Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-21T17:09:36.592Z Has data issue: false hasContentIssue false
  • English
  • Français

The interplay of polygenic plasticity and adrenocortical activity as sources of variability in pathways among family adversity, youth emotional reactivity, and psychological problems

Published online by Cambridge University Press:  15 April 2019

Patrick T. Davies ,
Dante Cicchetti ,
Morgan J. Thompson ,
Sonnette M. Bascoe  and
E. Mark Cummings
Patrick T. Davies*
Affiliation:
Department of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, NY, USA
Dante Cicchetti
Affiliation:
Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
Morgan J. Thompson
Affiliation:
Department of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, NY, USA
Sonnette M. Bascoe
Affiliation:
Department of Psychology, Roberts Wesleyan College, North Chili, NY, USA
E. Mark Cummings
Affiliation:
Department of Psychology, University of Notre Dame, Notre Dame, IN, USA
*
Author for Correspondence: Patrick T. Davies, P.O. Box 270266, Department of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, NY14627; E-mail: Patrick.davies@psych.rochester.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

This study examined the interplay between a polygenic composite and cortisol activity as moderators of the mediational pathway among family adversity, youth negative emotional reactivity to family conflict, and their psychological problems. The longitudinal design contained three annual measurement occasions with 279 adolescents (Mean age = 13.0 years) and their parents. Latent difference score analyses indicated that observational ratings of adversity in interparental and parent–child interactions at Wave 1 predicted increases in a multimethod, multi-informant assessment of youth negative emotional reactivity to family conflict from Waves 1 to 2. Changes in youth negative emotional reactivity, in turn, predicted increases in a multi-informant (i.e., parents, adolescent, and teacher) assessment of psychological problems from Waves 1 to 3. Consistent with differential susceptibility theory, the association between family adversity and negative emotional reactivity was stronger for adolescents who carried more sensitivity alleles in a polygenic composite consisting of 5-HTTLPR, DRD4 VNTR, and BDNF polymorphisms. Analyses of adolescent cortisol in the period surrounding a family disagreement task at Wave 1 revealed that overall cortisol output, rather than cortisol reactivity, served as an endophenotype of the polygenic composite. Overall cortisol output was specifically associated with polygenic plasticity and moderated the association between family adversity and youth negative emotional reactivity in the same for better or for worse manner as the genetic composite. Finally, moderator-mediated-moderation analyses indicated that the moderating role of the polygenic plasticity composite was mediated by the moderating role of adolescent cortisol output in the association between family adversity and their emotional reactivity.

Keywords

family adversityyouth emotional reactivityyouth psychopathology molecular geneticscortisoldifferential susceptibility
Type
Regular Articles
Information
Development and Psychopathology , Volume 32 , Issue 2 , May 2020 , pp. 587 - 603
Copyright
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Achenbach, T. M., Dumenci, L., & Rescorla, L. A. (2003). DSM-oriented and empirically based approaches to constructing scales from the same item pools. Journal of Clinical Child & Adolescent Psychology, 32, 328–340. doi:10.1207/S15374424JCCP3203_02CrossRefGoogle ScholarPubMed
Arbuckle, J. L. (2017). AMOS (Version 25.0) [Computer Program]. Chicago, IL: IBM SPSS.Google Scholar
Armbruster, D., Mueller, A., Moser, D. A., Lesch, K. P., Brocke, B., & Kirschbaum, C. (2009). Interaction effect of D4 dopamine receptor gene and serotonin transporter promoter polymorphism on the cortisol stress response. Behavioral Neuroscience, 123, 1288–1295. doi:10.1037/a0017615CrossRefGoogle ScholarPubMed
Armbruster, D., Müller-Alcazar, A., Strobel, A., Lesch, K., Kirschbaum, C., & Brocke, B. (2016). BDNF val66met genotype shows distinct associations with the acoustic startle reflex and the cortisol stress response in young adults and children. Psychoneuroendocrinology, 66, 39–46. doi:10.1016/j.psyneuen.2015.12.020CrossRefGoogle Scholar
Bai, S., & Repetti, R. L. (2015). Short-term resilience processes in the family. Family Relations, 64, 108–119. doi:10.1111/fare.12101CrossRefGoogle ScholarPubMed
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. doi:10.1017/S0954579410000635CrossRefGoogle ScholarPubMed
Barrios, C. S., Bufferd, S. J., Klein, D. N., & Dougherty, L. R. (2017). The interaction between parenting and children's cortisol reactivity at age 3 predicts increases in children's internalizing and externalizing symptoms at age 6. Development and Psychopathology, 29, 1319–1331. doi:10.1017/S0954579417000293CrossRefGoogle ScholarPubMed
Barsegyan, A., Mackenzie, S. M., Kurose, B. D., McGaugh, J. L., & Roozendaal, B. (2010). Glucocorticoids in the prefrontal cortex enhance memory consolidation and impair working memory by a common neural mechanism. Proceedings of the National Academy of Sciences of the USA, 107, 16655–16660. doi:10.1073/pnas.1011975107CrossRefGoogle ScholarPubMed
Beauchaine, T. P., & Zalewski, M. (2016). Physiological and developmental mechanisms of emotional lability in coercive relationships. In Dishion, T. J. & Snyder, J. J. (Eds.), The Oxford handbook of coercive relationship dynamics (pp. 39–52). New York: Oxford University Press.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. doi:10.1017/S0954579414000844CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. doi:10.1037/a0017376CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2013). Beyond risk, resilience, and dysregulation: Phenotypic plasticity and human development. Development and Psychopathology, 25, 1243–1261. doi:10.1017/S095457941300059XCrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2016). Differential susceptibility to environmental influences. In Cicchetti, D. (Ed.), Developmental psychopathology (3rd ed., Vol. 2, pp. 59–106). Hoboken, NJ: Wiley.Google Scholar
Boyce, W. T. (2016). Differential susceptibility of the developing brain to contextual adversity and stress. Neuropsychopharmacology, 41, 142–162. doi:10.1038/npp.2015.294CrossRefGoogle ScholarPubMed
Branje, S. (2018). Development of parent–adolescent relationships: Conflict interactions as a mechanism of change. Child Development Perspectives, 12, 171–176. doi:10.1111/cdep.12278CrossRefGoogle Scholar
Buehler, C., & Gerard, J. M. (2013). Cumulative family risk predicts increases in adjustment difficulties across early adolescence. Journal of Youth and Adolescence, 42, 905–920. doi:10.1007/s10964-012-9806-3CrossRefGoogle ScholarPubMed
Buehler, C., Lange, G., & Franck, K. L. (2007). Adolescents' cognitive and emotional responses to marital hostility. Child Development, 78, 775–789. doi:10.1111/j.1467-8624.2007.01032.xCrossRefGoogle ScholarPubMed
Burt, K. B., & Obradović, J. (2013). The construct of psychophysiological reactivity: Statistical and psychometric issues. Developmental Review, 33, 29–57. doi:10.1016/j.dr.2012.10.002CrossRefGoogle Scholar
Carver, C. S., LeMoult, J., Johnson, S. L., & Joormann, J. (2014). Gene effects and G × E interactions in the differential prediction of three aspects of impulsiveness. Social Psychological and Personality Science, 5, 730–739. doi:10.1177/1948550614527116CrossRefGoogle Scholar
Chen, Z., Patel, P. D., Sant, G., Meng, C., Teng, K. K., Hempstead, B. L., & Lee, F. S. (2004). Variant brain-derived neurotrophic factor (BDNF) (Met66) alters the intracellular trafficking and activity-dependent secretion of wild-type BDNF in neurosecretory cells and cortical neurons. Journal of Neuroscience, 24, 4401–4411. doi:10.1523/JNEUROSCI.0348-04.2004CrossRefGoogle ScholarPubMed
Clasen, P. C., Wells, T. T., Knopik, V. S., McGeary, J. E., & Beevers, C. G. (2011). 5-HTTLPR and BDNF Val66Met polymorphisms moderate effects of stress on rumination. Genes, Brain and Behavior, 10, 740–746. doi:10.1111/j.1601-183X.2011.00715.xCrossRefGoogle ScholarPubMed
Davies, P. T., & Cicchetti, D. (2014). How and why does the 5-HTTLPR gene moderate associations between maternal unresponsiveness and children's disruptive problems? Child Development, 85, 484–500. doi:10.1111/cdev.12148CrossRefGoogle ScholarPubMed
Davies, P., Cicchetti, D., & Hentges, R. F. (2015). Maternal unresponsiveness and child disruptive problems: The interplay of uninhibited temperament and dopamine transporter genes. Child Development, 86, 63–79. doi:10.1111/cdev.12281CrossRefGoogle ScholarPubMed
Davies, P. T., Cicchetti, D., & Martin, M. J. (2012). Toward greater specificity in identifying associations among interparental aggression, child emotional reactivity to conflict, and child problems. Child Development, 83, 1789–1804. doi:10.1111/j.1467-8624.2012.01804.xCrossRefGoogle ScholarPubMed
Davies, P. T., Martin, M. J., & Sturge-Apple, M. L. (2016). Emotional security theory and developmental psychopathology. In Cicchetti, D. (Ed.), Developmental psychopathology (3rd ed., Vol. 1, pp. 199–264). Hoboken, NJ: Wiley.Google Scholar
Del Giudice, M. (2017). Statistical tests of differential susceptibility: Performance, limitations, and improvements. Development and Psychopathology, 29, 1267–1278. doi:10.1017/S0954579416001292CrossRefGoogle ScholarPubMed
Del Giudice, M., Ellis, B. J., & Shirtcliff, E. A. (2011). The adaptive calibration model of stress responsivity. Neuroscience and Biobehavioral Reviews, 35, 1562–1592. doi:10.1016/j.neubiorev.2010.11.007CrossRefGoogle ScholarPubMed
de Quervain, D., Schwabe, L., & Roozendaal, B. (2017). Stress, glucocorticoids and memory: Implications for treating fear-related disorders. Nature Reviews Neuroscience, 18, 7–19. doi:10.1038/nrn.2016.155CrossRefGoogle ScholarPubMed
Doremus-Fitzwater, T. L., Varlinskaya, E. I., & Spear, L. P. (2010). Motivational systems in adolescence: Possible implications for age differences in substance abuse and other risk-taking behaviors. Brain and Cognition, 72, 114–123. doi:10.1016/j.bandc.2009.08.008CrossRefGoogle ScholarPubMed
Dougherty, L. R., Klein, D. N., Congdon, E., Canli, T., & Hayden, E. P. (2010). Interaction between 5-HTTLPR and BDNF Val66Met polymorphisms on HPA axis reactivity in preschoolers. Biological Psychology, 83, 93–100. doi:10.1016/j.biopsycho.2009.10.009CrossRefGoogle ScholarPubMed
Du Rocher Schudlich, T. D., Papp, L. M., & Cummings, E. M. (2004). Relations of husbands' and wives' dysphoria to marital conflict resolution strategies. Journal of Family Psychology, 18, 171–183. doi:10.1037/0893-3200.18.1.171CrossRefGoogle ScholarPubMed
Egan, M. F., Kojima, M., Callicott, J. H., Goldberg, T. E., Kolachana, B. S., Bertolino, A., … Weinberger, D. R. (2003). The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell, 112, 257–269. doi:10.1016/S0092-8674(03)00035-7CrossRefGoogle ScholarPubMed
Ellis, B. J., Boyce, W. T., Belsky, J., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2011). Differential susceptibility to the environment: An evolutionary–neurodevelopmental theory. Development and Psychopathology, 23, 7–28. doi:10.1017/S0954579410000611CrossRefGoogle Scholar
Ellis, B. J., Essex, M. J., & Boyce, W. T. (2005). Biological sensitivity to context: II. Empirical explorations of an evolutionary-developmental theory. Development and Psychopathology, 17, 303–328. doi:10.1017/S0954579405050157CrossRefGoogle ScholarPubMed
Ernst, M., Romeo, R. D., & Andersen, S. L. (2009). Neurobiology of the development of motivated behaviors in adolescence: A window into a neural systems model. Pharmacology, Biochemistry and Behavior, 93, 199–211. doi:10.1016/j.pbb.2008.12.013CrossRefGoogle ScholarPubMed
Flinn, M. V. (2006). Evolution and ontogeny of stress response to social challenges in the human child. Developmental Review, 26, 138–174. doi:10.1016/j.dr.2006.02.003CrossRefGoogle Scholar
Galván, A., & Tottenham, N. (2016). Adolescent brain development. In Cicchetti, D. (Ed.), Developmental psychopathology (3rd ed., Vol. 2, pp. 1–36). Hoboken, NJ: Wiley.Google Scholar
Gelernter, J., Kranzler, H., & Cubells, J. F. (1997). Serotonin transporter protein (SLC6A4) allele and haplotype frequencies and linkage disequilibria in African- and European-American and Japanese populations and in alcohol-dependent subjects. Human Genetics, 101, 243–246. doi:10.1007/s004390050624CrossRefGoogle ScholarPubMed
Goodman, R., & Scott, S. (1999). Comparing the Strengths and Difficulties Questionnaire and the Child Behavior Checklist: Is small beautiful? Journal of Abnormal Child Psychology, 27, 17–24. doi:10.1023/A:1022658222914CrossRefGoogle Scholar
Gunnar, M., & Vazquez, D. (2006). Stress neurobiology and developmental psychopathology. In Cicchetti, D. & Cohen, D. (Eds.), Developmental psychopathology (2nd ed., Vol. 2., pp. 533–577). Hoboken, NJ: Wiley.Google Scholar
Harold, G. T., & Sellers, R. (2018). Annual research review: Interparental conflict and youth psychopathology: An evidence review and practice focused update. Journal of Child Psychology and Psychiatry, 59, 374–402. doi:10.1111/jcpp.12893CrossRefGoogle ScholarPubMed
Heinz, A., Mann, K., Weinberger, D. R., & Goldman, D. (2001). Serotonergic dysfunction, negative mood states, and response to alcohol. Alcoholism: Clinical and Experimental Research, 25, 487–495. doi:10.1111/j.1530-0277.2001.tb02240.xCrossRefGoogle ScholarPubMed
Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011). The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: Evidence of genetic moderation. Archives of General Psychiatry, 68, 444–454. doi:10.1001/archgenpsychiatry.2010.189CrossRefGoogle ScholarPubMed
Kim, J., & Cicchetti, D. (2010). Longitudinal pathways linking child maltreatment, emotion regulation, peer relations, and psychopathology. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 51, 706–716. doi:10.1111/j.1469-7610.2009.02202.xCrossRefGoogle ScholarPubMed
Koss, K. J., Cummings, E. M., Davies, P. T., Hetzel, S., & Cicchetti, D. (2016). Harsh parenting and serotonin transporter and BDNF Val66Met polymorphisms as predictors of adolescent depressive symptoms. Journal of Clinical Child & Adolescent Psychology, 47, S205–S218. doi:10.1080/15374416.2016.1220311CrossRefGoogle ScholarPubMed
Kretschmer, T., Vitaro, F., & Barker, E. D. (2014). The association between peer and own aggression is moderated by the BDNF val-met polymorphism. Journal of Research on Adolescence, 24, 177–185. doi:10.1111/jora.12050CrossRefGoogle ScholarPubMed
Labella, M. H., & Masten, A. S. (2018). Family influences on the development of aggression and violence. Current Opinion in Psychology, 19, 11–16. doi:10.1016/j.copsyc.2017.03.028CrossRefGoogle ScholarPubMed
Laurent, H. K., Leve, L. D., Neiderhiser, J. M., Natsuaki, M. N., Shaw, D. S., Fisher, P. A., … Reiss, D. (2013). Effects of parental depressive symptoms on child adjustment moderated by hypothalamic pituitary adrenal activity: Within- and between-family risk. Child Development, 84, 528–542. doi:10.1111/j.1467-8624.2012.01859.xCrossRefGoogle ScholarPubMed
Lesch, K., Bengel, D., Heils, A., Sabol, S. Z., Greenberg, B. D., Petri, S., … Murphy, D. L. (1996). Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science, 274, 1527–1531. doi:10.1126/science.274.5292.1527CrossRefGoogle ScholarPubMed
Lindahl, K. M., Bregman, H. R., & Malik, N. M. (2012). Family boundary structures and child adjustment: The indirect role of emotional reactivity. Journal of Family Psychology, 26, 839–847. doi:10.1037/a0030444CrossRefGoogle ScholarPubMed
Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198–1202. doi:10.1080/01621459.1988.10478722CrossRefGoogle Scholar
Lonsdorf, T. B., Golkar, A., Lindström, K. M., Haaker, J., Öhman, A., Schalling, M., & Ingvar, M. (2015). BDNFval66met affects neural activation pattern during fear conditioning and 24 h delayed fear recall. Social Cognitive and Affective Neuroscience, 10, 664–671. doi:10.1093/scan/nsu102CrossRefGoogle ScholarPubMed
Luebbe, A. M., & Bell, D. J. (2014). Positive and negative family emotional climate differentially predict youth anxiety and depression via distinct affective pathways. Journal of Abnormal Child Psychology, 42, 897–911. doi:10.1007/s10802-013-9838-5CrossRefGoogle ScholarPubMed
MacKinnon, D. P., Fritz, M. S., Williams, J., & Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39, 384–389. doi:10.3758/BF03193007CrossRefGoogle ScholarPubMed
Malik, N. M., & Lindahl, K. M. (2004). System for Coding Interactions in Dyads (SCID). In Kerig, P. K. & Baucom, D. H. (Eds.), Couple observational coding systems (pp. 173–188). Mahwah, NJ: Erlbaum.Google Scholar
Maxwell, S. E., & Cole, D. A. (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12, 23–44. doi:10.1037/1082-989X.12.1.23CrossRefGoogle ScholarPubMed
McArdle, J. J. (2009). Latent variable modeling of differences and changes with longitudinal data. Annual Review of Psychology, 60, 577–605. doi:10.1146/annurev.psych.60.110707.163612CrossRefGoogle ScholarPubMed
McLaughlin, K. A., Kubzansky, L. D., Dunn, E. C., Waldinger, R., Vaillant, G., & Koenen, K. C. (2010). Childhood social environment, emotional reactivity to stress, and mood and anxiety disorders across the life course. Depression and Anxiety, 27, 1087–1094. doi:10.1002/da.20762CrossRefGoogle ScholarPubMed
Melby, J. N., & Conger, R. D. (2001). The Iowa Family Interaction rating scales: Instrument summary. In Kerig, P. K. & Lindahl, K. M. (Eds.), Family observational coding systems: Resources for systematic research (pp. 33–57). Mahwah, NJ: Erlbaum.Google Scholar
Miller, R., Wankerl, M., Stalder, T., Kirschbaum, C., & Alexander, N. (2013). The serotonin transporter gene-linked polymorphic region (5-HTTLPR) and cortisol stress reactivity: A meta-analysis. Molecular Psychiatry, 18, 1018–1024. doi:10.1038/mp.2012.124CrossRefGoogle ScholarPubMed
Monahan, K. C., Guyer, A. E., Silk, J., Fitzwater, T., & Steinberg, L. (2016). Integration of developmental neuroscience and contextual approaches to the study of adolescent psychopathology. In Cicchetti, D. (Ed.), Developmental psychopathology (3rd ed., Vol. 2, pp. 1–46). Hoboken, NJ: Wiley.Google Scholar
Montag, C., Weber, B., Fliessbach, K., Elger, C., & Reuter, M. (2009). The BDNF Val66Met polymorphism impacts parahippocampal and amygdala volume in healthy humans: Incremental support for a genetic risk factor for depression. Psychological Medicine, 39, 1831–1839. doi:10.1017/S0033291709005509CrossRefGoogle ScholarPubMed
Moore, S. R., & Depue, R. A. (2016). Neurobehavioral foundation of environmental reactivity. Psychological Bulletin, 142, 107–164. doi:10.1037/bul0000028CrossRefGoogle ScholarPubMed
Morris, A. S., Houltberg, B. J., Criss, M. M., & Bosler, C. D. (2017). Family context and psychopathology: The mediating role of children's emotion regulation. In Centifanti, L. C. & Williams, D. M. (Eds.), The Wiley handbook of developmental psychopathology (pp. 365–389). Hoboken, NJ: Wiley.CrossRefGoogle Scholar
Morris, A. S., Silk, J. S., Steinberg, L., Myers, S. S., & Robinson, L. R. (2007). The role of the family context in the development of emotion regulation. Social Development, 16, 361–388. doi:10.1111/j.1467-9507.2007.00389.xCrossRefGoogle ScholarPubMed
Obradović, J., Bush, N. R., & Boyce, W. T. (2011). The interactive effect of marital conflict and stress reactivity on externalizing and internalizing symptoms: The role of laboratory stressors. Development and Psychopathology, 23, 101–114. doi:10.1017/S0954579410000672CrossRefGoogle ScholarPubMed
Obradović, J., Bush, N. R., Stamperdahl, J., Adler, N. E., & Boyce, W. T. (2010). Biological sensitivity to context: The interactive effects of stress reactivity and family adversity on socioemotional behavior and school readiness. Child Development, 81, 270–289. doi:10.1111/j.1467-8624.2009.01394.xCrossRefGoogle ScholarPubMed
Odgers, C. L., Caspi, A., Nagin, D. S., Piquero, A. R., Slutske, W. S., Milne, B. J., … Moffitt, T. E. (2008). Is it important to prevent early exposure to drugs and alcohol among adolescents? Psychological Science, 19, 1037–1044. doi:10.1111/j.1467-9280.2008.02196.xCrossRefGoogle ScholarPubMed
Pagliaccio, D., Luby, J. L., Bogdan, R., Agrawal, A., Gaffrey, M. S., Belden, A. C., … Barch, D. M. (2014). Stress-system genes and life stress predict cortisol levels and amygdala and hippocampal volumes in children. Neuropsychopharmacology, 39, 1245–1253. doi:10.1038/npp.2013.327CrossRefGoogle ScholarPubMed
Pappa, I., Mileva-Seitz, V. R., Bakermans-Kranenburg, M. J., Tiemeier, H., & van IJzendoorn, M. H. (2015). The magnificent seven: A quantitative review of dopamine receptor d4 and its association with child behavior. Neuroscience and Biobehavioral Reviews, 57, 175–186. doi:10.1016/j.neubiorev.2015.08.009CrossRefGoogle ScholarPubMed
Pluess, M. (2017). Vantage sensitivity: Environmental sensitivity to positive experiences as a function of genetic differences: Genetic vantage sensitivity. Journal of Personality, 85, 38–50. doi:10.1111/jopy.12218CrossRefGoogle ScholarPubMed
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879–891. doi:10.3758/BRM.40.3.879CrossRefGoogle ScholarPubMed
Pruessner, J. C., Kirschbaum, C., Meinlschmid, G., & Hellhammer, D. H. (2003). Two formulas for computation of the area under the curve represent measures of total hormone concentration versus time-dependent change. Psychoneuroendocrinology, 28, 916–931. doi:10.1016/S0306-4530(02)00108-7CrossRefGoogle ScholarPubMed
Reimold, M., Smolka, M. N., Schumann, G., Zimmer, A., Wrase, J., Mann, K., … Heinz, A. (2007). Midbrain serotonin transporter binding potential measured with [11C]DASB is affected by serotonin transporter genotype. Journal of Neural Transmission, 114, 635–639. doi:10.1007/s00702-006-0609-0CrossRefGoogle ScholarPubMed
Repetti, R. L., Robles, T. F., & Reynolds, B. (2011). Allostatic processes in the family. Development and Psychopathology, 23, 921–938. doi:10.1017/S095457941100040XCrossRefGoogle ScholarPubMed
Repetti, R. L., Taylor, S. E., & Seeman, T. E. (2002). Risky families: Family social environments and the mental and physical health of offspring. Psychological Bulletin, 128, 330–366. doi:10.1037/0033-2909.128.2.330CrossRefGoogle ScholarPubMed
Roisman, G. I., Newman, D. A., Fraley, R. C., Haltigan, J. D., Groh, A. M., & Haydon, K. C. (2012). Distinguishing differential susceptibility from diathesis-stress: Recommendations for evaluating interaction effects. Development and Psychopathology, 24, 389–409. doi:10.1017/S0954579412000065CrossRefGoogle ScholarPubMed
Sbarra, D. A., & Allen, J. J. B. (2009). Decomposing depression: On the prospective and reciprocal dynamics of mood and sleep disturbances. Journal of Abnormal Psychology, 118, 171–182. doi:10.1037/a0014375CrossRefGoogle ScholarPubMed
Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57, 1–10. doi:10.1037/a0018082CrossRefGoogle ScholarPubMed
Schriber, R. A., & Guyer, A. E. (2016). Adolescent neurobiological susceptibility to social context. Developmental Cognitive Neuroscience, 19, 1–18. doi:10.1016/j.dcn.2015.12.009CrossRefGoogle ScholarPubMed
Sharpley, C. F., Palanisamy, S. K. A., Glyde, N. S., Dillingham, P. W., & Agnew, L. L. (2014). An update on the interaction between the serotonin transporter promoter variant (5-HTTLPR), stress and depression, plus an exploration of non-confirming findings. Behavioural Brain Research, 273, 89–105. doi:10.1016/j.bbr.2014.07.030CrossRefGoogle Scholar
Steeger, C. M., Cook, E. C., & Connell, C. M. (2017). The interactive effects of stressful family life events and cortisol reactivity on adolescent externalizing and internalizing behaviors. Child Psychiatry & Human Development, 48, 225–234. doi:10.1007/s10578-016-0635-6CrossRefGoogle ScholarPubMed
Steinberg, L. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52, 216–224. doi:10.1002/dev.20445Google ScholarPubMed
Suveg, C., Shaffer, A., Morelen, D., & Thomassin, K. (2011). Links between maternal and child psychopathology symptoms: Mediation through child emotion regulation and moderation through maternal behavior. Child Psychiatry & Human Development, 42, 507–520. doi:10.1007/s10578-011-0223-8CrossRefGoogle ScholarPubMed
Sweitzer, M. M., Halder, I., Flory, J. D., Craig, A. E., Gianaros, P. J., Ferrell, R. E., & Manuck, S. B. (2013). Polymorphic variation in the dopamine D4 receptor predicts delay discounting as a function of childhood socioeconomic status: Evidence for differential susceptibility. Social Cognitive and Affective Neuroscience, 8, 499–508. doi:10.1093/scan/nss020CrossRefGoogle ScholarPubMed
Telzer, E. H., van Hoorn, J., Rogers, C. R., & Do, K. T. (2018). Social influence on positive youth development: A developmental neuroscience perspective. Advances in Child Development and Behavior, 54, 215–258. doi:10.1016/bs.acdb.2017.10.003CrossRefGoogle ScholarPubMed
Turic, D., Swanson, J., & Sonuga-Barke, E. (2010). DRD4 and DAT1 in ADHD: Functional neurobiology to pharmacogenetics. Pharmacogenomics and Personalized Medicine, 3, 61–78. doi:10.2147/PGPM.S6800CrossRefGoogle ScholarPubMed
van IJzendoorn, M. H., Belsky, J., & Bakermans-Kranenburg, M. J. (2012). Serotonin transporter genotype 5HTTLPR as a marker of differential susceptibility? A meta-analysis of child and adolescent gene-by-environment studies. Translational Psychiatry, 2, e147. doi:10.1038/tp.2012.73CrossRefGoogle ScholarPubMed
Weeland, J., Overbeek, G., de Castro, B. O., & Matthys, W. (2015). Underlying mechanisms of gene-environment interactions in externalizing behavior: A systematic review and search for theoretical mechanisms. Clinical Child and Family Psychology Review, 18, 413–442. doi:10.1007/s10567-015-0196-4CrossRefGoogle ScholarPubMed
Yap, M. B. H., Schwartz, O. S., Byrne, M. L., Simmons, J. G., & Allen, N. B. (2010). Maternal positive and negative interaction behaviors and early adolescents' depressive symptoms: Adolescent emotion regulation as a mediator. Journal of Research on Adolescence, 20, 1014–1043. doi:10.1111/j.1532-7795.2010.00665.xCrossRefGoogle Scholar
Zhao, M., Chen, M., Chen, L., Yang, Y., Yang, J., Yang, X., … Pan, H. (2018). BDNF Val66Met polymorphism, life stress and depression: A meta-analysis of gene-environment interaction. Journal of Affective Disorders, 227, 226–235. doi:10.1016/j.jad.2017.10.024CrossRefGoogle ScholarPubMed