title: Development of GMDR-GPU for gene-gene interaction analysis and its application to WTCCC GWAS data for type 2 diabetes.
abstract: Although genome-wide association studies (GWAS) have identified a significant number of single-nucleotide polymorphisms (SNPs) associated with many complex human traits, the susceptibility loci identified so far can explain only a small fraction of the genetic risk. Among other possible explanations, the lack of a comprehensive examination of gene-gene interaction (G×G) is often considered a source of the missing heritability. Previously, we reported a model-free Generalized Multifactor Dimensionality Reduction (GMDR) approach for detecting G×G in both dichotomous and quantitative phenotypes. However, the computational burden and less efficient implementation of the original programs make them impossible to use for GWAS. In this study, we developed a graphics processing unit (GPU)-based GMDR program (named GWAS-GPU), which is able not only to analyze GWAS data but also to run much faster than the earlier version of the GMDR program. As a demonstration of the program, we used the GMDR-GPU software to analyze a publicly available GWAS dataset on type 2 diabetes (T2D) from the Wellcome Trust Case Control Consortium. Through an exhaustive search of pair-wise interactions and a selected search of three- to five-way interactions conditioned on significant pair-wise results, we identified 24 core SNPs in six genes (FTO: rs9939973, rs9940128, rs9922047, rs1121980, rs9939609, rs9930506; TSPAN8: rs1495377; TCF7L2: rs4074720, rs7901695, rs4506565, rs4132670, rs10787472, rs11196205, rs10885409, rs11196208; L3MBTL3: rs10485400, rs4897366; CELF4: rs2852373, rs608489; RUNX1: rs445984, rs1040328, rs990074, rs2223046, rs2834970) that appear to be important for T2D. Of these core SNPs, 11 in FTO, TSPAN8, and TCF7L2 have been reported to be associated with T2D, obesity, or both, providing an independent replication of previously reported SNPs. Importantly, we identified three new susceptibility genes; i.e., L3MBTL3, CELF4, and RUNX1, for T2D, a finding that warrants further investigation with independent samples.
authors.affiliation: Institute of Bioinformatics, Zhejiang University, Hangzhou, China.
authors.forename: Zhixiang
authors.initials: Z
authors.lastname: Zhu
authors.forename: Xiaoran
authors.initials: X
authors.lastname: Tong
authors.forename: Zhihong
authors.initials: Z
authors.lastname: Zhu
authors.forename: Meimei
authors.initials: M
authors.lastname: Liang
authors.forename: Wenyan
authors.initials: W
authors.lastname: Cui
authors.forename: Kunkai
authors.initials: K
authors.lastname: Su
authors.forename: Ming D
authors.initials: MD
authors.lastname: Li
authors.forename: Jun
authors.initials: J
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D000067878:CELF Proteins; D050676:Core Binding Factor Alpha 2 Subunit / Q000235:genetics / Q000378:metabolism; D004268:DNA-Binding Proteins / Q000235:genetics / Q000378:metabolism; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D004843:Epistasis, Genetic; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D058011:Multifactor Dimensionality Reduction; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D016601:RNA-Binding Proteins / Q000235:genetics / Q000378:metabolism; D012984:Software
chemical_list: D000067878:CELF Proteins; C422243:CELF4 protein, human; D050676:Core Binding Factor Alpha 2 Subunit; D004268:DNA-Binding Proteins; C502190:L3MBTL3 protein, human; D016601:RNA-Binding Proteins; C493728:RUNX1 protein, human