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A generalized family-based association test for dichotomous traits.

ABSTRACT: Recent advances in genotyping technology make it possible to utilize large-scale association analysis for disease-gene mapping. Powerful and robust family-based association methods are crucial for successful gene mapping. We propose a family-based association method, the generalized disequilibrium test (GDT), in which the genotype differences of all discordant relative pairs are utilized in assessing association within a family. The improvement of the GDT over existing methods is threefold: (1) information beyond first-degree relatives is incorporated efficiently, yielding substantial gains in power in comparison to existing tests; (2) the GDT statistic is implemented via a robust technique that does not rely on large sample theory, resulting in further power gains, especially at high levels of significance; and (3) covariates and weights based on family size are incorporated. Advantages of the GDT over existing methods are demonstrated by extensive computer simulations and by application to recently published large-scale genome-wide linkage data from the Type 1 Diabetes Genetics Consortium (T1DGC). In our simulations, the GDT consistently outperforms other tests for a common disease and frequently outperforms other tests for a rare disease; the power improvement is > 13% in 6 out of 8 extended pedigree scenarios. All of the six strongest associations identified by the GDT have been reported by other studies, whereas only three or four of these associations can be identified by existing methods. For the T1D association at gene UBASH3A, the GDT resulted in a genome-wide significance (p = 4.3 x 10(-6)), much stronger than the published significance (p = 10(-4)).

SUBMITTER: Chen WM

PROVIDER: S-EPMC2771538 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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A generalized family-based association test for dichotomous traits.

Chen Wei-Min WM Manichaikul Ani A Rich Stephen S SS

American journal of human genetics 20090901 3

Recent advances in genotyping technology make it possible to utilize large-scale association analysis for disease-gene mapping. Powerful and robust family-based association methods are crucial for successful gene mapping. We propose a family-based association method, the generalized disequilibrium test (GDT), in which the genotype differences of all discordant relative pairs are utilized in assessing association within a family. The improvement of the GDT over existing methods is threefold: (1) ...[more]

PMID: 19732865

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Project description:BackgroundFor dichotomous traits, the generalized disequilibrium test with the moment estimate of the variance (GDT-ME) is a powerful family-based association method. Genomic imprinting is an important epigenetic phenomenon and currently, there has been increasing interest of incorporating imprinting to improve the test power of association analysis. However, GDT-ME does not take imprinting effects into account, and it has not been investigated whether it can be used for association analysis when the effects indeed exist.ResultsIn this article, based on a novel decomposition of the genotype score according to the paternal or maternal source of the allele, we propose the generalized disequilibrium test with imprinting (GDTI) for complete pedigrees without any missing genotypes. Then, we extend GDTI and GDT-ME to accommodate incomplete pedigrees with some pedigrees having missing genotypes, by using a Monte Carlo (MC) sampling and estimation scheme to infer missing genotypes given available genotypes in each pedigree, denoted by MCGDTI and MCGDT-ME, respectively. The proposed GDTI and MCGDTI methods evaluate the differences of the paternal as well as maternal allele scores for all discordant relative pairs in a pedigree, including beyond first-degree relative pairs. Advantages of the proposed GDTI and MCGDTI test statistics over existing methods are demonstrated by simulation studies under various simulation settings and by application to the rheumatoid arthritis dataset. Simulation results show that the proposed tests control the size well under the null hypothesis of no association, and outperform the existing methods under various imprinting effect models. The existing GDT-ME and the proposed MCGDT-ME can be used to test for association even when imprinting effects exist. For the application to the rheumatoid arthritis data, compared to the existing methods, MCGDTI identifies more loci statistically significantly associated with the disease.ConclusionsUnder complete and incomplete imprinting effect models, our proposed GDTI and MCGDTI methods, by considering the information on imprinting effects and all discordant relative pairs within each pedigree, outperform all the existing test statistics and MCGDTI can recapture much of the missing information. Therefore, MCGDTI is recommended in practice.

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A generalized family-based association test for dichotomous traits.

Publications

A generalized family-based association test for dichotomous traits.

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