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A shrinkage method for testing the Hardy-Weinberg equilibrium in case-control studies.

ABSTRACT: Testing for the Hardy-Weinberg equilibrium (HWE) is often used as an initial step for checking the quality of genotyping. When testing the HWE for case-control data, the impact of a potential genetic association between the marker and the disease must be controlled for otherwise the results may be biased. Li and Li [2008] proposed a likelihood ratio test (LRT) that accounts for this potential genetic association and it is more powerful than the commonly used control-only ?² test. However, the LRT is not efficient when the marker is independent of the disease, and also requires numerical optimization to calculate the test statistic. In this article, we propose a novel shrinkage test for assessing the HWE. The proposed shrinkage test yields higher statistical power than the LRT when the marker is independent of or weakly associated with the disease, and converges to the LRT when the marker is strongly associated with the disease. In addition, the proposed shrinkage test has a closed form and can be easily used to test the HWE for large datasets that result from genome-wide association studies. We compare the performance of the shrinkage test with existing methods using simulation studies, and apply the shrinkage test to a genome-wide association dataset for Alzheimer's disease.

SUBMITTER: Zang Y

PROVIDER: S-EPMC3972031 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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A shrinkage method for testing the Hardy-Weinberg equilibrium in case-control studies.

Zang Yong Y Yuan Ying Y

Genetic epidemiology 20130811 7

Testing for the Hardy-Weinberg equilibrium (HWE) is often used as an initial step for checking the quality of genotyping. When testing the HWE for case-control data, the impact of a potential genetic association between the marker and the disease must be controlled for otherwise the results may be biased. Li and Li [2008] proposed a likelihood ratio test (LRT) that accounts for this potential genetic association and it is more powerful than the commonly used control-only χ² test. However, the LR ...[more]

PMID: 23934751

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Project description:In case-control genetic association studies, cases are subjects with the disease and controls are subjects without the disease. At the time of case-control data collection, information about secondary phenotypes is also collected. In addition to studies of primary diseases, there has been some interest in studying genetic variants associated with secondary phenotypes. In genetic association studies, the deviation from Hardy-Weinberg proportion (HWP) of each genetic marker is assessed as an initial quality check to identify questionable genotypes. Generally, HWP tests are performed based on the controls for the primary disease or secondary phenotype. However, when the disease or phenotype of interest is common, the controls do not represent the general population. Therefore, using only controls for testing HWP can result in a highly inflated type I error rate for the disease- and/or phenotype-associated variants. Recently, two approaches, the likelihood ratio test (LRT) approach and the mixture HWP (mHWP) exact test were proposed for testing HWP in samples from case-control studies. Here, we show that these two approaches result in inflated type I error rates and could lead to the removal from further analysis of potential causal genetic variants associated with the primary disease and/or secondary phenotype when the study of primary disease is frequency-matched on the secondary phenotype. Therefore, we proposed alternative approaches, which extend the LRT and mHWP approaches, for assessing HWP that account for frequency matching. The goal was to maintain more (possible causative) single-nucleotide polymorphisms in the sample for further analysis. Our simulation results showed that both extended approaches could control type I error probabilities. We also applied the proposed approaches to test HWP for SNPs from a genome-wide association study of lung cancer that was frequency-matched on smoking status and found that the proposed approaches can keep more genetic variants for association studies.

Project description:Objective: Departure from Hardy Weinberg Equilibrium (HWE) may occur due to a variety of causes, including purifying selection, inbreeding, population substructure, copy number variation or genotyping error. We searched for specific characteristics of HWE-departure due to genotyping error. Methods: Genotypes of a random set of genetic variants were obtained from the Exome Aggregation Consortium (ExAC) database. Variants with <80% successful genotypes or with minor allele frequency (MAF) <1% were excluded. HWE-departure (d-HWE) was considered significant at p < 10E-05 and classified as d-HWE with loss of heterozygosity (LoH d-HWE) or d-HWE with excess heterozygosity (gain of heterozygosity: GoH d-HWE). Missing genotypes, variant type (single nucleotide polymorphism (SNP) vs. insertion/deletion); MAF, standard deviation (SD) of MAF across populations (MAF-SD) and copy number variation were evaluated for association with HWE-departure. Results: The study sample comprised 3,204 genotype distributions. HWE-departure was observed in 134 variants: LoH d-HWE in 41 (1.3%), GoH d-HWE in 93 (2.9%) variants. LoH d-HWE was more likely in variants located within deletion polymorphisms (p < 0.001) and in variants with higher MAF-SD (p = 0.0077). GoH d-HWE was associated with low genotyping rate, with variants of insertion/deletion type and with high MAF (all at p < 0.001). In a sub-sample of 2,196 variants with genotyping rate >98%, LoH d-HWE was found in 29 (1.3%) variants, but no GoH d-HWE was detected. The findings of the non-random distribution of HWE-violating SNPs along the chromosome, the association with common deletion polymorphisms and indel-variant type, and the finding of excess heterozygotes in genomic regions that are prone to cross-hybridization were confirmed in a large sample of short variants from the 1,000 Genomes Project. Conclusions: We differentiated between two types of HWE-departure. GoH d-HWE was suggestive for genotyping error. LoH d-HWE, on the contrary, pointed to natural variabilities such as population substructure or common deletion polymorphisms.

Dataset Information

A shrinkage method for testing the Hardy-Weinberg equilibrium in case-control studies.

Publications

A shrinkage method for testing the Hardy-Weinberg equilibrium in case-control studies.

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