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Biological insights from 108 schizophrenia-associated genetic loci
Jacqueline I. Goldstein, Stephan Ripke, Hailiang Huang, Kai-How Farh, Brendan Bulik‐Sullivan, Kimberly D. Chambert, Giulio Genovese, Jordan W. Smoller, Phil Lee, Edward M. Scolnick, Elizabeth Bevilacqua, Jennifer L. Moran, Aarno Palotie, Tracey L. Petryshen, Richard A. Belliveau, Steven A. McCarroll, Sarah E. Bergen, Benjamin M. Neale, Alkes L. Price, Mark J. Daly, Paul Cormican, Aiden Corvin, Michael Gill, Gary Donohoe, Alexander Richards, Michael J. Owen, Noa Carrera, Marian L. Hamshere, Nick Craddock, David Kavanagh, Peter Holmans, George Kirov, Sophie E. Legge, Valentina Escott‐Price, Nigel Williams, Andrew Pocklington, Lyudmila Georgieva, James Walters, David Collier, Younes Mokrab, Tune H. Pers, Erik Söderman, Srdjan Djurovic, Morten Mattingsdal, Ole A. Andreassen, Ingrid Melle, Esben Agerbo, Preben Bo Mortensen, Henrik B. Rasmussen, Ditte Demontis, Line Olsen, Thomas Folkmann Hansen, Margot Albus, Madeline Alexander, Claudine Laurent, Douglas F. Levinson, Farooq Amin, Silviu‐Alin Bacanu, Bradley T. Webb, Tim B. Bigdeli, Brandon Wormley, Christian Hammer, Martin Begemann, Sergi Papiol, Hannelore Ehrenreich, Béla Melegh, Christina M. Hultman, Patrik K. E. Magnusson, Anna K. Kähler, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, René S. Kahn, Wiepke Cahn, Eric Strengman, Guiqing Cai, Jeremy M. Silverman, Vahram Haroutunian, Joseph D. Buxbaum, Elena Parkhomenko, Joseph I. Friedman, Elodie Drapeau, Kenneth L. Davis, Abraham Reichenberg, Dominique Campion, Rita M. Cantor, Frans Henskens, Vaughan J. Carr, Christos Pantelis, Patricia T. Michie, Rodney J. Scott, Stanley V. Catts, Ulrich Schall, Raymond Chan, Hon‐Cheong So, Ronald Y.L. Chen, Emily Wong, Eric Chen, Wei Cheng, Eric Cheung, Jimmy Lee, Siow Ann Chong, Kang Sim, Mythily Subramaniam, C. Robert Cloninger, Dragan M. Švrakić, David Cohen, Nadine Cohen, Yunjung Kim, Stephanie Williams, Martilias S. Farrell, James J. Crowley, Paola Giusti‐Rodríguez, Jin Szatkiewicz, David Curtis, Jonathan Pimm, Andrew McQuillin, Hugh Gurling, Michael Davidson, Mark Weiser, Franziska Degenhardt, Stefan Herms, Sven Cichon, Jurgen Del‐Favero, Manuel Mattheisen, Ole Mors, George N. Papadimitriou, Dimitris Dikeos, Timothy G. Dinan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan G. Eriksson, Veikko Salomaa, Laurent Essioux, Ayman H. Fanous, Thomas G. Schulze, Stephanie H. Witt, Jana Strohmaier, Sandra Meier, Josef Frank, Marcella Rietschel, Lude Franke, Juha Karjalainen, Ann Olincy, Robert Freedman, Nelson B. Freimer, Marion Friedl, Bettina Konte, Annette M. Hartmann, Dan Rujescu, Menachem Fromer, Shaun Purcell, Stephanie Godard, В. Е. Голимбет, Qingqin S. Li, Srihari Gopal, Dai Wang, Naomi R. Wray, Bryan Mowry, Peter M. Visscher, Jacob Gratten, Sang Lee, Lieuwe de Haan, Carin J. Meijer, Mark Hansen, Pamela Sklar, Per Hoffmann, Tõnu Esko, Joel N. Hirschhorn, David M. Hougaard, Mads V. Hollegaard, Masashi Ikeda, Nakao Iwata, Inge Joa, Sara Marsal, Antonio Julià
Bibliographic record
VenueNature · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Institute of Mental HealthStanley Center for Psychiatric Research, Broad InstituteDiakonhjemmetUniversitetet i OsloKarolinska InstitutetLundbeckfondenTrinity College DublinMedical Research CouncilCardiff UniversityAarhus UniversitetBroad InstituteDanmarks Tekniske UniversitetWellcome TrustVirginia Commonwealth UniversityKing's College LondonEli Lilly and CompanyEmory UniversityMassachusetts General HospitalNational Institute for Health and Care ResearchH. Lundbeck A/SU.S. Department of Veterans Affairs
KeywordsSchizophrenia (object-oriented programming)Genome-wide association studyGenetic associationBiologyGeneticsAlleleGenePsychosisGenomeGenotypeMedicineSingle-nucleotide polymorphismPsychiatry
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 head0.008
GPT teacher head0.239
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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 designObservational
Domainnot available
GenreEmpirical
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".
Quick stats
Citations8,086
Published2014
Admission routes1
Has abstractno