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Efficient Strategy for Detecting Gene × Gene Joint Action and Its Application in Schizophrenia

Authors

  • Sungho Won,

    Corresponding author
    1. Department of Applied Statistics, Chung-Ang University, Seoul, Korea
    2. Research Center for Data Science, Chung-Ang University, Seoul, Korea
    • Correspondence to: Sungho Won, Department of Applied Statistics, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea. E-mail: swon@cau.ac.kr

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  • Min-Seok Kwon,

    1. Bioinformatics Program, Seoul National University, Seoul, Korea
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  • Manuel Mattheisen,

    1. Institute of Human Genetics, University of Bonn, Bonn, Germany
    2. Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
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  • Suyeon Park,

    1. Department of Applied Statistics, Chung-Ang University, Seoul, Korea
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  • Changsoon Park,

    1. Department of Applied Statistics, Chung-Ang University, Seoul, Korea
    2. Research Center for Data Science, Chung-Ang University, Seoul, Korea
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  • Daisuke Kihara,

    1. Department of Computer Sciences, Purdue University, West Lafayette, Indiana, United States of America
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  • Sven Cichon,

    1. Institute of Human Genetics, University of Bonn, Bonn, Germany
    2. Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
    3. Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany
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  • Roel Ophoff,

    1. Department of Medical Genetics, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
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  • Markus M. Nöthen,

    1. Institute of Human Genetics, University of Bonn, Bonn, Germany
    2. Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
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  • Marcella Rietschel,

    1. Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Mannheim, Mannheim, Germany
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  • Max Baur,

    1. Institute for Medical Biometry, Informatics, and Epidemiology, University of Bonn, Bonn, Germany
    2. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
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  • Andre G. Uitterlinden,

    1. Department of Internal Medicine, Genetics Laboratory, Eramsmus Medical Center Rotterdam, The Netherlands
    2. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
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  • A. Hofmann,

    1. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
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  • GROUP Investigators,

    1. For a full list of members see Acknowledgments
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  • Christoph Lange

    1. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
    2. Institute for Genomic Mathematics, University of Bonn, Bonn, Germany
    3. Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America
    4. Center for Genomic Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
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ABSTRACT

We propose a new approach to detect gene × gene joint action in genome-wide association studies (GWASs) for case-control designs. This approach offers an exhaustive search for all two-way joint action (including, as a special case, single gene action) that is computationally feasible at the genome-wide level and has reasonable statistical power under most genetic models. We found that the presence of any gene × gene joint action may imply differences in three types of genetic components: the minor allele frequencies and the amounts of Hardy-Weinberg disequilibrium may differ between cases and controls, and between the two genetic loci the degree of linkage disequilibrium may differ between cases and controls. Using Fisher's method, it is possible to combine the different sources of genetic information in an overall test for detecting gene × gene joint action. The proposed statistical analysis is efficient and its simplicity makes it applicable to GWASs. In the current study, we applied the proposed approach to a GWAS on schizophrenia and found several potential gene × gene interactions. Our application illustrates the practical advantage of the proposed method.

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