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Quantitative Genetic Analysis of Longitudinal Trends in Height: Preliminary Results from the Louisville Twin Study

Published online by Cambridge University Press:  01 August 2014

K. Phillips  and
A.P. Matheny Jr.
K. Phillips*
Affiliation:
University of Louisville School of Medicine, Kentucky, USA
A.P. Matheny Jr.
Affiliation:
University of Louisville School of Medicine, Kentucky, USA
*
Louisville Twin Study, CDU-HSC-MDR-111, University of Louisville School of Medicine, Louisville KY 40292, USA

Abstract

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A preliminary series of quantitative genetic models was applied to a subset of longitudinal height data, spanning birth to maturity, gathered from twin families in the Louisville Twin Study. Descriptive Cholesky factor parameterization was found to give more satisfactory results than did a system of constraints based on a model of developmental transmission of a time-constant and time-specific factors. The results from application of two autosomal sex-limitation models are contrasted with those from a model specifying both autosomal and sex-chromosomal patterns of inheritance. The latter model was more conducive to parameter reduction. Although these models do not constitute conclusive tests of autosomal sex-limitation versus sex-linkage, the more parsimonious model is consistent with previous research suggesting a stature locus on the long arm of the Y chromosome. Heritability of height is estimated at about 90% or greater from 6 years of age on. Substantial and fairly constant longitudinal genetic correlations are found from 3 years of age on. Shared environmental effects unrelated to parental height were seen for birth length, corrected for gestational age, to height at 3 years of age, but these are not satisfactorily differentiated from possible twin effects in the present sample. The genetic consequences of assortative mating are emphasized since failure to take assortment into account can lead to overestimation of shared environmental effects and under-estimation of genetic effects. The results indicate that about 20% of within-gender variability for mature height can be attributed to the genetic consequences of assortment, even though the phenotypic marital correlation of 0.22 is quite modest. The importance of testing the assumption of multivariate normality underlying the application of the method of maximum-likelihood is also highlighted.

Keywords

HeightLongitudinal analysisAssortative matingGenetic covarianceTwin families
Type
Research Article
Information
Acta geneticae medicae et gemellologiae: twin research , Volume 39 , Issue 2 , April 1990 , pp. 143 - 163
Copyright
Copyright © The International Society for Twin Studies 1990

References

REFERENCES

1.Alvesalo, L, de la Chapelle, A (1981): Tooth sizes in two males with deletions of the long arm of the Y-chromosome. Ann Hum Genet 45:49–54.Google Scholar
2.Alvesalo, L, Tammisalo E (1981): Enamel thickness in 45,X females' permanent teeth. Am J Hum Genet 33:464–469.Google Scholar
3.Alvesalo, L, Tammisalo, E, Therman, E (1987): 47,XXX females, sex chromosomes, and tooth crown structure. Hum Genet 77:345–348.CrossRefGoogle Scholar
4.Brissenden, JEUllrich, A, Francke, U (1984): Human chromosomal mapping of genes for insulin-like growth factors I and II and epidermal growth factor. Nature 310:781–784.CrossRefGoogle ScholarPubMed
5.Bronshtein, IN, Semendyayev, KA (1985): Handbook of Mathematics. New York: Van Nos-trand Reinhold.Google Scholar
6.Burgoyne, PS (1982): Genetic homology and crossing over in the X and Y chromosomes of mammals. Hum Genet 61:85–90.CrossRefGoogle ScholarPubMed
7.Burgoyne, PS (1986): Mammalian X and Y crossover. Nature 319:258–259.Google Scholar
8.CERN (1977): MINUIT: A System for Function Minimization and Analysis of the Parameter Errors and Correlations. Geneva: European Organization for Nuclear Research.Google Scholar
9.Cook, HJ, Brown, WRA, Rappold, GA (1985): Hypervariable telomeric sequences from the human sex chromosomes are pseudoautosomal. Nature 317:687–692.CrossRefGoogle Scholar
10.Crow, JF, Kimura, M (1970): An Introduction to Population Genetics Theory. New York: Harper & Row.Google Scholar
11.Eaves, LJ, Last, KA, Young, PA, Martin, NG (1978): Model-fitting approaches to the analysis of human behavior. Heredity 41:249–320.CrossRefGoogle Scholar
12.Eaves, LJ, Long, J, Heath, AC (1986): A theory of developmental change in quantitative phenotypes applied to cognitive development. Behav Genet 16:143–162.CrossRefGoogle ScholarPubMed
13.Eaves, LJ, Hewitt, JK, Heath, AC (1988): The quantitative genetic study of human developmental change: A model and its limitations. In Weir, BS, Eisen, EJ, Goodman, MM, Namkoong, G (eds): Proceedings of the Second International Conference on Quantitative Genetics. Sunderland, Mass: Sinauer.Google Scholar
14.Eaves, LJ, Eysenck, HJ, Martin, NG (1989): Genes, Culture and Personality: An Empirical Approach. London: Academic Press.Google Scholar
15.Fishbein, S (1977): Intra-pair similarity in physical growth of monozygotic and dizygotic twins during puberty. Ann Hum Biol 4:417–430.CrossRefGoogle Scholar
16.Fulker, DW, Baker, LA, Bock, RD (1983): Estimating components of covariance using LIS-REL. Data Anal 1:5–8.Google Scholar
17.Garn, SM, Rohmann, CG (1962): X-linked inheritance of developmental timing in man. Nature 196:695–696.CrossRefGoogle ScholarPubMed
18.Gedda, L, Brenci, G, Gatti, I (1981): Low birth weight in twins versus singletons: Separate entities and different implications for child growth and survival. Acta Genet Med Gemellol 30:1–8.Google ScholarPubMed
19.Haley, CS (1984): Detecting sex-associated variation with the families of MZ and DZ twins. Acta Genet Med Gemellol 33:287–301.Google Scholar
20.Hopper, JL (1986): On analysis of path models by the multivariate normal model for pedigree analysis. Genet Epidemiol 3:279–281.CrossRefGoogle ScholarPubMed
21.Hopper, JL, Mathews, JD (1982): Extensions to multivariate normal models for pedigree analysis. Ann Hum Genet 46:373–383.Google Scholar
22.Kora, GA, Korn, TM (1968): Mathematical Handbook for Scientists and Engineers, 2nd ed. New York: McGraw-Hill.Google Scholar
23.Leroy, B, Lefort, F, Neveu, P, Risse, RJ, Trévise, P, Jeny, R (1982): Intrauterine growth charts for twin fetuses. Acta Genet Med Gemellol 31:199–206.Google ScholarPubMed
24.Meyer, JM (1989): Modeling the Inheritance of Time to Onset. Unpublished doctoral dissertation. Richmond, Virginia: Virginia Commonwealth University.Google Scholar
25.Morton, NE (1957): Further scoring types in sequential linkage tests, with a critical review of autosomal and partial sex linkage in man. Am J Hum Genet 9:55–75.Google Scholar
26.Orvanová, E, Susanne, C (1988): Twin studies on growth, development and motor performance: A review. Internat J Anthro 3:163–80.Google Scholar
27.Owerbach, D, Rutter, WJ, Martial, JA, Baxter, JD, Shows, TB (1980): Genes for growth hormone, chorionic somatomammotropin and growth hormone-like genes on chromosome 17 in humans. Science 209:289–292.CrossRefGoogle ScholarPubMed
28.Page, DC, Mosher, R, Simpson, EM, Fisher, EMC, Mardon, G, Pollack, J, McGillivray, B, de la Chapelle, A, Brown, LG (1987): The sex-determining region of the human Y chromosome encodes a finger protein. Cell 51:1091–1104.CrossRefGoogle ScholarPubMed
29.Phillips, K, Fulker, DW (1989): Quantitative genetic analysis of longitudinal trends in adoption designs with application to IQ in the Colorado Adoption Project. Behav Genet 19:621–658.CrossRefGoogle ScholarPubMed
30.Rouyer, F, Simmler, M, Johnsson, C, Vergnaud, G, Cooke, HJ, Weissenbach, J (1986): A gradient of sex linkage in the pseudoautosomal region of the human sex chromosomes. Nature 319: 291–295.Google Scholar
31.Simmler, M, Rouyer, F, Vergnaud, G, Nyström-Lahti, M, Ngo, KY, de la Chapelle, A, Weissenbach, J (1985): Pseudoautosomal DNA sequences in the pairing region of the human sex chromosomes. Nature 317:692–697.Google Scholar
32.Stephens, MA (1974): EDF statistics for goodness of fit and some comparisons. J Am Stat Assoc 69:730–737.Google Scholar
33.Tanner, JM, Prader, A, Habich, H, Ferguson-Smith, MA (1959): Genes on the Y chromosome influencing rate of maturation in man. The Lancet 2:141–144.CrossRefGoogle Scholar
34.Tricoli, JV, Rail, LB, Scott, J, Bell, GI, Shows, TB (1984): Localization of insulin-like growth factor genes to human chromosomes 11 and 12. Nature 310:784–786.Google Scholar
35.Van Eerdewegh, P (1982): Statistical Selection in Multivariate Systems with Applications in Quantitative Genetics. Unpublished doctoral dissertation. St. Louis, Missouri: Washington University.Google Scholar
36.Wilson, RS (1981): Synchronized developmental pathways for infant twins. In Gedda, L, Parisi, P, Nance, WE (eds.): Twin Research 3 Part B: Intelligence, Personality, and Development. New York: Alan R. Liss.Google Scholar
37.Wilson, RS (1983): The Louisville Twin Study: Developmental synchronies in behavior. Child Dev 54:298–316.Google Scholar
38.Wilson, RS (1984): Twins and chronogenetics: Correlated pathways of development. Acta Genet Med Gemellol 33:149–157.Google ScholarPubMed
39.Wilson, RS, Matheny, AP Jr (1986): Behavior-genetics research in infant temperament: The Louisville Twin Study. In Plomin, R, Dunn, J (eds.): The Study of Temperament: Changes, Continuities, and Challenges. Hillsdale NJ: Lawrence Erlbaum.Google Scholar
40.Wright, S (1921): Systems of mating. I. The biometric relations between parent and offspring. Genetics 6:111–123.CrossRefGoogle ScholarPubMed
41.Yamada, K, Ohta, M, Yoshimura, K, Hasekura, H (1981): A possible association of Y chromosome heterochromatin with stature. Hum Genet 58:268–270.CrossRefGoogle ScholarPubMed