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Testing Twin Means and Estimating Genetic Variance. Basic Methodology for the Analysis of Quantitative Twin Data

Published online by Cambridge University Press:  01 August 2014

Joe C. Christian
Joe C. Christian*
Affiliation:
Department of Medical Genetics, Indiana University School of Medicine, Indianapolis
*
Department of Medical Genetics, Indiana University School of Medicine, 1100 West Michigan Street, Indianapolis, IN 46202, USA

Abstract

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Twin methodology for the analysis of continuously distributed traits is presented as a guideline for initial steps in the analysis of twin data. Tests for heterogeneity of twin means and variances are reviewed along with estimates of genetic variance.

Analysis of twin data appears on the surface to be a rather simple task, but investigators may well be confused by the wealth of choices available for hypothesis testing. This paper is designed to help the less experienced investigator, with perhaps a modest amount of data, begin analysis with maximum attention to testing all testable assumptions of the twin model, and using recent examples of applications of the methods.

Keywords

Twin data analysisGenetic varianceAssociations with twin typeTwin placentationEnvironmental covarianceHeritability estimates
Type
Research Article
Information
Acta geneticae medicae et gemellologiae: twin research , Volume 28 , Issue 1 , January 1979 , pp. 35 - 40
Copyright
Copyright © The International Society for Twin Studies 1979

References

REFERENCES

1.Byton, E, Slavin, B (1974). Serum IgG levels in feto-fetal transfusion syndrome. Arch Dis Childhood 49:908–910.Google Scholar
2.Christian, JC, Kang, KW, Norton, JA Jr (1974). Choice of an estimate of genetic variance from twin data. Am J Hum Genet 26:154–161.Google ScholarPubMed
3.Christian, JC, Feinleib, M, Norton, JA Jr (1975): Statistical analysis of genetic variance in twins. Am J Hum Genet 27:807.Google Scholar
4.Christian, JC, Kang, KW, Nance, WE (1975): Plasma cholesterol in newborn human twins (abstr). J Am Oil Chem 52:123a.Google Scholar
5.Christian, JC, Feinleib, M, Hulley, SB, Castelli, RR, Fabsitz, RR, Garrison, RJ, Borhani, NO, Rosenmann, RH, Wagner, J (1976). Genetics of plasma cholesterol and triglycerides: A study of adult male twins. Acta Genet Med Gemellol 25:145–149.Google Scholar
6.Christian, JC, Uchida, IA (1976): Plasma cholesterol variation in monochorionic and dichorionic mono monozygotic twins (abstr). Excerpta Medica Int Cong Ser 397:28.Google Scholar
7.Christian, JC, Kang, KW, Norton, JA Jr (1977). Comparison of within-pair and among-component estimates of genetic variance from twin data. Am J Hum Genet 29:208–210.Google Scholar
8.Christian, JC, Norton, JA Jr (1977). A proposed test of the difference between the means of monozygotic and dizygotic twins. Acta Genet Med Gemellol 26:49–54.CrossRefGoogle ScholarPubMed
9.Christian, JC (1978): The use of twin registers in the study of birth defects. In Summitt, RL, Bergsma, D (eds): “Cell Surface Factors, Immune Deficiencies, Twin Studies.” New York: Alan R. Liss for The National Foundation-March of Dimes. Birth Defects: Original Article Series XIV: 6A, pp 167–178.Google Scholar
10.Corey, LA, Kang, KW, Christian, JC, Norton, JA Jr, Harris, RE, Nance, WE (1976). Effects of chorion type on variation in cord blood cholesterol of monozygotic twins. Am J Hum Genet 28:433–441.Google Scholar
11.Elston, RC, Boklage, CE (1978): An examination of fundamental assumptions of the twin method. In Nance, WE, Allen, G, Parisi, P (eds): “Twin Research: Part A, Psychology and Methodology.” New York: Alan R. Liss, pp 189–199.Google Scholar
12.Falconer, DS (1960): “Introduction to Quantitative Genetics.” New York: Ronald Press.Google Scholar
13.Feinleib, M, Garrison, RJ, Fabsitz, R, Christian, JC, Hrubec, Z, Borhani, NO, Kannel, WB, Rosenman, R, Schwartz, JT, Wagner, JO (1977). The NHLBI twin study of cardiovascular disease risk factors: Methodology and summary of results. Am J Epidemiol 106:284–295.CrossRefGoogle ScholarPubMed
14.Haseman, JK, Elston, RC (1970). The estimation of genetic variance from twin data. Behav Genet 1:11–19.CrossRefGoogle ScholarPubMed
15.Havlik, R, Garrison, R, Fabsitz, R, Feinleib, M (1977). Genetic variability of clinical chemical values. Clin Chem (Winston-Salem, NC) 23:659–662.Google ScholarPubMed
16.Kempthorne, O, Osborne, RH (1961): The interpretation,of twin data. Am J Hum Genet 13:320–339.Google Scholar
17.Melnick, M, Myrianthopoulos, NC, Christian, JC (in press): The effects of chorion type on variation in IQ in the NCPP twin population. Am J Hum Genet.Google Scholar
18.Nance, WE (1976). Note on the analysis of twin data. Am J Hum Genet 28:297–299.Google Scholar
19.Rao, DC, Morton, NE, Yee, S (1976). Resolution of cultural and biological inheritance by path analysis. Am J Hum Genet 28:228–242.Google Scholar
20.Reed, T, Sprague, FR, Kang, KW, Nance, WE, Christian, JC (1975). Genetic analysis of dermato-glyphic patterns in twins. Hum Hered 25:263–275.CrossRefGoogle Scholar
21.Reed, T, Uchida, IA, Christian, JC (1976): Dermatoglyphic variation in monozygotic twins of differing placental types (abstr). Excerpta Medica Int Cong Ser 397:37.Google Scholar
22.Reed, T, Uchida, IA, Norton, JA Jr, Christian, JC (in press): Comparisons of dermatoglyphic patterns in monochorionic and dichorionic twins. Am J Hum Genet.Google Scholar
23.Sokal, RR, Rohlf, FJ (1969): “Biometry.” San Francisco: WH Freeman.Google Scholar
24.Strong, SJ, Corney, G (1967): The placenta in twin pregnancy. Oxford: Pergamon Press.Google Scholar