Skip to main content
PMC home page
American Journal of Human Genetics logoLink to American Journal of Human Genetics
. 1999 Mar;64(3):871–885. doi: 10.1086/302288

Analysis of affected sib pairs, with covariates--with and without constraints.

C M Greenwood 1, S B Bull 1
PMCID: PMC1377805  PMID: 10053022

Abstract

Covariate models have previously been developed as an extension to affected-sib-pair methods in which the covariate effects are jointly estimated with the degree of excess allele sharing. These models can estimate the differences in sib-pair allele sharing that are associated with measurable environment or genes. When there are no covariates, the pattern of identical-by-descent allele sharing in affected sib pairs is expected to fall within a small triangular region of the potential parameter space, under most genetic models. By restriction of the estimated allele sharing to this triangle, improved power is obtained in tests for genetic linkage. When the affected-sib-pair model is generalized to allow for covariates that affect allele sharing, however, new constraints and new methods for the application of constraints are required. Three generalized constraint methods are proposed and evaluated by use of simulated data. The results compare the power of the different methods, with and without covariates, for a single-gene model with age-dependent onset and for quantitative and qualitative gene-environment and gene-gene interaction models. Covariates can improve the power to detect linkage and can be particularly valuable when there are qualitative gene-environment interactions. In most situations, the best strategy is to assume that there is no dominance variance and to obtain constrained estimates for covariate models under this assumption.

Full Text

The Full Text of this article is available as a PDF (299.0 KB).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Abel L., Müller-Myhsok B. Robustness and power of the maximum-likelihood-binomial and maximum-likelihood-score methods, in multipoint linkage analysis of affected-sibship data. Am J Hum Genet. 1998 Aug;63(2):638–647. doi: 10.1086/301958. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Beaty T. H. Evolving methods in genetic epidemiology. I. Analysis of genetic and environmental factors in family studies. Epidemiol Rev. 1997;19(1):14–23. doi: 10.1093/oxfordjournals.epirev.a017936. [DOI] [PubMed] [Google Scholar]
  3. Craddock N., Khodel V., Van Eerdewegh P., Reich T. Mathematical limits of multilocus models: the genetic transmission of bipolar disorder. Am J Hum Genet. 1995 Sep;57(3):690–702. [PMC free article] [PubMed] [Google Scholar]
  4. Dawson D. V., Kaplan E. B., Elston R. C. Extensions to sib-pair linkage tests applicable to disorders characterized by delayed onset. Genet Epidemiol. 1990;7(6):453–466. doi: 10.1002/gepi.1370070607. [DOI] [PubMed] [Google Scholar]
  5. Flanders W. D., Khoury M. J. Extensions to methods of sib-pair linkage analyses. Genet Epidemiol. 1991;8(6):399–408. doi: 10.1002/gepi.1370080606. [DOI] [PubMed] [Google Scholar]
  6. Greenwood C. M., Bull S. B. Incorporation of covariates into genome scanning using sib-pair analysis in bipolar affective disorder. Genet Epidemiol. 1997;14(6):635–640. doi: 10.1002/(SICI)1098-2272(1997)14:6<635::AID-GEPI14>3.0.CO;2-R. [DOI] [PubMed] [Google Scholar]
  7. Holmans P. Asymptotic properties of affected-sib-pair linkage analysis. Am J Hum Genet. 1993 Feb;52(2):362–374. [PMC free article] [PubMed] [Google Scholar]
  8. Khoury M. J., Stewart W., Beaty T. H. The effect of genetic susceptibility on causal inference in epidemiologic studies. Am J Epidemiol. 1987 Oct;126(4):561–567. doi: 10.1093/oxfordjournals.aje.a114695. [DOI] [PubMed] [Google Scholar]
  9. Knapp M. Even a deficit of shared marker alleles in affected sib pairs can yield evidence for linkage. Am J Hum Genet. 1996 Aug;59(2):485–486. [PMC free article] [PubMed] [Google Scholar]
  10. Kong A., Frigge M., Bell G. I., Lander E. S., Daly M. J., Cox N. J. Diabetes, dependence, asymptotics, selection and significance. Nat Genet. 1997 Oct;17(2):148–148. doi: 10.1038/ng1097-148. [DOI] [PubMed] [Google Scholar]
  11. Kruglyak L., Lander E. S. Complete multipoint sib-pair analysis of qualitative and quantitative traits. Am J Hum Genet. 1995 Aug;57(2):439–454. [PMC free article] [PubMed] [Google Scholar]
  12. Lander E. S., Green P. Construction of multilocus genetic linkage maps in humans. Proc Natl Acad Sci U S A. 1987 Apr;84(8):2363–2367. doi: 10.1073/pnas.84.8.2363. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Liò P., Morton N. E. Comparison of parametric and nonparametric methods to map oligogenes by linkage. Proc Natl Acad Sci U S A. 1997 May 13;94(10):5344–5348. doi: 10.1073/pnas.94.10.5344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Louis E. J., Payami H., Thomson G. The affected sib method. V. Testing the assumptions. Ann Hum Genet. 1987 Jan;51(Pt 1):75–92. doi: 10.1111/j.1469-1809.1987.tb00867.x. [DOI] [PubMed] [Google Scholar]
  15. Lunetta K. L., Rogus J. J. Strategy for mapping minor histocompatibility genes involved in graft-versus-host disease: a novel application of discordant sib pair methodology. Genet Epidemiol. 1998;15(6):595–607. doi: 10.1002/(SICI)1098-2272(1998)15:6<595::AID-GEPI4>3.0.CO;2-4. [DOI] [PubMed] [Google Scholar]
  16. Motro U., Thomson G. The affected sib method. I. Statistical features of the affected sib-pair method. Genetics. 1985 Jul;110(3):525–538. doi: 10.1093/genetics/110.3.525. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Olson J. M. Multipoint linkage analysis using sib pairs: an interval mapping approach for dichotomous outcomes. Am J Hum Genet. 1995 Mar;56(3):788–798. [PMC free article] [PubMed] [Google Scholar]
  18. Risch N. Linkage strategies for genetically complex traits. II. The power of affected relative pairs. Am J Hum Genet. 1990 Feb;46(2):229–241. [PMC free article] [PubMed] [Google Scholar]
  19. Suarez B. K., Rice J., Reich T. The generalized sib pair IBD distribution: its use in the detection of linkage. Ann Hum Genet. 1978 Jul;42(1):87–94. doi: 10.1111/j.1469-1809.1978.tb00933.x. [DOI] [PubMed] [Google Scholar]
  20. Suarez B. K. The affected sib pair IBD distribution for HLA-linked disease susceptibility genes. Tissue Antigens. 1978 Aug;12(2):87–93. doi: 10.1111/j.1399-0039.1978.tb01303.x. [DOI] [PubMed] [Google Scholar]
  21. Suarez B. K., Van Eerdewegh P. A comparison of three affected-sib-pair scoring methods to detect HLA-linked disease susceptibility genes. Am J Med Genet. 1984 May;18(1):135–146. doi: 10.1002/ajmg.1320180117. [DOI] [PubMed] [Google Scholar]
  22. Whittemore A. S., Tu I. P. Simple, robust linkage tests for affected sibs. Am J Hum Genet. 1998 May;62(5):1228–1242. doi: 10.1086/301820. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Yang Q., Khoury M. J. Evolving methods in genetic epidemiology. III. Gene-environment interaction in epidemiologic research. Epidemiol Rev. 1997;19(1):33–43. doi: 10.1093/oxfordjournals.epirev.a017944. [DOI] [PubMed] [Google Scholar]

Articles from American Journal of Human Genetics are provided here courtesy of American Society of Human Genetics

RESOURCES