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Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders
Raymond K. Walters, Renato Polimanti, Emma C. Johnson, Jeanette N. McClintick, Mark J. Adams, Amy Adkins, Fazil Alıev, Silviu‐Alin Bacanu, Anthony Batzler, Sarah Bertelsen, Joanna M. Biernacka, Tim B. Bigdeli, Li‐Shiun Chen, Toni‐Kim Clarke, Yi‐Ling Chou, Franziska Degenhardt, Anna R. Docherty, Alexis C. Edwards, Pierre Fontanillas, Jerome C. Foo, Louis Fox, Josef Frank, Ina Giegling, Scott D. Gordon, Laura M. Hack, Annette M. Hartmann, Sarah M. Hartz, Stefanie Heilmann‐Heimbach, Stefan Herms, Colin A. Hodgkinson, Per Hoffmann, Jouke‐Jan Hottenga, Martin A. Kennedy, Mervi Alanne-Kinnunen, Bettina Konte, Jari Lahti, Marius Lahti‐Pulkkinen, Dongbing Lai, Lannie Ligthart, Anu Loukola, Brion S. Maher, Hamdi Mbarek, Andrew M. McIntosh, Matthew B. McQueen, Jacquelyn L. Meyers, Yuri Milaneschi, Teemu Palviainen, John F. Pearson, Roseann E. Peterson, Samuli Ripatti, Euijung Ryu, Nancy L. Saccone, Jessica E. Salvatore, Sandra Sanchez‐Roige, Melanie L. Schwandt, Richard Sherva, Fabian Streit, Jana Strohmaier, Nathaniel Thomas, Jen‐Chyong Wang, Bradley T. Webb, Robbee Wedow, Leah Wetherill, Amanda G. Wills, Danfeng Chen, Doo‐Sup Choi, William Copeland, Robert Culverhouse, Norbert Dahmen, Louisa Degenhardt, Benjamin W. Domingue, Sarah L. Elson, Mark A. Frye, Wolfgang Gäbel, Caroline Hayward, Marcus Ising, Margaret A. Keyes, Falk Kiefer, John R. Kramer, Samuel Kuperman, Susanne Lucae, Michael T. Lynskey, Wolfgang Maier, Karl Mann, Satu Männistö, Bertram Müller‐Myhsok, Alison D. Murray, John I. Nürnberger, Aarno Palotie, Ulrich W. Preuss, Katri Räikkönen, Maureen Reynolds, Monika Ridinger, Norbert Scherbaum, Marc A. Schuckit, Michael Soyka, Jens Treutlein, Stephanie H. Witt, Norbert Wodarz, Peter Zill, Daniel E. Adkins, Joseph M. Boden, Dorret I. Boomsma, Laura J. Bierut, Sandra A. Brown, Kathleen K. Bucholz, Sven Cichon, E. Jane Costello, Harriet de Wit, Nancy Diazgranados, Danielle M. Dick, Johan G. Eriksson, Lindsay A. Farrer, Tatiana Foroud, Nathan A. Gillespie, Alison Goate, David Goldman, Richard A. Grucza, Dana B. Hancock, Kathleen Mullan Harris, Andrew C. Heath, Victor Hesselbrock, John K. Hewitt, Christian J. Hopfer, L. John Horwood, William Iacono, Eric O. Johnson, Jaakko Kaprio, Victor M. Karpyak, Kenneth S. Kendler, Henry R. Kranzler, Kenneth Krauter, Paul Lichtenstein, Penelope A. Lind, Matt McGue, James MacKillop, Pamela A. F. Madden, Hermine H. Maes, Patrik K. E. Magnusson, Nicholas G. Martin, Sarah E. Medland, Grant W. Montgomery, Elliot C. Nelson, Markus M. Nöthen, Abraham A. Palmer, Nancy L. Pedersen, Brenda W.J.H. Penninx, Bernice Porjesz, John P. Rice, Marcella Rietschel, Brien P. Riley, Richard J. Rose, Dan Rujescu, Pei‐Hong Shen, Judy L. Silberg, Michael C. Stallings, Ralph E. Tarter, Michael M. Vanyukov, Scott Vrieze, Tamara L. Wall, John B. Whitfield, Hongyu Zhao, Benjamin M. Neale, Joel Gelernter, Howard J. Edenberg, Arpana Agrawal
Bibliographic record
VenueNature Neuroscience · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteNational Human Genome Research InstituteNational Health and Medical Research CouncilNational Center for Advancing Translational SciencesMedical Research CouncilNational Institute on Alcohol Abuse and AlcoholismH. Lundbeck A/SCenter for Individualized Medicine, Mayo ClinicGillings School of Public HealthAgency for Healthcare Research and QualityNational Institutes of HealthNederlandse Organisatie voor Wetenschappelijk OnderzoekAvera Institute for Human GeneticsYale UniversityU.S. Department of Veterans AffairsStiftelsen för Strategisk ForskningNational Institute on Drug AbuseUniversity of PennsylvaniaVetenskapsrådetVirginia Commonwealth UniversityGeorgia Clinical and Translational Science AllianceWellcome TrustEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentZonMwKarolinska InstitutetLundbeckfondenNational Institute of Mental HealthPfizer
KeywordsGenome-wide association studyAlcohol dependenceNeurosciencePsychologyPsychiatryNeuroimagingAlcoholGeneticsSingle-nucleotide polymorphismBiologyGene
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)0.001
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.018
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 head0.010
GPT teacher head0.291
Teacher spread0.281 · 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
Citations711
Published2018
Admission routes1
Has abstractno