Record W2905226148 · doi:10.1016/j.biopsych.2018.11.024

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

2018· review· en· W2905226148 on OpenAlexaff

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

DOI10.1016/j.biopsych.2018.11.024

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001

metaresearch head score (Gemma)0.001

Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated

Candidate categoriesMeta-epidemiology (narrow)

Consensus categoriesnone

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Observational · Consensus signal: Observational

GenreCandidate signal: Review · Consensus signal: Review

Teacher disagreement score0.142

Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

Category	Codex	Gemma
Metaresearch	0.001	0.001
Meta-epidemiology (narrow)	0.000	0.000
Meta-epidemiology (broad)	0.002	0.001
Bibliometrics	0.000	0.000
Science and technology studies	0.000	0.000
Scholarly communication	0.000	0.000
Open science	0.000	0.000
Research integrity	0.001	0.000
Insufficient payload (model declined to judge)	0.000	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 head0.123

GPT teacher head0.342

Teacher spread0.220 · 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