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Testing the association between polymorphic markers and quantitative traits in pedigrees.

V T George, R C Elston

    Genetic Epidemiology
    |January 1, 1987
    PubMed
    Summary
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    This study introduces a statistical model to analyze genetic markers and quantitative traits in families. It accounts for complex familial correlations and non-normal trait distributions, improving association analysis.

    Area of Science:

    • Biostatistics
    • Statistical Genetics
    • Human Genetics

    Background:

    • Quantitative traits in human populations are influenced by genetic and environmental factors.
    • Analyzing the association between genetic markers and quantitative traits is crucial for understanding disease etiology.
    • Existing models often assume trait normality and do not fully account for familial correlations.

    Purpose of the Study:

    • To propose a flexible statistical model for assessing the relationship between polymorphic genetic markers and quantitative traits in human pedigrees.
    • To develop a method that adjusts for covariates like age and sex.
    • To accommodate non-normal trait distributions and familial correlation structures.

    Main Methods:

    • An iterative maximum likelihood estimation procedure is employed.

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  • The model incorporates a familial correlation structure for the quantitative trait.
  • It allows for a broad class of skewed or kurtotic underlying distributions.

    • Main Results:

    • The proposed model effectively measures and tests associations between genetic markers and quantitative traits.
    • The model's performance is illustrated and compared to standard methods.
    • Results demonstrate the utility of accounting for familial correlations and non-normal distributions.

    Conclusions:

    • The developed statistical model offers a robust approach for genetic association studies in human pedigrees.
    • It provides a more accurate analysis by handling complex trait distributions and familial dependencies.
    • This method enhances the understanding of genetic influences on quantitative traits.