Minimal phenotyping yields genome-wide association signals of low specificity for major depression
Year: 2020
Type: article
Study design: Observational Study
Abstract: Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD. Genetic analyses of depression based on minimal phenotyping identify nonspecific genetic risk factors shared between major depressive disorder (MDD) and other psychiatric conditions, suggesting that this approach may have limited ability to identify pathways specific to MDD.
Source: Nature Genetics
Authors: Na Cai, Joana A. Revez, Mark J. Adams, Till F. M. Andlauer, Gerome Breen, Enda M. Byrne, Toni-Kim Clarke, Andreas J. Forstner, Hans J. Grabe, Steven P. Hamilton, Douglas F. Levinson, Cathryn M. Lewis, Glyn Lewis, Nicholas G. Martin, Yuri Milaneschi, Ole Mors, Bertram Müller-Myhsok, Brenda W. J. H. Penninx, Roy H. Perlis, Giorgio Pistis, James B. Potash, Martin Preisig, Jianxin Shi, Jordan W. Smoller, Fabien Streit, Henning Tiemeier, Rudolf Uher, Sandra Van der Auwera, Alexander Viktorin, Myrna M. Weissman, Kenneth S. Kendler, Jonathan Flint
Institutions: European Bioinformatics Institute, Wellcome Sanger Institute, Helmholtz Munich, The University of Queensland, Institute for Molecular Bioscience, University of Edinburgh, TUM Klinikum, Max Planck Institute of Psychiatry, Technical University of Munich, King's College London, NIHR Maudsley Biomedical Research Centre, University of Bonn, Philipps University of Marburg, University of Basel, University Hospital Bonn, Universitätsmedizin Greifswald, Universität Greifswald, Kaiser Permanente Northern California, Stanford University, University College London, QIMR Berghofer Medical Research Institute, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Aarhus University Hospital, Lundbeck Foundation, University of Liverpool, Munich Cluster for Systems Neurology, Harvard University, Massachusetts General Hospital, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Johns Hopkins University, Johns Hopkins Medicine, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Broad Institute, Stanley Center for Psychiatric Research, Heidelberg University, Central Institute of Mental Health, Erasmus MC, Erasmus University Rotterdam, Dalhousie University, Karolinska Institutet, New York State Psychiatric Institute, Columbia University, Virginia Commonwealth University, University of California, Los Angeles
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, John Templeton Foundation, GlaxoSmithKline, Wellcome Trust, European Bioinformatics Institute, Fresenius Medical Care North America, National Institute for Health and Care Research, King's College London, University of Oxford, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Lundbeckfonden, Chinese Society of Clinical Oncology, Neuraxpharm, NIHR Maudsley Biomedical Research Centre, National Institute of Mental Health, Cilag
Awards: Cardiovascular diseases and psychiatric disorders in the general population: a prospective follow-up study, Cardiovascular diseases and psychiatric disorders in the general population: a prospective follow-up study, G2601817178, G2957143966, G3248287424, Family study of specific subthreshold and threshold mood, anxiety, substance use and schizophrenia spectrum syndromes in the general population, Psychiatric disorders in 35 to 65 year-old residents of the city of Lausanne and their association to cardiovasular risk factors: a population based survey, G3987400284, G4782823791, G5282548929, G5531419334, G5599442719, G5735209081, G5807518093, G5928719961, G5981938709, G6715704539, G6927407676, G7262634952, Cardiovascular diseases and psychiatric disorders in the general population: a prospective follow-up study, 7/7 Psychiatric Genomics Consortium: Finding actionable variation, G7975901996, G8253295407, G8499801373, Cardiovascular diseases and psychiatric disorders in the general population: a prospective follow-up study, 1/7 PGC: Advancing Discovery and Impact
OpenAlex ID: W3013660197