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Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci
Vinicius Tragante, Michael R. Barnes, Santhi K. Ganesh, Matthew B. Lanktree, Wei Guo, Nora Franceschini, Erin N. Smith, Toby Johnson, Michael V. Holmes, Sandosh Padmanabhan, Konrad J. Karczewski, Berta Almoguera, John Barnard, Jens Baumert, Yen-Pei C. Chang, Clara C. Elbers, Martin Farrall, Mary Fischer, Tom R. Gaunt, Johannes M.I.H. Gho, Christian Gieger, Anuj Goel, Yan Gong, Aaron Isaacs, Marcus E. Kleber, Irene Mateo Leach, Caitrin W. McDonough, Matthijs F.L. Meijs, Olle Melander, Christopher P. Nelson, Ilja M. Nolte, Nathan Pankratz, Jonathan A. Shaffer, Sonia Shah, Maciej Tomaszewski, Peter J. van der Most, Erik P.A. van Iperen, Judith M. Vonk, Kate Witkowska, Caroline O.L. Wong, Li Zhang, Amber L. Beitelshees, Gerald S. Berenson, Deepak L. Bhatt, Morris J. Brown, Amber Burt, Rhonda M. Cooper‐DeHoff, John Connell, Karen J. Cruickshanks, Sean Curtis, Christian Delles, Ron T. Gansevoort, Xiuqing Guo, Haiqing Shen, Claire E. Hastie, Marten H. Hofker, G. Kees Hovingh, Daniel Seung Kim, Susan Kirkland, Ronald Klein, Leslie A. Lange, S. Maiwald, Christopher Newton‐Cheh, Eoin OʼBrien, N. Charlotte Onland‐Moret, Walter Palmas, Afshin Parsa, Brenda W.J.H. Penninx, Mary Pettinger, Ramachandran S. Vasan, Jane Ranchalis, Paul M. Ridker, Lynda Rose, Peter Sever, Daichi Shimbo, Laura D. Steele, Ronald P. Stolk, Barbara Thorand, Mieke D. Trip, Cornelia M. van Duijn, W. M. Monique Verschuren, Cisca Wijmenga, Sharon B. Wyatt, J. Hunter Young, Aeilko H. Zwinderman, Connie R. Bezzina, Eric Boerwinkle, Juan P. Casas, Mark J. Caulfield, Aravinda Chakravarti, Daniel I. Chasman, Karina W. Davidson, Pieter A. Doevendans, Anna F. Dominiczak, Garret A. FitzGerald, John G. Gums, Myriam Fornage, Håkon Håkonarson, Indrani Halder, Hans L. Hillege, Thomas Illig, Gail P. Jarvik, Julie A. Johnson, John J.P. Kastelein, Wolfgang Köenig, Meena Kumari, Winfried März, Sarah S. Murray, Jeffery R. O’Connell, Albertine J. Oldehinkel, James S. Pankow, Daniel J. Rader, Susan Redline, Muredach P. Reilly, Eric E. Schadt, Kandice Kottke‐Marchant, Harold Snieder, M Snyder, Alice Stanton, Martin D. Tobin, André G. Uitterlinden, Pim van der Harst, Yvonne T. van der Schouw, Nilesh J. Samani, Hugh Watkins, Andrew D. Johnson, Alex P. Reiner, Xiaofeng Zhu, Paul I. W. de Bakker, Daniel Levy, Folkert W. Asselbergs, Patricia B. Munroe, Brendan J. Keating
Bibliographic record
VenueThe American Journal of Human Genetics · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsDalhousie UniversityMcMaster University
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteU.S. National Library of MedicineNational Institute on AgingNational Institute of General Medical SciencesMedical Research CouncilNational Institute for Health and Care ResearchBritish Heart FoundationWellcome Trust
KeywordsGeneticsGeneMeta-analysisBiologyComputational biologyEvolutionary biologyMedicineInternal medicine
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 distilled prediction
Teacher imitationNot 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.182
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 head0.066
GPT teacher head0.345
Teacher spread0.279 · 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 teacher head, not a consensus.
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
Citations165
Published2014
Admission routes1
Has abstractno