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Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use
David M. Brazel, Yu Jiang, Jordan M. Hughey, Valérie Turcot, Xiaowei Zhan, Jian Gong, Chiara Batini, J. Dylan Weissenkampen, Mengzhen Liu, Daniel R. Barnes, Sarah Bertelsen, Yi‐Ling Chou, A. Mesut Erzurumluoglu, Jessica D. Faul, Jeff Haessler, Anke R. Hammerschlag, Chris Hsu, Manav Kapoor, Dongbing Lai, Nhung Le, Christiaan de Leeuw, Anu Loukola, Massimo Mangino, Carl Melbourne, Giorgio Pistis, Beenish Qaiser, Rebecca Rohde, Yaming Shao, Heather M. Stringham, Leah Wetherill, Wei Zhao, Arpana Agrawal, Laura J. Bierut, Chu Chen, Charles B. Eaton, Alison Goate, Christopher Haiman, Andrew C. Heath, William G. Iacono, Nicholas G. Martin, Tinca J. C. Polderman, Alex P. Reiner, John P. Rice, David Schlessinger, H. Steven Scholte, Jennifer A. Smith, Jean‐Claude Tardif, Hilary A. Tindle, Andries R. van der Leij, Michael Boehnke, Jenny Chang‐Claude, Francesco Cucca, Sean P. David, Tatiana Foroud, Joanna M. M. Howson, Sharon L. R. Kardia, Charles Kooperberg, Markku Laakso, Guillaume Lettre, Pamela A. F. Madden, Matt McGue, Kari E. North, Daniëlle Posthuma, Timothy D. Spector, Daniel O. Stram, Martin D. Tobin, David R. Weir, Jaakko Kaprio, Gonçalo R. Abecasis, Dajiang J. Liu, Scott Vrieze, Praveen Surendran, Robin Young, Asif Rasheed, Maria Samuel, Jukka Kontto, Markus Perola, Muriel Caslake, Anton J. M. de Craen, Stella Trompet, Maria Uria-Nickelsen, Anders Mälarstig, Dermot F. Reily, Maarten Hoek, Thomas Vogt, J. Wouter Jukema, Naveed Sattar, Ian Ford, Chris J. Packard, Dewan S Alam, Abdulla al Shafi Majumder, Emanuele Di Angelantonio, Rajiv Chowdhury, Philippe Amouyel, Dominique Arveiler, Stefan Blankenberg, Jean Ferrières, Frank Kee, Kari Kuulasmaa, Martina Müller‐Nurasyid, Giovanni Veronesi, Jarmo Virtamo, Philippe Frossard, Børge G. Nordestgaard, Danish Saleheen, John Danesh, Adam S. Butterworth, Victoria E. Jackson, Tibor V. Varga, Helen R. Warren, Vinicius Tragante, Ioanna Tachmazidou, Sarah E. Harris, Evangelos Evangelou, Jonathan Marten, Weihua Zhang, Elisabeth Altmaier, Jian’an Luan, Claudia Langenberg, Robert A. Scott, Hanieh Yaghootkar, Kathleen Stirrups, Stavroula Kanoni, Eirini Marouli, Fredrik Karpe, Anna F. Dominiczak, Peter Sever, Neil Poulter, Olov Rolandsson, Clemens Baumbach, Saima Afaq, John C. Chambers, Jaspal S. Kooner, Nicholas J. Wareham, Frida Renström, Göran Hallmans, Riccardo E. Marioni, Janie Corley, John M. Starr, Niek Verweij, Rudolf A. de Boer, Peter van der Meer, Ersin Yavas, Ilonca Vaartjes, Michiel L. Bots, Folkert W. Asselbergs, Hans J. Grabe, Henry Völzke, Matthias Nauck, Stefan Weiß, Paul D.P. Pharoah, Alison M. Dunning, Joe Dennis, Deborah J. Thompson, Kyriaki Michailidou, Douglas F. Easton, Antonis C. Antoniou, Jessica Tyrrell, Evelin Mihailov, Nilesh J. Samani, Kaixin Zhou, Matthew Neville, Andres Metspalu, Ian P. Hall, David P. Strachan, Ian J. Deary, Timothy M. Frayling, Caroline Hayward, Pim van der Harst, Eleftheria Zeggini, Patricia B. Munroe, Jan‐Håkan Jansson, Paul W. Franks, Panos Deloukas, Mark J. Caulfield, Louise V. Wain
Bibliographic record
VenueBiological Psychiatry · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Science Foundation Graduate Research Fellowship ProgramNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on Drug AbuseBritish Heart FoundationNational Institute on Alcohol Abuse and AlcoholismEconomic and Social Research CouncilMedical Research CouncilNational Institute on AgingNational Science Foundation of Sri LankaNational Institute of General Medical SciencesNational Institute for Health and Care ResearchNational Human Genome Research InstituteNederlandse Organisatie voor Wetenschappelijk OnderzoekWellcome TrustNational Institutes of HealthCancer Research UKNational Heart, Lung, and Blood InstitutePfizer
KeywordsNonsynonymous substitutionGeneticsBiologyExomeHeritabilityGenome-wide association studyMissing heritability problemGenetic architectureExome sequencing1000 Genomes ProjectImputation (statistics)PhenotypeSingle-nucleotide polymorphismGenetic associationCopy-number variationGenotypeGeneGenomeMissing data
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)0.002
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: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| 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) | 0.003 | 0.001 |
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 head0.123
GPT teacher head0.342
Teacher spread0.220 · 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".
Quick stats
Citations88
Published2018
Admission routes1
Has abstractno