DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.

Journal: PLoS computational biology
PMID: 32012148

Abstract

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.

Authors

  • Janine Arloth
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Gökcen Eraslan
    Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
  • Till F M Andlauer
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Jade Martins
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Stella Iurato
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Brigitte Kühnel
    Research Unit of Molecular Epidemiology and Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
  • Melanie Waldenberger
    Research Unit of Molecular Epidemiology and Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
  • Josef Frank
    Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
  • Ralf Gold
    German Competence Network Multiple Sclerosis (KKNMS), Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Bernhard Hemmer
    Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
  • Felix Luessi
    German Competence Network Multiple Sclerosis (KKNMS), Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Sandra Nischwitz
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Friedemann Paul
    Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Department of Neurology, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), NeuroCure Clinical Research Center, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universitt zu Berlin, Berlin Institute of Health (BIH), Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine, 10117 Berlin, Germany; Einstein Center for Digital Future Berlin, Germany.
  • Heinz Wiendl
    German Competence Network Multiple Sclerosis (KKNMS), Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Christian Gieger
    Research Unit of Molecular Epidemiology and Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
  • Stefanie Heilmann-Heimbach
    Institute of Human Genetics, University Hospital Bonn and Division of Genomics, Life & Brain Research Centre, University of Bonn School of Medicine, Bonn, Germany.
  • Tim Kacprowski
    Interfaculty Institute for Genetics and Functional Genomics, University Medicine and University of Greifswald, Greifswald, Germany.
  • Matthias Laudes
    Department I of Internal Medicine, Kiel University, Kiel, Germany.
  • Thomas Meitinger
    Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany and Institute of Human Genetics, Technical University of Munich, Munich, Germany.
  • Annette Peters
    Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
  • Rajesh Rawal
    Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
  • Konstantin Strauch
    Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany and Institute of Medical Informatics, Biometry, and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.
  • Susanne Lucae
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Bertram Müller-Myhsok
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Marcella Rietschel
    Department of Genetic Epidemiology in Psychiatry, Institute of Central Mental Health, Medical Faculty Mannheim, University of Heidelberg.
  • Fabian J Theis
    Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany.
  • Elisabeth B Binder
    Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
  • Nikola S Mueller
    Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.

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