Parental phenotypes in family-based association analysis - PubMed (original) (raw)

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Parental phenotypes in family-based association analysis

Shaun Purcell et al. Am J Hum Genet. 2005 Feb.

Abstract

Family-based association designs are popular, because they offer inherent control of population stratification based on age, sex, ethnicity, and environmental exposure. However, the efficiency of these designs is hampered by current analytic strategies that consider only offspring phenotypes. Here, we describe the incorporation of parental phenotypes and, specifically, the inclusion of parental genotype-phenotype correlation terms in association tests, providing a series of tests that effectively span an efficiency-robustness spectrum. The model is based on the between-within-sibship association model presented in 1999 by Fulker and colleagues for quantitative traits and extended here to nuclear families. By use of a liability-threshold-model approach, standard dichotomous and/or qualitative disease phenotypes can be analyzed (and can include appropriate corrections for phenotypically ascertained samples), which allows for the application of this model to analysis of the commonly used affected-proband trio design. We show that the incorporation of parental phenotypes can considerably increase power, as compared with the standard transmission/disequilibrium test and equivalent quantitative tests, while providing both significant protection against stratification and a means of evaluating the contribution of stratification to positive results. This methodology enables the extraction of more information from existing family-based collections that are currently being genotyped and analyzed by use of standard approaches.

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Figures

Figure 1

Figure 1

Qualitative-trait simulations. A, Proportion of trios with at least one affected parent, with varying polygenic variance. B,

λ_O_

, with varying polygenic variance. C, Proportion of trios with at least one affected parent, with varying familial variance. D,

λ_O_

, with varying familial variance. Within each plot, the results are stratified by frequency of disease (1%, 5%, 10%, and 20%).

Figure 2

Figure 2

Qualitative-trait simulations. Power for the three tests (FAMT, FAMW, and TDTW) are plotted against residual polygenic variance (_X_-axes) for the four disease frequencies (1%, 5%, 10%, and 20%).

Figure 3

Figure 3

Qualitative-trait simulations. Power for the three tests (FAMT, FAMW, and TDTW) are plotted against residual familial variance (_X_-axes) for the four disease frequencies (1%, 5%, 10%, and 20%).

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References

Electronic-Database Information

    1. Authors' Web site, http://www.broad.mit.edu/~shaun/parents/ (for scripts that implement the methods discussed above by use of the model-fitting package Mx)
    1. Genetic Power Calculator (GPC), http://statgen.iop.kcl.ac.uk/gpc/
    1. Mx, http://www.vcu.edu/mx/

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