Here we report on detailed three-dimensional maps revealing how brain structure is influenced by individual genetic differences. A genetic continuum was detected in which brain structure was increasingly similar in subjects with increasing genetic affinity. Genetic factors significantly influenced cortical structure in Broca's and Wernicke's language areas, as well as frontal brain regions (r2MZ > 0.8, p < 0.05). Preliminary correlations were performed suggesting that frontal gray matter differences may be linked to Spearman's g, which measures successful test performance across multiple cognitive domains (p < 0.05). These genetic brain maps reveal how genes determine individual differences, and may shed light on the heritability of cognitive and linguistic skills, as well as genetic liability for diseases that affect the human cortex.
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Collins, F. S. & McKusick, V. A. Implications of the Human Genome Project for medical science. JAMA 285, 540–544 (2001).
Huerta, M. F. & Koslow, S. H. Neuroinformatics: opportunities across disciplinary and national borders. Neuroimage 4, 4–6 (1996).
Plomin, R. & Loehlin, J. C. Direct and indirect IQ heritability estimates: a puzzle. Behav. Genet. 19, 331–342 (1989).
McClearn, G. E. et al. Substantial genetic influence on cognitive abilities in twins 80 or more years old. Science 276, 1560–1563 (1997).
Alarcón, M., Plomin, R., Fulker, D. W., Corley, R. & DeFries, J. C. Multivariate path analysis of specific cognitive abilities data at 12 years of age in the Colorado Adoption Project. Behav. Genet. 28, 255–264 (1998).
Eley, T. C. & Plomin, R. Genetic analyses of emotionality. Curr. Opin. Neurobiol. 7, 279–284 (1997).
Tramo, M. J. et al. Brain size, head size, and intelligence quotient in monozygotic twins. Neurology 50, 1246–1252 (1998).
Oppenheim, J. S., Skerry, J. E., Tramo, M. J. & Gazzaniga, M. S. Magnetic resonance imaging morphology of the corpus callosum in monozygotic twins. Ann. Neurol. 26, 100–104 (1989).
Pfefferbaum, A., Sullivan, E. V., Swan, G. E. & Carmelli, D. Brain structure in men remains highly heritable in the seventh and eighth decades of life. Neurobiol. Aging 21, 63–74 (2000).
Biondi, A. et al. Are the brains of monozygotic twins similar? A three-dimensional MR study. Am. J. Neuroradiol. 19, 1361–1367 (1998).
Bartley, A. J., Jones, D. W. & Weinberger, D. R. Genetic variability of human brain size and cortical gyral patterns. Brain 120, 257–269 (1997).
Thompson, P. M. et al. Cortical change in Alzheimer's disease detected with a disease-specific population-based brain atlas. Cereb. Cortex 11, 1–16 (2001).
Giedd, J. N. et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nat. Neurosci. 2, 861–863 (1999).
Kaprio, J., Koskenvuo, M. & Rose, R. J. Change in cohabitation and intrapair similarity of monozygotic (MZ) cotwins for alcohol use, extraversion, and neuroticism. Behav. Genet. 20, 265–276 (1990).
Cannon, T. D. et al. The inheritance of neuropsychological dysfunction in twins discordant for schizophrenia. Am. J. Hum. Gen. 67, 369–382 (2000).
Zijdenbos, A. P. & Dawant, B. M. Brain segmentation and white matter lesion detection in MR images. Crit. Rev. Biomed. Eng. 22, 401–465 (1994).
Sowell, E. R. et al. In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nat. Neurosci. 2, 859–861 (1999).
MacDonald, D., Avis, D. & Evans, A. C. Multiple surface identification and matching in magnetic resonance images. Proc. SPIE 2359, 160–169 (1994).
Wright, I. C. et al. A voxel-based method for the statistical analysis of gray and white matter density applied to schizophrenia. Neuroimage 2, 244–252 (1995).
Ashburner, J. & Friston, K. J. Voxel-based morphometry—the methods. Neuroimage 11, 805–821 (2000).
Thompson, P. M., Woods, R. P., Mega, M. S. & Toga, A. W. Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain. Hum. Brain Mapp. 9, 81–92 (2000).
Falconer, D. S. Introduction to Quantitative Genetics Edn. 3 (Longman, Essex, UK, 1989).
Neale, M. C. & Cardon, L. R. Methodology for Genetic Studies of Twins and Families (Kluwer Academic, Boston, 1992).
Feldman, M. W. & Otto, S. P. Twin studies, heritability, and intelligence. Science 278, 1383–1384 (1997).
Loehlin, J. C. & Nichols, R. C. Heredity, Environment and Personality (Univ. of Texas Press, Austin, Texas, 1976).
Thompson, P. M. et al. in Handbook on Medical Image Analysis (ed. Fitzpatrick, M.) 1066–1131 (SPIE, Bellingham, Washington, 2000).
Rajkowska, G. & Goldman-Rakic, P. S. Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System. Cereb. Cortex 5, 323–337 (1995).
Smith, C. in Textbook of Human Genetics (eds. Fraser, G. & Mayo, O. Blackwell, Oxford, 1975).
Huntley, R. M. C. in Genetic and Environmental Factors in Human Ability (eds. Meade, J. E. & Parkes, A. S., Oliver and Boyd, Edinburgh, Scotland, 1966).
Gayan, J. & Olson, R. K. Reading disability: evidence for a genetic etiology. Eur. Child Adolesc. Psychiatry 8, 52–55 (1999).
Pennington, B. F. et al. A twin MRI study of size variations in human brain. J. Cogn. Neurosci. 12, 223–232 (2000).
Tramo, M. J. et al. Surface area of human cerebral cortex and its gross morphological subdivisions. J. Cogn. Neurosci. 7, 292–301 (1995).
Devlin, B., Daniels, M. & Roeder, K. The heritability of IQ. Nature 388, 468–471 (1997).
Finkel, D. et al. Longitudinal and cross-sectional twin data on cognitive abilities in adulthood: the Swedish adoption/twin study of aging. Devel. Psychol. 34, 1400–1413 (1998).
Swan, G. E. et al. Heritability of cognitive performance in aging twins. The National Heart, Lung, and Blood Institute Twin Study. Arch. Neurol. 47, 259–262 (1990).
Loehlin, J. C. Partitioning environmental and genetic contributions to behavioral development. Am. Psychol. 44, 1285–1292 (1989).
Chipuer, H. M., Rovine, M. J., Plomin, R. LISREL Modeling: genetic and environmental influences on IQ revisited. Intelligence 14, 11–29 (1990).
Plomin, R. & Petrill, S.A. Genetics and intelligence: what's new? Intelligence 24, 53–78 (1997).
Duncan, J. et al. A neural basis for general intelligence. Science 289, 457–460 (2000).
Funahashi, S., Bruce, C. J. & Goldman-Rakic, P. S. Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. J. Neurophysiol. 61, 331–349 (1989).
Rutter, M., Silberg, J., O'Connor, T. & Simonoff, E. Genetics and child psychiatry: I. Advances in quantitative and molecular genetics. J. Child Psychol. Psychiatry 40, 3–18 (1999).
Williams, R. W., Strom, R. C., & Goldowitz, D. Natural variation in neuron number in mice is linked to a major quantitative trait locus on Chr 11. J. Neurosci. 18, 138–146 (1998).
Hill, L. et al. DNA pooling and dense marker maps: a systematic search for genes for cognitive ability. Neuroreport 10, 843–848 (1999).
Cannon, T. D. et al. Regional gray matter, white matter, and cerebrospinal fluid distributions in schizophrenic patients, their siblings, and controls. Arch. Gen. Psychiatry 51, 651–661 (1998).
Weinberger, D. R., DeLisi, L. E., Neophytides, A. N. & Wyatt, R. J. Familial aspects of CT scan abnormalities in chronic schizophrenic patients. Psychiatry Res. 4, 65–71 (1981).
Suddath, R. L. et al. Anatomical abnormalities in the brains of monozygotic twins discordant for schizophrenia. N. Engl. J. Med. 322, 789–794 (1990).
Kreft, I. & de Leeuw, J. Introducing Multilevel Modeling (Sage, London, 1998).
Littell, R. C., Milliken, G. A., Stroup, W. W. & Wolfinger, R. D. SAS System for Mixed Models (SAS Institute, Cary, North Carolina, 1996).
Hedeker, D., Gibbons, R. D. & Flay, B. R. Random-effects regression models for clustered data with an example from smoking prevention research. J. Consult. Clin. Psychol. 62, 757–765 (1994).
Grant support was provided by a P41 Resource Grant from the National Center for Research Resources (P.T., A.W.T.; RR13642) and by a National Institute of Mental Health grant (T.D.C.). Additional support for algorithm development was provided by the National Library of Medicine, NINDS, the National Science Foundation, and a Human Brain Project grant to the International Consortium for Brain Mapping, funded jointly by NIMH and NIDA. Special thanks go to U. Mustonen, A. Tanksanen, T. Pirkola, and A. Tuulio-Henriksson for their contributions to subject recruitment and assessment.
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Thompson, P., Cannon, T., Narr, K. et al. Genetic influences on brain structure. Nat Neurosci 4, 1253–1258 (2001). https://doi.org/10.1038/nn758
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