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Commentary for Special Issue of Prevention Science “Using Genetics in Prevention: Science Fiction or Science Fact?”

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Abstract

A growing number of prevention studies have incorporated genetic information. In this commentary, I discuss likely reasons for growing interest in this line of research and reflect on the current state of the literature. I review challenges associated with the incorporation of genotypic information into prevention studies, as well as ethical considerations associated with this line of research. I discuss areas where developmental psychologists and prevention scientists can make substantive contributions to the study of genetic predispositions, as well as areas that could benefit from closer collaborations between prevention scientists and geneticists to advance this area of study. In short, this commentary tackles the complex questions associated with what we hope to achieve by adding genetic components to prevention research and where this research is likely to lead in the future.

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Notes

  1. This technique is called LD-tagging.

References

  • Albert, D., Belsky, D. W., Crowley, D. M., Latendresse, S. J., Aliev, F., Riley, B., et al. (2015). Can genetics predict response to complex behavioral interventions? Evidence from a genetic analysis of the fast track randomized control trial. Journal of Policy Analysis and Management, 34, 497–518.

    Article  PubMed  PubMed Central  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. doi:10.1017/s0954579410000635.

    Article  PubMed  Google Scholar 

  • Bakermans-Kranenburg, M. J., Van, I. M. H., Pijlman, F. T., Mesman, J., & Juffer, F. (2008). Experimental evidence for differential susceptibility: Dopamine D4 receptor polymorphism (DRD4 VNTR) moderates intervention effects on toddlers' externalizing behavior in a randomized controlled trial. Developmental Psychology, 44, 293–300. doi:10.1037/0012-1649.44.1.293.

    Article  PubMed  Google Scholar 

  • Bates, J. E., Pettit, G. S., Dodge, K. A., & Ridge, B. (1998). Interaction of temperamental resistance to control and restrictive parenting in the development of externalizing behavior. Developmental Psychology, 34, 982–995.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Beach, S. R. H., Lei, M. K., Brody, G. H., & Philibert, R. A. (2016). Prevention of early substance use mediates, and variation at SLC6A4 moderates, SAAF intervention effects on OXTR methylation. Prevention Science, 1–11. doi:10.1007/s11121-016-0709-5.

  • Belsky, J. (1997). Theory testing, effect-size evaluation, and differential susceptibility to rearing influence: The case of mothering and attachment. Child Development, 68, 598–600.

    Article  CAS  PubMed  Google Scholar 

  • Belsky, J., Bakermans-Kranenburg, M. J., & Van IJzendoorn, M. H. (2007). For better and for worse: Differential susceptibility to environmental influences. Current Directions in Psychological Science, 16, 300–304.

    Article  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. doi:10.1038/mp.2009.44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brody, G. H., Beach, S. R., Philibert, R. A., Chen, Y. F., & Murry, V. M. (2009a). Prevention effects moderate the association of 5-HTTLPR and youth risk behavior initiation: Gene x environment hypotheses tested via a randomized prevention design. Child Development, 80, 645–661. doi:10.1111/j.1467-8624.2009.01288.x.

    Article  PubMed  Google Scholar 

  • Brody, G. H., Chen, Y. F., Beach, S. R., Philibert, R. A., & Kogan, S. M. (2009b). Participation in a family-centered prevention program decreases genetic risk for adolescents’ risky behaviors. Pediatrics, 124, 911–917. doi:10.1542/peds.2008-3464.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brody, G. H., Beach, S. R., 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.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brody, G. H., Chen, Y. F., Beach, S. R., Kogan, S. M., Yu, T., Diclemente, R. J., et al. (2014). Differential sensitivity to prevention programming: A dopaminergic polymorphism-enhanced prevention effect on protective parenting and adolescent substance use. Health Psychology, 33, 182–191. doi:10.1037/a0031253.

    Article  PubMed  Google Scholar 

  • Bronfenbrenner, U. (1994). Ecological models of human development. Readings on the development of children, 2, 37–43.

    Google Scholar 

  • Bujak, R., Struck-Lewicka, W., Markuszewski, M. J., & Kaliszan, R. (2015). Metabolomics for laboratory diagnostics. Journal of Pharmaceutical and Biomedical Analysis, 113, 108–120. doi:10.1016/j.jpba.2014.12.017.

    Article  CAS  PubMed  Google Scholar 

  • Burke, W., & Psaty, B. M. (2007). Personalized medicine in the era of genomics. JAMA, 298, 1682–1684. doi:10.1001/jama.298.14.1682.

    Article  CAS  PubMed  Google Scholar 

  • Carlson, C. S., Eberle, M. A., Rieder, M. J., Yi, Q., Kruglyak, L., & Nickerson, D. A. (2004). Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. American Journal of Human Genetics, 74, 106–120. doi:10.1086/381000.

    Article  CAS  PubMed  Google Scholar 

  • Caspi, A., McClay, J., Moffitt, T. E., Mill, J., Martin, J., Craig, I. W., et al. (2002). Role of genotype in the cycle of violence in maltreated children. Science, 297, 851–854. doi:10.1126/science.1072290.

    Article  CAS  PubMed  Google Scholar 

  • Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., et al. (2003). Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science, 301, 386–389. doi:10.1126/science.1083968.

    Article  CAS  PubMed  Google Scholar 

  • Christenhusz, G. M., Devriendt, K., & Dierickx, K. (2013). To tell or not to tell? A systematic review of ethical reflections on incidental findings arising in genetics contexts. European Journal of Human Genetics, 21, 248–255. doi:10.1038/ejhg.2012.130.

    Article  PubMed  Google Scholar 

  • Cleveland, H. H., Griffin, A. M., Wolf, P. S., Wiebe, R. P., Schlomer, G. L., Feinberg, M. E., et al. (2017). Transactions between substance use intervention, the oxytocin receptor (OXTR) gene, and peer substance use predicting youth alcohol use. Prevention Science. doi:10.1007/s11121-017-0749-5.

  • Collins, F. S., & Varmus, H. (2015). A new initiative on precision medicine. The New England Journal of Medicine, 372, 793–795. doi:10.1056/NEJMp1500523.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dick, D. M., Li, T. K., Edenberg, H. J., Hesselbrock, V., Kramer, J., Kuperman, S., et al. (2004). A genome-wide screen for genes influencing conduct disorder. Molecular Psychiatry, 9, 81–86. doi:10.1038/sj.mp.4001368.

    Article  CAS  PubMed  Google Scholar 

  • Dick, D. M., Viken, R. J., Kaprio, J., Pulkkinen, L., & Rose, R. J. (2005). Understanding the covariation among childhood externalizing symptoms: Genetic and environmental influences on conduct disorder, attention deficit hyperactivity disorder, and oppositional defiant disorder symptoms. Journal of Abnormal Child Psychology, 33, 219–229. doi:10.1007/s10802-005-1829-8.

    Article  PubMed  Google Scholar 

  • Dick, D. M., Bierut, L., Hinrichs, A., Fox, L., Bucholz, K. K., Kramer, J., et al. (2006). The role of GABRA2 in risk for conduct disorder and alcohol and drug dependence across developmental stages. Behavior Genetics, 36, 577–590. doi:10.1007/s10519-005-9041-8.

    Article  PubMed  Google Scholar 

  • Dick, D. M., Pagan, J. L., Viken, R., Purcell, S., Kaprio, J., Pulkkinen, L., & Rose, R. J. (2007). Changing environmental influences on substance use across development. Twin Research and Human Genetics, 10, 315–326. doi:10.1375/twin.10.2.315.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dick, D. M., Aliev, F., Wang, J. C., Saccone, S., Hinrichs, A., Bertelsen, S., et al. (2008). A systematic single nucleotide polymorphism screen to fine-map alcohol dependence genes on chromosome 7 identifies association with a novel susceptibility gene ACN9. Biological Psychiatry, 63, 1047–1053. doi:10.1016/j.biopsych.2007.11.005.

    Article  CAS  PubMed  Google Scholar 

  • Dick, D. M., Riley, B., & Latendresse, S. (2011). Incorporating genetics into your studies: A guide for social scientists. Frontiers in Psychiatry, 2(17). doi:10.3389/fpsyt.2011.00017.

  • Dick, D. M., Barr, P., Cho, S.B., Cooke, M., Kuo, S., Lewis, T., Neale, Z., Salvatore, J., Savage, J., Su, J. (2017). Post-GWAS in psychiatric genetics: A developmental perspective on the “other” next steps. Under review.

    Google Scholar 

  • Dishion, T. J., Brennan, L. M., Shaw, D. S., McEachern, A. D., Wilson, M. N., & Jo, B. (2014). Prevention of problem behavior through annual family check-ups in early childhood: Intervention effects from home to early elementary school. Journal of Abnormal Child Psychology, 42, 343–354. doi:10.1007/s10802-013-9768-2.

    Article  PubMed  PubMed Central  Google Scholar 

  • Farrell, M. S., Werge, T., Sklar, P., Owen, M. J., Ophoff, R. A., O’Donovan, M. C., et al. (2015). Evaluating historical candidate genes for schizophrenia. Molecular Psychiatry, 20, 555–562. doi:10.1038/mp.2015.16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Feero, W. G., & Guttmacher, A. E. (2014). Genomics, personalized medicine, and pediatrics. Academic Pediatrics, 14, 14–22. doi:10.1016/j.acap.2013.06.008.

    Article  PubMed  PubMed Central  Google Scholar 

  • Friedman, N., & Rando, O. J. (2015). Epigenomics and the structure of the living genome. Genome Research, 25, 1482–1490. doi:10.1101/gr.190165.115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Glenn, A. L., Lochman, J. E., Dishion, T., Powell, N. P., Boxmeyer, C., & Qu, L. (2017). Oxytocin receptor gene variant interacts with intervention delivery format in predicting intervention outcomes for youth with conduct problems. Prevention Science. doi:10.1007/s11121-017-0777-1.

  • Green, R. C., Berg, J. S., Grody, W. W., Kalia, S. S., Korf, B. R., Martin, C. L., et al. (2013). ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genetics in Medicine, 15, 565–574. doi:10.1038/gim.2013.73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Guo, G., Wilhelmsen, K., & Hamilton, N. (2007). Gene–lifecourse interaction for alcohol consumption in adolescence and young adulthood: Five monoamine genes. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 144, 417–423.

    Article  Google Scholar 

  • Guttmacher, A. E., & Collins, F. S. (2003). Welcome to the genomic era. The New England Journal of Medicine, 349, 996–998. doi:10.1056/NEJMe038132.

    Article  CAS  PubMed  Google Scholar 

  • Guttmacher, A. E., Porteous, M. E., & McInerney, J. D. (2007). Educating health-care professionals about genetics and genomics. Nature Reviews. Genetics, 8, 151–157. doi:10.1038/nrg2007.

    Article  CAS  PubMed  Google Scholar 

  • Hendrickson, B. C., Donohoe, C., Akmaev, V. R., Sugarman, E. A., Labrousse, P., Boguslavskiy, L., et al. (2009). Differences in SMN1 allele frequencies among ethnic groups within North America. Journal of Medical Genetics, 46, 641–644. doi:10.1136/jmg.2009.066969.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hettema, J. M., Neale, M. C., & Kendler, K. S. (2001). A review and meta-analysis of the genetic epidemiology of anxiety disorders. The American Journal of Psychiatry, 158, 1568–1578. doi:10.1176/appi.ajp.158.10.1568.

    Article  CAS  PubMed  Google Scholar 

  • Humphery-Smith, I. (2015). The 20th anniversary of proteomics and some of its origins. Proteomics, 15, 1773–1776. doi:10.1002/pmic.201400582.

    Article  CAS  PubMed  Google Scholar 

  • Irons, D. E., Iacono, W. G., Oetting, W. S., & McGue, M. (2012). Developmental trajectory and environmental moderation of the effect of ALDH2 polymorphism on alcohol use. Alcoholism, Clinical and Experimental Research, 36, 1882–1891. doi:10.1111/j.1530-0277.2012.01809.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kessler, R. C., Crum, R. M., Warner, L. A., Nelson, C. B., Schulenberg, J., & Anthony, J. C. (1997). Lifetime co-occurrence of DSM-III-R alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Archives of General Psychiatry, 54, 313–321.

    Article  CAS  PubMed  Google Scholar 

  • Latendresse, S. J., Musci, R., & Maher, B. S. (2017). Critical issues in the inclusion of genetic and epigenetic information in prevention and intervention trials. Prevention Science. doi:10.1007/s11121-017-0785-1.

  • Leve, L. D., Neiderhiser, J. M., Harold, G. T., Natsuaki, M. N., Bohannan, B. J., & Cresko, W. A. (2017). Naturalistic experimental designs as tools for understanding the role of genes and the environment in prevention research. Prevention Science. doi:10.1007/s11121-017-0746-8.

  • Li, J. J., Cho, S. B., Salvatore, J. E., Edenberg, H. J., Agrawal, A., Chorlian, D. B., et al. (2017). The impact of peer substance use and polygenic risk on trajectories of heavy episodic drinking across adolescence and emerging adulthood. Alcoholism, Clinical and Experimental Research, 41, 65–75. doi:10.1111/acer.13282.

    Article  CAS  PubMed  Google Scholar 

  • Maher, B. S., Latendresse, S., & Vanyukov, M. M. (2016). Informing prevention and intervention policy using genetic studies of resistance. Prevention Science, 1–9. doi:10.1007/s11121-016-0730-8.

  • McCarthy, S., Das, S., Kretzschmar, W., Delaneau, O., Wood, A. R., Teumer, A., et al., the Haplotype Reference. (2016). A reference panel of 64,976 haplotypes for genotype imputation. Nature Genetics, 48, 1279–1283. doi:10.1038/ng.3643.

  • McDonald, D., Birmingham, A., & Knight, R. (2015). Context and the human microbiome. Microbiome, 3, 52. doi:10.1186/s40168-015-0117-2.

    Article  PubMed  PubMed Central  Google Scholar 

  • Musci, R. J., Fairman, B., Masyn, K. E., Uhl, G., Maher, B., Sisto, D. Y., et al. (2016). Polygenic score × intervention moderation: An application of discrete-time survival analysis to model the timing of first marijuana use among urban youth. Prevention Science, 1–9. doi:10.1007/s11121-016-0729-1.

  • O’Donovan, M. C. (2015). What have we learned from the Psychiatric Genomics Consortium. World Psychiatry, 14, 291–293. doi:10.1002/wps.20270.

    Article  PubMed  PubMed Central  Google Scholar 

  • Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., et al. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, 533, 539–542. doi:10.1038/nature17671.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pappa, I., St Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M. G., et al. (2016). A genome-wide approach to children’s aggressive behavior: The EAGLE consortium. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 171, 562–572.

    Article  CAS  Google Scholar 

  • Ripke, S., Wray, N. R., Lewis, C. M., Hamilton, S. P., Weissman, M. M., Breen, G., et al. (2013). A mega-analysis of genome-wide association studies for major depressive disorder. Molecular Psychiatry, 18, 497–511. doi:10.1038/mp.2012.21.

    Article  CAS  PubMed  Google Scholar 

  • Russell, M. A., Schlomer, G. L., Cleveland, H. H., Feinberg, M. E., Greenberg, M. T., Spoth, R. L., et al. (2017). PROSPER intervention effects on adolescents' alcohol misuse vary by GABRA2 genotype and age. Prevention Science. doi:10.1007/s11121-017-0751-y.

  • Salvatore, J. E., Aliev, F., Edwards, A. C., Evans, D. M., Macleod, J., Hickman, M., et al. (2014). Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment. Genes (Basel), 5, 330–346. doi:10.3390/genes5020330.

    Article  Google Scholar 

  • Salvatore, J. E., Aliev, F., Bucholz, K., Agrawal, A., Hesselbrock, V., Hesselbrock, M., et al. (2015). Polygenic risk for externalizing disorders: Gene-by-development and gene-by-environment effects in adolescents and young adults. Clinical Psychological Science: A Journal of the Association for Psychological Science, 3, 189–201. doi:10.1177/2167702614534211.

    Article  Google Scholar 

  • Schizophrenia Working Group of the Psychiatric Genomics Consortium. (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511, 421–427. doi:10.1038/nature13595.

    Article  PubMed Central  Google Scholar 

  • Schlaepfer, I. R., Hoft, N. R., Collins, A. C., Corley, R. P., Hewitt, J. K., Hopfer, C. J., et al. (2008). The CHRNA5/A3/B4 gene cluster variability as an important determinant of early alcohol and tobacco initiation in young adults. Biological Psychiatry, 63, 1039–1046. doi:10.1016/j.biopsych.2007.10.024.

    Article  CAS  PubMed  Google Scholar 

  • The Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium. (2011). Genome-wide association study identifies five new schizophrenia loci. Nature Genetics., 43, 969–976. doi:10.1038/ng.940.

    Article  Google Scholar 

  • Turley, P., Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., . . . Benjamin, D. J. (2017). MTAG: Multi-trait analysis of GWAS. bioRxiv.

  • Walsh, C. G., Ribeiro, J. D., & Franklin, J. C. (2017). Predicting risk of suicide attempts over time through machine learning. Clinical Psychological Science, 5, 457–469.

    Article  Google Scholar 

  • Webb, B. T., Edwards, A. C., Wolen, A. R., Salvatore, J. E., Aliev, F., Riley, B. P., et al. (2017). Molecular genetic influences on normative and problematic alcohol use in a population-based sample of college students. Frontiers in Genetics, 8. doi:10.3389/fgene.2017.00030.

  • Wolf, S. M., Lawrenz, F. P., Nelson, C. A., Kahn, J. P., Cho, M. K., Clayton, E. W., et al. (2008). Managing incidental findings in human subjects research: Analysis and recommendations. The Journal of Law, Medicine & Ethics, 36, 219–248, 211. doi:10.1111/j.1748-720X.2008.00266.x.

    Article  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zheng, Y., Albert, D., McMahon, R. J., Dodge, K., & Dick, D. (2016). Glucocorticoid receptor (NR3C1) gene polymorphism moderate intervention effects on the developmental trajectory of African-American adolescent alcohol abuse. Prevention Science, 1–11. doi:10.1007/s11121-016-0726-4.

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  1. Departments of Psychology and Human & Molecular Genetics, College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Box 842018, Richmond, VA, 23284-2018, USA

    Danielle M. Dick

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Dr. Danielle M. Dick is supported by grants R01 AA015416; K02 AA018755; P50 AA0022537; R37 AA011408; and U10 AA008401 from the National Institutes of Health (NIH)/National Institute on Alcohol Abuse and Alcoholism (NIAAA), as well as the BTtoP Category II Research Grant from the Bringing Theory to Practice (BTtoP) Project.

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Dick, D.M. Commentary for Special Issue of Prevention Science “Using Genetics in Prevention: Science Fiction or Science Fact?”. Prev Sci 19, 101–108 (2018). https://doi.org/10.1007/s11121-017-0828-7

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