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Cumulative prenatal exposure to adversity reveals associations with a broad range of neurodevelopmental outcomes that are moderated by a novel, biologically informed polygenetic score based on the serotonin transporter solute carrier family C6, member 4 (SLC6A4) gene expression

Published online by Cambridge University Press:  22 November 2017

Patrícia P. Silveira ,
Irina Pokhvisneva ,
Carine Parent ,
Shirong Cai ,
Anu Sathyan Sathyapalan Rema ,
Birit F. P. Broekman ,
Anne Rifkin-Graboi ,
Michael Pluess ,
Kieran J. O'Donnell  and
Michael J. Meaney
Patrícia P. Silveira*
Affiliation:
McGill University Canadian Institute for Advanced Research
Irina Pokhvisneva
Affiliation:
McGill University
Carine Parent
Affiliation:
McGill University
Shirong Cai
Affiliation:
Singapore Institute for Clinical Sciences Agency for Science, Technology and Research (A*STAR)
Anu Sathyan Sathyapalan Rema
Affiliation:
Singapore Institute for Clinical Sciences Agency for Science, Technology and Research (A*STAR)
Birit F. P. Broekman
Affiliation:
Singapore Institute for Clinical Sciences Agency for Science, Technology and Research (A*STAR)
Anne Rifkin-Graboi
Affiliation:
Singapore Institute for Clinical Sciences Agency for Science, Technology and Research (A*STAR)
Michael Pluess
Affiliation:
Queen Mary University of London
Kieran J. O'Donnell
Affiliation:
McGill University Canadian Institute for Advanced Research
Michael J. Meaney
Affiliation:
McGill University Canadian Institute for Advanced Research Singapore Institute for Clinical Sciences Agency for Science, Technology and Research (A*STAR)
*
Address correspondence and reprint requests to: Patrícia Pelufo Silveira, Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Douglas Mental Health University Institute, Montreal, Québec, H4H 1R3, Canada; E-mail: [email protected].
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Abstract

While many studies focus on the association between early life adversity and the later risk for psychopathology, few simultaneously explore diverse forms of environmental adversity. Moreover, those studies that examined the cumulative impact of early life adversity focus uniquely on postnatal influences. The objective of this study was to focus on the fetal period of development to construct and validate a cumulative prenatal adversity score in relation to a wide range of neurodevelopmental outcomes. We also examined the interaction of this adversity score with a biologically informed genetic score based on the serotonin transporter gene. Prenatal adversities were computed in two community birth cohorts using information on health during pregnancy, birth weight, gestational age, income, domestic violence/sexual abuse, marital strain, as well as maternal smoking, anxiety, and depression. A genetic score based on genes coexpressed with the serotonin transporter in the amygdala, hippocampus, and prefrontal cortex during prenatal life was constructed with an emphasis on functionally relevant single nucleotide polymorphisms, that is, expression quantitative trait loci. Prenatal adversities predicted a wide range of developmental and behavioral alterations in children as young as 2 years of age in both cohorts. There were interactions between the genetic score and adversities for several domains of the Child Behavior Checklist (CBCL), with pervasive developmental problems remaining significant adjustment for multiple comparisons. Scores combining different prenatal adverse exposures predict childhood behavior and interact with the genetic background to influence the risk for psychopathology.

Type
Special Issue Articles
Information
Development and Psychopathology , Volume 29 , Special Issue 5: Biological and Behavioral Effects of Early Adversity on Multiple Levels of Development , December 2017 , pp. 1601 - 1617
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

This work was funded by the Toxic Stress Research network of the JPB Foundation. The Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) Cohort was funded by the Canadian Institutes for Health Research, the Ludmer Family Foundation, the Norlien Foundation (Calgary, Canada), the WOCO Foundation (London, Canada), the Blema & Arnold Steinberg Family Foundation, and the Faculty of Medicine of McGill University. Additional funding was provided by the Jacobs Foundation (Switzerland). The Growing Up in Singapore Towards Healthy Outcomes (GUSTO) project is funded by the National Medical Research Council (Singapore) and the Agency for Science, Technology and Research (Singapore). We thank the MAVAN and GUSTO study groups and all staff. The voluntary participation of all families is greatly appreciated.

References

Abeliovich, A., & Hammond, R. (2007). Midbrain dopamine neuron differentiation: Factors and fates. Developmental Biology, 304, 447–454.Google Scholar
Achenbach, T. M., & Rescorla, L. A. (2000). Manual for the ASEBA School-Age Forms and Profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, and Families.Google Scholar
Anda, R. F., Croft, J. B., Felitti, V. J., Nordenberg, D., Giles, W. H., Williamson, D. F., & Giovino, G. A. (1999). Adverse childhood experiences and smoking during adolescence and adulthood. Journal of the American Medical Association, 282, 1652–1658.Google Scholar
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2006). Gene-environment interaction of the dopamine D4 receptor (DRD4) and observed maternal insensitivity predicting externalizing behavior in preschoolers. Developmental Psychobiology, 48, 406–409.Google Scholar
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2007). Research Review: Genetic vulnerability or differential susceptibility in child development: The case of attachment. Journal of Child Psychology and Psychiatry, 48, 1160–1173.Google Scholar
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2011). Differential susceptibility to rearing environment depending on dopamine-related genes: New evidence and a meta-analysis. Development and Psychopathology, 23, 39–52.CrossRefGoogle ScholarPubMed
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2015). The hidden efficacy of interventions: Gene × Environment experiments from a differential susceptibility perspective. Annual Review of Psychology, 66, 381–409.Google Scholar
Bayley, N. (1993). Bayley Scales of Infant Development. San Antonio, TX: Psychological Corporation.Google Scholar
Bayley, N. (2006). Bayley Scales of Infant Development (3rd ed.). San Antonio, TX: Psychological Corporation.Google Scholar
Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561–571.Google Scholar
Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummett, B., & Williams, R. (2009). Vulnerability genes or plasticity genes? Molecular Psychiatry, 14, 746–754.Google Scholar
Belsky, J., Newman, D. A., Widaman, K. F., Rodkin, P., Pluess, M., Fraley, R. C., … Roisman, G. I. (2015). Differential susceptibility to effects of maternal sensitivity? A study of candidate plasticity genes. Development and Psychopathology, 27, 725–746.Google Scholar
Belsky, J., & Pluess, M. (2009a). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908.CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2009b). The Nature (and nurture?) of plasticity in early human development. Perspectives of Psychological Science, 4, 345–351.Google Scholar
Bjorkenstam, E., Burstrom, B., Vinnerljung, B., & Kosidou, K. (2016). Childhood adversity and psychiatric disorder in young adulthood: An analysis of 107,704 Swedes. Journal of Psychiatric Research, 77, 67–75.Google Scholar
Bouvette-Turcot, A. A., Fleming, A. S., Wazana, A., Sokolowski, M. B., Gaudreau, H., Gonzalez, A., … MAVAN Research Team. (2015). Maternal childhood adversity and child temperament: An association moderated by child 5-HTTLPR genotype. Genes Brain and Behavior, 14, 229–237.Google Scholar
Boyce, W. T., & Ellis, B. J. (2005). Biological sensitivity to context: I. An evolutionary- developmental theory of the origins and functions of stress reactivity. Development and Psychopathology, 17, 271–301.Google Scholar
Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53, 371–399.Google Scholar
Breslau, N., & Chilcoat, H. D. (2000). Psychiatric sequelae of low birth weight at 11 years of age. Biological Psychiatry, 47, 1005–1011.Google Scholar
Brody, G. H., Chen, Y. F., Beach, S. R., Kogan, S. M., Yu, T., Diclemente, R. J., … Philibert, R. A. (2014). Differential sensitivity to prevention programming: A dopaminergic polymorphism-enhanced prevention effect on protective parenting and adolescent substance use. Health Psychology, 33, 182–191.Google Scholar
Broekman, B. F., Chan, Y. H., Goh, L., Fung, D., Gluckman, P. D., Saw, S. M., & Meaney, M. J. (2011). Influence of birth weight on internalizing traits modulated by serotonergic genes. Pediatrics, 128, e1250–e1258.Google Scholar
Bukh, J. D., Bock, C., Vinberg, M., Werge, T., Gether, U., & Vedel Kessing, L. (2009). Interaction between genetic polymorphisms and stressful life events in first episode depression. Journal of Affective Disorders, 1–3, 107–115.Google Scholar
Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., … Poulton, R. (2003). Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science, 301, 386–389.Google Scholar
Chapman, D. P., Whitfield, C. L., Felitti, V. J., Dube, S. R., Edwards, V. J., & Anda, R. F. (2004). Adverse childhood experiences and the risk of depressive disorders in adulthood. Journal of Affective Disorders, 82, 217–225.CrossRefGoogle ScholarPubMed
Cheng, A., Scott, A. L., Ladenheim, B., Chen, K., Ouyang, X., Lathia, J. D., … Shih, J. C. (2010). Monoamine oxidases regulate telencephalic neural progenitors in late embryonic and early postnatal development. Journal of Neuroscience, 30, 10752–10762.CrossRefGoogle ScholarPubMed
Chew, A. L., Morris, J. D. (1984). Validation of the Lollipop Test: A diagnostic screening test of school readiness. Educational and Psychological Measurement, 44, 5.Google Scholar
Christakis, D. A. (2016). Focusing on the smaller adverse childhood experiences: The overlooked importance of aces. JAMA Pediatrics, 170, 725–726.Google Scholar
Cicchetti, D., & Banny, A. (2014). A developmental psychopathology perspective on child maltreatment. In Lewis, M. & Rudolph, K. (Eds.), Handbook of developmental psychopathology (pp. 723–741). New York: Springer.CrossRefGoogle Scholar
Copeland, W., Shanahan, L., Costello, E. J., & Angold, A. (2009). Configurations of common childhood psychosocial risk factors. Journal of Child Psychology and Psychiatry, 50, 451–459.Google Scholar
Costello, E. J., Worthman, C., Erkanli, A., & Angold, A. (2007). Prediction from low birth weight to female adolescent depression: A test of competing hypotheses. Archives of General Psychiatry, 64, 338–344.Google Scholar
Cox, J. L., Holden, J. M., & Sagovsky, R. (1987). Detection of postnatal depression: Development of the 10-item Edinburgh Postnatal Depression Scale. British Journal of Psychiatry, 150, 782–786.CrossRefGoogle ScholarPubMed
Dalle Molle, R., Fatemi, H., Dagher, A., Levitan, R. D., Silveira, P. P., & Dube, L. (2017). Gene and environment interaction: Is the differential susceptibility hypothesis relevant for obesity? Neuroscience & Biobehavioral Reviews, 73, 326–339.Google Scholar
Dias, B. G., Maddox, S. A., Klengel, T., & Ressler, K. J. (2015). Epigenetic mechanisms underlying learning and the inheritance of learned behaviors. Trends in Neuroscience, 38, 96–107.CrossRefGoogle ScholarPubMed
Dong, M., Anda, R. F., Felitti, V. J., Dube, S. R., Williamson, D. F., Thompson, T. J., … Giles, W. H. (2004). The interrelatedness of multiple forms of childhood abuse, neglect, and household dysfunction. Child Abuse and Neglect, 28, 771–784.Google Scholar
Dong, M., Giles, W. H., Felitti, V. J., Dube, S. R., Williams, J. E., Chapman, D. P., & Anda, R. F. (2004). Insights into causal pathways for ischemic heart disease: Adverse childhood experiences study. Circulation, 110, 1761–1766.CrossRefGoogle ScholarPubMed
Dougherty, L. R., Smith, V. C., Bufferd, S. J., Stringaris, A., Leibenluft, E., Carlson, G. A., & Klein, D. N. (2013). Preschool irritability: Longitudinal associations with psychiatric disorders at age 6 and parental psychopathology. Journal of the American Academy of Child & Adolescent Psychiatry, 52, 1304–1313.Google Scholar
Dube, S. R., Anda, R. F., Felitti, V. J., Chapman, D. P., Williamson, D. F., & Giles, W. H. (2001). Childhood abuse, household dysfunction, and the risk of attempted suicide throughout the life span: Findings from the Adverse Childhood Experiences Study. Journal of the American Medical Association, 286, 3089–3096.Google Scholar
Dube, S. R., Anda, R. F., Felitti, V. J., Edwards, V. J., & Croft, J. B. (2002). Adverse childhood experiences and personal alcohol abuse as an adult. Addictive Behaviors, 27, 713–725.Google Scholar
Dube, S. R., Felitti, V. J., Dong, M., Chapman, D. P., Giles, W. H., & Anda, R. F. (2003). Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: The adverse childhood experiences study. Pediatrics, 111, 564–572.Google Scholar
Duncan, L. E., & Keller, M. C. (2011). A critical review of the first 10 years of candidate gene- by-environment interaction research in psychiatry. American Journal of Psychiatry, 168, 1041–1049.Google Scholar
Dunn, L. M., & Dunn, D. D. (2006). Peabody Picture Vocabulary Test. Toronto: Pearson.Google Scholar
Edwards, V. J., Holden, G. W., Felitti, V. J., & Anda, R. F. (2003). Relationship between multiple forms of childhood maltreatment and adult mental health in community respondents: Results from the adverse childhood experiences study. American Journal of Psychiatry, 160, 1453–1460.Google Scholar
Eley, T. C., Sugden, K., Corsico, A., Gregory, A. M., Sham, P., McGuffin, P., … Craig, I. W. (2004). Gene-environment interaction analysis of serotonin system markers with adolescent depression. Molecular Psychiatry, 9, 908–915.Google Scholar
Enoch, M. A., Kitzman, H., Smith, J. A., Anson, E., Hodgkinson, C. A., Goldman, D., & Olds, D. (2016). A prospective cohort study of influences on externalizing behaviors across childhood: Results from a nurse home visiting randomized controlled trial. Journal of the American Academy of Child & Adolescent Psychiatry, 55, 376–382.Google Scholar
Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., … Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14, 245–258.Google Scholar
Ford, B. Q., Mauss, I. B., Troy, A. S., Smolen, A., & Hankin, B. (2014). Emotion regulation moderates the risk associated with the 5-HTT gene and stress in children. Emotion, 14, 930–939.Google Scholar
Glover, V. (2014). Maternal depression, anxiety and stress during pregnancy and child outcome; what needs to be done. Clinical Obstetetrics and Gynaecology, 28, 25–35.Google Scholar
Green, J. G., McLaughlin, K. A., Berglund, P. A., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2010). Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication: I. Associations with first onset of DSM-IV disorders. Archives of General Psychiatry, 67, 113–123.Google Scholar
Gunnar, M., & Quevedo, K. (2007). The neurobiology of stress and development. Annual Review of Psychology, 58, 145–173.Google Scholar
Hellstrom, I. C., Dhir, S. K., Diorio, J. C., & Meaney, M. J. (2012). Maternal licking regulates hippocampal glucocorticoid receptor transcription through a thyroid hormone-serotonin-NGFI-A signaling cascade. Philosophical Translations of the Royal Society of London B: Biological Sciences, 367, 2495–2510.Google Scholar
Hu, X. Z., Lipsky, R. H., Zhu, G., Akhtar, L. A., Taubman, J., Greenberg, B. D., … Goldman, D. (2006). Serotonin transporter promoter gain-of-function genotypes are linked to obsessive-compulsive disorder. American Journal of Human Genetics, 78, 815–826.Google Scholar
Hyde, C. L., Nagle, M. W., Tian, C., Chen, X., Paciga, S. A., Wendland, J. R., … Winslow, A. R. (2016). Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nature Genetics, 48, 1031–1036.Google Scholar
Institut de la statistique du Québec, & Québec, D. S. (Ed.). (1998). Enquête sociale et de santé 1998 (Annexe 2, p. 60). Sante-Foy, Québec: Les Publications du Québec.Google Scholar
Kanner, A. D., Coyne, J. C., Schaefer, C., & Lazarus, R. S. (1981). Comparison of two modes of stress measurement: Daily hassles and uplifts versus major life events. Journal of Behavioral Medicine, 4, 1–39.Google Scholar
Kendler, K. S., Kuhn, J. W., & Prescott, C. A. (2004). Childhood sexual abuse, stressful life events and risk for major depression in women. Psychological Medicine, 34, 1475–1482.Google Scholar
Kendler, K. S., Kuhn, J. W., Vittum, J., Prescott, C. A., & Riley, B. (2005). The interaction of stressful life events and a serotonin transporter polymorphism in the prediction of episodes of major depression: A replication. Archives of General Psychiatry, 62, 529–535.CrossRefGoogle Scholar
Kessler, R. C., Davis, C. G., & Kendler, K. S. (1997). Childhood adversity and adult psychiatric disorder in the US National Comorbidity Survey. Psychological Medicine, 27, 1101–1119.Google Scholar
Kramer, M. S., Goulet, L., Lydon, J., Seguin, L., McNamara, H., Dassa, C., … Koren, G. (2001). Socio-economic disparities in preterm birth: Causal pathways and mechanisms. Paediatric and Perinatal Epidemiology, 15(Suppl. 2), 104–123.Google Scholar
Kramer, M. S., Platt, R. W., Wen, S. W., Joseph, K. S., Allen, A., Abrahamowicz, M., … Fetal/Infant Health Study Group of the Canadian Perinatal Surveillance System. (2001). A new and improved population-based Canadian reference for birth weight for gestational age. Pediatrics, 108, E35 Google Scholar
Kramer, M. S., Wilkins, R., Goulet, L., Seguin, L., Lydon, J., Kahn, S. R., … Montreal Prematurity Study Group. (2009). Investigating socio-economic disparities in preterm birth: Evidence for selective study participation and selection bias. Paediatric and Perinatal Epidemiology, 23, 301–309.Google Scholar
Lahti, M., Eriksson, J. G., Heinonen, K., Kajantie, E., Lahti, J., Wahlbeck, K., … Raikkonen, K. (2014). Late preterm birth, post-term birth, and abnormal fetal growth as risk factors for severe mental disorders from early to late adulthood. Psychological Medicine. Advance online publication.Google ScholarPubMed
Laursen, T. M., Munk-Olsen, T., Nordentoft, M., & Bo Mortensen, P. (2007). A comparison of selected risk factors for unipolar depressive disorder, bipolar affective disorder, schizoaffective disorder, and schizophrenia from a Danish population-based cohort. Journal of Clinical Psychiatry, 68, 1673–1681.Google Scholar
Lemelin, J. P., Boivin, M., Forget-Dubois, N., Dionne, G., Seguin, J. R., Brendgen, M., … Perusse, D. (2007). The genetic-envirionmental etiology of cognitive school readiness and later academic achievement in early childhood. Child Developement, 78, 1855–1869.Google Scholar
Li, J. J., Berk, M. S., & Lee, S. S. (2013). Differential susceptibility in longitudinal models of gene–environment interaction for adolescent depression. Development and Psychopathology, 25, 991–1003.Google Scholar
Lobel, M., & Dunkel-Schetter, C. (1990). Conceptualizing stress to study effects on health: Environmental, perceptual, and emotional components. Anxiety Research, 3, 213–230.Google Scholar
Lobel, M., Dunkel-Schetter, C., & Scrimshaw, S. C. (1992). Prenatal maternal stress and prematurity: A prospective study of socioeconomically disadvantaged women. Health Psychology, 11, 32–40.Google Scholar
Lorant, V., Deliege, D., Eaton, W., Robert, A., Philippot, P., & Ansseau, M. (2003). Socioeconomic inequalities in depression: A meta-analysis. American Journal of Epidemiology, 157, 98–112.Google Scholar
Luthar, S. S., Cicchetti, D., & Becker, B. (2000). The construct of resilience: A critical evaluation and guidelines for future work. Child Development, 71, 543–562.Google Scholar
McCarthy, S., Das, S., Kretzschmar, W., Delaneau, O., Wood, A. R., Teumer, A., … Haplotype Reference, C. (2016). A reference panel of 64,976 haplotypes for genotype imputation. Nature Genetics, 48, 1279–1283.Google Scholar
Meaney, M. J. (2010). Epigenetics and the biological definition of Gene × Environment interactions. Child Development, 81, 41–79.Google Scholar
Meaney, M. J., & Ferguson-Smith, A. C. (2010). Epigenetic regulation of the neural transcriptome: The meaning of the marks. Nature Neuroscience, 13, 1313–1318.Google Scholar
Miller, J. A., Ding, S. L., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., … Lein, E. S. (2014). Transcriptional landscape of the prenatal human brain. Nature, 508, 199–206.Google Scholar
Ming, Q. S., Zhang, Y., Chai, Q. L., Chen, H. Y., Hou, C. J., Wang, M. C., … Yao, S. Q. (2013). Interaction between a serotonin transporter gene promoter region polymorphism and stress predicts depressive symptoms in Chinese adolescents: A multi-wave longitudinal study. BMC Psychiatry, 13, 142.Google Scholar
Newberger, E. H., Barkan, S. E., Lieberman, E. S., McCormick, M. C., Yllo, K., Gary, L. T., & Schechter, S. (1992). Abuse of pregnant women and adverse birth outcome: Current knowledge and implications for practice. Journal of the American Medical Association, 267, 2370–2372.Google Scholar
Nikolova, Y. S., Ferrell, R. E., Manuck, S. B., & Hariri, A. R. (2011). Multilocus genetic profile for dopamine signaling predicts ventral striatum reactivity. Neuropsychopharmacology, 36, 1940–1947.Google Scholar
O'Donnell, K. A., Gaudreau, H., Colalillo, S., Steiner, M., Atkinson, L., Moss, E., … MAVAN Research Team. (2014). The Maternal Adversity Vulnerability and Neurodevelopment (MAVAN) Project: Theory and methodology. Canadian Journal of Psychiatry, 59, 497–508.Google Scholar
O'Donnell, K. J., Glover, V., Barker, E. D., & O'Connor, T. G. (2014). The persisting effect of maternal mood in pregnancy on childhood psychopathology. Development and Psychopathology, 26, 393–403.Google Scholar
O'Donnell, K. J., & Meaney, M. J. (2017). Fetal origins of mental health: The developmental origins of health and disease hypothesis. American Journal of Psychiatry, 174, 319–328.Google Scholar
Okamoto, Y., & Case, R. (1996). Exploring the microstructure of children's central conceptual structures in the domain of number. Monographs of the Society for Research in Child Development, 61, 27–58.Google Scholar
Oliver, B. R., Kretschmer, T., & Maughan, B. (2014). Configurations of early risk and their association with academic, cognitive, emotional and behavioural outcomes in middle childhood. Social Psychiatry and Psychiatric Epidemiology, 49, 723–732.Google Scholar
Parker, B., McFarlane, J., Soeken, K., Torres, S., & Campbell, D. (1993). Physical and emotional abuse in pregnancy: A comparison of adult and teenage women. Nursing Research, 42, 173–178.Google Scholar
Pearlin, L. I., & Schooler, C. (1978). The structure of coping. Journal of Health and Social Behavior, 19, 2–21.Google Scholar
Pearson, R. M., Evans, J., Kounali, D., Lewis, G., Heron, J., Ramchandani, P. G., … Stein, A. (2013). Maternal depression during pregnancy and the postnatal period: Risks and possible mechanisms for offspring depression at age 18 years. JAMA Psychiatry, 70, 1312–1319.Google Scholar
Pesonen, A. K., Raikkonen, K., Strandberg, T. E., & Jarvenpaa, A. L. (2006). Do gestational age and weight for gestational age predict concordance in parental perceptions of infant temperament? Journal of Pediatric Psychology, 31, 331–336.Google Scholar
Phillips, D. I. W., Barker, D. J. P., Fall, C. H. D., Seckl, J. R., Whorwood, C. B., Wood, P. J., & Walker, B. R. (1998). Elevated plasma cortisol concentrations: A link between low birth weight and the insulin resistance syndrome? Journal of Clinical Endocrinology & Metabolism, 83, 757–760.Google Scholar
Piccolo, L. R., Merz, E. C., He, X., Sowell, E. R., Noble, K. G., & Pediatric Imaging, Neurocognition Genetics Study. (2016). Age-related differences in cortical thickness vary by socioeconomic status. PLOS ONE, 11, e0162511.Google Scholar
Pluess, M. (2015). Individual differences in environmental sensitivity. Child Development Perspectives, 9, 138–143.Google Scholar
Pluess, M., & Belsky, J. (2011). Prenatal programming of postnatal plasticity? Development and Psychopathology, 23, 29–38.Google Scholar
Pluess, M., & Belsky, J. (2013). Vantage sensitivity: Individual differences in response to positive experiences. Psychological Bulletin, 139, 901–916.Google Scholar
Pluess, M., Belsky, J., & Neuman, R. J. (2009). Prenatal smoking and attention-deficit/hyperactivity disorder: DRD4-7R as a plasticity gene. Biological Psychiatry, 66, e5–e6.Google Scholar
Pluess, M., Velders, F. P., Belsky, J., van IJzendoorn, M. H., Bakermans-Kranenburg, M. J., … Tiemeier, H. (2011). Serotonin transporter polymorphism moderates effects of prenatal maternal anxiety on infant negative emotionality. Biological Psychiatry, 69, 520–525.Google Scholar
Ports, K. A., Ford, D. C., & Merrick, M. T. (2016). Adverse childhood experiences and sexual victimization in adulthood. Child Abuse and Neglect, 51, 313–322.Google Scholar
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics, 38, 904–909.Google Scholar
Qiu, A., Rifkin-Graboi, A., Chen, H., Chong, Y. S., Kwek, K., Gluckman, P. D., … Meaney, M. J. (2013). Maternal anxiety and infants’ hippocampal development: Timing matters. Translational Psychiatry, 3, e306.Google Scholar
Qiu, A., Tuan, T. A., Ong, M. L., Li, Y., Chen, H., Rifkin-Graboi, A., … Meaney, M. J. (2015). COMT haplotypes modulate associations of antenatal maternal anxiety and neonatal cortical morphology. American Journal of Psychiatry, 172, 163–172.CrossRefGoogle ScholarPubMed
Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.Google Scholar
Raikkonen, K., Pesonen, A. K., Heinonen, K., Kajantie, E., Hovi, P., Jarvenpaa, A. L., … Andersson, S. (2008). Depression in young adults with very low birth weight. Archives of General Psychiatry, 65, 290–296.Google Scholar
R Core Team. (2014). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
Rice, F., Harold, G. T., Boivin, J., van den Bree, M., Hay, D. F., & Thapar, A. (2010). The links between prenatal stress and offspring development and psychopathology: Disentangling environmental and inherited influences. Psychological Medicine, 40, 335–345.Google Scholar
Rifkin-Graboi, A., Bai, J., Chen, H., Hameed, W. B., Sim, L. W., Tint, M. T., … Qiu, A. (2013). Prenatal maternal depression associates with microstructure of right amygdala in neonates at birth. Biological Psychiatry, 74, 837–844.Google Scholar
Rifkin-Graboi, A., Meaney, M. J., Chen, H., Bai, J., Hameed, W. B., Tint, M. T., … Qiu, A. (2015). Antenatal maternal anxiety predicts variations in neural structures implicated in anxiety disorders in newborns. Journal of the American Academy of Child & Adolescent Psychiatry, 54, 313–321.Google Scholar
Robinson, E. B., St. Pourcain, B., Anttila, V., Kosmicki, J. A., Bulik-Sullivan, B., Grove, J., … Daly, M. J. (2016). Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nature Genetics, 48, 552–555.Google Scholar
Rocha, T. B., Hutz, M. H., Salatino-Oliveira, A., Genro, J. P., Polanczyk, G. V., Sato, J. R., … Kieling, C. (2015). Gene–environment interaction in youth depression: Replication of the 5-HTTLPR moderation in a diverse setting. American Journal of Psychiatry, 172, 978–985.Google Scholar
Schizophrenia Working Group of the Psychiatric Genomics Consortium. (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511, 421–427.Google Scholar
Shonkoff, J. P., Boyce, W. T., & McEwen, B. S. (2009). Neuroscience, molecular biology, and the childhood roots of health disparities: Building a new framework for health promotion and disease prevention. Journal of the American Medical Association, 301, 2252–2259.Google Scholar
Slopen, N., Loucks, E. B., Appleton, A. A., Kawachi, I., Kubzansky, L. D., Non, A. L., … Gilman, S. E. (2015). Early origins of inflammation: An examination of prenatal and childhood social adversity in a prospective cohort study. Psychoneuroendocrinology, 51, 403–413.Google Scholar
Soh, S. E., Tint, M. T., Gluckman, P. D., Godfrey, K. M., Rifkin-Graboi, A., Chan, Y. H., … GUSTO Study Group. (2014). Cohort profile: Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort study. International Journal of Epidemiology, 43, 1401–1409.Google Scholar
Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Stice, E., Yokum, S., Burger, K., Epstein, L., & Smolen, A. (2012). Multilocus genetic composite reflecting dopamine signaling capacity predicts reward circuitry responsivity. Journal of Neuroscience, 32, 10093–10100.Google Scholar
Taylor, S. E., Way, B. M., Welch, W. T., Hilmert, C. J., Lehman, B. J., & Eisenberger, N. I. (2006). Early family environment, current adversity, the serotonin transporter promoter polymorphism, and depressive symptomatology. Biological Psychiatry, 60, 671–676.Google Scholar
Uher, R., Caspi, A., Houts, R., Sugden, K., Williams, B., Poulton, R., & Moffitt, T. E. (2011). Serotonin transporter gene moderates childhood maltreatment's effects on persistent but not single-episode depression: Replications and implications for resolving inconsistent results. Journal of Affective Disorders, 135, 56–65.Google Scholar
Uher, R., & McGuffin, P. (2008). The moderation by the serotonin transporter gene of environmental adversity in the aetiology of mental illness: Review and methodological analysis. Molecular Psychiatry, 13, 131–146.Google Scholar
Uher, R., & McGuffin, P. (2010). The moderation by the serotonin transporter gene of environmental adversity in the etiology of depression: 2009 update. Molecular Psychiatry, 15, 18–22.Google Scholar
Wazana, A., Moss, E., Jolicoeur-Martineau, A., Graffi, J., Tsabari, G., Lecompte, V., … Meaney, M. J. (2015). The interplay of birth weight, dopamine receptor D4 gene (DRD4), and early maternal care in the prediction of disorganized attachment at 36 months of age. Development and Psychopathology, 27, 1145–1161.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, 847–854.Google Scholar
Wilhelm, K., Mitchell, P. B., Niven, H., Finch, A., Wedgwood, L., Scimone, A., … Schofield, P. R. (2006). Life events, first depression onset and the serotonin transporter gene. British Journal of Psychiatry, 188, 210–215.Google Scholar
Wray, N. R., & Goddard, M. E. (2010). Multi-locus models of genetic risk of disease. Genome Medicine, 2, 10.Google Scholar
Yu, Q., Daugherty, A. M., Anderson, D. M., Nishimura, M., Brush, D., Hardwick, A., … Ofen, N. (2017). Socioeconomic status and hippocampal volume in children and young adults. Developmental Science. Advance online publication.Google Scholar
Zhang, T. Y., Labonte, B., Wen, X. L., Turecki, G., & Meaney, M. J. (2013). Epigenetic mechanisms for the early environmental regulation of hippocampal glucocorticoid receptor gene expression in rodents and humans. Neuropsychopharmacology, 38, 111–123.Google Scholar
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