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Minimal Phenotyping Yields GWAS Hits of Low Specificity for Major Depression bioRxiv preprint doi: https://doi.org/10.1101/440735; this version posted July 2, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Minimal phenotyping yields GWAS hits of low specificity for major depression Na Cai, Ph.D.1,2, Joana A. Revez, Ph.D. 3, Mark J Adams, Ph.D.4, Till F. M. Andlauer, Ph.D.5,6, Gerome Breen, Ph.D.7,8, Edna M. Byrne, Ph.D.3, Toni-Kim Clarke, Ph.D.4, Andreas J. Forstner, M.D.9,10,11, Hans J. Grabe, M.D.12, Steven P. Hamilton, M.D.13, Douglas F. Levinson, M.D.14, Cathryn M. Lewis, Ph.D.8,15, Glyn Lewis, Ph.D.16, Nicholas G. Martin, Ph.D.17, Yuri Milaneschi, Ph.D.18, Ole Mors, Ph.D.19,20, Bertram Müller-Myhsok, M.D.21,22,23, Brenda W. J. H. Pennix, Ph.D.18, Roy H. Perlis, M.D.24,25, Giorgio Pistis, Ph.D.26, James B. Potash, M.D.27, Martin Preisig, M.D.26, Jianxin Shi, Ph.D.28, Jordan W. Smoller, M.D.25,29,30, Fabien Streit, Ph.D.31, Henning Tiemeier, M.D.32,33,34, Rudolf Uher, M.D.35, Sandra Van der Auwera, Ph.D.12, Alexander Viktorin, Ph.D.36, Myrna M. Weissman, Ph.D.37,38, MDD Working Group of the Psychiatric Genomics Consortium, Kenneth S. Kendler, M.D.39, Jonathan Flint, M.D.40 1. Wellcome Sanger Institute, Wellcome Genome Campus, Cambridgeshire, UK 2. European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridgeshire, UK 3. Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia 4. Division of Psychiatry, University of Edinburgh, Edinburgh, UK 5. Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany 6. Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany 7. NIHR Maudsley Biomedical Research Centre, King's College London, London, UK 8. Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK 9. Department of Biomedicine, University of Basel, Basel, Switzerland 10. Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany 11. Centre for Human Genetics, University of Marburg, Marburg, Germany 12. Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Mecklenburg-Vorpommern, Germany 13. Department of Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, USA 14. Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA 15. Department of Medical & Molecular Genetics, King's College London, London, UK 16. Division of Psychiatry, University College London, London, UK 1 bioRxiv preprint doi: https://doi.org/10.1101/440735; this version posted July 2, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 17. Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia 18. Department of Psychiatry, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, Netherlands 19. Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark 20. iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Denmark 21. Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany 22. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany 23. University of Liverpool, Liverpool, UK 24. Department of Psychiatry, Harvard Medical School, Boston, MA, USA 25. Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA 26. Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland 27. Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA 28. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA 29. Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, USA 30. Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA 31. Department of Genetic Epidemiology in Psychiatry, Heidelberg University, Mannheim, Baden- Württemberg, Germany 32. Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands 33. Department of Child and Adolescent Psychiatry, Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands 34. Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, MA, USA 35. Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada 36. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden 37. Department of Psychiatry, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA 38. Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA 2 bioRxiv preprint doi: https://doi.org/10.1101/440735; this version posted July 2, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 39. Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA 40. Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA Corresponding author: Na Cai, Ph.D. Wellcome Sanger Institute Wellcome Genome Campus Hinxton CB10 1SA Cambridgeshire, UK Email: [email protected] Telephone: +44 (0)7821 070220 3 bioRxiv preprint doi: https://doi.org/10.1101/440735; this version posted July 2, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract Minimal phenotyping refers to the reliance on self-reported responses to one or two questions for disease case identification. This strategy has been applied to genome-wide association studies (GWAS) of major 2 depressive disorder (MDD). Here we report that the genotype derived heritability (h SNP) of depression defined by minimal phenotyping (14%, SE = 0.8%) is lower than strictly defined MDD (26%, SE = 2.2%), and that it shares as much genetic liability with strictly defined MDD (0.81, SE = 0.03) as it does with neuroticism (0.84, SE = 0.05), a trait not defined by the cardinal symptoms of depression. While they both show similar shared genetic liability with the personality trait neuroticism, a greater proportion of the genome contribute to the minimal phenotyping definitions of depression (80.2%, SE = 0.6%) than to strictly defined MDD (65.8%, SE = 0.6%). We find that GWAS loci identified in minimal phenotyping definitions of depression are not specific to MDD: they also predispose to other psychiatric conditions. Finally, genetic predictors based on minimal phenotyping definitions are not predictive of strictly defined MDD in independent cohorts. Our results reveal that genetic analysis of minimal phenotyping definitions of depression identifies non-specific genetic factors shared between MDD and other psychiatric conditions. Reliance on results from minimal phenotyping for MDD may thus bias views of the genetic architecture of MDD and impedes ability to identify pathways specific to MDD. 4 bioRxiv preprint doi: https://doi.org/10.1101/440735; this version posted July 2, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Introduction There is now little doubt that a key requisite for the robust identification of genetic risk loci underlying psychiatric disease is the use of an appropriately large sample. However, while the costs of genotyping and sequencing continue to fall, the cost of phenotyping remains high1, limiting sample collection. One solution for reducing the burden of case identification is to utilize minimal phenotyping, such as clinical information from hospital registers2, or reliance on subjects’ self-reported symptoms, help-seeking, diagnoses or medication, which are cheap and fast to collect. We refer to the latter strategy as “minimal phenotyping”, as it minimizes phenotyping costs and reduces data to a single or few self-reported answers. However, apart from the detection of more and more GWAS loci3-5 (Supplemental Table S1), the consequences of sacrificing symptomatic information for genetic analyses has rarely been investigated. The consequences may be particularly important for major depressive disorder (MDD) because of its phenotypic and likely etiological heterogeneity6, high degree of comorbidity with other psychiatric diseases7, and substantial discrepancies between self-assessment using symptom scales and diagnoses made with full diagnostic criteria8. While a majority of the population self-identify as having one or two depressive symptoms at any one time, only between 9 and 20% of the population
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