Skip to main content
Log in

Shared-Environmental Contributions to High Cognitive Ability

  • Original Research
  • Published:
Behavior Genetics Aims and scope Submit manuscript

Abstract

Using a combined sample of adolescent twins, biological siblings, and adoptive siblings, we estimated and compared the differential shared-environmentality for high cognitive ability and the shared-environmental variance for the full range of ability during adolescence. Estimates obtained via multiple methods were in the neighborhood of 0.20, and suggest a modest effect of the shared environment on both high and full-range ability. We then examined the association of ability with three measures of the family environment in a subsample of adoptive siblings: parental occupational status, parental education, and disruptive life events. Only parental education showed significant (albeit modest) association with ability in both the biological and adoptive samples. We discuss these results in terms of the need for cognitive-development research to combine genetically sensitive designs and modern statistical methods with broad, thorough environmental measurement.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. Let us assume a high heritability coefficient for adult IQ (0.8). Let us also assume that spouses select mates for psychometric IQ per se, and that the phenotypic spousal correlation perfectly induces the spousal genetic correlation. The latter two assumptions are generally not true, but they simplify the model, and enable a “worst-case” estimate of the biometric bias induced by assortative mating. Under these assumptions, the assortative mating coefficient will be \( \sqrt {0.8} \times 0.34 \times \sqrt {0.8} \), or 0.27. The expected additive-genetic correlation for DZ twins will therefore be 0.5 × (1 − 0.27), or 0.64. If we attempt to compute the Falconer estimate of narrow-sense heritability in twin data (a 2 = (r MZ − r DZ), which typically assumes no assortative mating) using r DZ = 0.64a 2 + c 2, we discover that the Falconer estimate only yields 0.72a 2, an underestimate of over 25%. The “missing” variance will be consumed by the Falconer shared-environmentality estimate (c 2 = 2r DZ − r MZ).

  2. On the suggestion of an anonymous referee, we conducted post-hoc analyses to investigate whether parental psychopathology predicted offspring IQ. We examined composite indicators of two of the primary phenotypes of interest in SIBS, substance abuse and behavioral disinhibition. As an indicator of substance abuse, we used scores on the first principal component extracted from measures of nicotine dependence (e.g., symptom count, per-day frequency of use), heavy alcohol consumption (e.g., frequency of drinking, largest number of drinks in one day), alcohol abuse and dependence (e.g., withdrawal and tolerance, interference with social and occupational functioning), illicit drug abuse and dependence (e.g., symptom count, number of different drugs used), and frequency of illicit drug use. As an indicator of behavioral disinhibition, we used scores on the first principal component extracted from measures such as lifetime symptom counts for conduct disorder, relevant life-events (e.g., trouble with the law, early age of first intercourse), a reverse-scored socialization scale, and personality scales measuring aggression and low constraint. For each family, we summed original parents’ scores on the substance abuse measure and on the behavioral disinhibition measure. We then estimated the regression of offspring IQ onto each of these, using mixed-effect linear models that controlled for sibling-pair clustering, sex, and ethnicity. The coefficient for the behavioral disinhibition variable was significant neither among biological (b = −1.18, SE = 1.28) nor adopted (b = −1.67, SE = 1.45) participants. Despite suggestive results for the substance abuse variable among biological participants (b = −2.09, SE = 1.05), its coefficient was significant in neither that subsample nor among adoptees (b = −0.63, SE = 1.29).

  3. However, one interesting aspect of our life-events results is the marked decline in ability for biological offspring at the upper life-events extreme (scores greater than eleven, which occurred for only two families). This suggests that a sufficiently disruptive environment can detrimentally affect cognitive ability, or alternately, that instability-producing behavior in parents and IQ decrements in their natural children may stem from common genetic factors. There were no adoptees with family life-events scores of this magnitude, so the effect of extreme environmental instability, independent of heredity, cannot be estimated. In general, adoptive samples do not represent the negative extremes of family environments, so results from adoption studies cannot rule out the possibility that exceptionally unfavorable environments can produce exceptionally unfavorable effects.

References

  • Baumrind D (1993) The average expectable environment is not good enough: a response to Scarr. Child Dev 64:1299–1317. doi:10.2307/1131536

    Article  PubMed  Google Scholar 

  • Bemmels HR, Burt SA, Legrand LN, Iacono WG, McGue M (2008) The heritability of life events: an adolescent twin and adoption study. Twin Res Hum Genet 11(3):257–265. doi:10.1375/twin.11.3.257

    Article  PubMed  Google Scholar 

  • Bouchard TJ, McGue M (1981) Familial studies of intelligence: a review. Science. New Series 212(4498):1055–1059

    Google Scholar 

  • Bouchard TJ, McGue M (2003) Genetic and environmental influences on human psychological differences. J Neurobiol 54:4–45. doi:10.1002/neu.10160

    Article  PubMed  Google Scholar 

  • Cherny SS, Cardon LR, Fulker DW, DeFries JC (1992) Differential heritability across levels of cognitive ability. Behav Genet 22(2):153–162. doi:10.1007/BF01066994

    Article  PubMed  Google Scholar 

  • Deary IJ, Spinath FM, Bates TC (2006) Genetics of intelligence. Eur J Hum Genet 14:690–700. doi:10.1038/sj.ejhg.5201588

    Article  PubMed  Google Scholar 

  • DeFries JC, Fulker DW (1985) Multiple regression analysis of twin data. Behav Genet 15(5):467–473. doi:10.1007/BF01066239

    Article  PubMed  Google Scholar 

  • DeFries JC, Fulker DW (1988) Multiple regression analysis of twin data: etiology of deviant scores versus individual differences. Acta Genet Med Gemellol 37:205–216

    PubMed  Google Scholar 

  • Detterman DK, Thompson LA, Plomin R (1990) Differences in heritability across groups differing in ability. Behav Genet 20(3):369–384. doi:10.1007/BF01065564

    Article  PubMed  Google Scholar 

  • Devlin B, Daniels M, Roeder K (1997) The heritability of IQ. Nature 388:468–471. doi:10.1038/41319

    Article  PubMed  Google Scholar 

  • Gottfried AW, Gottfried AE, Bathurst K, Guerin DW (1994) Gifted IQ: early developmental aspects: the Fullerton Longitudinal Study. Plenum Press, New York

    Google Scholar 

  • Heckman JJ (2006) Skill formation and the economics of investing in disadvantaged children. Science 312:1900–1902. doi:10.1126/science.1128898

    Article  PubMed  Google Scholar 

  • Holahan CK, Sears RK (1995) The gifted group in later maturity. Stanford University Press, Stanford

    Google Scholar 

  • Hollingshead AB (1957) Two factor index of social position. August B. Hollingshead, New Haven, CN

    Google Scholar 

  • Iacono WG, McGue M (2002) Minnesota Twin Family Study. Twin Res 5(5):482–487. doi:10.1375/136905202320906327

    Article  PubMed  Google Scholar 

  • Iacono WG, Carlson SR, Taylor J, Elkins IJ, McGue M (1999) Behavioral disinhibition and the development of substance-use disorders: findings from the Minnesota Twin Family Study. Dev Psychopathol 11:869–900. doi:10.1017/S0954579499002369

    Article  PubMed  Google Scholar 

  • Jensen AR (1980) Bias in mental testing. The Free Press, New York

    Google Scholar 

  • Kohler HP, Rodgers JL (2001) DF-analyses of heritability with double-entry twin data: asymptotic standard errors and efficient estimation. Behav Genet 31(2):179–191. doi:10.1023/A:1010253411274

    Article  PubMed  Google Scholar 

  • Matheny AP, Wachs TD, Ludwig JL, Philips K (1995) Bringing order out of chaos: psychometric characteristics of the confusion, hubbub, and order scale. J Appl Dev Psychol 16:429–444. doi:10.1016/0193-3973(95)90028-4

    Article  Google Scholar 

  • McGue M, Bouchard TJ, Iacono WG, Lykken DT (1993) Behavioral genetics of cognitive ability: a life-span perspective. In: Plomin R, McClearn GE (eds) Nature, nurture and psychology. American Psychological Association, Washington, pp 59–76

    Chapter  Google Scholar 

  • McGue M, Keyes M, Sharma A, Elkins I, Legrand L, Johnson W et al (2007) The environments of adopted and non-adopted youth: evidence on range restriction from the Sibling Interaction and Behavior Study (SIBS). Behav Genet 37:449–462. doi:10.1007/s10519-007-9142-7

    Article  PubMed  Google Scholar 

  • Neale MC, Boker SM, Xie G, Maes HH (2003) Mx: statistical modeling, 6th edn. VCU, Department of Psychiatry, Richmond, VA

    Google Scholar 

  • Neiss M, Rowe DC (2000) Parental education and child’s verbal IQ in adoptive and biological families in the National Longitudinal Study of Adolescent Health. Behav Genet 30(6):487–495. doi:10.1023/A:1010254918997

    Article  PubMed  Google Scholar 

  • Petrill SA, Saudino K, Cherny SS, Emde RN, Fulker DW et al (1998) Exploring the genetic and environmental etiology of high general cognitive ability in fourteen- to thirty-six-month-old twins. Child Dev 69(1):68–74

    PubMed  Google Scholar 

  • Petrill SA, Pike A, Price T, Plomin R (2004) Chaos in the home and socioeconomic status are associated with cognitive development in early childhood: environmental mediators identified in a genetic design. Intelligence 32:445–460. doi:10.1016/j.intell.2004.06.010

    Article  Google Scholar 

  • Pike A, Iervolino AC, Eley TC, Price TS, Plomin R (2006) Environmental risk and young children’s cognitive and behavioral development. Int J Behav Dev 30(1):55–66. doi:10.1177/0165025406062124

    Article  Google Scholar 

  • Rodgers JL, Kohler HP (2005) Reformulating and simplifying the DF analysis model. Behav Genet 35(2):211–217. doi:10.1007/s10519-004-1020-y

    Article  Google Scholar 

  • Rodgers JL, McGue M (1994) A simple algebraic demonstration of the validity of Defries-Fulker analysis in unselected samples with multiple kinship levels. Behav Genet 24(3):259–262. doi:10.1007/BF01067192

    Article  PubMed  Google Scholar 

  • Scarr S (1997) Behavior-genetic and socialization theories of intelligence: truce and reconciliation. In: Sternberg RJ, Grigorenko E (eds) Intelligence, heredity, and environment. Cambridge University Press, New York, pp 3–41

    Google Scholar 

  • Scarr S, McCartney K (1983) How people make their own environments: a theory of genotype → environment effects. Child Dev 54:424–443

    PubMed  Google Scholar 

  • Scarr S, Weinberg RA (1978) The influence of “family background” on intellectual attainment. Am Sociol Rev 43(5):674–692. doi:10.2307/2094543

    Article  Google Scholar 

  • Vandenberg SG, Kuse AR (1981) In search of the missing environmental variance in cognitive ability. In: Gedda L, Parisi P, Nance WE (eds) Twin Research 3: intelligence, personality, and development. Alan R. Liss Inc., New York, NY, pp 9–16

    Google Scholar 

  • Wilson RS (1983) The Louisville Twin Study: developmental synchronies in behavior. Child Dev 54:298–316. doi:10.2307/1129693

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by US Public Health Service grants # DA005147, AA009367, DA13240, AA11886, and MH66140, and by grant # 13575 from the John Templeton Foundation (“The Genetics of High Cognitive Abilities”). The authors give their special thanks to Brian M. Hicks for his assistance in the analysis of the life-events and parental-psychopathology data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robert M. Kirkpatrick.

Additional information

Edited by Robert Plomin.

Appendix: Life events item content

Appendix: Life events item content

Items from mother’s life events interview:

  1. 1.

    Divorce.

  2. 2.

    Former spouse remarrying.

  3. 3.

    Death of spouse.

  4. 4.

    Separation from spouse due to conflict.

  5. 5.

    Separation from spouse due to necessity.

  6. 6.

    Arguing a lot with spouse.

  7. 7.

    Treatment for emotional problem.

  8. 8.

    Treatment for alcohol/drugs.

  9. 9.

    Suicide attempt.

  10. 10.

    Fired/laid off.

  11. 11.

    Financial problems.

  12. 12.

    Bankruptcy.

  13. 13.

    Public assistance (welfare, etc.).

  14. 14.

    Public assistance cut off.

  15. 15.

    Arrested or jailed.

  16. 16.

    Moving 50 + miles.

  17. 17.

    Serious/chronic illness.

  18. 18.

    Hospitalization.

Items from father’s life events interview:

  1. 19.

    Treatment for emotional problems.

  2. 20.

    Treatment for alcohol/drugs.

  3. 21.

    Suicide attempt.

  4. 22.

    Fired/laid off.

  5. 23.

    Arrested or jailed.

  6. 24.

    Serious/chronic illness.

  7. 25.

    Hospitalization.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kirkpatrick, R.M., McGue, M. & Iacono, W.G. Shared-Environmental Contributions to High Cognitive Ability. Behav Genet 39, 406–416 (2009). https://doi.org/10.1007/s10519-009-9265-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10519-009-9265-0

Keywords

Navigation