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Gene–Environment Interaction in the Behavioral Sciences: Findings, Challenges, and Prospects

Part of the Advances in Development and Psychopathology: Brain Research Foundation Symposium Series book series (AIDP,volume 2)

Abstract

We review gene × environment interaction (G×E) research in behavioral and psychiatric genetics. Two approaches to G×E are contrasted: a latent-variable approach that seeks to determine whether the heritability of a behavioral outcome varies by environmental exposure, and a candidate-gene × environment approach that seeks to determine whether genotypes are differentially sensitive to environmental conditions. Three major challenges to current G×E research are identified: (1) most published G×E findings are based on small samples and thus a high proportion are likely to be false-positive reports; (2) imprecision in the assessment of the phenotype, environment, and the genotype can significantly attenuate the power of a G×E study; and (3) a G×E is not an inherent property of the organism but rather a feature of a statistical model and so its identification depends on the structure of that model. The promise of genomic medicine is that interventions can be tailored to individual treatments, a form of G×E. Nonetheless, there is currently limited evidence of gene × intervention interactions in behavioral and psychiatric genetics. Future gene × intervention research will benefit from what we have learned from earlier G×E research and especially the need for large samples and the standardization of assessments to enable pooling of data across multiple studies.

Keywords

  • Gene × environment interaction
  • Candidate-gene studies
  • Genome-wide Association Studies (GWAS)
  • False-positive findings
  • Diathesis–stress model
  • Social control model

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References

  • Ahmad, S., Rukh, G., Varga, T. V., Ali, A., Kurbasic, A., Shungin, D., … DIRECT Consortium. (2013). Gene × physical activity interactions in obesity: Combined analysis of 111,421 individuals of European Ancestry. PLoS Genetics, 9(7), e1003607. doi:10.1371/journal.pgen.1003607.

    Google Scholar 

  • Anastasi, A. (1958). Heredity, environment, and the question "How?". Psychological Review, 65(4), 197–208.

    CrossRef  PubMed  Google Scholar 

  • Anda, R. F., Felitti, V. J., Bremner, J. D., Walker, J. D., Whitfield, C., Perry, B. D., … Giles, W. H. (2006). The enduring effects of abuse and related adverse experiences in childhood—A convergence of evidence from neurobiology and epidemiology. [Review]. European Archives of Psychiatry and Clinical Neuroscience, 256(3), 174–186. doi:10.1007/s00406-005-0624-4.

  • 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(5), 406–409. doi:10.1002/dev.20152.

    CrossRef  PubMed  Google Scholar 

  • Barrdahl, M., Canzian, F., Joshi, A. D., Travis, R. C., Chang-Claude, J., Auer, P. L., … Campa, D. (2014). Post-GWAS gene–environment interplay in breast cancer: Results from the Breast and Prostate Cancer Cohort Consortium and a meta-analysis on 79000 women. Human Molecular Genetics, 23(19), 5260–5270. doi:10.1093/hmg/ddu223.

  • Bastiaansen, J. A., Servaas, M. N., Marsman, J. B. C., Ormel, J., Nolte, I. M., Riese, H., & Aleman, A. (2014). Filling the gap: Relationship between the serotonin-transporter-linked polymorphic region and Amygdala activation. Psychological Science, 25(11), 2058–2066. doi:10.1177/0956797614548877.

    CrossRef  PubMed  Google Scholar 

  • Baugh, C. M., Robbins, C. A., Stern, R. A., & McKee, A. C. (2014). Current understanding of chronic traumatic encephalopathy. [Review]. Current Treatment Options in Neurology, 16(9), 306. doi:10.1007/s11940-014-0306-5.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Beaver, K. M., DeLisi, M., Wright, J. P., & Vaughn, M. G. (2009). Gene–environment interplay and delinquent involvement evidence of direct, indirect, and interactive effects. Journal of Adolescent Research, 24(2), 147–168. doi:10.1177/0743558408329952.

    CrossRef  Google Scholar 

  • Becker, K., El-Faddagh, M., Schmidt, M. H., Esser, G., & Laucht, M. (2008). Interaction of dopamine transporter genotype with prenatal smoke exposure on ADHD symptoms. Journal of Pediatrics, 152(2), 263–269. doi:10.1016/j.jpeds.2007.07.004.

    CrossRef  PubMed  Google Scholar 

  • Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummett, B., & Williams, R. (2009). Vulnerability genes or plasticity genes? Molecular Psychiatry, 14(8), 746–754. doi:10.1038/mp.2009.44.

    CrossRef  PubMed  PubMed Central  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(3), 725–746.

    Google Scholar 

  • Berrington de Gonzales, A., & Cox, D. R. (2007). Interpretation of interaction: A review. Annals of Applied Statistics, 1, 371–385.

    CrossRef  Google Scholar 

  • Bierut, L. J., Johnson, E. O., & Saccone, N. L. (2014). A glimpse into the future—Personalized medicine for smoking cessation. [Review]. Neuropharmacology, 76, 592–599. doi:10.1016/j.neuropharm.2013.09.009.

    CrossRef  PubMed  Google Scholar 

  • Boardman, J. D. (2009). State-level moderation of genetic tendencies to smoke. American Journal of Public Health, 99(3), 480–486. doi:10.2105/ajph.2008.134932.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Boardman, J. D., Blalock, C. L., & Pampel, F. C. (2010). Trends in the genetic influences on smoking. Journal of Health and Social Behavior, 51(1), 108–123. doi:10.1177/0022146509361195.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Boffetta, P., Winn, D. M., Ioannidis, J. P., Thomas, D. C., Little, J., Smith, G. D., … Khoury, M. J. (2012). Recommendations and proposed guidelines for assessing the cumulative evidence on joint effects of genes and environments on cancer occurrence in humans. International Journal of Epidemiology, 41(3), 686–704. doi:10.1093/ije/dys010.

  • Bosker, F. J., Hartman, C. A., Nolte, I. M., Prins, B. P., Terpstra, P., Posthuma, D., … Nolen, W. A. (2011). Poor replication of candidate genes for major depressive disorder using genome-wide association data. Molecular Psychiatry, 16(5), 516–532. doi:10.1038/mp.2010.38.

  • Brody, G. H., Beach, S. R. H., Hill, K. G., Howe, G. W., Prado, G., & Fullerton, S. M. (2013). Using genetically informed, randomized prevention trials to test etiological hypotheses about child and adolescent drug use and psychopathology. American Journal of Public Health, 103, S19–S24. doi:10.2105/ajph.2012.301080.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Button, T. M. M., Lau, J. Y. F., Maughan, B., & Eley, T. C. (2008). Parental punitive discipline, negative life events and gene–environment interplay in the development of externalizing behavior. Psychological Medicine, 38(1), 29–39. doi:10.1017/s0033291707001328.

    CrossRef  PubMed  Google Scholar 

  • Button, T. M. M., Hewitt, J. K., Rhee, S. H., Corley, R. P., & Stallings, M. C. (2010). The moderating effect of religiosity on the genetic variance of problem alcohol use. Alcoholism: Clinical and Experimental Research, 34(9), 1619–1624. doi:10.1111/j.1530-0277.2010.01247.x.

    CrossRef  Google Scholar 

  • Caspi, A., McClay, J., Moffitt, T. E., Mill, J., Martin, J., Craig, I. W., … Poulton, R. (2002). Role of genotype in the cycle of violence in maltreated children. Science, 297, 851–854.

    Google Scholar 

  • Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I., Harrington, H. L., … Poulton, R. (2003). Influence of life stress on depression: Moderation by polymorphism in the 5-HTT gene. Science, 301, 386–389.

    Google Scholar 

  • Caspi, A., Hariri, A. R., Holmes, A., Uher, R., & Moffitt, T. E. (2010). Genetic sensitivity to the environment: the case of the serotonin transporter gene and its implications for studying complex diseases and traits. American Journal of Psychiatry, 167(5), 509–527. doi:10.1176/appi.ajp.2010.09101452.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Chan, I. S., & Ginsburg, G. S. (2011). Personalized medicine: Progress and promise. In A. Chakravarti & E. Green (Eds.), Annual review of genomics and human genetics (Vol. 12, pp. 217–244). Palo Alto, CA: Annual Reviews.

    Google Scholar 

  • Charmantier, A., & Garant, D. (2005). Environmental quality and evolutionary potential: Lessons from wild populations. [Review]. Proceedings of the Royal Society B: Biological Sciences, 272(1571), 1415–1425. doi:10.1098/rspb.2005.3117.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Chen, L. S., Baker, T. B., Piper, M. E., Breslau, N., Cannon, D. S., Doheny, K. F., … Bierut, L. J. (2012). Interplay of genetic risk factors (CHRNA5-CHRNA3-CHRNB4) and cessation treatments in smoking cessation success. American Journal of Psychiatry, 169(7), 735–742. doi:10.1176/appi.ajp.2012.11101545.

  • Clayton, D., & McKeigue, P. M. (2001). Epidemiological methods for studying genes and environmental factors in complex diseases. [Review]. Lancet, 358(9290), 1356–1360. doi:10.1016/s0140-6736(01)06418-2.

    CrossRef  PubMed  Google Scholar 

  • Colhoun, H. M., McKeigue, P. M., & Smith, G. D. (2003). Problems of reporting genetic associations with complex outcomes. [Review]. Lancet, 361(9360), 865–872. doi:10.1016/s0140-6736(03)12715-8.

    CrossRef  PubMed  Google Scholar 

  • Crawford, A. A., Lewis, G., Lewis, S. J., & Munafo, M. R. (2013). Systematic review and meta-analysis of serotonin transporter genotype and discontinuation from antidepressant treatment. [Review]. European Neuropsychopharmacology, 23(10), 1143–1150. doi:10.1016/j.euroneuro.2012.12.001.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • De Gonzalez, A. B., & Cox, D. R. (2007). Interpretation of interaction: A review. [Review]. Annals of Applied Statistics, 1(2), 371–385. doi:10.1214/07-aoas124.

    CrossRef  Google Scholar 

  • Dehghan, A., Dupuis, J., Barbalic, M., Bis, J. C., Eiriksdottir, G., Lu, C., … Chasman, D. I. (2011). Meta-analysis of genome-wide association studies in > 80 000 subjects identifies multiple loci for C-reactive protein levels. Circulation, 123(7), 731–U151. doi:10.1161/circulationaha.110.948570.

  • Dick, D. M. (2011). Gene–environment interaction in psychological traits and disorders. Annual Review of Clinical Psychology, 7, 383–409. doi:10.1146/annurev-clinpsy-032210-104518.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Dick, D. M., Viken, R., Purcell, S., Kaprio, J., Pulkkinen, L., & Rose, R. J. (2007). Parental monitoring moderates the importance of genetic and environmental influences on adolescent smoking. Journal of Abnormal Psychology, 116(1), 213–218.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Dick, D. M., Latendresse, S. J., Lansford, J. E., Budde, J. P., Goate, A., Dodge, K. A., … Bates, J. E. (2009). Role of GABRA2 in trajectories of externalizing behavior across development and evidence of moderation by parental monitoring. Archives of General Psychiatry, 66(6), 649–657.

    Google Scholar 

  • Dick, D. M., Meyers, J. L., Latendresse, S. J., Creemers, H. E., Lansford, J. E., Pettit, G. S., … Huizink, A. C. (2011). CHRM2, parental monitoring, and adolescent externalizing behavior: Evidence for gene–environment interaction. Psychological Science, 22(4), 481–489. doi:10.1177/0956797611403318.

  • Dudbridge, F., & Fletcher, O. (2014). Gene–environment dependence creates spurious gene–environment interaction. American Journal of Human Genetics, 95(3), 301–307. doi:10.1016/j.ajhg.2014.07.014.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Duncan, A. E., Scherrer, J., Fu, Q., Bucholz, K. K., Heath, A. C., True, W. R., … Jacob, T. (2006). Exposure to paternal alcoholism does not predict development of alcohol-use disorders in offspring: Evidence from an offspring-of-twins study. Journal of Studies on Alcohol, 67(5), 649–656.

    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. [Review]. American Journal of Psychiatry, 168(10), 1041–1049. doi:10.1176/appi.ajp.2011.11020191.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Duncan, L. E., Pollastri, A. R., & Smoller, J. W. (2014). Mind the gap why many geneticists and psychological scientists have discrepant views about gene–environment interaction (G×E) research. American Psychologist, 69(3), 249–268. doi:10.1037/a0036320.

    CrossRef  PubMed  Google Scholar 

  • Eaves, L., & Verhulst, B. (2014). Problems and pit-falls in testing for G × E and epistasis in candidate gene studies of human behavior. Behavior Genetics, 44(6), 578–590. doi:10.1007/s10519-014-9674-6.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Eaves, L. J. (2006). Genotype × environment interaction in psychopathology: Fact or artifact? Twin Research and Human Genetics, 9(1), 1–8. doi:10.1375/183242706776403073.

    CrossRef  PubMed  Google Scholar 

  • Feinberg, M. E., Button, T. M. M., Neiderhiser, J. M., Reiss, D., & Hetherington, E. M. (2007). Parenting and adolescent antisocial behavior and depression—Evidence of genotype × parenting environment interaction. Archives of General Psychiatry, 64(4), 457–465. doi:10.1001/archpsyc.64.4.457.

    CrossRef  PubMed  Google Scholar 

  • Fisher, R. A. (1918). The correlation between relatives on the supposition of Mendelian inheritance. Transactions of the Royal Society of Edinburgh, 52, 399–433.

    CrossRef  Google Scholar 

  • Fortier, I., Doiron, D., Little, J., Ferretti, V., L’Heureux, F., Stolk, R. P., … International Harmonization. (2011). Is rigorous retrospective harmonization possible? Application of the DataSHaPER approach across 53 large studies. International Journal of Epidemiology, 40(5), 1314–1328. doi:10.1093/ije/dyr106.

    Google Scholar 

  • Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., … Wellcome Trust Case Control Consortium. (2007). A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science, 316(5826), 889–894. doi:10.1126/science.1141634.

    Google Scholar 

  • van Gelder, M., Bretveld, R. W., & Roeleveld, N. (2010). Web-based Questionnaires: The future in epidemiology? American Journal of Epidemiology, 172(11), 1292–1298. doi:10.1093/aje/kwq291.

    CrossRef  PubMed  Google Scholar 

  • Gottesman, I. I., & Gould, T. D. (2003). The endophenotype concept in psychiatry: Etymology and strategic intentions. American Journal of Psychiatry, 160(4), 636–645.

    CrossRef  PubMed  Google Scholar 

  • Gottlieb, G. (1995). Some conceptual deficiencies in developmental behavior genetics. Human Development, 38(3), 131–141.

    CrossRef  Google Scholar 

  • Griffiths, P. E., & Tabery, J. (2008). Behavioral genetics and development: Historical and conceptual causes of controversy. [Review]. New Ideas in Psychology, 26(3), 332–352. doi:10.1016/j.newideapsych.2007.07.016.

    CrossRef  Google Scholar 

  • Hamilton, C. M., Strader, L. C., Pratt, J. G., Maiese, D., Hendershot, T., Kwok, R. K., … Haines, J. (2011). The PhenX toolkit: Get the most from your measures. American Journal of Epidemiology, 174(3), 253–260. doi:10.1093/aje/kwr193.

  • Hamilton, S. P. (2015). The promise of psychiatric pharmacogenomics. [Review]. Biological Psychiatry, 77(1), 29–35. doi:10.1016/j.biopsych.2014.09.009.

    CrossRef  PubMed  Google Scholar 

  • Harden, K. P., Hill, J. E., Turkheimer, E., & Emery, R. E. (2008). Gene–environment correlation and interaction in peer effects on adolescent alcohol and tobacco use. Behavior Genetics, 38(4), 339–347. doi:10.1007/s10519-008-9202-7.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Hein, R., Beckmann, L., & Chang-Claude, J. (2008). Sample size requirements for indirect association studies of gene–environment interactions (G × E). Genetic Epidemiology, 32(3), 235–245. doi:10.1002/gepi.20298.

    CrossRef  PubMed  Google Scholar 

  • Henderson, N. D. (1990). Why do gene–environment interactions appear more often in laboratory animal studies than in human behavioral genetic research? Behavioral and Brain Sciences, 13(1), 136–137.

    CrossRef  Google Scholar 

  • Hicks, B. M., South, S. C., DiRago, A. C., Iacono, W. G., & McGue, M. (2009). Environmental adversity and increasing genetic risk for externalizing disorders. Archives of General Psychiatry, 66(6), 640–648.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Hunter, D. J. (2005). Gene–environment interactions in human diseases. [Review]. Nature Reviews Genetics, 6(4), 287–298. doi:10.1038/nrg1578.

    CrossRef  PubMed  Google Scholar 

  • Hyde, L. W., Bogdan, R., & Hariri, A. R. (2011). Understanding risk for psychopathology through imaging gene–environment interactions. [Review]. Trends in Cognitive Sciences, 15(9), 417–427. doi:10.1016/j.tics.2011.07.001.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), 696–701. doi:10.1371/journal.pmed.0020124.

    CrossRef  Google Scholar 

  • Jordan, B. D., Relkin, N. R., Ravdin, L. D., Jacobs, A. R., Bennett, A., & Gandy, S. (1997). Apolipoprotein E epsilon4 associated with chronic traumatic brain injury in boxing [see comments]. JAMA, 278(2), 136–140.

    CrossRef  PubMed  Google Scholar 

  • Kaufman, J., Yang, B. Z., Douglas-Palumberi, H., Grasso, D., Lipschitz, D., Houshyar, S., … Gelernter, J. (2006). Brain-derived neurotrophic factor-5-HTTLPR gene interactions and environmental modifiers of depression in children. Biological Psychiatry, 59(8), 673–680. doi:10.1016/j.biopsych.2005.10.026.

  • Kilpeläinen, T. O., Qi, L., Brage, S., Sharp, S. J., Sonestedt, E., Demerath, E., … Loos, R. J. F. (2011). Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218,166 adults and 19,268 children. PLoS Medicine, 8(11), e1001116. doi:10.1371/journal.pmed.1001116.

  • Koopmans, J. R., Slutske, W. S., van Baal, G. C., & Boomsma, D. I. (1999). The influence of religion on alcohol use initiation: Evidence for genotype × environment interaction. Behavior Genetics, 29, 445–453.

    CrossRef  PubMed  Google Scholar 

  • Kottgen, A., Albrecht, E., Teumer, A., Vitart, V., Krumsiek, J., Hundertmark, C., … MAGIC Consortium. (2013). Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nature Genetics, 45(2), 145–154. doi:10.1038/ng.2500.

    Google Scholar 

  • Kutner, K. C., Erlanger, D. M., Tsai, J., Jordan, B., & Relkin, N. R. (2000). Lower cognitive performance of older football players possessing apolipoprotein E epsilon 4. Neurosurgery, 47(3), 651–657. doi:10.1097/00006123-200009000-00026.

    PubMed  Google Scholar 

  • Legrand, L. N., Keyes, M., McGue, M., Iacono, W. G., & Krueger, R. F. (2008). Rural environments reduce the genetic influence on adolescent substance use and rule-breaking behavior. Psychological Medicine, 38(9), 1341–1350. doi:10.1017/s0033291707001596.

    CrossRef  PubMed  Google Scholar 

  • Manolio, T. A., Chisholm, R. L., Ozenberger, B., Roden, D. M., Williams, M. S., Wilson, R., … Ginsburg, G. S. (2013). Implementing genomic medicine in the clinic: The future is here. [Review]. Genetics in Medicine, 15(4), 258–267. doi:10.1038/gim.2012.157.

  • Manuck, S. B., & McCaffery, J. M. (2014). Gene–environment interaction. [Review; Book Chapter]. Annual Review of Psychology, 65, 41–70. doi:10.1146/annurev-psych-010213-115100.

    CrossRef  PubMed  Google Scholar 

  • Marchini, J., & Howie, B. (2010). Genotype imputation for genome-wide association studies. [Review]. Nature Reviews Genetics, 11(7), 499–511. doi:10.1038/nrg2796.

    CrossRef  PubMed  Google Scholar 

  • Moffitt, T. E., Caspi, A., & Rutter, M. (2005). Strategy for investigating interactions between measured genes and measured environments. Archives of General Psychiatry, 62, 473–481.

    CrossRef  PubMed  Google Scholar 

  • Moffitt, T. E., Caspi, A., & Rutter, M. (2006). Measured gene–environment interactions in psychopathology concepts, research strategies, and implications for research, intervention, and public understanding of genetics. [Review]. Perspectives on Psychological Science, 1(1), 5–27. doi:10.1111/j.1745-6916.2006.00002.x.

    CrossRef  PubMed  Google Scholar 

  • Munafò, M. R., Brown, S. M., & Hariri, A. R. (2008). Serotonin transporter (5-HTTLPR) genotype and amygdala activation: A meta-analysis. Biological Psychiatry, 63(9), 852–857. doi:10.1016/j.biopsych.2007.08.016.

    CrossRef  PubMed  Google Scholar 

  • Munafò, M. R., Zammit, S., & Flint, J. (2014). Practitioner review: A critical perspective on geneenvironment interaction models—What impact should they have on clinical perceptions and practice? [Review]. Journal of Child Psychology and Psychiatry, 55(10), 1092–1101. doi:10.1111/jcpp.12261.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Murphy, S. E., Norbury, R., Godlewska, B. R., Cowen, P. J., Mannie, Z. M., Harmer, C. J., & Munafo, M. R. (2013). The effect of the serotonin transporter polymorphism (5-HTTLPR) on amygdala function: a meta-analysis. Molecular Psychiatry, 18(4), 512–520. doi:10.1038/mp.2012.19.

    CrossRef  PubMed  Google Scholar 

  • Offit, K. (2011). Personalized medicine: New genomics, old lessons. [Review]. Human Genetics, 130(1), 3–14. doi:10.1007/s00439-011-1028-3.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Olfson, E., & Bierut, L. J. (2012). Convergence of genome-wide association and candidate gene studies for alcoholism. Alcoholism: Clinical and Experimental Research, 36(12), 2086–2094. doi:10.1111/j.1530-0277.2012.01843.x.

    CrossRef  Google Scholar 

  • Park, J. H., Wacholder, S., Gail, M. H., Peters, U., Jacobs, K. B., Chanock, S. J., & Chatterjee, N. (2010). Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nature Genetics, 42(7), 570–U139. doi:10.1038/ng.610.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Perlis, R. H. (2014). Pharmacogenomic testing and personalized treatment of depression. [Review]. Clinical Chemistry, 60(1), 53–59. doi:10.1373/clinchem.2013.204446.

    CrossRef  PubMed  Google Scholar 

  • Purcell, S. (2002). Variance components models for gene–environment interaction in twin analysis. Twin Research, 6, 554–571.

    CrossRef  Google Scholar 

  • Ragoussis, J. (2009). Genotyping technologies for genetic research. Annual review of genomics and human genetics (Vol. 10, pp. 117–133). Palo Alto, CA: Annual Reviews.

    Google Scholar 

  • Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., … LifeLines Cohort Study. (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science, 340(6139), 1467–1471. doi:10.1126/science.1235488.

    Google Scholar 

  • Rose, R. J., Dick, D. M., Viken, R. J., & Kaprio, J. (2001). Gene–environment interaction in patterns of adolescent drinking: Regional residency moderates longitudinal influences on alcohol use. Alcoholism: Clinical and Experimental Research, 25(5), 637–643.

    CrossRef  Google Scholar 

  • Rutter, M. (2014). Commentary: G × E in child psychiatry and psychology: a broadening of the scope of enquiry as prompted by Munafo et al. (2014). [Editorial Material]. Journal of Child Psychology and Psychiatry, 55(10), 1102–1104. doi:10.1111/jcpp.12309.

    CrossRef  PubMed  Google Scholar 

  • Rutter, M., & Silberg, J. (2002). Gene–environmental interplay in relation to emotional and behavioral disturbance. Annual Review of Psychology, 53, 463–490.

    CrossRef  PubMed  Google Scholar 

  • Salvatore, J. E., Aliev, F., Edwards, A. C., Evans, D. M., Macleod, J., Hickman, M., … Dick, D. M. (2014). Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment. [Meeting Abstract]. Genes, 5, 330–346.

    Google Scholar 

  • Sameroff, A. J., Seifer, R., & Bartko, W. T. (1997). Environmental perspectives on adaptation during childhood and adolescence. In S. S. Luthar, J. A. Brrack, D. Cicchetti, & J. R. Weisz (Eds.), Developmental psychopathology: Perspectives on adjustment, risk and disorder (pp. 507–526). Cambridge, England: Cambridge University Press.

    Google Scholar 

  • Shanahan, M. J., & Hofer, S. M. (2005). Social context in gene–environment interactions: Retrospect and prospect. Journal of Gerontology, 60B, 65–76.

    CrossRef  Google Scholar 

  • Sheese, B. E., Voelker, P. M., Rothbart, M. K., & Posner, M. I. (2007). Parenting quality interacts with genetic variation in dopamine receptor D4 to influence temperament in early childhood. Development and Psychopathology, 19(4), 1039–1046. doi:10.1017/s0954579407000521.

    CrossRef  PubMed  Google Scholar 

  • Siontis, K. C. M., Patsopoulos, N. A., & Ioannidis, J. P. A. (2010). Replication of past candidate loci for common diseases and phenotypes in 100 genome-wide association studies. European Journal of Human Genetics, 18(7), 832–837. doi:10.1038/ejhg.2010.26.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Smith, P. G., & Day, N. E. (1984). The design of case-control studies: The influence of confounding and interactions. International Journal of Epidemiology, 13(3), 356–365. doi:10.1093/ije/13.3.356.

    CrossRef  PubMed  Google Scholar 

  • Speliotes, E. K., Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., … MAGIC. (2010). Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature Genetics, 42(11), 937–948. doi:10.1038/ng.686

    Google Scholar 

  • Sullivan, P. F. (2007). Spurious genetic associations. Biological Psychiatry, 61(10), 1121–1126. doi:10.1016/j.biopsych.2006.11.010.

    CrossRef  PubMed  Google Scholar 

  • Sullivan, P. F. (2010). The Psychiatric GWAS Consortium: Big science comes to psychiatry. [Editorial Material]. Neuron, 68(2), 182–186. doi:10.1016/j.neuron.2010.10.003.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Tabery, J. (2008). R. A. Fisher, Lancelot Hogben, and the origin(s) of genotype–environment interaction. Journal of the History of Biology, 41(4), 717–761. doi:10.1007/s10739-008-9155-y.

    CrossRef  PubMed  Google Scholar 

  • Tabery, J. (2014). Beyond versus: The struggle to understand the interaction of nature and nurture. Cambridge: MIT Press.

    CrossRef  Google Scholar 

  • Teasdale, G. M., Nicoll, J. A. R., Murray, G., & Fiddes, M. (1997). Association of apolipoprotein E polymorphism with outcome after head injury. [Article]. Lancet, 350(9084), 1069–1071. doi:10.1016/s0140-6736(97)04318-3.

    CrossRef  PubMed  Google Scholar 

  • Thomas, D. C., Lewinger, J. P., Murcray, C. E., & Gauderman, W. J. (2012). Invited Commentary: GE-Whiz! Ratcheting gene–environment studies up to the whole genome and the whole exposome. [Editorial Material]. American Journal of Epidemiology, 175(3), 203–207. doi:10.1093/aje/kwr365.

    CrossRef  PubMed  Google Scholar 

  • Thompson, P. M., Stein, J. L., Medland, S. E., Hibar, D. P., Vasquez, A. A., Renteria, M. E., … Saguenay Youth Study Group. (2014). The ENIGMA Consortium: Large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging and Behavior, 8(2), 153–182. doi:10.1007/s11682-013-9269-5.

    Google Scholar 

  • Thompson, W. D. (1991). Effect modification and the limits of biological inference from epidemiological data. [Editorial Material]. Journal of Clinical Epidemiology, 44(3), 221–232. doi:10.1016/0895-4356(91)90033-6.

    CrossRef  PubMed  Google Scholar 

  • Turkheimer, E. (2000). Three laws of behavior genetics and what they mean. Current Directions in Psychological Science, 9, 160–164.

    CrossRef  Google Scholar 

  • Turkheimer, E., Haley, A., Waldron, M., D’Onofrio, B., & Gottesman, I. I. (2003). Socioeconomic status modifies heritability of IQ in young children. Psychological Science, 14, 623–628.

    CrossRef  PubMed  Google Scholar 

  • Uher, R., GENDEP Investigators, MARS Investigators, & STAR*D Investigators. (2013). Common genetic variation and antidepressant efficacy in major depressive disorder: A meta-analysis of three genome-wide pharmacogenetic studies. American Journal of Psychiatry, 170(2), 207–217. doi:10.1176/appi.ajp.2012.12020237.

    Google Scholar 

  • Visscher, P. M., Hill, W. G., & Wray, N. R. (2008). Heritability in the genomics era—Concepts and misconceptions. [Review]. Nature Reviews Genetics, 9(4), 255–266. doi:10.1038/nrg2322.

    CrossRef  PubMed  Google Scholar 

  • Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J. (2012). Five years of GWAS discovery. [Review]. American Journal of Human Genetics, 90(1), 7–24. doi:10.1016/j.ajhg.2011.11.029.

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Wahlsten, D. (1990). Insensitivity of the analysis of variance to heredity–environment interaction. Behavioral and Brain Sciences, 13(1), 109–120.

    CrossRef  Google Scholar 

  • Willer, C. J., Schmidt, E. M., Sengupta, S., Peloso, G. M., Gustafsson, S., Kanoni, S., … Global Lipids Genetics Consortium. (2013). Discovery and refinement of loci associated with lipid levels. Nature Genetics, 45(11), 1274–1283. doi:10.1038/ng.2797.

    Google Scholar 

  • Winham, S. J., & Biernacka, J. M. (2013). Gene–environment interactions in genome-wide association studies: Current approaches and new directions. Journal of Child Psychology and Psychiatry, 54(10), 1120–1134. doi:10.1111/jcpp.12114.

    CrossRef  PubMed  Google Scholar 

  • Wong, M. Y., Day, N. E., Luan, J. A., Chan, K. P., & Wareham, N. J. (2003). The detection of gene–environment interaction for continuous traits: Should we deal with measurement error by bigger studies or better measurement? International Journal of Epidemiology, 32(1), 51–57. doi:10.1093/ije/dyg002.

    CrossRef  PubMed  Google Scholar 

  • Wood, A. R., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., … LifeLines Cohort Study. (2014). Defining the role of common variation in the genomic and biological architecture of adult human height. Nature Genetics, 46(11), 1173–1186. doi:10.1038/ng.3097.

    Google Scholar 

  • Zhu, J. W., Loos, R. J. F., Lu, L., Zong, G., Gan, W., Ye, X. W., … Lin, X. (2014). Associations of genetic risk score with obesity and related traits and the modifying effect of physical activity in a Chinese Han population. PLoS One, 9(3), e91442. doi:10.1371/journal.pone.0091442.

  • Zondervan, K. T., & Cardon, L. R. (2004). The complex interplay among factors that influence allelic association. Nature Reviews Genetics, 5, 89–100.

    CrossRef  PubMed  Google Scholar 

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McGue, M., Carey, B.E. (2017). Gene–Environment Interaction in the Behavioral Sciences: Findings, Challenges, and Prospects. In: Tolan, P., Leventhal, B. (eds) Gene-Environment Transactions in Developmental Psychopathology. Advances in Development and Psychopathology: Brain Research Foundation Symposium Series, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-49227-8_3

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