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The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

2019· review· en· W2984805909 on OpenAlexfundno aff
Jonathan R. I. Coleman, Héléna A. Gaspar, Julien Bryois, Enda M. Byrne, Andreas J. Forstner, Peter Holmans, Christiaan de Leeuw, Manuel Mattheisen, Andrew McQuillin, Jennifer M. Whitehead Pavlides, Stephan Ripke, Eli A. Stahl, Vassily Trubetskoy, Maciej Trzaskowski, Abdel Abdellaoui, Mark J. Adams, Annelie Nordin Adolfsson, Esben Agerbo, Diego Albani, Ney Alliey‐Rodriguez, Thomas D. Als, Till F. M. Andlauer, Verneri Antilla, Swapnil Awasthi, Silviu‐Alin Bacanu, Marie Bækvad‐Hansen, Nicholas Bass, Michael Bauer, Aartjan T.F. Beekman, Richard A. Belliveau, Tim B. Bigdeli, Elisabeth B. Binder, Erlend Bøen, Marco P. Boks, James Boocock, Henriette N. Buttenschøn, Jonas Bybjerg‐Grauholm, William Byerley, Miguel Casas, Felecia Cerrato, Pablo Cervantes, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Jane Christensen, Claire Churchhouse, Toni‐Kim Clarke, Lucía Colodro‐Conde, Baptiste Couvy‐Duchesne, Gregory E. Crawford, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Jurgen Del‐Favero, J. Raymond DePaulo, Eske M. Derks, Neşe Direk, Srdjan Djurovic, Amanda Dobbyn, Thalia C. Eley, Torbjørn Elvsåshagen, Valentina Escott‐Price, Chun Chieh Fan, Hilary K. Finucane, Sascha B. Fischer, Matthew Flickinger, Tatiana Foroud, Liz Forty, Christine Fraser, Louise Frisén, Katrin Gade, Fernando S. Goes, Jaqueline Goldstein, Melissa J. Green, Tiffany A. Greenwood, Jakob Grove, Weihua Guan, Christine Søholm Hansen, Thomas Folkmann Hansen, Martin Hautzinger, Urs Heilbronner, Maria Hipolito, Per Hoffmann, Dominic Holland, Georg Homuth, Jouke‐Jan Hottenga, Laura M. Huckins, Marcus Ising, Stéphane Jamain, Rick Jansen, Jessica Johnson, Simone de Jong, Anders Juréus, Radhika Kandaswamy, James L. Kennedy, Farnush Farhadi Hassan Kiadeh, Sarah Kittel‐Schneider, James A. Knowles, Isaac S. Kohane, Anna C. Koller, Warren W. Kretzschmar, Jesper Krogh, Ralph Kupka, Zoltán Kutalik, William Lawson, Phil H. Lee, Jun Z. Li, Chunyu Liu, Loes M. Olde Loohuis, Anna Maaser, Donald J. MacIntyre, Dean F. MacKinnon, Pamela B. Mahon, Wolfgang Maier, Jonathan Marchini, Lina Martinsson, Steve McCarroll, Patrick J. McGrath, Helena Medeiros, Sarah E. Medland, Divya Mehta, Fan Meng, Christel M. Middeldorp, Yuri Milaneschi, Lili Milani, Saira Saeed Mirza, Francis M. Mondimore, Derek W. Morris, Thomas W. Mühleisen, Niamh Mullins, Matthias Nauck, Caroline M. Nievergelt, Michel G. Nivard, Evaristus Nwulia, Dale R. Nyholt, Paul F. O’Reilly, Anil P. S. Ori, Lilijana Oruč, Urban Ösby, Högni Óskarsson, Jodie N. Painter, José Guzmán‐Parra, Amy Perry, Roseann E. Peterson, Erik Pettersson, Wouter J. Peyrot, Andrea Pfennig, Giorgio Pistis, Shaun Purcell, Per Qvist, Eline J. Regeer, Céline S. Reinbold, John P. Rice, Brien P. Riley, Fabio Rivas, Margarita Rivera, Panos Roussos, Douglas M. Ruderfer, Euijung Ryu, Alan F. Schatzberg, William A. Scheftner, Robert A. Schoevers, Nicholas J. Schork, Eva C. Schulte, Tatyana Shehktman, Jianxin Shi, Stanley I. Shyn, Engilbert Sigurðsson, Olav B. Smeland, Johannes H. Smit, Janet L. Sobell, Anne T. Spijker, Michael Steffens, John S. Strauss, Fabian Streit, Henning Teismann, Alexander Teumer, Robert C. Thompson, Wesley K. Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, André G. Uitterlinden, Daniel Umbricht, Helmut Vedder, Weiqing Wang, Bradley T. Webb, Cynthia Shannon Weickert, Thomas W. Weickert, Shantel Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H. Witt, Yang Wu, Hualin Simon Xi, Jian Yang, Allan H. Young, Peter P. Zandi, Peng Zhang, Futao Zhang, Sebastian Zöllner, Rolf Adolfsson, Ingrid Agartz, Martin Alda, Volker Arolt, Lena Backlund, Frank Bellivier, Wade H. Berrettini, Joanna M. Biernacka, Michael Boehnke, Aiden Corvin, Nicholas Craddock, Mark J. Daly, Udo Dannlowski, Enrico Domenici, Katharina Domschke, Tõnu Esko, Janice M. Fullerton, Elliot S. Gershon, Eco J. C. de Geus, Michael Gill, Maria Grigoroiu‐Serbânescu, Joanna Hauser, Caroline Hayward, David M. Hougaard, Christina M. Hultman, Ian Jones, Lisa Jones, René S. Kahn, Kenneth S. Kendler, George Kirov, Stefan Kloiber, Mikael Landén, Marion Leboyer, Glyn Lewis, Qingqin S. Li, Jolanta Lissowska, Susanne Lucae, Patrik K. E. Magnusson, Nicholas G. Martin, Susan L. McElroy, Andrew M. McIntosh, Francis J. McMahon, Ingrid Melle, Philip B. Mitchell, Gunnar Morken, Ole Mors, Preben Bo Mortensen, Bertram Müller-Myhsok, Benjamin M. Neale, Merete Nordentoft, Markus M. Nöthen, Michael O‘Donovan, Ketil J. Øedegaard, Michael J. Owen, Sara A. Paciga, Carlos N. Pato, Michele T. Pato, Nancy L. Pedersen, Roy H. Perlis, David J. Porteous, Daniëlle Posthuma, Josep Antoni Ramos‐Quiroga, Marcella Rietschel, Guy A. Rouleau, Peter R. Schofield, Alessandro Serretti, Jordan W. Smoller, Hreinn Stefánsson, Eystein Stordal, Henning Tiemeier, Gustavo Turecki, Rudolf Uher, Eduard Vieta, Henry Völzke, Thomas Werge, Ole A. Andreassen, Anders D. Børglum, Sven Cichon, Howard J. Edenberg, Arianna Di Florio, John R. Kelsoe, Cathryn M. Lewis, Roel A. Ophoff, Pamela Sklar, Patrick F. Sullivan, Naomi R. Wray, Weihua Guan, Gerome Breen

Bibliographic record

VenueBiological Psychiatry · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Mental HealthNational Health and Medical Research CouncilStanley Center for Psychiatric Research, Broad InstituteUniversity of California, San DiegoNational Institutes of HealthH. Lundbeck A/SMedical Research CouncilServierSiemens HealthineersNational Institute on AgingMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaChinese Society of Clinical OncologyNovo Nordisk FondenNSW Ministry of HealthRheinische Friedrich-Wilhelms-Universität BonnVetenskapsrådetRegion HovedstadenNovo NordiskEuropean Regional Development FundUniversitat de BarcelonaKing's College LondonMax-Planck-GesellschaftStanley Medical Research InstituteBundesministerium für Bildung und ForschungMinisterio de Economía y CompetitividadCenter for Individualized Medicine, Mayo ClinicDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekDepartament d'Innovació, Universitats i Empresa, Generalitat de CatalunyaGeneralitat de CatalunyaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversität GreifswaldAgence Nationale de la RechercheCanadian Institutes of Health ResearchOffice of Health and Medical ResearchUniversità di BolognaAstraZenecaEuropean CommissionScottish Funding CouncilDepartment of Health and Social CareBroad InstituteQIMR Berghofer Medical Research InstituteNorges ForskningsrådErasmus Medisch CentrumStiftelsen för Strategisk ForskningNeuroscience Research AustraliaWellcome TrustNational Institute on Alcohol Abuse and AlcoholismStockholms Läns LandstingHøjteknologifondenU.S. Department of Health and Human ServicesGlaxoSmithKlineMayo ClinicWayne and Gladys Valley FoundationDepartament de Salut, Generalitat de CatalunyaNational Science FoundationUniversity of MichiganLundbeckfondenCentro de Investigación Biomédica en Red de Salud MentalEli Lilly and CompanyKaiser PermanenteState University of New YorkMaudsley CharityWestfälische Wilhelms-Universität MünsterInstituto de Salud Carlos IIIEllison Medical FoundationJanssen Research and DevelopmentZonMwNational Alliance for Research on Schizophrenia and DepressionAgència de Gestió d'Ajuts Universitaris i de RecercaNational Institute for Health and Care ResearchCilagRobert Wood Johnson FoundationSunovionPfizer
KeywordsGenome-wide association studyAssociation (psychology)GeneticsMoodPsychologyGenetic associationClinical psychologyPsychiatryBiologyGenotypePsychotherapistSingle-nucleotide polymorphismGene

Abstract

fetched live from OpenAlex

BACKGROUND: Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction. METHODS: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424). RESULTS: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder. CONCLUSIONS: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.347
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations210
Published2019
Admission routes1
Has abstractyes

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