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Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence
Jeanne E. Savage, Philip R. Jansen, Sven Stringer, Kyoko Watanabe, Julien Bryois, Christiaan de Leeuw, Mats Nagel, Swapnil Awasthi, Peter B. Barr, Jonathan R. I. Coleman, Katrina L. Grasby, Anke R. Hammerschlag, Jakob Kaminski, Robert Karlsson, Eva Krapohl, Max Lam, Marianne Nygaard, Chandra A. Reynolds, Joey W. Trampush, Hannah Young, Delilah Zabaneh, Sara Hägg, Narelle K. Hansell, Ida Karlsson, Sten Linnarsson, Grant W. Montgomery, Ana B. Muñoz‐Manchado, Erin Burke Quinlan, Günter Schumann, Nathan Skene, Bradley T. Webb, Tonya White, Dan E. Arking, Dimitrios Avramopoulos, Robert M. Bilder, Panos Bitsios, Katherine E. Burdick, Tyrone D. Cannon, Ornit Chiba‐Falek, Andrea Christoforou, Elizabeth T. Cirulli, Eliza Congdon, Aiden Corvin, Gail Davies, Ian J. Deary, Pamela DeRosse, Dwight Dickinson, Srdjan Djurovic, Gary Donohoe, Emily Drabant Conley, Johan G. Eriksson, Thomas Espeseth, Nelson B. Freimer, Stella G. Giakoumaki, Ina Giegling, Michael Gill, David C. Glahn, Ahmad R. Hariri, Alex Hatzimanolis, Matthew C. Keller, Emma Knowles, Deborah K. Attix, Bettina Konte, Jari Lahti, Stéphanie Le Hellard, Todd Lencz, David C. Liewald, Edythe London, Astri J. Lundervold, Anil K. Malhotra, Ingrid Melle, Derek W. Morris, Anna C. Need, William Ollier, Aarno Palotie, Antony Payton, Neil Pendleton, Russell A. Poldrack, Katri Räikkönen, Ivar Reinvang, Panos Roussos, Dan Rujescu, Fred W. Sabb, Matthew A. Scult, Olav B. Smeland, Nikolaos Smyrnis, John M. Starr, Vidar M. Steen, Nikos C. Stefanis, Richard E. Straub, Kjetil Sundet, Henning Tiemeier, Aristotle N. Voineskos, Daniel R. Weinberger, Elisabeth Widén, Jin Yu, Gonçalo R. Abecasis, Ole A. Andreassen, Gerome Breen, Lene Christiansen, Birgit Debrabant, Danielle M. Dick, Andreas Heinz, Jens Hjerling‐Leffler, M. Arfan Ikram, Kenneth S. Kendler, Nicholas G. Martin, Sarah E. Medland, Nancy L. Pedersen, Robert Plomin, Tinca J. C. Polderman, Stephan Ripke, Sophie van der Sluis, Patrick F. Sullivan, Scott Vrieze, Margaret J. Wright, Daniëlle Posthuma
Bibliographic record
VenueNature Genetics · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersJane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los AngelesNIH Clinical CenterNational Institute of Dental and Craniofacial ResearchNational Institute of Neurological Disorders and StrokeNational Institute of Biomedical Imaging and BioengineeringNational Human Genome Research InstituteSyddansk UniversitetNational Institute of Mental HealthInstitute for Molecular Bioscience, University Of QueenslandUniversity of GalwayMedical Research CouncilNational Institute on Drug AbuseBiotechnology and Biological Sciences Research CouncilStanley Center for Psychiatric Research, Broad InstitutePfizerUniversity of California, Los AngelesNational Institutes of HealthNational Institute on AgingNational University of IrelandNational Institute on Alcohol Abuse and AlcoholismCentre for Cognitive Ageing and Cognitive EpidemiologyYale UniversityKarolinska InstitutetQueensland Brain InstituteH. Lundbeck A/SJohns Hopkins UniversityUniversitetet i OsloUniversitetet i BergenNational Center for Research ResourcesNational and Kapodistrian University of AthensUniversity of CreteImperial College LondonUniversity of TorontoSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungBroad InstituteDirectorate for Biological SciencesNorthwell HealthTrinity College DublinErasmus Universitair Medisch Centrum RotterdamUniversity of OregonKing's College LondonVirginia Commonwealth UniversityHelsingin YliopistoHaukeland UniversitetssjukehusNederlandse Organisatie voor Wetenschappelijk OnderzoekWellcome TrustUniversity of Southern CaliforniaNational Science FoundationUniversity of MinnesotaMassachusetts General HospitalDepartment of Psychology and Neuroscience, Duke UniversityEli Lilly and CompanyUniversity of North Carolina at Chapel HillBrigham and Women's Hospital
KeywordsBiologyGenome-wide association studyComputational biologyGenetic associationGeneticsMeta-analysisAssociation (psychology)GenomeSingle-nucleotide polymorphismGeneGenotype
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)0.003
metaresearch head score (Gemma)0.005
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: Review
Teacher disagreement score0.003
Threshold uncertainty score0.016
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 head0.054
GPT teacher head0.341
Teacher spread0.286 · 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 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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Citations1,418
Published2018
Admission routes2
Has abstractno