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A Variance-Component Framework for Pedigree Analysis of Continuous and Categorical Outcomes

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Abstract

Variance-component methods are popular and flexible analytic tools for elucidating the genetic mechanisms of complex quantitative traits from pedigree data. However, variance-component methods typically assume that the trait of interest follows a multivariate normal distribution within a pedigree. Studies have shown that violation of this normality assumption can lead to biased parameter estimates and inflations in type-I error. This limits the application of variance-component methods to more general trait outcomes, whether continuous or categorical in nature. In this paper, we develop and apply a general variance-component framework for pedigree analysis of continuous and categorical outcomes. We develop appropriate models using generalized-linear mixed model theory and fit such models using approximate maximum-likelihood procedures. Using our proposed method, we demonstrate that one can perform variance-component pedigree analysis on outcomes that follow any exponential-family distribution. Additionally, we also show how one can modify the method to perform pedigree analysis of ordinal outcomes. We also discuss extensions of our variance-component framework to accommodate pedigrees ascertained based on trait outcome. We demonstrate the feasibility of our method using both simulated data and data from a genetic study of ovarian insufficiency.

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Authors and Affiliations

  1. Department of Human Genetics, Emory University, 615 Michael Street, Suite 301, Atlanta, GA, 30322, USA

    Michael P. Epstein, Jessica E. Hunter, Emily G. Allen & Stephanie L. Sherman

  2. Department of Biostatistics, Harvard University, Boston, MA, USA

    Xihong Lin

  3. Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA

    Michael Boehnke

Authors
  1. Michael P. Epstein
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  2. Jessica E. Hunter
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  3. Emily G. Allen
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  4. Stephanie L. Sherman
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  5. Xihong Lin
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  6. Michael Boehnke
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Corresponding author

Correspondence to Michael P. Epstein.

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Epstein, M.P., Hunter, J.E., Allen, E.G. et al. A Variance-Component Framework for Pedigree Analysis of Continuous and Categorical Outcomes. Stat Biosci 1, 181–198 (2009). https://doi.org/10.1007/s12561-009-9010-5

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  • DOI: https://doi.org/10.1007/s12561-009-9010-5

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