Behavior Genetics

, Volume 17, Issue 4, pp 331–341

Testing genetic models for multiple symptoms: An application to the genetic analysis of liability to depression

  • L. J. Eaves
  • N. G. Martin
  • A. C. Heath
  • K. S. Kendler
Article

Abstract

A model is presented which allows for the contribution of genes and environment to categorical data on multiple symptoms. The model distinguishes between parameters needed to express the relationship between a latent trait and observed responses and the parameters required to represent the causes of variation in the latent trait. The regression of the latent trait on covariates may also be specified. The model is applied to symptoms of depression in 1983 pairs of adult female monozygotic and dizygotic twins. A model which allows only for polygenic variation in the latent trait is supported as well as the “mixed model,” which also allows for the effects of a major gene. The likelihood is significantly lower when all genetic effects are ascribed to a single gene. Practical limitations of the method are discussed.

Key Words

latent trait depression mixed model twins symptoms major gene segregation polygenes psychometrics heritability 

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References

  1. Bedford, A., Foulds, G. A., and Sheffield, B. B. (1976). A new personal disturbance scale (DSSI/SAD).Br. J. Soc. Clin. Psychol. 15:387–394.Google Scholar
  2. Bock, R. D., and Aitkin, M. (1981). Marginal maximum-likelihood estimation of item parameters: Application of an EM algorithm.Psychometrika 46:443–459.Google Scholar
  3. Bock, R. D., and Lieberman, M. (1970). Fitting a response model forn dichotomously scored items.Psychometrika 35:179–197.Google Scholar
  4. Cloninger, C. R., Martin, R. L., Guze, S. B., and Clayton, P. J. (1985). Diagnosis and prognosis in schizophrenia.Arch. Gen. Psychiat. 42:15–25.Google Scholar
  5. Eaves, L. J. (1983). Errors of inference in the detection of major gene effects on psychological test scores.Am. J. Hum. Genet. 35:1179–1189.Google Scholar
  6. Eaves, L. J. (1984). The resolution of genotype x environment interaction in segregation analysis of nuclear families.Genet. Epidemiol. 1:215–228.Google Scholar
  7. Eysenck, H. J. (1952).The Scientific Study of Personality, Routledge and Kegan Paul, London.Google Scholar
  8. Jardine, R., Martin, N. G., and Henderson, A. S. (1984). Genetic covariation between neuroticism and the symptoms of anxiety and depression.Genet. Epidemiol. 1:89–107.Google Scholar
  9. Kendler, K. S., Heath, A. C., Martin, N. G., and Eaves, L. J. (1986). Symptoms of anxiety and depression in a volunteer twin population: The etiologic role of genetic and environmental factors.Arch. Gen. Psychiat. 43:213–221.Google Scholar
  10. Kendler, K. S., Heath, A. C., Martin, N. G., and Eaves, L. J. (1987). Anxiety and depression: Same genes, different environments?.Arch. Gen. Psychiat. 44:451–457.Google Scholar
  11. Lalouel, J. M., Rao, D. C., Morton, N. E., and Elston, R. C. (1983). A unified model for complex segregation analysis.Am. J. Hum. Genet. 35:816–826.Google Scholar
  12. Lord, F. M., and Novick, M. R. (1968).Statistical Theories of Mental Test Scores, Addison-Wesley, Reading, Mass.Google Scholar
  13. Mislevy, R. J. (1984). Estimating latent distributions.Psychometrika 49:359–381.Google Scholar
  14. Numerical Algorithms Group (1982).FORTRAN Subroutine Library, Mark 9, NAG, Oxford.Google Scholar

Copyright information

© Plenum Publishing Corporation 1987

Authors and Affiliations

  • L. J. Eaves
    • 1
  • N. G. Martin
    • 1
  • A. C. Heath
    • 1
  • K. S. Kendler
    • 1
  1. 1.Department of Human Genetics and Department of PsychiatryMedical College of VirginiaRichmond

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