1932

Abstract

Behavior genetics studies how genetic differences among people contribute to differences in their psychology and behavior. Here, I describe how the conclusions and methods of behavior genetics have evolved in the postgenomic era in which the human genome can be directly measured. First, I revisit the first law of behavioral genetics stating that everything is heritable, and I describe results from large-scale meta-analyses of twin data and new methods for estimating heritability using measured DNA. Second, I describe new methods in statistical genetics, including genome-wide association studies and polygenic score analyses. Third, I describe the next generation of work on gene × environment interaction, with a particular focus on how genetic influences vary across sociopolitical contexts and exogenous environments. Genomic technology has ushered in a golden age of new tools to address enduring questions about how genes and environments combine to create unique human lives.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-psych-052220-103822
2021-01-04
2024-06-21
Loading full text...

Full text loading...

/deliver/fulltext/psych/72/1/annurev-psych-052220-103822.html?itemId=/content/journals/10.1146/annurev-psych-052220-103822&mimeType=html&fmt=ahah

Literature Cited

  1. Bakermans-Kranenburg MJ, van IJzendoorn MH 2015. The hidden efficacy of interventions: gene × environment experiments from a differential susceptibility perspective. Annu. Rev. Psychol. 66:381–409
    [Google Scholar]
  2. Barcellos SH, Carvalho LS, Turley P 2018. Education can reduce health differences related to genetic risk of obesity. PNAS 115:42E9765–72
    [Google Scholar]
  3. Barr PB, Dick DM. 2019. The genetics of externalizing problems. Curr. Top. Behav. Neurosci In press. https://doi.org/10.1007/7854_2019_120
    [Crossref] [Google Scholar]
  4. Belsky DW, Domingue BW, Wedow R, Arseneault L, Boardman JD et al. 2018. Genetic analysis of social-class mobility in five longitudinal studies. PNAS 115:31E7275–84
    [Google Scholar]
  5. Benjamin DJ, Cesarini D, Chabris CF, Glaeser EL, Laibson DI et al. 2012. The promises and pitfalls of genoeconomics. Annu. Rev. Econ. 4:62762
    [Google Scholar]
  6. Bierbach D, Laskowski KL, Wolf M 2017. Behavioural individuality in clonal fish arises despite near-identical rearing conditions. Nat. Commun. 8:15361
    [Google Scholar]
  7. Border R, Johnson EC, Evans LM, Smolen A, Berley N et al. 2019. No support for historical candidate gene or candidate gene-by-interaction hypotheses for major depression across multiple large samples. Am. J. Psychiatry 176:5376–87
    [Google Scholar]
  8. Branigan AR, McCallum KJ, Freese J 2013. Variation in the heritability of educational attainment: an international meta-analysis. Soc. Forces 92:1109–40
    [Google Scholar]
  9. Briley DA, Tucker-Drob EM. 2017. Comparing the developmental genetics of cognition and personality over the life span. J. Personal. 85:151–64
    [Google Scholar]
  10. Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J et al. 2019. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res 47:D1D1005–12
    [Google Scholar]
  11. Burt SA, Plaisance KS, Hambrick DZ 2019. Understanding “what could be”: a call for “experimental behavioral genetics. .” Behav. Genet. 49:2235–43
    [Google Scholar]
  12. Case A, Deaton A. 2017. Mortality and morbidity in the 21st century. Brook. Pap. Econ. Act. 2017:1397–476
    [Google Scholar]
  13. Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW et al. 2003. Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301:5631386–89
    [Google Scholar]
  14. Ceci SJ, Papierno PB. 2005. The rhetoric and reality of gap closing: when the “have-nots” gain but the “haves” gain even more. Am. Psychol. 60:2149–60
    [Google Scholar]
  15. Chabris CF, Hebert BM, Benjamin DJ, Beauchamp J, Cesarini D et al. 2012. Most reported genetic associations with general intelligence are probably false positives. Psychol. Sci. 23:111314–23
    [Google Scholar]
  16. Chabris CF, Lee JJ, Cesarini D, Benjamin DJ, Laibson DI 2015. The fourth law of behavior genetics. Curr. Dir. Psychol. Sci. 24:4304–12
    [Google Scholar]
  17. Charney E. 2012. Behavior genetics and postgenomics. Behav. Brain Sci. 35:5331–58
    [Google Scholar]
  18. Cheesman R, Hunjan A, Coleman JRI, Ahmadzadeh Y, Plomin R et al. 2019. Comparison of adopted and non-adopted individuals reveals gene–environment interplay for education in the UK Biobank. bioRxiv 707695. https://doi.org/10.1101/707695
    [Crossref]
  19. Columbia Law Sch 2017. Faculty statement on Charles Murray Lecture. Columbia Law School March 20. https://web.law.columbia.edu/open-university-project/academic-freedom/faculty-murray-statement
    [Google Scholar]
  20. Conley D, Rauscher E, Dawes C, Magnusson PKE, Siegal ML 2013. Heritability and the equal environments assumption: evidence from multiple samples of misclassified twins. Behav. Genet. 43:5415–26
    [Google Scholar]
  21. Cooke ME, Meyers JL, Latvala A, Korhonen T, Rose RJ et al. 2015. Gene–environment interaction effects of peer deviance, parental knowledge and stressful life events on adolescent alcohol use. Twin Res. Hum. Genet. 18:5507–17
    [Google Scholar]
  22. Dar-Nimrod I, Heine SJ. 2011. Genetic essentialism: on the deceptive determinism of DNA. Psychol. Bull. 137:5800–18
    [Google Scholar]
  23. Deaton A. 2013. The Great Escape: Health, Wealth, and the Origins of Inequality Princeton, NJ: Princeton Univ. Press
    [Google Scholar]
  24. Dennett DC. 2015. Elbow Room: The Varieties of Free Will Worth Wanting Cambridge, MA: MIT Press. , 2nd. ed.
    [Google Scholar]
  25. Dick DM, Rose R, Viken R, Kaprio J, Koskenvuo M 2001. Exploring gene–environment interactions: socioregional moderation of alcohol use. J. Abnorm. Psychol. 110:4625–32
    [Google Scholar]
  26. Dick DM, Viken R, Purcell S, Kaprio J, Pulkkinen L, Rose RJ 2007. Parental monitoring moderates the importance of genetic and environmental influences on adolescent smoking. J. Abnorm. Psychol. 116:1213–18
    [Google Scholar]
  27. Dishion TJ, Kavanagh K. 2003. Intervening in Adolescent Problem Behavior: A Family-Centered Approach New York: Guilford
    [Google Scholar]
  28. Dobzhansky T. 1962. Genetics and equality: equality of opportunity makes the genetic diversity among men meaningful. Science 137:3524112–15
    [Google Scholar]
  29. Dudbridge F. 2013. Power and predictive accuracy of polygenic risk scores. PLOS Genet 9:3e1003348
    [Google Scholar]
  30. Duncan LE, Keller MC. 2011. A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. Am. J. Psychiatry 168:101041–49
    [Google Scholar]
  31. Duncan LE, Pollastri AR, Smoller JW 2014. Mind the gap: why many geneticists and psychological scientists have discrepant views about gene–environment interaction (G×E) research. Am. Psychol. 69:3249–68
    [Google Scholar]
  32. Duncan LE, Shen H, Gelaye B, Meijsen J, Ressler K et al. 2019. Analysis of polygenic risk score usage and performance in diverse human populations. Nat. Commun. 10:3328
    [Google Scholar]
  33. Engelhardt LE, Briley DA, Mann FD, Harden KP, Tucker-Drob EM 2015. Genes unite executive functions in childhood. Psychol. Sci. 26:81151–63
    [Google Scholar]
  34. Engelhardt LE, Church JA, Harden KP, Tucker‐Drob EM 2019. Accounting for the shared environment in cognitive abilities and academic achievement with measured socioecological contexts. Dev. Sci. 22:1e12699
    [Google Scholar]
  35. Engelhardt LE, Mann FD, Briley DA, Church JA, Harden KP, Tucker-Drob EM 2016. Strong genetic overlap between executive functions and intelligence. J. Exp. Psychol. Gen. 145:91141–59
    [Google Scholar]
  36. Engzell P, Tropf FC. 2019. Heritability of education rises with intergenerational mobility. PNAS 116:5125386–88
    [Google Scholar]
  37. Fisher RA. 1919. The correlation between relatives on the supposition of Mendelian inheritance. Earth Environ. Sci. Trans. R. Soc. Edinb. 52:2399–433
    [Google Scholar]
  38. Fletcher JM, Conley D. 2013. The challenge of causal inference in gene–environment interaction research: leveraging research designs from the social sciences. Am. J. Public Health 103:Suppl. 1S42–45
    [Google Scholar]
  39. Fox D. 2019. Subversive science. Penn State Law Rev 124:1153–91
    [Google Scholar]
  40. Freese J. 2008. Genetics and the social science explanation of individual outcomes. Am. J. Sociol. 114:Suppl. 1S1–35
    [Google Scholar]
  41. Freund J, Brandmaier AM, Lewejohann L, Kirste I, Kritzler M et al. 2013. Emergence of individuality in genetically identical mice. Science 340:6133756–59
    [Google Scholar]
  42. Friedman NP, Miyake A, Young SE, DeFries JC, Corley RP, Hewitt JK 2008. Individual differences in executive functions are almost entirely genetic in origin. J. Exp. Psychol. Gen. 137:2201–25
    [Google Scholar]
  43. Goldberger AS. 1979. Heritability. Economica 46:184327–47
    [Google Scholar]
  44. Halldorsdottir T, Binder EB. 2017. Gene × environment interactions: from molecular mechanisms to behavior. Annu. Rev. Psychol. 68:215–41
    [Google Scholar]
  45. Hamer D, Sirota L. 2000. Beware the chopsticks gene. Mol. Psychiatry 5:111–13
    [Google Scholar]
  46. Hannikainen IR. 2019. Ideology between the lines: lay inferences about scientists’ values and motives. Soc. Psychol. Personal. Sci. 10:6832–41
    [Google Scholar]
  47. Harden KP, Domingue BW, Belsky DW, Boardman JD, Crosnoe R et al. 2019. Genetic associations with mathematics tracking and persistence in secondary school. bioRxiv 598532. https://doi.org/10.1101/598532
    [Crossref]
  48. Harden KP, Hill JE, Turkheimer E, Emery RE 2008. Gene–environment correlation and interaction in peer effects on adolescent alcohol and tobacco use. Behav. Genet. 38:4339–47
    [Google Scholar]
  49. Henrich J, Heine SJ, Norenzayan A 2010. The weirdest people in the world. Behav. Brain Sci. 33:2–361–83
    [Google Scholar]
  50. Herrnstein RJ, Murray C. 1996. The Bell Curve: Intelligence and Class Structure in American Life New York: Free Press
    [Google Scholar]
  51. Hewitt JK. 2012. Editorial policy on candidate gene association and candidate gene-by-environment interaction studies of complex traits. Behav. Genet. 42:11–2
    [Google Scholar]
  52. Jencks C, Philipps M. 1998. The black-white test score gap: why it persists and what can be done. Brookings March 1
    [Google Scholar]
  53. Jensen A. 1969. How much can we boost IQ and scholastic achievement?. Harv. Educ. Rev. 39:11–123
    [Google Scholar]
  54. Jerskey BA, Panizzon MS, Jacobson KC, Neale MC, Grant MD et al. 2010. Marriage and divorce: a genetic perspective. Personal. Individ. Differ. 49:5473–78
    [Google Scholar]
  55. Johnson W, Deary IJ, Silventoinen K, Tynelius P, Rasmussen F 2010. Family background buys an education in Minnesota but not in Sweden. Psychol. Sci. 21:91266–73
    [Google Scholar]
  56. Keller MC. 2014. Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution. Biol. Psychiatry 75:118–24
    [Google Scholar]
  57. Kendler KS, Turkheimer E, Ohlsson H, Sundquist J, Sundquist K 2015. Family environment and the malleability of cognitive ability: a Swedish national home-reared and adopted-away cosibling control study. PNAS 112:154612–17
    [Google Scholar]
  58. Kent DM, Rothwell PM, Ioannidis JP, Altman DG, Hayward RA 2010. Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal. Trials 11:185
    [Google Scholar]
  59. Koellinger PD, Harden KP. 2018. Using nature to understand nurture. Science 359:6374386–87
    [Google Scholar]
  60. Kong A, Thorleifsson G, Frigge ML, Vilhjalmsson BJ, Young AI et al. 2018. The nature of nurture: effects of parental genotypes. Science 359:6374424–28
    [Google Scholar]
  61. Krueger RF, Hicks BM, Patrick CJ, Carlson SR, Iacono WG, McGue M 2002. Etiologic connections among substance dependence, antisocial behavior and personality: modeling the externalizing spectrum. J. Abnorm. Psychol. 111:3411–24
    [Google Scholar]
  62. Kuo SI-C, Salvatore JE, Aliev F, Ha T, Dishion TJ, Dick DM 2019. The Family Check-Up intervention moderates polygenic influences on long-term alcohol outcomes: results from a randomized intervention trial. Prev. Sci. 20:7975–85
    [Google Scholar]
  63. Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O et al. 2018. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50:81112–21
    [Google Scholar]
  64. Lerner RM. 2006. Another nine-inch nail for behavioral genetics. ! Hum. Dev. 49:6336–42
    [Google Scholar]
  65. Lewontin RC. 1974. Annotation: the analysis of variance and the analysis of causes. Am. J. Hum. Genet. 26:3400–11
    [Google Scholar]
  66. Linneweber GA, Andriatsilavo M, Dutta SB, Bengochea M, Hellbruegge L et al. 2020. A neurodevelopmental origin of behavioral individuality in the Drosophila visual system. Science 367:64821112–19
    [Google Scholar]
  67. Mann FD, Patterson MW, Grotzinger AD, Kretsch N, Tackett JL et al. 2016. Sensation seeking, peer deviance, and genetic influences on adolescent delinquency: evidence for person-environment correlation and interaction. J. Abnorm. Psychol. 125:5679–91
    [Google Scholar]
  68. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA et al. 2009. Finding the missing heritability of complex diseases. Nature 461:7265747–53
    [Google Scholar]
  69. Manski CF. 2011. Genes, eyeglasses, and social policy. J. Econ. Perspect. 25:483–94
    [Google Scholar]
  70. Manuck SB, McCaffery JM. 2014. Gene–environment interaction. Annu. Rev. Psychol. 65:41–70
    [Google Scholar]
  71. Martin AR, Gignoux CR, Walters RK, Wojcik GL, Neale BM et al. 2017. Human demographic history impacts genetic risk prediction across diverse populations. Am. J. Hum. Genet. 100:4635–49
    [Google Scholar]
  72. Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ 2019. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51:4584–91
    [Google Scholar]
  73. McSwiggan S, Elger B, Appelbaum PS 2017. The forensic use of behavioral genetics in criminal proceedings: case of the MAOA-L genotype. Int. J. Law Psychiatry 50:17–23
    [Google Scholar]
  74. Merton RK. 1968. The Matthew effect in science: The reward and communication systems of science are considered. Science 159:381056–63
    [Google Scholar]
  75. Morris TT, Davies NM, Smith GD 2019. Can education be personalised using pupils’ genetic data?. bioRxiv 645218. https://doi.org/10.1101/645218
    [Crossref]
  76. Mostafavi H, Harpak A, Agarwal I, Conley D, Pritchard JK, Przeworski M 2020. Variable prediction accuracy of polygenic scores within an ancestry group. eLife 9:e48376
    [Google Scholar]
  77. Murray C. 2020. Human Diversity: The Biology of Gender, Race, and Class New York: Twelve
    [Google Scholar]
  78. Okbay A, Becker J, Benjamin D, Burik CA, Cesarini D, Turley P 2019. A repository of polygenic scores. Behav. Genet. 49:6507 (Abstr.)
    [Google Scholar]
  79. Panofsky A. 2014. Misbehaving Science Chicago: Univ. Chicago Press
    [Google Scholar]
  80. Papageorge NW, Thom K. 2020. Genes, education, and labor market outcomes: evidence from the Health and Retirement Study. J. Eur. Econ. Assoc. 18:135199
    [Google Scholar]
  81. Parens E. 2004. Genetic differences and human identities: on why talking about behavioral genetics is important and difficult. Hastings Cent. Rep. 34:1S4–35
    [Google Scholar]
  82. Plomin R. 2018. Blueprint: How DNA Makes Us Who We Are Cambridge, MA: MIT Press
    [Google Scholar]
  83. Polderman TJC, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A et al. 2015. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 47:7702–9
    [Google Scholar]
  84. Rawls J. 1999 (1971). A Theory of Justice Cambridge, MA: Harvard Univ. Press. , Rev.. ed.
    [Google Scholar]
  85. Rietveld CA, Medland SE, Derringer J, Yang J, Esko T et al. 2013. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340:61391467–71
    [Google Scholar]
  86. Rimfeld K, Krapohl E, Trzaskowski M, Coleman JRI, Selzam S et al. 2018a. Genetic influence on social outcomes during and after the Soviet era in Estonia. Nat. Hum. Behav. 2:4269–75
    [Google Scholar]
  87. Rimfeld K, Malanchini M, Krapohl E, Hannigan LJ, Dale PS, Plomin R 2018b. The stability of educational achievement across school years is largely explained by genetic factors. npj Sci. Learn. 3:116
    [Google Scholar]
  88. Rutter M, Moffitt TE, Caspi A 2006. Gene–environment interplay and psychopathology: multiple varieties but real effects. J. Child Psychol. Psychiatry 47:3–4226–61
    [Google Scholar]
  89. Rutter M, Silberg J. 2002. Gene–environment interplay in relation to emotional and behavioral disturbance. Annu. Rev. Psychol. 53:463–90
    [Google Scholar]
  90. Sandin S, Lichtenstein P, Kuja-Halkola R, Hultman C, Larsson H, Reichenberg A 2017. The heritability of autism spectrum disorder. JAMA 318:121182–84
    [Google Scholar]
  91. Schmitz L, Conley D. 2016. The long-term consequences of Vietnam-era conscription and genotype on smoking behavior and health. Behav. Genet. 46:43–58
    [Google Scholar]
  92. Schmitz L, Conley D. 2017. Modeling gene–environment interactions with quasi-natural experiments. J. Personal. 85:110–21
    [Google Scholar]
  93. Schulz W, Schunck R, Diewald M, Johnson W 2017. Pathways of intergenerational transmission of advantages during adolescence: social background, cognitive ability, and educational attainment. J. Youth Adolesc. 46:102194–214
    [Google Scholar]
  94. Sharma S, Powers A, Bradley B, Ressler KJ 2016. Gene × environment determinants of stress- and anxiety-related disorders. Annu. Rev. Psychol. 67:239–61
    [Google Scholar]
  95. Slutske WS, Deutsch AR, Piasecki TM 2019. Neighborhood density of alcohol outlets moderates genetic and environmental influences on alcohol problems. Addiction 114:5815–22
    [Google Scholar]
  96. Sotoudeh R, Harris KM, Conley D 2019. Effects of the peer metagenomic environment on smoking behavior. PNAS 116:3316302–7
    [Google Scholar]
  97. State v. Yepez, A-1-CA-35330 (N.M. Ct. App 2018.)
  98. Tabery J. 2014. Beyond Versus: The Struggle to Understand the Interaction of Nature and Nurture Cambridge, MA: MIT Press
    [Google Scholar]
  99. Tick B, Bolton P, Happé F, Rutter M, Rijsdijk F 2016. Heritability of autism spectrum disorders: a meta-analysis of twin studies. J. Child Psychol. Psychiatry 57:5585–95
    [Google Scholar]
  100. Trejo S, Domingue BW. 2019. Genetic nature or genetic nurture? Quantifying bias in analyses using polygenic scores. bioRxiv 524850. https://doi.org/10.1101/524850
    [Crossref]
  101. Tropf FC, Lee SH, Verweij RM, Stulp G, van der Most PJ et al. 2017. Hidden heritability due to heterogeneity across seven populations. Nat. Hum. Behav. 1:10757–65
    [Google Scholar]
  102. Tucker-Drob EM, Bates TC. 2016. Large cross-national differences in gene × socioeconomic status interaction on intelligence. Psychol. Sci. 27:2138–49
    [Google Scholar]
  103. Tucker-Drob EM, Briley DA, Harden KP 2013. Genetic and environmental influences on cognition across development and context. Curr. Dir. Psychol. Sci. 22:5349–55
    [Google Scholar]
  104. Tucker‐Drob EM, Harden KP. 2012. Early childhood cognitive development and parental cognitive stimulation: evidence for reciprocal gene–environment transactions. Dev. Sci. 15:2250–59
    [Google Scholar]
  105. Turkheimer E. 1998. Heritability and biological explanation. Psychol. Rev. 105:4782–91
    [Google Scholar]
  106. Turkheimer E. 2000. Three laws of behavior genetics and what they mean. Curr. Dir. Psychol. Sci. 9:5160–64
    [Google Scholar]
  107. Turkheimer E. 2011. Genetics and human agency: comment on Dar-Nimrod and Heine 2011. Psychol. Bull. 137:5825–28
    [Google Scholar]
  108. Turkheimer E, Haley A, Waldron M, D'Onofrio B, Gottesman II 2003. Socioeconomic status modifies heritability of IQ in young children. Psychol. Sci. 14:6623–28
    [Google Scholar]
  109. van der Sluis S, Posthuma D, Dolan CV 2012. A note on false positives and power in G × E modelling of twin data. Behav. Genet. 42:1170–86
    [Google Scholar]
  110. Van Hulle CA, Lahey BB, Rathouz PJ 2013. Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies. Behav. Genet. 43:171–84
    [Google Scholar]
  111. Visscher PM, Hill WG, Wray NR 2008. Heritability in the genomics era—concepts and misconceptions. Nat. Rev. Genet. 9:4255–66
    [Google Scholar]
  112. Visscher PM, Medland SE, Ferreira MAR, Morley KI, Zhu G et al. 2006. Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings. PLOS Genet 2:3e41
    [Google Scholar]
  113. Wainschtein P, Jain DP, Yengo L, Zheng Z, TOPMed Anthropometry Work. Group, et al. 2019. Recovery of trait heritability from whole genome sequence data. bioRxiv 588020. https://doi.org/10.1101/588020
    [Crossref]
  114. Westfall J, Yarkoni T. 2016. Statistically controlling for confounding constructs is harder than you think. PLOS ONE 11:3e0152719
    [Google Scholar]
  115. Willoughby EA, Love AC, McGue M, Iacono WG, Quigley J, Lee JJ 2019. Free will, determinism, and intuitive judgments about the heritability of behavior. Behav. Genet. 49:2136–53
    [Google Scholar]
  116. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK et al. 2010. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42:7565–69
    [Google Scholar]
  117. Yeager DS, Hanselman P, Walton GM, Murray JS, Crosnoe R et al. 2019. A national experiment reveals where a growth mindset improves achievement. Nature 573:7774364–69
    [Google Scholar]
  118. Young AI. 2019. Solving the missing heritability problem. PLOS Genet 15:6e1008222
    [Google Scholar]
  119. Young AI, Benonisdottir S, Przeworski M, Kong A 2019. Deconstructing the sources of genotype-phenotype associations in humans. Science 365:64601396–400
    [Google Scholar]
  120. Zhang T-Y, Meaney MJ. 2010. Epigenetics and the environmental regulation of the genome and its function. Annu. Rev. Psychol. 61:439–66
    [Google Scholar]
/content/journals/10.1146/annurev-psych-052220-103822
Loading
/content/journals/10.1146/annurev-psych-052220-103822
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error