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Quantitative genetic analysis of longitudinal trends in adoption designs with application to IQ in the Colorado Adoption Project

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Abstract

A factor model is presented that provides for either multivariate or developmental specification of longitudinal genetic and environmental effects in the presence of assortative mating and cultural transmission. Delta path methods are employed for the treatment of assortative mating and selective placement effects. The proportions of genetic and environmental variance and covariance attributable to assortative mating and cultural transmission are modeled explicitly. The model was applied to cognitive ability data on 493 families in the Colorado Adoption Project by means of maximum-likelihood pedigree analysis. A test of the assumption of multivariate normality of error provided an additional model criterion beyond the log-likelihood ratio statistic. No significant effects were found for cultural transmission, genetic-environmental covariance, or selective placement. The results suggest that the phenotypic stability of IQ during early childhood is largely, if not entirely, genetic in origin and that these longitudinal genetic effects can be represented most parsimoniously in the form of developmental transmission.

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References

  • Anderson, T. W. (1960). Some stochastic process models for intelligence test scores. In Arrow, K. J., Karlin, S., and Suppes, P. (eds.),Mathematical Methods in the Social Sciences, Standard University Press, Stanford, Calif., pp. 205–220.

    Google Scholar 

  • Anderson, T. W. (1971).The Statistical Anaysis of Time Series, John Wiley and Sons, New York.

    Google Scholar 

  • Bayley, N. (1949). Consistency and variability in the growth of intelligence from birth to eighteen years.J. Genet. Psychol. 75:165–196.

    Google Scholar 

  • Bayley, N. (1969).Manual for the Bayley Scales of Infant Development, Psychological Corporation, New York.

    Google Scholar 

  • Boomsma, D. I., and Molenaar, P. C. M. (1987). The genetic analysis of repeated measures. I. Simplex models.Behav. Genet. 17:111–123.

    Google Scholar 

  • Bronshtein, I. N., and Semendyayev, K. A. (1985).Handbook of Mathematics, Van Nostrand Reinhold, New York.

    Google Scholar 

  • Carey, G. (1985). Sibling imitation and contrast effects.Behav. Genet. 15:319–341.

    Google Scholar 

  • Carey, G. (1986). A general multivariate approach to linear modeling in human genetics.Am. J. Hum. Genet. 39:775–786.

    Google Scholar 

  • CERN (1977).MINUIT: A System for Function Minimization and Analysis of the Parameter Errors and Correlations, European Organization for Nuclear Research, Geneva, Switzerland.

    Google Scholar 

  • Cloninger, C. R. (1980). Interpretation of intrinsic and extrinsic structural relations by path analysis: Theory and application to assortative mating.Genet. Res. 36, 133–145.

    Google Scholar 

  • Corey, L. A., Eaves, L. J., Mellen, B. G., and Nance, W. E. (1986). Testing for developmental changes in gene expression on resemblance for quantitative traits in kinships of twins: Application to height, weight, and blood pressure.Genet. Epidemiol. 3:73–83.

    Google Scholar 

  • Corley, R. P. (1987).Genetic and Environmental Continuity Among Measures of General Cognitive Ability in Infancy, Early childhood, and Adulthood Using Combined Parent-Offspring and Sibling Data from the Colorado Adoption Project, Unpublished doctoral dissertation, University of Colorado, Boulder.

    Google Scholar 

  • Crow, J. F., and Kimura, M. (1970).An Introduction to Population Genetics Theory, Harper & Row, New York.

    Google Scholar 

  • DeFries, J. C., Johnson, R. C., Kuse, A. R., McClearn, G. E., Polovina, J., Vandenberg, S. G., and Wilson, J. R. (1979). Familial resemblance for specific cognitive abilities.Behav. Genet. 9:23–43.

    Google Scholar 

  • DeFries, J. C., Plomin, R. Vandenberg, S. G., and Kuse, A. R. (1981). Parent-offspring resemblance for cognitive abilities in the Colorado Adoption Project: Biological, adoptive, and control parents and one-year-old children.Intelligence 5:245–277.

    Google Scholar 

  • DeFries, J. C., Plomin, R., and LaBuda, M. C. (1987). Genetic stability of cognitive development from childhood to adulthood.Dev. Psychol. 23:4–12.

    Google Scholar 

  • Eaves, L. J. (1976). A model for sibling effects in man.Heredity 36:205–214.

    Google Scholar 

  • Eaves, L. J., Last, K. A., Young, P. A., and Martin, N. G. (1978). Model-fitting approaches to the analysis of human behavior.Heredity 41:249–320.

    Google Scholar 

  • Eaves, L. J., Long, J., and Heath, A. C. (1986). A theory of developmental change in quantitative phenotypes applied to cognitive development.Behav. Genet. 16:143–162.

    Google Scholar 

  • Fisher, R. A. (1918). The correlation between relatives on the supposition of Mendelian inheritance.Trans. Roy. Soc. Edinburgh 52:399–433.

    Google Scholar 

  • Frederiksen, C. H., and Rotondo, J. A. (1979). Time-series models and the study of longitudinal change. In Nesselroade, J. R., and Baltes, P. B. (eds.),Longitudinal Research in the Study of Behavior and Development, Academic Press, New York, pp. 111–153.

    Google Scholar 

  • Fulker, D. W. (1982). Extensions of the classical twin method. In Bonné-Tamir, B., Cohen T., and Goodman, R. M. (eds.),Human Genetics, Part A: The Unfolding Genome, Alan R. Liss, New York, pp. 395–406.

    Google Scholar 

  • Fulker, D. (1988). Genetic and cultural transmission in human behavior. In Weir, B. S., Eisen, E. J., Goodman, M. M., and Namkoong, G. (eds.),Proceedings of the Second International Conference on Quantitative Genetics, Sinauer, Sunderland, Mass., pp. 318–340.

    Google Scholar 

  • Fulker, D. W., Baker, L. A., and Bock, R. D. (1983). Estimating components of covariance using LISREL.Data Anal. 1:5–8.

    Google Scholar 

  • Fulker, D. W., and DeFries, J. C. (1983). Genetic and environmental transmission in the Colorado Adoption Project: Path analysis.Br. J. Math. Stat. Psychol. 36:175–188.

    Google Scholar 

  • Guttman, L. (1954). A new approach to factor analysis: The radex. In Lazarsfeld, P. F. (ed.),Mathematical Thinking in the Social Sciences, Free Press, Glencoe, Ill., pp. 258–349.

    Google Scholar 

  • Hewitt, J. K., Eaves, L. J., Neale, M. C., and Meyer, J. M. (1988). Resolving causes of developmental continuity or “tracking”. I. Longitudinal twin studies during growth.Behav. Genet. 18:133–151.

    Google Scholar 

  • Hopper, J. L., and Mathews, J. D. (1982). Extensions to multivariate normal models for pedigree analysis.Ann. Hum. Genet. 46:373–383.

    Google Scholar 

  • Jöreskog, K. G. (1970). Estimation and testing of simplex models.Br. J. Math. Stat. Psychol. 23:121–145.

    Google Scholar 

  • Jöreskog, K. G. (1974). Analyzing psychological data by structural analysis of covariance matrices. In Krantz, D. H., Atkinson, R. G., Luce, R. D., and Suppes, P. (eds.),Contemporary Developments in Mathematical Psychology, Vol. II. Measurement, Psychophysics, and Neural Information Processing, W. H. Freeman, San Francisco, pp. 1–56.

    Google Scholar 

  • Jöreskog, K. G. (1978). Structural analysis of covariance and correlation matrices.Psychometrika 43:443–447.

    Google Scholar 

  • Jöreskog, K. G. (1979). Statistical estimation of structural models in longitudinal-developmental investigations. In Nesselroade, J. R., and Baltes, P. B. (eds.),Longitudinal Research in the Study of Behavior and Development, Academic Press, New York, pp. 303–351.

    Google Scholar 

  • Jöreskog, K. G., and Sörbom, D. (1985). Simultaneous analysis of longitudinal data from several cohorts. In Mason, W. M., and Fienberg, S. E. (eds.),Cohort Analysis in Social Research, Springer-Verlag, New York, pp. 323–341.

    Google Scholar 

  • Korn, G. A., and Korn, T. M. (1968).Mathematical Handbook for Scientists and Engineers, 2nd ed., McGraw-Hill, New York.

    Google Scholar 

  • LaBuda, M. C., DeFries, J. C., Plomin, R., and Fulker, D. W. (1986). Longitudinal stability of cognitive ability from infancy to early childhood: Genetic and environmental etiologies.Child Dev. 57:1142–1150.

    Google Scholar 

  • Lange, K., Westlake, J., and Spence, M. A. (1976). Extensions to predigree analysis. III. Variance components by the scoring method.Ann. Hum. Genet. 39:485–491.

    Google Scholar 

  • Numerical Algorithms Group (1984).NAG Fortran Library Manual—Mark 11, Numerical Algorithms Group, Oxford.

    Google Scholar 

  • Pearson, K. (1902). Mathematical contributions to the theory of evolution. XI. On the influence of natural selection on the variability and correlation of organs.Phil. Trans. Roy. Soc. London,Ser. A 200:1–66.

    Google Scholar 

  • Phillips, D. K. (1988).Quantitative Genetic Analysis of Longitudinal Trends in IQ in the Colorado Adoption Project. Unpublished doctoral dissertation, University of Colorado, Boulder.

    Google Scholar 

  • Phillips, K. (1989). Delta path methods for modeling the effects of multiple selective associations in adoption designs.Behav. Genet. 19:609–620.

    Google Scholar 

  • Phillips, K., Fulker, D. W., and Rose, R. J. (1987a). Path analysis of seven fear factors in adult twin and sibling pairs and their parents.Genet. Epidemiol. 4:345–355.

    Google Scholar 

  • Phillips, K., Plomin, R., Fulker, D. W., and DeFries, J. C. (1987b). General cognitive ability of 7-year-old children in the Colorado Adoption Project (CAP): Path analysis of genetic and environmental transmission.Behav. Genet. 17:635 (abstr.).

    Google Scholar 

  • Plomin, R., and DeFries, J. C. (1983). The Colorado Adoption Project.Child Dev. 54:276–289.

    Google Scholar 

  • Plomin, R., and DeFries, J. C. (1985).Origins of Individual Differences in Infancy: The Colorado Adoption Project, Academic Press, Orlando, Fla.

    Google Scholar 

  • Plomin, R., DeFries, J. C., and Loehlin, J. C. (1977). Genotype-environment interaction and correlation in the analysis of human behavior.Psychol. Bull. 84:309–322.

    Google Scholar 

  • Rice, J., Cloninger, C. R., and Reich, T. (1978). Multifactorial inheritance with cultural transmission and assortative mating. I. Description and basic properties of unitary models.Am. J. Hum. Genet. 30:618–643.

    Google Scholar 

  • Stephens, M. A. (1974). EDF statistics for goodness of fit and some comparisons.J. Am. Stat. Assoc. 69:730–737.

    Google Scholar 

  • Terman, L. M., and Merrill, M. A. (1973).Stanford-Binet Intelligence Scale: 1972 Norms Edition, Houghton-Mifflin, Boston.

    Google Scholar 

  • Van Eerdewegh, P. (1982).Statistical Selection in Multivariate Systems with Applications in Quantitative Genetics, Unpublished doctoral dissertation, Washington University, St. Louis, Mo.

    Google Scholar 

  • Vogler, G. P. (1985). Multivariate path analysis of familial resemblance.Genet. Epidemiol. 2:35–53.

    Google Scholar 

  • Wechsler, D. (1974).Manual for the Wechsler Intelligence Scale for Children-Revised, Psychological Corporation, New York.

    Google Scholar 

  • Wilson, R. S. (1983). The Louisville Twin Study: Developmental synchronies in behavior.Child Dev. 54:298–316.

    Google Scholar 

  • Wright, S. (1921). Systems of mating. I. The biometric relations between parent and offspring.Genetics 6:111–123.

    Google Scholar 

  • Wright, S. (1968).Evolution and Genetics of Populations, Vol. I., University of Chicago Press, Chicago.

    Google Scholar 

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This research was supported in part by Grants HD-10333, HD-18426, and HD-19802 from the National Institute of Child Health and Human Development (NICHD), by Grant BNS-8200310 from the National Science Foundation, and by a grant from the Spencer Foundation. Data analyses were made possible by grants of supercomputer time for use at the Princeton John von Neumann Center awarded by the University of Colorado as a member of the Consortium for Scientific Computing to David Fulker and Gregory Carey and by Grant NSF-14003 from the National Science Foundation to David Fulker. The paper was written while the first author was supported by Training Grant HD-07289 from the NICHD and by a grant from the John D. and Catherine T. MacArthur Foundation. It is based on a dissertation presented by the first author in partial fulfillment of the requirements for the Ph.D degree in psychology. Preparation of the manuscript was facilitated by Grant RR-07013-20 awarded to the University of Colorado by the Biomedical Research Support Grant Program, Division of Research Resources, National Institutes of Health.

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Phillips, K., Fulker, D.W. Quantitative genetic analysis of longitudinal trends in adoption designs with application to IQ in the Colorado Adoption Project. Behav Genet 19, 621–658 (1989). https://doi.org/10.1007/BF01066028

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