Behavior Genetics

, 36:65 | Cite as

Cognitive Traits Link to Human Chromosomal Regions

  • Steven BuyskeEmail author
  • Marsha E. Bates
  • Neda Gharani
  • Tara C. Matise
  • Jay A. Tischfield
  • Paul Manowitz


Human cognition in normal and disease states is both environmentally and genetically mediated. Except for measures of language-specific abilities, however, few cognitive measures have been associated with specific genes or chromosomal regions. We performed genome-wide linkage analysis of five neuropsychological tests in the Collaborative Study on Genetics of Alcoholism sample. The sample included 1579 individuals (53% female, 76% White Non-Hispanic) in 217 families. There were 390 markers with mean intermarker distance of 9.6 cM. Performance on the Digit Symbol Substitution Test, a component of the Wechsler Adult Intelligence Scale-R, showed significant linkage to 14q11.2 and suggestive linkage to 14q24.2. This test of sustained visual attention also involves visual-motor coordination and executive functions. Performance on the WAIS-R Digit Span Test of immediate memory and mental flexibility showed suggestive linkage to 11q25. Although the validity of these results beyond populations with a susceptibility for alcohol dependence is unclear, these results are among the first linkage results for non-language components of cognition.


Cognitive trait Digit Span Digit Symbol genetic linkage quantitative trait loci Wechlser Adult Intelligence Scale-R 



We thank Chunsheng He and Xiangyang Kong for computational assistance, William G. Johnson for background information, and Ann Jurecic for editorial assistance. Data were provided by the Collaborative Study on the Genetics of Alcoholism (U10AA008401). This work was supported by grants from the National Institute on Alcohol Abuse and Alcoholism (S.B., M.E.B., J.A.T., P.M.) and the National Institute of Mental Health (S.B., N.G., T.C.M., and J.A.T.).


  1. Abecasis G.R., Cherny S.S., Cookson W.O., Cardon L.R. (2002). Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30(1):97–101CrossRefPubMedGoogle Scholar
  2. Almasy L., Blangero J. (1998). Multipoint quantitative-trait linkage analysis in general pedigrees. Am. J. Hum. Genet. 62(5):1198–1211CrossRefPubMedGoogle Scholar
  3. Bates M, Convit A. (1999). Neuropsychology and neuroimaging of alcohol and illicit drug abuse. In: Calev A. (ed.). The Assessment of Neuropsychological Functions in Psychiatric Disorders. American Psychiatric Press, Washington, DC, pp. 373–445Google Scholar
  4. Begleiter H., Reich T., Hesselbrock V., Porjesz B., Li T.-K., Schuckit M.A., Edenberg H.J. (1995). The collaborative study on the genetics of alcoholism. Alcohol Health Res. World 19:228–236Google Scholar
  5. Bierut L.J., Rice J.P., Goate A., Hinrichs A.L., Saccone N.L., Foroud T., Edenberg H.J., Cloninger C.R., Begleiter H., Conneally P.M., Crowe R.R., Hesselbrock V., Li T.K., Nurnberger Jr. J. I., Porjesz B., Schuckit M.A., Reich T. (2004). A genomic scan for habitual smoking in families of alcoholics: common and specific genetic factors in substance dependence. Am. J. Med. Genet. 124A:19–27CrossRefPubMedGoogle Scholar
  6. Block J.B., (1968). Hereditary components in the performance of twins on the WAIS. In: Vandenberg S. (ed.). Progress in Human Behavior Genetics. John Hopkins University Press, Baltimore MDGoogle Scholar
  7. Boehnke M. (1991). Allele frequency estimation from data on relatives. Am. J. Hum. Genet. 48(1):22–25PubMedGoogle Scholar
  8. Egan M.F., Goldberg T.E., Kolachana B.S., Callicott J.H., Mazzanti C.M., Straub R.E., Goldman D., Weinberger D.R. (2001). Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc. Natl. Acad. Sci. USA 98(12):6917–6922CrossRefPubMedGoogle Scholar
  9. Egan M.F., Kojima M., Callicott J.H., Goldberg T.E., Kolachana B.S., Bertolino A., Zaitsev E., Gold B., Goldman D., Dean M., Lu B., Weinberger D. R. (2003). The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 112(2):257–269CrossRefPubMedGoogle Scholar
  10. Feskens E.J.M., Havekes L.M., Kalmijn S., Knijff P.D., Launer L.J., Kromhout D. (1994). Apolipoprotein E4 allele and cognitive decline in elderly men. Br. Med. J. 309:1202–1206Google Scholar
  11. Foroud T., Edenberg H.J., Goate A., Rice J., Flury L., Koller D.L., Bierut L.J., Conneally P.M., Nurnberger J.I., Bucholz K.K., Li T.K., Hesselbrock V., Crowe R., Schuckit M., Porjesz B., Begleiter H., Reich T. (2000). Alcoholism susceptibility loci: Confirmation studies in a replicate sample and further mapping. Alcohol. Clin. Exp. Res. 24:933–945CrossRefPubMedGoogle Scholar
  12. Goldberg T.E., Weinberger D.R. (2004). Genes and the parsing of cognitive processes. Trends Cogn. Sci. 8(7):325–335CrossRefPubMedGoogle Scholar
  13. Goldman-Rakic P.S. (1987). Development of cortical circuitry and cognitive function. Child Dev. 58:601–622PubMedCrossRefGoogle Scholar
  14. Green P., Falls K., Crooks S. (1990). Documentation for CRIMAP, version 2.4. Washington University School of Medicine, St. Louis, MOGoogle Scholar
  15. Gregoire J., Van der Linden M., (1997). Effects of age on forward and backward digit spans. Aging Neuropsychol. Cogn. 4:140–149CrossRefGoogle Scholar
  16. Heaton R., Grant I., Matthews C. (1992). HRB Norms Program. Psychological Assessment Resources, Inc, Lutz, FloridaGoogle Scholar
  17. Hester R.L., Kinsella G.J., Ong B. (2004). Effect of age on forward and backward span tasks. J. Int. Neuropsychol. Soc. 10:475–481CrossRefPubMedGoogle Scholar
  18. Horn J.L., Cattell R.B. (1966). Refinement and test of theory of fluid and crystallized general intelligences. J. Educ. Psychol. 57(5):253–270PubMedCrossRefGoogle Scholar
  19. Kaplan H.I., Sadock B.J. (1995). Comprehensive Textbook of Psychiatry/VI. Williams & Wilkins, Baltimore, MDGoogle Scholar
  20. Kruglyak L., Daly M.J., Reeve-Daly M.P., Lander E.S. (1996). Parametric and nonparametric linkage analysis: a unified multipoint approach. Am. J. Hum. Genet. 58(6):1347–1363PubMedGoogle Scholar
  21. Kruglyak L., Lander E.S. (1998). Faster multipoint linkage analysis using Fourier transforms. J. Comput. Biol. 5(1):1–7PubMedCrossRefGoogle Scholar
  22. Lander E., Kruglyak L. (1995). Genetic dissection of complex traits: Guidelines for interpreting and reporting linkage results. Nat. Genet. 11: 241–247CrossRefPubMedGoogle Scholar
  23. Langley K., Marshall L., van den Bree M., Thomas H., Owen M., O’Donovan M., Thapar A. (2004). Association of the dopamine D4 receptor gene 6-repeat allele with neuropsychological test performance of children with ADHD. Am. J. Psychiatry 161:133–138CrossRefPubMedGoogle Scholar
  24. Lezak M.D. (1995). Neuropsychological Assessment. Oxford University Press, New YorkGoogle Scholar
  25. Merritt H.H., Rowland L.P. (2000). Merritt’s Textbook of Neurology. Lippincott Williams & Wilkins, PhiladelphiaGoogle Scholar
  26. Missler M., Zhang W., Rohlmann A., Kattenstroth G., Hammer R.E., Gottmann K., Sudhof T.C. (2003). Alpha-neurexins couple Ca2+ channels to synaptic vesicle exocytosis. Nature 423(6943):939–948CrossRefPubMedGoogle Scholar
  27. Mukhopadhyay N., Almasy L., Schroeder M., Mulvihill W.P., Weeks D.E. (1999). Mega2, a data-handling program for facilitating genetic linkage and association analyses. Am. J. Hum. Genet. 65:A436Google Scholar
  28. Parkin A.J., Lawrence A. (1994). A dissociation in the relation between memory tasks and frontal lobe tests in the normal elderly. Neuropsychologia, 32:1523–1532CrossRefPubMedGoogle Scholar
  29. Payton A., Holland F., Diggle P., Rabbitt P., Horan M., Davidson Y., Gibbons L., Worthington J., Ollier W.E., Pendleton N. (2003). Cathepsin D exon 2 polymorphism associated with general intelligence in a healthy older population. Mol. Psychiatry 8(1):14–18CrossRefPubMedGoogle Scholar
  30. Plomin R., Hill L., Craig I.W., McGuffin P., Purcell S., Sham P., Lubinski D., Thompson L.A., Fisher P.J., Turic D., Owen M. J. (2001). A genome-wide scan of 1842 DNA markers for allelic associations with general cognitive ability: a five-stage design using DNA pooling and extreme selected groups. Behav. Genet. 31(6):497–509CrossRefPubMedGoogle Scholar
  31. Plomin R., Spinath F.M. (2004). Intelligence: genetics, genes, and genomics. J. Pers. Soc. Psychol. 86(1):112–129CrossRefPubMedGoogle Scholar
  32. Reich T., Edenberg H.J., Goate A., Williams J.T., Rice J.P., Van Eerdewegh P., Foroud T., Hesselbrock V., Schuckit M.A., Bucholz K., Porjesz B., Li T.K., Conneally P.M., Nurnberger Jr. J.I., Tischfield J.A., Crowe R.R., Cloninger C.R., Wu W., Shears S., Carr K., Crose C., Willig C., Begleiter H. (1998). Genome-wide search for genes affecting the risk for alcohol dependence. Am. J. Med. Genet. 81:207–215CrossRefPubMedGoogle Scholar
  33. Reitan R.M., Wolfson D. (1993). The Halstead-Reitan Neuropsychological Test Battery: Theory and Clinical Interpretation. Neuropsychology Press, Tucson, AZGoogle Scholar
  34. Rijsdijk F.V., Vernon P.A., Boomsma D.I. (2002). Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study. Behav. Genet. 32:199–210CrossRefPubMedGoogle Scholar
  35. Robbins T.W. (1998). Dissociating executive functions of the prefrontal cortex. In: Roberts A.C., Robbins T.W., Weiskrantz L., (eds). The Prefrontal Cortex: Executive and Cognitive Functions. Oxford University Press, New YorkGoogle Scholar
  36. Royall D.R., Lauterbach E.C., Cummings J.L., Reeve A., Rummans T.A., Kaufer D.I., LaFrance W.C., Jr., Coffey C.E. (2002). Executive control function: a review of its promise and challenges for clinical research. A report from the Committee on Research of the American Neuropsychiatric Association. J. Neuropsychiatry Clin. Neurosci. 14(4):377–405PubMedGoogle Scholar
  37. Sham P.C., Purcell S., Cherny S.S., Abecasis G.R. (2002). Powerful regression-based quantitative-trait linkage analysis of general pedigrees. Am. J. Hum. Genet. 71: 238–253CrossRefPubMedGoogle Scholar
  38. Spreen O., Strauss E. (1998). A Compendium of Neuropsychological Tests: Administration, Norms and Commentary. Oxford University Press, New YorkGoogle Scholar
  39. Stromswold K. (2001). The heritability of language: a review and meta-analysis of twin, adoption, and linkage studies. Language 77:647–723CrossRefGoogle Scholar
  40. Stuss D.T., Shallice T., Alexander M.P. (1995). A multidisciplinary approach to anterior attentional functions. Ann. N. Y. Acad. Sci. 769:191–211PubMedCrossRefGoogle Scholar
  41. Tambs K., Sundet J.M., Magnus P. (1984). Heritability analysis of the WAIS: a study of twins. Intelligence 8:283–293CrossRefGoogle Scholar
  42. Wechsler D. (1981). WAIS-R Manual. The Psychological Corporation, New YorkGoogle Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • Steven Buyske
    • 1
    • 2
    • 3
    • 6
    Email author
  • Marsha E. Bates
    • 2
    • 5
  • Neda Gharani
    • 3
  • Tara C. Matise
    • 3
  • Jay A. Tischfield
    • 2
    • 3
    • 4
    • 5
  • Paul Manowitz
    • 2
    • 5
  1. 1.Department of StatisticsRutgers UniversityPiscatawayUSA
  2. 2.Center of Alcohol StudiesRutgers UniversityPiscatawayUSA
  3. 3.Department of GeneticsRutgers UniversityPiscatawayUSA
  4. 4.Department of PediatricsUniversity of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical SchoolPiscatawayUSA
  5. 5.Department of PsychiatryUniversity of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical SchoolPiscatawayUSA
  6. 6.Department of StatisticsRutgers UniversityPiscatawayUSA

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