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A rapid association test procedure robust under different genetic models accounting for population stratification.

ABSTRACT: For genome-wide association studies (GWAS) using case-control data with stratification, a commonly used association test is the generalized Armitage (GA) trend test implemented in the software EIGENSTRAT. The GA trend test uses principal component analysis to correct for population stratification. It usually assumes an additive disease model and can have high power when the underlying disease model is additive or multiplicative, but may have relatively low power when the underlying disease model is recessive or dominant. The purpose of this paper is to provide a test procedure for GWAS with increased power over the GA trend test under the recessive and dominant models, while maintaining the power of the GA trend test under the additive and multiplicative models.We extend a Hardy-Weinberg disequilibrium (HWD) trend test for a homogeneous population to account for population stratification, and then propose a robust association test procedure for GWAS that incorporates information from the extended HWD trend test into the GA trend test.Our simulation studies and application of our method to a GWAS data set indicate that our proposed method can achieve the purpose described above.

SUBMITTER: Chen W

PROVIDER: S-EPMC3786013 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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A rapid association test procedure robust under different genetic models accounting for population stratification.

Chen Wenan W Chen Xiangning X Archer Kellie J KJ Liu Nianjun N Li Qizhai Q Zhao Zhongming Z Sun Shumei S Gao Guimin G

Human heredity 20130403 1

<h4>Objective</h4>For genome-wide association studies (GWAS) using case-control data with stratification, a commonly used association test is the generalized Armitage (GA) trend test implemented in the software EIGENSTRAT. The GA trend test uses principal component analysis to correct for population stratification. It usually assumes an additive disease model and can have high power when the underlying disease model is additive or multiplicative, but may have relatively low power when the underl ...[more]

PMID: 23571404

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Project description:Abstract Background: The development of successful DNA-driven, molecular subtyping methods for SZ is highly desirable because identifying subtypes that are predictive of symptoms, outcome, or treatment response could lead to better understanding of the etiology of SZ. Here, a molecular subtyping method was developed and tested based on data from the largest collection of SZ case–control samples available. The method developed and tested here accounts for sex and ancestry. Methods: Model-based recursive partitioning was applied to (1) 346 human, biological, pathway-based polygenic risk scores based on extant GWAS enrichment data from the PGC, (2) C4 gene expression data, (3) corresponding major histocompatibility complex single-nucleotide polymorphisms (MHC SNPs) rs210133 and rs123360412, (4) 10 empirically derived ancestry principle components, and (5) binary sex data. Models were tested using the Wellcome Trust case–control consortium (WTCCC) SZ data. Results: Resulting molecular subtypes explain significant heterogeneity in schizophrenia symptoms and age at onset. In this application, sex and factors pertaining to general DNA/RNA function and repair were as relevant as factors related to axon development. C4 expression, MHC SNPs, and ancestry components were dropped in the best step-wise fitting model, in addition to all two-way interactions. Molecular subtypes accounted for significant variation in AAO (P = 5.8*10–5) and in both negative and positive symptoms (P = .027 and 5.5*10–4, respectively). Conclusion: Based on a partitioning method using biological pathway data, we were able to derive molecular subtypes that are phenotypically informative. It was unexpected that (1) axonal pathways are overall less important than their cell RMR homologues and (2) C4 expression is not involved in the resulting subtypes. Application of partitioning methods to empirically derived, pathway-based polygenic risk scores, accounting for critical covariates, can lead to important insights into complex, heterogeneous disorders.

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A rapid association test procedure robust under different genetic models accounting for population stratification.

Publications

A rapid association test procedure robust under different genetic models accounting for population stratification.

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