Learning to Love Animal (Models) (or) How (Not) to Study Genes as a Social Scientist

  • Dalton Conley
Part of the Handbooks of Sociology and Social Research book series (HSSR)


In this chapter, I will argue that social science and genomics can be integrated – however, the way this marriage is currently occurring rests on spurious methods and assumptions and, as a result, will yield few lasting insights. However, recent advances in both econometrics and in developmental genomics provide scientists with a novel opportunity to understand how genes and (social) environment interact. To presage my argument: Key to any causal inference about genetically heterogeneous effects of social conditions is that either genetics be exogenously manipulated while environment is held constant (and measured properly), and/or that environmental variation is exogenous in nature – i.e. experimental or arising from a natural experiment of sorts. Further, allele selection should be motivated by findings from genetic experiments in (model) animal studies linked to orthologous human genes. Likewise, genetic associations found in human population studies should then be tested through knock-out and over-expression studies in model organisms. Finally, gene silencing can be a promising avenue of research in humans if careful thought is given to when and which cells are harvested for analysis.


Attention Deficit Hyperactivity Disorder Attention Deficit Hyperactivity Disorder Stressful Life Event Fraternal Twin Regression Discontinuity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Angrist JD (1989) Using the draft lottery to measure the effect of military service on civilian labor market outcomes. In: Ehrenberg R (ed) Research in labor economics, vol 10. JAI Press, Inc., GreenwichGoogle Scholar
  2. Angrist JD, Krueger AB (2001) Instrumental variables and the search for identification: from supply and demand to natural experiments. J Econ Perspect 15(4):69–85CrossRefGoogle Scholar
  3. Brookes K et al (2006) The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1, and 16 other genes. Mol Psychiatry 11:934–953CrossRefGoogle Scholar
  4. Caldji C, Tannenbaum B, Sharma S, Francis D, Plotsky PM, Meaney MJ (1998) Maternal care during infancy regulates the development of neural systems mediating the expression of fearfulness in the rat. Proc Natl Acad Sci U S A 95(9):5335–5340CrossRefGoogle Scholar
  5. Caspi A et al (2002) Role of genotype in the cycle of violence in maltreated children. Science 297:851–854CrossRefGoogle Scholar
  6. Caspi A et al (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 297:851–854CrossRefGoogle Scholar
  7. Conley D (2009) GE interactions in college social networks. Research in progressGoogle Scholar
  8. Conley D, Glauber R (2006) Parental educational investment and children’s academic risk: estimates of the impact of sibship size and birth order from exogenous variation in fertility. J Hum Resour 41(4):722–737Google Scholar
  9. Ding W, Lehrer SF, Rosenquist JN, Audrain-McGovern J (2006) The impact of poor health on education: new evidence using genetic markers. NBER Working Papers 12304. National Bureau of Economic ResearchGoogle Scholar
  10. Duncan GJ, Guo G (2009) Dopamine transporter genotype and freshman roommate assignment to a binge drinker. Research in progressGoogle Scholar
  11. Goldberger AS (1979) Heritability. Economica 46(184):327–47CrossRefGoogle Scholar
  12. Guo G, Stearns E (2002) The social influences on the realization of genetic potential for intellectual development. Soc Forces 80(3):881–910CrossRefGoogle Scholar
  13. Hamer D (2002) Rethinking behavior genetics. Science 298(5591):71–72CrossRefGoogle Scholar
  14. Hamer DH, Hu S, Magnuson V, Hu N, Pattatucci A (1993) A linkage between DNA markers on the X chromosome and male sexual orientation. Science 261(5119):321–327CrossRefGoogle Scholar
  15. Isalan M et al (2008) Evolvability and hierarchy in rewired bacterial gene networks. Nature 452:840–845CrossRefGoogle Scholar
  16. Jeong H, Mason SP, Barabási A-L, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411:41–42CrossRefGoogle Scholar
  17. Katz LF, Kling JR, Liebman JB (2001) Moving to opportunity in Boston: early results of a randomized mobility experiment. Q J Econ 116:607–654CrossRefGoogle Scholar
  18. Knowler WC, Williams RC, Pettit DJ, Steinberg AG (1988) GM3;5, 13, 14 and type 2 diabetes mellitus: an association in American Indians with genetic admixture. Am J Hum Genet 43:520–526Google Scholar
  19. Krishnan V, Nestler EJ (2008) The molecular neurobiology of depression. Nature 455:894–902CrossRefGoogle Scholar
  20. Lee DS (2008) Randomized experiments from non-random selection in the U.S. house elections. J Econom 142:675–697CrossRefGoogle Scholar
  21. Lichtenstein P, Pedersen NL, McClearn GE (1992) The origins of individual differences in occupational status and educational level: a study of twins reared apart and together. Acta Sociol 35:13–31CrossRefGoogle Scholar
  22. Lleras-Muney A (2005) The relationship between education and adult mortality in the United States. Rev Econ Stud 72(1):189–221CrossRefGoogle Scholar
  23. McGowan PO, Sasaki A, Huang TCT, Unterberger A, Suderman M, Ernst C, Meany MJ, Turecki G, Szyf M (2008) Promoter-wide hypermethylation of the ribsomomal rna gene promoter in the suicide brain. PLoS One 3(5):1–10CrossRefGoogle Scholar
  24. Plomin R, DeFries JC, McClearn GE, McGuffin P (2001) Behavioral genetics, 4th edn. Worth Publishers, New YorkGoogle Scholar
  25. Rice G, Anderson C, Risch N, Ebers G (1999) Male homosexuality: absence of linkage to microsatellite markers at Xq28. Science 284:665CrossRefGoogle Scholar
  26. Rodgers JL, Rowe DC, Buster M (1999) Nature, nurture and first sexual intercourse in the USA: fitting behavioural genetic models to NLSY kinship data. J Biosoc Sci 31:29–41CrossRefGoogle Scholar
  27. Rowe DC, Teachman J (2001) Behavioral genetic research designs and social policy studies. In: Thornton A (ed) The well-being of children and families: research and data needs. University of Michigan Press, Ann Arbor, pp 157–187Google Scholar
  28. Sacerdote B (2004) What happens when we randomly assign children to families? NBER Working Paper No. 10894Google Scholar
  29. Stelzl U, Worm U, Lalowski M, Haenig C, Brembeck F, Goehler H, Stroedicke M, Zenkner M, Schoenherr A, Koeppen S, Timm J, Mintzlaff S, Abraham C, Bock N, Kietzmann S, Goedde A, Toksöz E, Droege A, Krobitsch S, Korn B, Birchmeier W, Lehrach H, Wanker E (2005) A human protein–protein interaction network: a resource for annotating the proteome. Cell 122:957–968CrossRefGoogle Scholar
  30. Strully KW (2009) Job loss and health in the U.S. labor market. Demography 46(2):221–246CrossRefGoogle Scholar
  31. Thornton KR, Jensen JD (2007) Controlling the false-positive rate in multilocus genome scans for selection. Genetics 175:737–750CrossRefGoogle Scholar
  32. van der Klaauw W (2002) Estimating the effect of financial aid offers on college enrollment: a regression-discontinuity approach. Int Econ Rev 43:1249–1287CrossRefGoogle Scholar
  33. Winship C, Morgan S (1999) The estimation of causal effects from observational data. Annu Rev Sociol 25:659–706CrossRefGoogle Scholar
  34. Wong AH et al (2005) Phenotypic differences in genetically identical organisms: the epigenetic perspective. Hum Mol Genet 14(Review issue 1):R11–R18CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Center for Advanced Social Science ResearchNew York UniversityNew YorkUSA

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