Advertisement

Behavior Genetics

, Volume 40, Issue 2, pp 125–134 | Cite as

A Bivariate Twin Study of Regional Brain Volumes and Verbal and Nonverbal Intellectual Skills During Childhood and Adolescence

  • Gregory L. WallaceEmail author
  • Nancy Raitano Lee
  • Elizabeth C. Prom-Wormley
  • Sarah E. Medland
  • Rhoshel K. Lenroot
  • Liv S. Clasen
  • James E. Schmitt
  • Michael C. Neale
  • Jay N. Giedd
Original Research

Abstract

Twin studies indicate that both intelligence and brain structure are moderately to highly heritable. Recent bivariate studies of adult twins also suggest that intelligence and brain morphometry are influenced by shared genetic factors. The current study examines shared genetic and environmental factors between brain morphometry and intelligence in a sample of children and adolescents (twins, twin siblings, and singletons; n = 649, ages 4–19). To extend previous studies, brain morphometric data were parsed into subregions (lobar gray/white matter volumes, caudate nucleus, lateral ventricles) and intelligence into verbal and nonverbal skills (Wechsler Vocabulary and Block Design subtests). Phenotypic relationships between brain volumes and intelligence were small. Verbal skills shared unique environmental effects with gray matter volumes while nonverbal skills shared genetic effects with both global and regional gray and white matter. These results suggest that distinct mechanisms contribute to the small phenotypic relationships between brain volumes and verbal versus nonverbal intelligence.

Keywords

Twin Magnetic resonance imaging Brain Intelligence Verbal Nonverbal 

Notes

Acknowledgments

This research was supported by the Intramural Research Program of the NIH, National Institute of Mental Health (GW, NRL, LSC, RL, JG), extramural grant funding from the NIH (MH-20030; EP-W, SEM, JES, MCN), and an NHMRC Australia, Sidney Sax Public Fellowship (443036; SEM). We would like to express our gratitude to the individuals who volunteered their time to contribute to this research.

References

  1. Axelrod BN (2002) Validity of the Wechsler abbreviated scale of intelligence and other very short forms of estimating intellectual functioning. Assessment 9(1):17–23CrossRefPubMedGoogle Scholar
  2. Bates TC, Luciano M, Lind PA, Wright MJ, Montgomery GW, Martin NG (2008) Recently-derived variants of brain-size genes ASPM, MCPH1, CDK5RAP and BRCA1 not associated with general cognition, reading or language. Intelligence 36(6):689–693CrossRefGoogle Scholar
  3. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol 57(1):289–300Google Scholar
  4. Byrne B, Olson RK, Samuelsson S, Wadsworth S, Corley R, DeFries JC, Willcutt E (2006) Genetic and environmental influences on early literacy. J Res Reading 29(1):33–49CrossRefGoogle Scholar
  5. Carmelli D, Swan GE, DeCarli C, Reed T (2002) Quantitative genetic modeling of regional brain volumes and cognitive performance in older male twins. Biol Psychol 61(1–2):139–155CrossRefPubMedGoogle Scholar
  6. Collins DL, Neelin P, Peters TM, Evans AC (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 18(2):192–205CrossRefPubMedGoogle Scholar
  7. Collins DL, Holmes CJ, Peters TM, Evans AC (1995) Automatic 3-D model-based neuroanatomical segmentation. Hum Brain Mapp 3(3):190–208CrossRefGoogle Scholar
  8. Denckla MB (1985) Revised neurological examination for subtle signs. Psychopharmacol Bull 21(4):773–800PubMedGoogle Scholar
  9. Edwards AWF (1984) Likelihood. Cambridge University Press, CambridgeGoogle Scholar
  10. Flashman LA, Andreasen NC, Flaum M, Swayze VW (1998) Intelligence and regional brain volumes in normal controls. Intelligence 25(3):149–160CrossRefGoogle Scholar
  11. Galton F (1869) Hereditary genius: an inquiry into its laws and consequences. Macmillan, LondonGoogle Scholar
  12. Geschwind DH, Miller BL, DeCarli C, Carmelli D (2002) Heritability of lobar brain volumes in twins supports genetic models of cerebral laterality and handedness. Proc Natl Acad Sci USA 99(5):3176–3181CrossRefPubMedGoogle Scholar
  13. Giedd JN, Blumenthal J, Jeffries NO, Castellanos FX, Liu H, Zijdenbos A, Paus T, Evans AC, Rapoport JL (1999) Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci 2(10):861–863CrossRefPubMedGoogle Scholar
  14. Giedd JN, Lalonde FN, Celano MJ, White SL, Wallace GL, Lee NR, Lenroot RK (2009) Anatomical brain magnetic resonance imaging of typically developing children and adolescents. J Am Acad of Child Adolesc Psychiatry 48(5):465–470CrossRefGoogle Scholar
  15. Haworth CM, Wright MJ, Luciano M, Martin NG, de Geus EJ, van Beijsterveldt CE, Bartels M, Posthuma D, Boomsma DI, Davis OS, Kovas Y, Corley RP, Defries JC, Hewitt JK, Olson RK, Rhea SA, Wadsworth SJ, Iacono WG, McGue M, Thompson LA, Hart SA, Petrill SA, Lubinski D, Plomin R (2009) The heritability of general cognitive ability increases linearly from childhood to young adulthood. Mol Psychiatry [Epub ahead of print]Google Scholar
  16. Hollingshead AB, Redlich FC (1958) Social class and mental illness: a community study. Wiley, New YorkCrossRefGoogle Scholar
  17. Hulshoff Pol HE, Schnack HG, Posthuma D, Mandl RC, Baare WF, van Oel C, van Haren NE, Collins DL, Evans AC, Amunts K, Burgel U, Zilles K, de Geus E, Boomsma DI, Kahn RS (2006) Genetic contributions to human brain morphology and intelligence. J Neurosci 26(40):10235–10242CrossRefPubMedGoogle Scholar
  18. Lenroot RK, Gogtay N, Greenstein DK, Wells EM, Wallace GL, Clasen LS, Blumenthal JD, Lerch J, Zijdenbos AP, Evans AC, Thompson PM, Giedd JN (2007) Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage 36(4):1065–1073CrossRefPubMedGoogle Scholar
  19. Lerch JP, Worsley K, Shaw WP, Greenstein DK, Lenroot RK, Giedd J, Evans AC (2006) Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI. Neuroimage 31(3):993–1003CrossRefPubMedGoogle Scholar
  20. McDaniel MA (2005) Big-brained people are smarter: a meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence 33(4):337–346CrossRefGoogle Scholar
  21. McGue M, Bouchard TJ Jr, Iacono WG, Lykken DT (1993) Behavioral genetics of cognitive ability: a life-span perspective. American Psychological Association, Washington, DCGoogle Scholar
  22. Nagy Z, Westerberg H, Klingberg T (2004) Maturation of white matter is associated with the development of cognitive functions during childhood. J Cogn Neurosci 16(7):1227–1233CrossRefPubMedGoogle Scholar
  23. Neale M, Cardon L (1992) Methodology for genetic studies of twins and families. Kluwer, DordrechtGoogle Scholar
  24. Neale MC, Boker SM, Xie G, Maes HH (2006) Mx: statistical modeling, 6th edn. Department of Psychiatry, Richmond, VAGoogle Scholar
  25. Payton A (2006) Investigating cognitive genetics and its implications for the treatment of cognitive deficit. Genes Brain Behav 5:144–153Google Scholar
  26. Peper JS, Brouwer RM, Boomsma DI, Kahn RS, Hulshoff Pol HE (2007) Genetic influences on human brain structure: a review of brain imaging studies in twins. Hum Brain Mapp 28(6):464–473CrossRefPubMedGoogle Scholar
  27. Plomin R, Craig I (1997) Human behavioral genetics of cognitive abilities and disabilities. BioEssays 19(12):1117–1124CrossRefPubMedGoogle Scholar
  28. Plomin R, DeFries JC, McClearn GE, Rutter M (1997a) Behavioral genetics, 3rd edn. W.H. Freeman and Company, New YorkGoogle Scholar
  29. Plomin R, Fulker DW, Corley R, DeFries JC (1997b) Nature, nurture, and cognitive development from 1 to 16 years: a parent-offspring adoption study. Psychol Sci 8(6):442–447CrossRefGoogle Scholar
  30. Posthuma D, De Geus EJ, Baare WF, Hulshoff Pol HE, Kahn RS, Boomsma DI (2002) The association between brain volume and intelligence is of genetic origin. Nat Neurosci 5(2):83–84CrossRefPubMedGoogle Scholar
  31. Posthuma D, Baare WF, Hulshoff Pol HE, Kahn RS, Boomsma DI, De Geus EJ (2003) Genetic correlations between brain volumes and the WAIS-III dimensions of verbal comprehension, working memory, perceptual organization, and processing speed. Twin Res 6(2):131–139CrossRefPubMedGoogle Scholar
  32. Sattler JM (1992) Assessment of children: revised and updated, 3rd edn. Jerome M. Sattler Publisher, Inc., San Diego, CAGoogle Scholar
  33. Schmitt JE, Eyler LT, Giedd JN, Kremen WS, Kendler KS, Neale MC (2007) Review of twin and family studies on neuroanatomic phenotypes and typical neurodevelopment. Twin Res Hum Genet 10(5):683–694CrossRefPubMedGoogle Scholar
  34. Schmitt JE, Lenroot RK, Wallace GL, Ordaz S, Taylor KN, Kabani N, Greenstein D, Lerch JP, Kendler KS, Neale MC, Giedd JN (2008) Identification of genetically mediated cortical networks: a multivariate study of pediatric twins and siblings. Cereb Cortex 18(8):1737–1747CrossRefPubMedGoogle Scholar
  35. Shaw P (2007) Intelligence and the developing human brain. Bioessays 29(10):962–973CrossRefPubMedGoogle Scholar
  36. Shaw P, Greenstein D, Lerch J, Clasen L, Lenroot R, Gogtay N, Evans A, Rapoport J, Giedd J (2006) Intellectual ability and cortical development in children and adolescents. Nature 440(7084):676–679CrossRefPubMedGoogle Scholar
  37. Sled JG, Zijdenbos AP, Evans AC (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17(1):87–97CrossRefPubMedGoogle Scholar
  38. Thompson PM, Cannon TD, Narr KL, van Erp T, Poutanen VP, Huttunen M, Lonnqvist J, Standertskjold-Nordenstam CG, Kaprio J, Khaledy M, Dail R, Zoumalan CI, Toga AW (2001) Genetic influences on brain structure. Nat Neurosci 4(12):1253–1258CrossRefPubMedGoogle Scholar
  39. Wallace GL, Eric Schmitt J, Lenroot R, Viding E, Ordaz S, Rosenthal MA, Molloy EA, Clasen LS, Kendler KS, Neale MC, Giedd JN (2006) A pediatric twin study of brain morphometry. J Child Psychol Psychiatry 47(10):987–993CrossRefPubMedGoogle Scholar
  40. Wechsler D (1967) Wechsler preschool and primary scale of intelligence. The Psychological Corporation, San AntonioGoogle Scholar
  41. Wechsler D (1974) Wechsler intelligence scale for children-R. The Psychological Corporation, San AntonioGoogle Scholar
  42. Wechsler D (1981) Wechsler adult intelligence scale-revised. The Psychological Corporation, San AntonioGoogle Scholar
  43. Wechsler D (1989) Wechsler preschool and primary scale of intelligence-revised. The Psychological Corporation, San AntonioGoogle Scholar
  44. Wechsler D (1991) Wechsler intelligence scale for children, 3rd edn. The Psychological Corporation, San AntonioGoogle Scholar
  45. Wechsler D (1999) Wechsler abbreviated scale of intelligence. The Psychological Corporation, San AntonioGoogle Scholar
  46. Wechsler D (2002) Wechsler preschool and primary scale of intelligence, 3rd edn. The Psychological Corporation, San AntonioGoogle Scholar
  47. Zijdenbos AP, Forghani R, Evans AC (2002) Automatic “pipeline” analysis of 3-D MRI data for clinical trials: application to multiple sclerosis. IEEE Trans Med Imaging 21(10):1280–1291CrossRefPubMedGoogle Scholar

Copyright information

© US Government  2010

Authors and Affiliations

  • Gregory L. Wallace
    • 1
    Email author
  • Nancy Raitano Lee
    • 1
  • Elizabeth C. Prom-Wormley
    • 2
  • Sarah E. Medland
    • 2
    • 3
  • Rhoshel K. Lenroot
    • 1
  • Liv S. Clasen
    • 1
  • James E. Schmitt
    • 2
  • Michael C. Neale
    • 2
  • Jay N. Giedd
    • 1
  1. 1.Child Psychiatry Branch, National Institute of Mental HealthNational Institutes of HealthBethesdaUSA
  2. 2.Virginia Institute for Psychiatric and Behavioral GeneticsVirginia Commonwealth UniversityRichmondUSA
  3. 3.Genetic Epidemiology UnitQueensland Institute of Medical ResearchBrisbaneAustralia

Personalised recommendations