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Neonatal DNA methylation and early-onset conduct problems: A genome-wide, prospective study

Published online by Cambridge University Press:  09 June 2017

Charlotte A. M. Cecil*
Affiliation:
King's College London
Esther Walton
Affiliation:
University of Bristol
Sara R. Jaffee
Affiliation:
University of Pennsylvania
Tom O'Connor
Affiliation:
University of Rochester Medical Center
Barbara Maughan
Affiliation:
King's College London
Caroline L. Relton
Affiliation:
University of Bristol
Rebecca G. Smith
Affiliation:
Exeter University
Wendy McArdle
Affiliation:
University of Bristol
Tom R. Gaunt
Affiliation:
University of Bristol
Isabelle Ouellet-Morin
Affiliation:
University of Montreal
Edward D. Barker*
Affiliation:
King's College London
*
Address correspondence and preprint requests to: Charlotte A. M. Cecil or Edward D. Barker, Department of Psychology, King's College London, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London, UK SE5 8AF; E-mail: [email protected] or [email protected].
Address correspondence and preprint requests to: Charlotte A. M. Cecil or Edward D. Barker, Department of Psychology, King's College London, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London, UK SE5 8AF; E-mail: [email protected] or [email protected].

Abstract

Early-onset conduct problems (CP) are a key predictor of adult criminality and poor mental health. While previous studies suggest that both genetic and environmental risks play an important role in the development of early-onset CP, little is known about potential biological processes underlying these associations. In this study, we examined prospective associations between DNA methylation (cord blood at birth) and trajectories of CP (4–13 years), using data drawn from the Avon Longitudinal Study of Parents and Children. Methylomic variation at seven loci across the genome (false discovery rate < 0.05) differentiated children who go on to develop early-onset (n = 174) versus low (n = 86) CP, including sites in the vicinity of the monoglyceride lipase (MGLL) gene (involved in endocannabinoid signaling and pain perception). Subthreshold associations in the vicinity of three candidate genes for CP (monoamine oxidase A [MAOA], brain-derived neurotrophic factor [BDNF], and FK506 binding protein 5 [FKBP5]) were also identified. Within the early-onset CP group, methylation levels of the identified sites did not distinguish children who will go on to persist versus desist in CP behavior over time. Overall, we found that several of the identified sites correlated with prenatal exposures, and none were linked to known genetic methylation quantitative trait loci. Findings contribute to a better understanding of epigenetic patterns associated with early-onset CP.

Type
Regular Articles
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole Avon Longitudinal Study of Parents and Children (ALSPAC) team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. We thank all involved with the ALSPAC DNA methylation, particularly the laboratory scientists and bioinformaticians who contributed considerable time and expertise to the data in this paper. The UK Medical Research Council and the Wellcome Trust (Grant 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors, who will serve as guarantors for the contents of this paper. This research was specifically supported by National Institute of Child and Human Development Grant R01HD068437 (to E.D.B.). The first author (C.A.M.C.) is supported by Economic and Social Research Council Grant ES/N001273/1.

References

Barfield, R. T., Kilaru, V., Smith, A. K., & Conneely, K. N. (2012). CpGassoc: An R function for analysis of DNA methylation microarray data. Bioinformatics, 28, 12801281. doi:10.1093/bioinformatics/bts124Google Scholar
Barker, D. J. (2007). The origins of the developmental origins theory. Journal of Internal Medicine, 261, 412417.10.1111/j.1365-2796.2007.01809.xGoogle Scholar
Barker, E. D., Cecil, C. A. M., Walton, E., & Meehan, A. (2017). Genetic contributions to disruptive and impulse-control disorders. In Lochman, J. & Matthys, W. (Eds.), The Wiley handbook of disruptive and impulse-control disorders. Hoboken, NJ: Wiley.Google Scholar
Barker, E. D., Kirkham, N., Ng, J., & Jensen, S. K. (2013). Prenatal maternal depression symptoms and nutrition, and child cognitive function. British Journal of Psychiatry, 203, 417421. doi:10.1192/bjp.bp.113.129486Google Scholar
Barker, E. D., & Maughan, B. (2009). Differentiating early-onset persistent versus childhood-limited conduct problem youth. American Journal of Psychiatry, 166, 900908. doi:10.1176/appi.ajp.2009.08121770Google Scholar
Barker, E. D., Oliver, B. R., & Maughan, B. (2010). Co-occurring problems of early onset persistent, childhood limited, and adolescent onset conduct problem youth. Journal of Child Psychology and Psychiatry, 51, 12171226. doi:10.1111/j.1469-7610.2010.02240.xGoogle Scholar
Barnett, B. E., Hanna, B., & Parker, G. (1983). Life event scales for obstetric groups. Journal of Psychosomatic Research, 27, 313320.Google Scholar
Booij, L., Tremblay, R. E., Leyton, M., Séguin, J. R., Vitaro, F., Gravel, P., … Diksic, M. (2010). Brain serotonin synthesis in adult males characterized by physical aggression during childhood: A 21-year longitudinal study. PLOS ONE, 5, e11255.10.1371/journal.pone.0011255Google Scholar
Boyd, A., Golding, J., Macleod, J., Lawlor, D. A., Fraser, A., Henderson, J., … Davey Smith, G. (2013). Cohort profile: the “Children of the 90s”—The index offspring of the Avon Longitudinal Study of Parents and Children. International Journal of Epidemiology, 42, 111127. doi:10.1093/ije/dys064Google Scholar
Brown, G. W., Sklair, F., Harris, T. O., & Birley, J. L. T. (1973). Life-events and psychiatric disorders: Part 1. Some methodological issues. Psychological Medicine, 3, 7487.10.1017/S0033291700046365Google Scholar
Bryushkova, L., Zai, C., Chen, S., Pappa, I., Mileva, V., Tiemeier, H., … Beitchman, J. H. (2016). FKBP5 interacts with maltreatment in a sample of children with extreme, pervasive, and persistent aggression. Psychiatry Research. Advance online publication.10.1016/j.psychres.2015.09.052Google Scholar
Bywater, T. J. (2012). Perspectives on the Incredible Years programme: Psychological management of conduct disorder. British Journal of Psychiatry, 201, 8587. doi:10.1192/bjp.bp.111.107920Google Scholar
Carey, C. E., Agrawal, A., Zhang, B., Conley, E. D., Degenhardt, L., Heath, A. C., … Bogdan, R. (2015). Monoacylglycerol lipase (MGLL) polymorphism rs604300 interacts with childhood adversity to predict cannabis dependence symptoms and amygdala habituation: Evidence from an endocannabinoid system-level analysis. Journal of Abnormal Psychology, 124, 860877. doi:10.1037/abn0000079Google Scholar
Cecil, C. A., Lysenko, L. J., Jaffee, S. R., Pingault, J. B., Smith, R. G., Relton, C. L., … Barker, E. D. (2014). Environmental risk, oxytocin receptor gene (OXTR) methylation and youth callous-unemotional traits: A 13-year longitudinal study. Molecular Psychiatry, 19, 10711077. doi:10.1038/mp.2014.95Google Scholar
Cecil, C. A. M., Walton, E., Smith, R. G., Viding, E., McCrory, E. J., Relton, C. L., … Barker, E. D. (2016). DNA methylation and substance-use risk: A prospective, genome-wide study spanning gestation to adolescence. Translational Psychiatry, 6, e976.Google Scholar
Cecil, C. A. M., Walton, E., & Viding, E. (2015). DNA methylation, substance use and addiction: A systematic review of recent animal and human research from a developmental perspective. Current Addiction Reports, 2, 331346. doi:10.1007/s40429-015-0072-9Google Scholar
Checknita, D., Maussion, G., Labonte, B., Comai, S., Tremblay, R. E., Vitaro, F., … Turecki, G. (2015). Monoamine oxidase A gene promoter methylation and transcriptional downregulation in an offender population with antisocial personality disorder. British Journal of Psychiatry, 206, 216222. doi:10.1192/bjp.bp.114.144964Google Scholar
Chen, Y. A., Lemire, M., Choufani, S., Butcher, D. T., Grafodatskaya, D., Zanke, B. W., … Weksberg, R. (2013). Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics, 8, 203209. doi:10.4161/epi.23470Google Scholar
Cicchetti, D., & Rogosch, F. A. (1996). Equifinality and multifinality in developmental psychopathology. Development and Psychopathology, 8, 597600.10.1017/S0954579400007318Google Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
Colman, I., Murray, J., Abbott, R. A., Maughan, B., Kuh, D., Croudace, T. J., & Jones, P. B. (2009). Outcomes of conduct problems in adolescence: 40 year follow-up of national cohort. British Medical Journal, 338, a298110.1136/bmj.a2981Google Scholar
Dadds, M. R., Moul, C., Cauchi, A., Dobson-Stone, C., Hawes, D. J., Brennan, J., & Ebstein, R. E. (2014). Methylation of the oxytocin receptor gene and oxytocin blood levels in the development of psychopathy. Development and Psychopathology, 26, 3340. doi:10.1017/s0954579413000497Google Scholar
Egger, H. L., & Angold, A. (2006). Common emotional and behavioral disorders in preschool children: Presentation, nosology, and epidemiology. Journal of Child Psychology and Psychiatry, 47, 313337.10.1111/j.1469-7610.2006.01618.xGoogle Scholar
Farrington, D. P. (2001). Predicting adult official and self-reported violence. In Pinard, G.-F. & Pagani, L. (Eds.), Clinical assessment of dangerousness: Empirical contributions. Cambridge: Cambridge University Press.Google Scholar
Farrington, D. P., Gallagher, B., Morley, L., Ledger, R. J. S., & West, D. J. (1988). Are there any successful men from criminogenic backgrounds? Psychiatry, 51, 116130.Google Scholar
Fergusson, D. M., Horwood, L. J., & Ridder, E. M. (2005). Show me the child at seven: The consequences of conduct problems in childhood for psychosocial functioning in adulthood. Journal of Child Psychology and Psychiatry, 46, 837849.Google Scholar
Fraser, A., Macdonald-Wallis, C., Tilling, K., Boyd, A., Golding, J., Davey Smith, G., … Lawlor, D. A. (2013). Cohort profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. International Journal of Epidemiology, 42, 97110. doi:10.1093/ije/dys066Google Scholar
Gao, X., Jia, M., Zhang, Y., Breitling, L. P., & Brenner, H. (2015). DNA methylation changes of whole blood cells in response to active smoking exposure in adults: A systematic review of DNA methylation studies. Clinical Epigenetics, 7, 113. doi:10.1186/s13148-015-0148-3Google Scholar
Gaunt, T. R., Shihab, H. A., Hemani, G., Min, J. L., Woodward, G., Lyttleton, O., … Ho, K. (2016). Systematic identification of genetic influences on methylation across the human life course. Genome Biology, 17, 1.Google Scholar
Goodman, R. (2001). Psychometric properties of the Strengths and Difficulties Questionnaire. Journal of the American Academy of Child & Adolescent Psychiatry, 40, 13371345. doi:10.1097/00004583-200111000-00015Google Scholar
Guadagna, S., Esiri, M. M., Williams, R. J., & Francis, P. T. (2012). Tau phosphorylation in human brain: Relationship to behavioral disturbance in dementia. Neurobiology of Aging, 33, 27982806. doi:10.1016/j.neurobiolaging.2012.01.015Google Scholar
Guillemin, C., Provencal, N., Suderman, M., Cote, S. M., Vitaro, F., Hallett, M., … Szyf, M. (2014). DNA methylation signature of childhood chronic physical aggression in T cells of both men and women. PLOS ONE, 9, e86822. doi:10.1371/journal.pone.0086822Google Scholar
Hennings, J. M., Uhr, M., Klengel, T., Weber, P., Putz, B., Touma, C., … Lucae, S. (2015). RNA expression profiling in depressed patients suggests retinoid-related orphan receptor alpha as a biomarker for antidepressant response. Translational Psychiatry, 5, e538. doi:10.1038/tp.2015.9Google Scholar
Hopfer, C. J., Lessem, J. M., Hartman, C. A., Stallings, M. C., Cherny, S. S., Corley, R. P., … Crowley, T. J. (2007). A genome-wide scan for loci influencing adolescent cannabis dependence symptoms: Evidence for linkage on chromosomes 3 and 9. Drug and Alcohol Dependence, 89, 3441. doi:10.1016/j.drugalcdep.2006.11.015Google Scholar
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, 86. doi:10.1186/1471-2105-13-86Google Scholar
Iwasaki, S., Ishiguro, H., Higuchi, S., Onaivi, E. S., & Arinami, T. (2007). Association study between alcoholism and endocannabinoid metabolic enzyme genes encoding fatty acid amide hydrolase and monoglyceride lipase in a Japanese population. Psychiatric Genetics, 17, 215220. doi:10.1097/YPG.0b013e32809913d8Google Scholar
Jaenisch, R., & Bird, A. (2003). Epigenetic regulation of gene expression: How the genome integrates intrinsic and environmental signals. Nature Genetics, 33(Suppl.), 245254. doi:10.1038/ng1089Google Scholar
Jaffee, S. R., Caspi, A., Moffitt, T. E., Dodge, K. A., Rutter, M., Taylor, A., & Tully, L. A. (2005). Nature × Nurture: Genetic vulnerabilities interact with physical maltreatment to promote conduct problems. Development and Psychopathology, 17, 6784.10.1017/S0954579405050042Google Scholar
Johnson, W. E., Li, C., & Rabinovic, A. (2007). Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118127. doi:10.1093/biostatistics/kxj037Google Scholar
Jones, M. J., Fejes, A. P., & Kobor, M. S. (2013). DNA methylation, genotype and gene expression: Who is driving and who is along for the ride? Genome Biology, 14, 126. doi:10.1186/gb-2013-14-7-126Google Scholar
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, D. (2002). The human genome browser at UCSC. Genome Research, 12, 9961006.Google Scholar
Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: Developmental follow-back of a prospective-longitudinal cohort. Archives of General Psychiatry, 60, 709717.10.1001/archpsyc.60.7.709Google Scholar
Klengel, T., Pape, J., Binder, E. B., & Mehta, D. (2014). The role of DNA methylation in stress-related psychiatric disorders. Neuropharmacology, 80, 115132. doi:10.1016/j.neuropharm.2014.01.013Google Scholar
Kofink, D., Boks, M. P., Timmers, H. T., & Kas, M. J. (2013). Epigenetic dynamics in psychiatric disorders: Environmental programming of neurodevelopmental processes. Neuroscience Biobehavioral Review, 37, 831845. doi:10.1016/j.neubiorev.2013.03.020Google Scholar
Lewis, C. R., & Olive, M. F. (2014). Early-life stress interactions with the epigenome: Potential mechanisms driving vulnerability toward psychiatric illness. Behavioural Pharmacology, 25, 341351. doi:10.1097/fbp.0000000000000057Google Scholar
Liao, J. C., Yang, T. T., Weng, R. R., Kuo, C. T., & Chang, C. W. (2015). TTBK2: A tau protein kinase beyond tau phosphorylation. BioMed Research International, 2015, 575170. doi:10.1155/2015/575170Google Scholar
Lutz, P. E., & Turecki, G. (2014). DNA methylation and childhood maltreatment: From animal models to human studies. Neuroscience, 264, 142156. doi:10.1016/j.neuroscience.2013.07.069Google Scholar
McAdams, T. A., Salekin, R. D., Marti, C. N., Lester, W. S., & Barker, E. D. (2014). Co-occurrence of antisocial behavior and substance use: Testing for sex differences in the impact of older male friends, low parental knowledge and friends' delinquency. Journal of Adolescence, 37, 247256.10.1016/j.adolescence.2014.01.001Google Scholar
McGowan, P. O., & Roth, T. L. (2015). Epigenetic pathways through which experiences become linked with biology. Development and Psychopathology, 27, 637648. doi:10.1017/s0954579415000206Google Scholar
Moffitt, T. E. (2006). Life-course persistent versus adolescence-limited antisocial behaviour. In Cicchetti, C. & Cohen, D. J. (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (pp. 570598). Hoboken, NJ: Wiley.Google Scholar
Moffitt, T. E., Arseneault, L., Jaffee, S. R., Kim-Cohen, J., Koenen, K. C., Odgers, C. L., … Viding, E. (2008). Research review: DSM-V conduct disorder: Research needs for an evidence base. Journal of Child Psychology and Psychiatry, 49, 333.Google Scholar
Moffitt, T. E., Caspi, A., Harrington, H., & Milne, B. J. (2002). Males on the life-course-persistent and adolescence-limited antisocial pathways: Follow-up at age 26 years. Development and Psychopathology, 14, 179207.10.1017/S0954579402001104Google Scholar
Monk, C., Spicer, J., & Champagne, F. A. (2012). Linking prenatal maternal adversity to developmental outcomes in infants: The role of epigenetic pathways. Development and Psychopathology, 24, 1361.Google Scholar
Moul, C., Dobson-Stone, C., Brennan, J., Hawes, D. J., & Dadds, M. R. (2015). Serotonin 1B receptor gene (HTR1B) methylation as a risk factor for callous-unemotional traits in antisocial boys. PLOS ONE, 10, e0126903.Google Scholar
Muldoon, P. P., Chen, J., Harenza, J. L., Abdullah, R. A., Sim-Selley, L. J., Cravatt, B. F., … Damaj, M. I. (2015). Inhibition of monoacylglycerol lipase reduces nicotine withdrawal. British Journal of Pharmacology, 172, 869882. doi:10.1111/bph.12948Google Scholar
Murgatroyd, C., & Spengler, D. (2011). Epigenetics of early child development. Frontiers in Psychiatry, 2, 16.Google Scholar
Nelson, R. J., & Trainor, B. C. (2007). Neural mechanisms of aggression. Nature Reviews Neuroscience, 8, 536546.Google Scholar
Nigg, J. T. (2016). Where do epigenetics and developmental origins take the field of developmental psychopathology? Journal of Abnormal Child Psychology, 44, 405419.Google Scholar
Odgers, C. L., Caspi, A., Broadbent, J. M., Dickson, N., Hancox, R. J., Harrington, H., … Moffitt, T. E. (2007). Prediction of differential adult health burden by conduct problem subtypes in males. Archives of General Psychiatry, 64, 476484. doi:10.1001/archpsyc.64.4.476Google Scholar
Odgers, C. L., Moffitt, T. E., Broadbent, J. M., Dickson, N., Hancox, R. J., Harrington, H., … Caspi, A. (2008). Female and male antisocial trajectories: From childhood origins to adult outcomes. Development and Psychopathology, 20, 673716. doi:10.1017/S0954579408000333Google Scholar
Pan, Z., Shen, Y., Ge, B., Du, C., McKeithan, T., & Chan, W. C. (2007). Studies of a germinal centre B-cell expressed gene, GCET2, suggest its role as a membrane associated adapter protein. British Journal of Haematology, 137, 578590. doi:10.1111/j.1365-2141.2007.06597.xGoogle Scholar
Pappa, I., St. Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M. G., … Tiemeier, H. (2015). A genome-wide approach to children's aggressive behavior: The EAGLE consortium. American Journal of Medical Genetics B: Neuropsychiatric Genetics. Advance online publication. doi:10.1002/ajmg.b.32333Google Scholar
Pidsley, R., Wong, C. C. Y., Volta, M., Lunnon, K., Mill, J., & Schalkwyk, L. C. (2013). A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics, 14, 293. doi:10.1186/1471-2164-14-293Google Scholar
Pingault, J. B., Cecil, C. A. M., Murray, J., Munafò, M. R., & Viding, E. (2016). Causal inference in psychopathology: A systematic review of Mendelian randomisation studies aiming to identify environmental risk factors for psychopathology. Psychopathology Review. Advance online publication.Google Scholar
Pingault, J.-B., Rijsdijk, F., Zheng, Y., Plomin, R., & Viding, E. (2015). Developmentally dynamic genome: Evidence of genetic influences on increases and decreases in conduct problems from early childhood to adolescence. Scientific Reports, 5, 10053.Google Scholar
Price, M. E., Cotton, A. M., Lam, L. L., Farre, P., Emberly, E., Brown, C. J., … Kobor, M. S. (2013). Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array. Epigenetics Chromatin, 6, 4. doi:10.1186/1756-8935-6-4Google Scholar
Provençal, N., Suderman, M. J., Caramaschi, D., Wang, D., Hallett, M., Vitaro, F., … Szyf, M. (2013). Differential DNA methylation regions in cytokine and transcription factor genomic loci associate with childhood physical aggression. PLOS ONE, 8, e71691. doi:10.1371/journal.pone.0071691Google Scholar
Provençal, N., Suderman, M. J., Guillemin, C., Vitaro, F., Côté, S. M., Hallett, M., … Szyf, M. (2014). Association of childhood chronic physical aggression with a DNA methylation signature in adult human T cells. PLOS ONE, 9, e89839. doi:10.1371/journal.pone.0089839Google Scholar
R Core Team. (2014). R: A language and environment for statistical computing [Computer software]. Retrieved from http://www.R-project.org/Google Scholar
Relton, C. L., & Davey Smith, G. (2012). Two-step epigenetic Mendelian randomization: A strategy for establishing the causal role of epigenetic processes in pathways to disease. International Journal of Epidemiology, 41, 161176. doi:10.1093/ije/dyr233Google Scholar
Relton, C. L., Gaunt, T., McArdle, W., Ho, K., Duggirala, A., Shihab, H., … Davey Smith, G. (2015). Data resource profile: Accessible Resource for Integrated Epigenomic Studies (ARIES). International Journal of Epidemiology. Advance online publication. doi:10.1093/ije/dyv072Google Scholar
Richmond, R. C., Simpkin, A. J., Woodward, G., Gaunt, T. R., Lyttleton, O., McArdle, W. L., … Tilling, K. (2015). Prenatal exposure to maternal smoking and offspring DNA methylation across the lifecourse: Findings from the Avon Longitudinal Study of Parents and Children (ALSPAC). Human Molecular Genetics, 24, 22012217.Google Scholar
Rijlaarsdam, J., Cecil, C., Walton, E., Chapman Mesirow, M. S., Relton, C., Gaunt, T. R., … Barker, E. (2016). Prenatal unhealthy diet, insulin-like growth factor 2 gene (IGF2) methylation and attention deficit hyperactivity disorder (ADHD) symptoms for early-onset conduct problem youth: Prenatal unhealthy diet, IGF2 methylation and ADHD. Journal of Child Psychology and Psychiatry. Advance online publication.Google Scholar
Rijlaarsdam, J., Pappa, I., Walton, E., Bakermans-Kranenburg, M. J., Mileva-Seitz, V. R., Rippe, R. C., … van IJzendoorn, M. H. (2016). An epigenome-wide association meta-analysis of prenatal maternal stress in neonates: A model approach for replication. Epigenetics. Advance online publication. doi:10.1080/15592294.2016.1145329Google Scholar
Rodgers, A. B., & Bale, T. L. (2015). Germ cell origins of posttraumatic stress disorder risk: The transgenerational impact of parental stress experience. Biological Psychiatry, 78, 307314.10.1016/j.biopsych.2015.03.018Google Scholar
Rodriguez-Arias, M., Navarrete, F., Daza-Losada, M., Navarro, D., Aguilar, M. A., Berbel, P., … Manzanares, J. (2013). CB1 cannabinoid receptor-mediated aggressive behavior. Neuropharmacology, 75, 172180. doi:10.1016/j.neuropharm.2013.07.013Google Scholar
Salvatore, J. E., & Dick, D. M. (2016). Genetic influences on conduct isorder. Neuroscience & Biobehavioral Reviews. Advance online publication.Google Scholar
Shumay, E., Logan, J., Volkow, N. D., & Fowler, J. S. (2012). Evidence that the methylation state of the monoamine oxidase A (MAOA) gene predicts brain activity of MAO A enzyme in healthy men. Epigenetics, 7, 11511160. doi:10.4161/epi.21976Google Scholar
Szyf, M., & Bick, J. (2013). DNA methylation: A mechanism for embedding early life experiences in the genome. Child Development, 84, 4957.Google Scholar
Tobi, E. W., Goeman, J. J., Monajemi, R., Gu, H., Putter, H., Zhang, Y., … Müller, F. (2014). DNA methylation signatures link prenatal famine exposure to growth and metabolism. Nature Communications, 5, 5592.Google Scholar
Tremblay, R. E., & Szyf, M. (2010). Developmental origins of chronic physical aggression and epigenetics. Epigenomics, 2, 495499.Google Scholar
Tsai, P. C., & Bell, J. T. (2015). Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation. International Journal of Epidemiology. Advance online publication. doi:10.1093/ije/dyv041Google Scholar
Turecki, G., & Meaney, M. J. (2016). Effects of the social environment and stress on glucocorticoid receptor gene methylation: A systematic review. Biological Psychiatry, 79, 8796.10.1016/j.biopsych.2014.11.022Google Scholar
Tyrka, A. R., Parade, S. H., Eslinger, N. M., Marsit, C. J., Lesseur, C., Armstrong, D. A., … Seifer, R. (2015). Methylation of exons 1 D, 1 F, and 1 H of the glucocorticoid receptor gene promoter and exposure to adversity in preschool-aged children. Development and Psychopathology, 27, 577585.10.1017/S0954579415000176Google Scholar
van Mil, N. H., Steegers-Theunissen, R. P., Bouwland-Both, M. I., Verbiest, M. M., Rijlaarsdam, J., Hofman, A., … Verhulst, F. C. (2014). DNA methylation profiles at birth and child ADHD symptoms. Journal of Psychiatric Reserch, 49, 5159.Google Scholar
Waltes, R., Chiocchetti, A. G., & Freitag, C. M. (2015). The neurobiological basis of human aggression: A review on genetic and epigenetic mechanisms. American Journal of Medical Genetics B: Neuropsychiatric Genetics. Advance online publication. doi:10.1002/ajmg.b.32388Google Scholar
Walton, E., Pingault, J.-B., Cecil, C., Gaunt, T., Relton, C., Mill, J., & Barker, E. (2016). Epigenetic profiling of ADHD symptoms trajectories: A prospective, methylome-wide study. Molecular Psychiatry. Advance online publication.Google Scholar
Wang, D., Szyf, M., Benkelfat, C., Provençal, N., Turecki, G., Caramaschi, D., … Booij, L. (2012). Peripheral SLC6A4 DNA methylation is associated with in vivo measures of human brain serotonin synthesis and childhood physical aggression. PLOS ONE, 7, e39501.Google Scholar
Weaver, I. C., 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, 847854.Google Scholar
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, 417424. doi:10.1016/j.jaac.2013.12.025Google Scholar
Wolke, D., Steer, C., & Bowen, E. (2004). The ALSPAC Family Adversity Index (FAI): Background and development. Unpublished manuscript, University of Bristol.Google Scholar
Zannas, A., & Binder, E. (2014). Gene–environment interactions at the FKBP5 locus: Sensitive periods, mechanisms and pleiotropism. Genes, Brain and Behavior, 13, 2537.Google Scholar
Zannas, A. S., & West, A. E. (2014). Epigenetics and the regulation of stress vulnerability and resilience. Neuroscience, 264, 157170.Google Scholar
Zannas, A. S., Wiechmann, T., Gassen, N. C., & Binder, E. B. (2015). Gene–stress–epigenetic regulation of FKBP5: Clinical and translational implications. Neuropsychopharmacology. Advance online publication.Google Scholar
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