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Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes

Authors

  • Tune H. Pers,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    2. Institute of Preventive Medicine, Copenhagen University Hospital, Centre for Health and Society, Copenhagen, Denmark
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    • Tune H. Pers and Niclas Tue Hansen to be considered joint first authors.

  • Niclas Tue Hansen,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
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    • Tune H. Pers and Niclas Tue Hansen to be considered joint first authors.

  • Kasper Lage,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    2. Pediatric Surgical Research Laboratories, MassGeneral Hospital for Children, Massachusetts General Hospital, Boston, Massachusetts
    3. Harvard Medical School, Boston, Massachusetts
    4. Broad Institute of Harvard and MIT, Cambridge, Massachusetts
    5. Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
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  • Pernille Koefoed,

    1. Department of Neuroscience and Pharmacology, Laboratory of Neuropsychiatry, University of Copenhagen, Copenhagen, Denmark
    2. Center of Psychiatry, Rigshospitalet, Copenhagen, Denmark
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  • Piotr Dworzynski,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
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  • Martin Lee Miller,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
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  • Tracey J. Flint,

    1. Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
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  • Erling Mellerup,

    1. Department of Neuroscience and Pharmacology, Laboratory of Neuropsychiatry, University of Copenhagen, Copenhagen, Denmark
    2. Center of Psychiatry, Rigshospitalet, Copenhagen, Denmark
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  • Henrik Dam,

    1. Center of Psychiatry, Rigshospitalet, Copenhagen, Denmark
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  • Ole A. Andreassen,

    1. Top-project, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Srdjan Djurovic,

    1. Top-project, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Ingrid Melle,

    1. Top-project, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Anders D. Børglum,

    1. Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
    2. Institute of Human Genetics, University of Aarhus, Aarhus, Denmark
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  • Thomas Werge,

    1. Research Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Copenhagen University Hospital, Roskilde, Denmark
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  • Shaun Purcell,

    1. Broad Institute of Harvard and MIT, Cambridge, Massachusetts
    2. Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
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  • Manuel A. Ferreira,

    1. Broad Institute of Harvard and MIT, Cambridge, Massachusetts
    2. Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
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  • Irene Kouskoumvekaki,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
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  • Christopher T. Workman,

    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
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  • Torben Hansen,

    1. Hagedorn Research Institute, Gentofte, Denmark
    2. Marie Krogh Center for Metabolic Research, University of Copenhagen, Copenhagen, Denmark
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  • Ole Mors,

    1. Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
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  • Søren Brunak

    Corresponding author
    1. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    2. Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
    • Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
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Abstract

Meta-analyses of large-scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome-wide association (GWA) studies, protein-protein interaction screens, disease similarity, linkage studies, and gene expression experiments into a multi-layered evidence network which is used to prioritize the entire protein-coding part of the genome identifying a shortlist of candidate genes. We report specifically results on bipolar disorder, a genetically complex disease where GWA studies have only been moderately successful. We validate one such candidate experimentally, YWHAH, by genotyping five variations in 640 patients and 1,377 controls. We found a significant allelic association for the rs1049583 polymorphism in YWHAH (adjusted P = 5.6e−3) with an odds ratio of 1.28 [1.12–1.48], which replicates a previous case-control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available framework for identifying risk genes in highly polygenic diseases. The method is made available as a web service at www.cbs.dtu.dk/services/metaranker. Genet. Epidemiol. 2011. © 2011 Wiley-Liss, Inc. 35:318-332, 2011

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