholarPubMed
Gouin, J. P., Zhou, Q. Q., Booij, L., Boivin, M., Côté, S. M., Hébert, M., … Vitaro, F. (2017). Associations among oxytocin receptor gene (OXTR) DNA methylation in adulthood, exposure to early life adversity, and childhood trajectories of anxiousness. Scientific Reports, 7(1), 7446. https://doi.org/10.1038/s41598-017-07950-x.CrossRefGoogle ScholarPubMed
Haltigan, J. D., Roisman, G. I., & Fraley, R. C. (2013). The predictive significance of early caregiving experiences for symptoms of psychopathology through midadolescence: Enduring or transient effects? Development and Psychopathology, 25(1), 209221. https://doi.org/10.1017/S0954579412000260.CrossRefGoogle ScholarPubMed
Hannon, E., Dempster, E., Viana, J., Burrage, J., Smith, A. R., Macdonald, R., … Mill, J. (2016). An integrated genetic-epigenetic analysis of schizophrenia: Evidence for co-localization of genetic associations and differential DNA methylation. Genome Biology, 17, 176. https://doi.org/10.1186/s13059-016-1041-x 10.1186/s13059-016-1041-x [pii].CrossRefGoogle ScholarPubMed
Houseman, E. A., Accomando, W. P., Koestler, D. C., Christensen, B. C., Marsit, C. J., Nelson, H. H., … Kelsey, K. T. (2012). DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, 13(1), 86. https://doi.org/10.1186/1471-2105-13-86.CrossRefGoogle ScholarPubMed
Illumina. (2020). Infinium MethylationEPIC Kit | Methylation profiling array for EWAS. https://www.illumina.com/products/by-type/microarray-kits/infinium-methylation-epic.html.Google Scholar
Joubert, B. R., Felix, J. F., Yousefi, P., Bakulski, K. M., Just, A. C., Breton, C., … London, S. J. (2016). DNA methylation in newborns and maternal smoking in pregnancy: Genome-wide consortium meta-analysis. The American Journal of Human Genetics, 98(4), 680696. https://doi.org/10.1016/j.ajhg.2016.02.019.CrossRefGoogle ScholarPubMed
Kimbrel, N. A., Nelson-Gray, R. O., & Mitchell, J. T. (2007). Reinforcement sensitivity and maternal style as predictors of psychopathology. Personality and Individual Differences, 42(6), 11391149. https://doi.org/10.1016/j.paid.2006.06.028.CrossRefGoogle Scholar
Knop, J., Joëls, M., & van der Veen, R. (2017). The added value of rodent models in studying parental influence on offspring development: Opportunities, limitations and future perspectives. Current Opinion in Psychology, 15, 174181. https://doi.org/10.1016/j.copsyc.2017.02.030.CrossRefGoogle ScholarPubMed
Kok, R., Linting, M., Bakermans-Kranenburg, M. J., van IJzendoorn, M. H., Jaddoe, V. W. V., Hofman, A., … Tiemeier, H. (2013). Maternal sensitivity and internalizing problems: Evidence from two longitudinal studies in early childhood. Child Psychiatry & Human Development, 44(6), 751765. https://doi.org/10.1007/s10578-013-0369-7.CrossRefGoogle ScholarPubMed
Kok, R., Thijssen, S., Bakermans-Kranenburg, M. J., Jaddoe, V. W. V., Verhulst, F. C., White, T., … Tiemeier, H. (2015). Normal variation in early parental sensitivity predicts child structural brain development. Journal of the American Academy of Child & Adolescent Psychiatry, 54(10), 824831.e1. https://doi.org/10.1016/j.jaac.2015.07.009.CrossRefGoogle ScholarPubMed
Kooijman, M. N., Kruithof, C. J., van Duijn, C. M., Duijts, L., Franco, O. H., van IJzendoorn, M. H., … Jaddoe, V. W. V. (2016). The Generation R Study: Design and cohort update 2017. European Journal of Epidemiology, 31(12), 12431264. https://doi.org/10.1007/s10654-016-0224-9.CrossRefGoogle ScholarPubMed
Ladd-Acosta, C., & Fallin, M. D. (2016). The role of epigenetics in genetic and environmental epidemiology. Epigenomics, 8(2), 271283. https://doi.org/10.2217/epi.15.102.CrossRefGoogle ScholarPubMed
Lee, , Chang, D.-E., Yeom, M., Kim, G.-H., Choi, K.-D., Shim, I., … Hahm, D.-H. (2005). Gene expression profiling in hypothalamus of immobilization-stressed mouse using cDNA microarray. Molecular Brain Research, 135(1), 293300. https://doi.org/10.1016/j.molbrainres.2004.11.016.CrossRefGoogle ScholarPubMed
Lee, Y. H., Kim, J.-H., & & Song, G. G. (2013). Pathway analysis of a genome-wide association study in schizophrenia. Gene, 525(1), 107115. https://doi.org/10.1016/j.gene.2013.04.014.CrossRefGoogle Scholar
Lehne, B., Drong, A. W., Loh, M., Zhang, W., Scott, W. R., Tan, S.-T., … Chambers, J. C. (2015). A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies. Genome Biology, 16(1), 37. https://doi.org/10.1186/s13059-015-0600-x.CrossRefGoogle ScholarPubMed
Liang, L., & Cookson, W. O. C. (2014). Grasping nettles: Cellular heterogeneity and other confounders in epigenome-wide association studies. Human Molecular Genetics, 23(R1), R83R88. https://doi.org/10.1093/hmg/ddu284.CrossRefGoogle ScholarPubMed
Liang, S., Wang, X., Zou, M., Wang, H., Zhou, X., Sun, C., … Tomoda, A. (2014). Family-based association study of ZNF533, DOCK4 and IMMP2L gene polymorphisms linked to autism in a northeastern Chinese Han population. Journal of Zhejiang University SCIENCE B, 15(3), 264271. https://doi.org/10.1631/jzus.B1300133.CrossRefGoogle Scholar
Lisowski, P., Juszczak, G. R., Goscik, J., Wieczorek, M., Zwierzchowski, L., & Swiergiel, A. H. (2011). Effect of chronic mild stress on hippocampal transcriptome in mice selected for high and low stress-induced analgesia and displaying different emotional behaviors. European Neuropsychopharmacology, 21(1), 4562. https://doi.org/10.1016/j.euroneuro.2010.08.004.CrossRefGoogle ScholarPubMed
Madigan, S., Prime, H., Graham, S. A., Rodrigues, M., Anderson, N., Khoury, J., … Jenkins, J. M. (2019). Parenting behavior and child language: A meta-analysis. Pediatrics, 144(4), e20183556. https://doi.org/10.1542/peds.2018-3556.CrossRefGoogle ScholarPubMed
Maestrini, E., Pagnamenta, A. T., Lamb, J. A., Bacchelli, E., Sykes, N. H., Sousa, I., … Monaco, A. P. (2010). High-density SNP association study and copy number variation analysis of the AUTS1 and AUTS5 loci implicate the IMMP2LDOCK4 gene region in autism susceptibility. Molecular Psychiatry, 15(9), 954968. https://doi.org/10.1038/mp.2009.34.CrossRefGoogle ScholarPubMed
Marzi, S. J., Sugden, K., Arseneault, L., Belsky, D. W., Burrage, J., Corcoran, D. L., … Caspi, A. (2018). Analysis of DNA methylation in young people: Limited evidence for an association between victimization stress and epigenetic variation in blood. American Journal of Psychiatry, 175(6), 517529. https://doi.org/10.1176/appi.ajp.2017.17060693.CrossRefGoogle ScholarPubMed
Meaney, M. J. (2001). Maternal care, gene expression, and the transmission of individual differences in stress reactivity across generations. Annual Review of Neuroscience, 24(1), 11611192. https://doi.org/10.1146/annurev.neuro.24.1.1161.CrossRefGoogle Scholar
Mehta, D., Klengel, T., Conneely, K. N., Smith, A. K., Altmann, A., Pace, T. W., … Binder, E. B. (2013). Childhood maltreatment is associated with distinct genomic and epigenetic profiles in posttraumatic stress disorder. Proceedings of the National Academy of Sciences, 110(20), 83028307. https://doi.org/10.1073/pnas.1217750110.CrossRefGoogle ScholarPubMed
Mulder, R. H., Rijlaarsdam, J., & Van IJzendoorn, M. H. (2017). DNA methylation: A mediator between parenting stress and adverse child development? In K., Deater-Deckard, & R., Panneton (Eds.), Parental stress and early child development: Adaptive and maladaptive outcomes. Cham: Springer. https://doi.org/10.1007/978-3-319-55376-4_7.Google Scholar
Mulder, R. H., Walton, E., Neumann, A., Houtepen, L. C., Felix, J. F., Bakermans-Kranenburg, M. J., … Cecil, C. A. M. (2020). Epigenomics of being bullied: Changes in DNA methylation following bullying exposure. Epigenetics, 15(6–7), 750764. https://doi.org/10.1080/15592294.2020.1719303.CrossRefGoogle ScholarPubMed
Murphy, T. M., Crawford, B., Dempster, E. L., Hannon, E., Burrage, J., Turecki, G., … Mill, J. (2017). Methylomic profiling of cortex samples from completed suicide cases implicates a role for PSORS1C3 in major depression and suicide. Translational Psychiatry, 7(1), e989. https://doi.org/10.1038/tp.2016.249.CrossRefGoogle ScholarPubMed
Naumova, O. Yu., Lee, M., Koposov, R., Szyf, M., Dozier, M., & Grigorenko, E. L. (2012). Differential patterns of whole-genome DNA methylation in institutionalized children and children raised by their biological parents. Development and Psychopathology, 24(01), 143155. https://doi.org/10.1017/S0954579411000605.CrossRefGoogle ScholarPubMed
Noro, F., Gianfagna, F., Gialluisi, A., De Curtis, A., Di Castelnuovo, A., Napoleone, E., … Izzi, B., & Moli-Family Study Investigators. (2019). ZBTB12 DNA methylation is associated with coagulation- and inflammation-related blood cell parameters: Findings from the Moli-family cohort. Clinical Epigenetics, 11(1), 74. https://doi.org/10.1186/s13148-019-0665-6.CrossRefGoogle ScholarPubMed
Oberlander, T. F., Weinberg, J., Papsdorf, M., Grunau, R., Misri, S., & Devlin, A. M. (2008). Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3C1) and infant cortisol stress responses. Epigenetics, 3(2), 97106. https://doi.org/10.4161/epi.3.2.6034.CrossRefGoogle ScholarPubMed
Papale, L. A., Madrid, A., Li, S., & Alisch, R. S. (2017). Early-life stress links 5-hydroxymethylcytosine to anxiety-related behaviors. Epigenetics, 12(4), 264276. https://doi.org/10.1080/15592294.2017.1285986.CrossRefGoogle ScholarPubMed
Phipson, B., Maksimovic, J., & Oshlack, A. (2016). Missmethyl: An R package for analyzing data from Illumina's HumanMethylation450 platform. Bioinformatics (Oxford, England), 32(2), 286288. https://doi.org/10.1093/bioinformatics/btv560.CrossRefGoogle Scholar
Price, A. L., Weale, M. E., Patterson, N., Myers, S. R., Need, A. C., Shianna, K. V., … Reich, D. (2008). Long-range LD can confound genome scans in admixed populations. The American Journal of Human Genetics, 83(1), 132135. https://doi.org/10.1016/j.ajhg.2008.06.005.CrossRefGoogle ScholarPubMed
Provençal, N., Suderman, M. J., Guillemin, C., Massart, R., Ruggiero, A., Wang, D., … Szyf, M. (2012). The signature of maternal rearing in the methylome in rhesus macaque prefrontal cortex and t cells. The Journal of Neuroscience, 32(44), 1562615642. https://doi.org/10.1523/JNEUROSCI.1470-12.2012.CrossRefGoogle ScholarPubMed
Provenzi, L., Fumagalli, M., Giorda, R., Morandi, F., Sirgiovanni, I., Pozzoli, U., … Montirosso, R. (2017). Maternal sensitivity buffers the association between SLC6A4 methylation and socio-emotional stress response in 3-month-old full term, but not very preterm infants. Frontiers in Psychiatry, 8, 171. https://doi.org/10.3389/fpsyt.2017.00171.CrossRefGoogle Scholar
Raby, K. L., Roisman, G. I., Fraley, R. C., & Simpson, J. A. (2015). The enduring predictive significance of early maternal sensitivity: Social and academic competence through age 32 years. Child Development, 86(3), 695708. https://doi.org/10.1111/cdev.12325.CrossRefGoogle ScholarPubMed
Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529541. https://doi.org/10.1038/nrg3000.CrossRefGoogle ScholarPubMed
Reuben, A., Moffitt, T. E., Caspi, A., Belsky, D. W., Harrington, H., Schroeder, F., … Danese, A. (2016). Lest we forget: Comparing retrospective and prospective assessments of adverse childhood experiences in the prediction of adult health. Journal of Child Psychology and Psychiatry, 57(10), 11031112. https://doi.org/10.1111/jcpp.12621.CrossRefGoogle ScholarPubMed
Rijlaarsdam, J., Stevens, G. W. J. M., Jansen, P. W., Ringoot, A. P., Jaddoe, V. W. V., Hofman, A., … Tiemeier, H. (2014). Maternal childhood maltreatment and offspring emotional and behavioral problems: Maternal and paternal mechanisms of risk transmission. Child Maltreatment, 19(2), 6778. https://doi.org/10.1177/1077559514527639.CrossRefGoogle ScholarPubMed
Roberts, S., Suderman, M., Zammit, S., Watkins, S. H., Hannon, E., Mill, J., … Fisher, H. L. (2019). Longitudinal investigation of DNA methylation changes preceding adolescent psychotic experiences. Translational Psychiatry, 9(1), 112. https://doi.org/10.1038/s41398-019-0407-8.CrossRefGoogle ScholarPubMed
Rzehak, P., Saffery, R., Reischl, E., Covic, M., Wahl, S., Grote, V., … Koletzko, B. (2016). Maternal smoking during pregnancy and DNA-methylation in children at age 5.5 years: Epigenome-wide-analysis in the European childhood obesity project (CHOP)-study. PLoS ONE, 11(5), e0155554. https://doi.org/10.1371/journal.pone.0155554.CrossRefGoogle ScholarPubMed
Shatz, C. J. (2009). MHC class I: An unexpected role in neuronal plasticity. Neuron, 64(1), 4045. https://doi.org/10.1016/j.neuron.2009.09.044.CrossRefGoogle ScholarPubMed
Shi, L. (2013). Dock protein family in brain development and neurological disease. Communicative & Integrative Biology, 6(6), e26839. https://doi.org/10.4161/cib.26839.CrossRefGoogle ScholarPubMed
Smith, A. K., Kilaru, V., Kocak, M., Almli, L. M., Mercer, K. B., Ressler, K. J., … Conneely, K. N. (2014). Methylation quantitative trait loci (meQTLs) are consistently detected across ancestry, developmental stage, and tissue type. BMC Genomics, 15(1), 145. https://doi.org/10.1186/1471-2164-15-145.CrossRefGoogle ScholarPubMed
Sobue, A., Ito, N., Nagai, T., Shan, W., Hada, K., Nakajima, A., … Yamada, K. (2018). Astroglial major histocompatibility complex class I following immune activation leads to behavioral and neuropathological changes. Glia, 66(5), 10341052. https://doi.org/10.1002/glia.23299.CrossRefGoogle Scholar
Stams, G.-J. J. M., Juffer, F., & van IJzendoorn, M. H. (2002). Maternal sensitivity, infant attachment, and temperament in early childhood predict adjustment in middle childhood: The case of adopted children and their biologically unrelated parents. Developmental Psychology, 38(5), 806821. https://doi.org/10.1037//0012-1649.38.5.806.CrossRefGoogle ScholarPubMed
Stenz, L., Prados, J., Courtet, P., Prada, P., Nicastro, R., Adouan, W., … Perroud, N. (2016). Borderline personality disorder and childhood maltreatment: A genome-wide methylation analysis. European Psychiatry, 33(S1), S183. https://doi.org/10.1016/j.eurpsy.2016.01.400.CrossRefGoogle Scholar
Suderman, M., Staley, J. R., French, R., Arathimos, R., Simpkin, A., & Tilling, K. (2018). dmrff: Identifying differentially methylated regions efficiently with power and control. BioRxiv, 508556. https://doi.org/10.1101/508556.Google Scholar
Sullivan, P. F. (2007). Spurious genetic associations. Biological Psychiatry, 61(10), 11211126. https://doi.org/10.1016/j.biopsych.2006.11.010.CrossRefGoogle ScholarPubMed
Szyf, M. (2013). The genome- and system-wide response of DNA methylation to early life adversity and its implication on mental health. The Canadian Journal of Psychiatry, 58(12), 697704. https://doi.org/10.1177/070674371305801208.CrossRefGoogle ScholarPubMed
Teh, A. L., Pan, H., Chen, L., Ong, M.-L., Dogra, S., Wong, J., … Holbrook, J. D. (2014). The effect of genotype and in utero environment on interindividual variation in neonate DNA methylomes. Genome Research, 24(7), 10641074. https://doi.org/10.1101/gr.171439.113.CrossRefGoogle ScholarPubMed
Thomas, J. C., Letourneau, N., Campbell, T. S., Tomfohr-Madsen, L., & Giesbrecht, G. F. (2017). Developmental origins of infant emotion regulation: Mediation by temperamental negativity and moderation by maternal sensitivity. Developmental Psychology, 53(4), 611628. https://doi.org/10.1037/dev0000279.CrossRefGoogle ScholarPubMed
Turecki, G., & Meaney, M. J. (2016). Effects of the social environment and stress on glucocorticoid receptor gene methylation: A systematic review. Biological Psychiatry, 79(2), 8796. https://doi.org/10.1016/j.biopsych.2014.11.022.CrossRefGoogle ScholarPubMed
Unternaehrer, E., Meyer, A. H., Burkhardt, S. C. A., Dempster, E., Staehli, S., Theill, N., … Meinlschmidt, G. (2015). Childhood maternal care is associated with DNA methylation of the genes for brain-derived neurotrophic factor (BDNF) and oxytocin receptor (OXTR) in peripheral blood cells in adult men and women. Stress (Amsterdam, The Netherlands), 18(4), 451461. https://doi.org/10.3109/10253890.2015.1038992.CrossRefGoogle ScholarPubMed
van Iterson, M., van Zwet, E. W., Bios Consortium, & Heijmans, B. T. (2017). Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution. Genome Biology, 18, 19. https://doi.org/10.1186/s13059-016-1131-9 10.1186/s13059-016-1131-9 [pii].CrossRefGoogle ScholarPubMed
Weaver, I. C. G., Cervoni, N., Champagne, F. A., D'Alessio, A. C., Sharma, S., Seckl, J. R., … Meaney, M. J. (2004). Epigenetic programming by maternal behavior. Nature Neuroscience, 7(8), 847854. https://doi.org/10.1038/nn1276.CrossRefGoogle ScholarPubMed
Weaver, I. C. G., Champagne, F. A., Brown, S. E., Dymov, S., Sharma, S., Meaney, M. J., & Szyf, M. (2005). Reversal of maternal programming of stress responses in adult offspring through methyl supplementation: Altering epigenetic marking later in life. Journal of Neuroscience, 25(47), 1104511054. https://doi.org/10.1523/JNEUROSCI.3652-05.2005.CrossRefGoogle ScholarPubMed
Weder, N., Zhang, H., Jensen, K., Yang, B. Z., Simen, A., Jackowski, A., … Kaufman, J. (2014). Child abuse, depression, and methylation in genes involved with stress, neural plasticity, and brain circuitry. Journal of the American Academy of Child & Adolescent Psychiatry, 53(4), 417424.e5. https://doi.org/10.1016/j.jaac.2013.12.025.CrossRefGoogle ScholarPubMed
White, T., Muetzel, R. L., El Marroun, H., Blanken, L. M. E., Jansen, P., Bolhuis, K., … Tiemeier, H. (2018). Paediatric population neuroimaging and the Generation R Study: The second wave. European Journal of Epidemiology, 33(1), 99125. https://doi.org/10.1007/s10654-017-0319-y.CrossRefGoogle ScholarPubMed
Zhang, Y., You, X., Li, S., Long, Q., Zhu, Y., Teng, Z., … Zeng, Y. (2020). Peripheral blood leukocyte RNA-Seq identifies a set of genes related to abnormal psychomotor behavior characteristics in patients with schizophrenia. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, 26, e922426. https://doi.org/10.12659/MSM.922426.Google ScholarPubMed
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