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Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry
Mariaelisa Graff, Anne E. Justice, Kristin L. Young, Eirini Marouli, Xinruo Zhang, Rebecca S. Fine, Elise Lim, Victoria L. Buchanan, Kristin A. Rand, Mary F. Feitosa, Mary K. Wojczynski, Lisa R. Yanek, Yaming Shao, Rebecca Rohde, Adebowale Adeyemo, Melinda C. Aldrich, Matthew Allison, Christine B. Ambrosone, Stefan Ambs, Christopher I. Amos, Donna K. Arnett, Larry D. Atwood, Elisa V. Bandera, Traci M. Bartz, Diane M. Becker, Sonja I. Berndt, Leslie Bernstein, Lawrence F. Bielak, William J. Blot, Erwin P. Böttinger, Donald W. Bowden, Jonathan P. Bradfield, Jennifer A. Brody, Ulrich Broeckel, Gregory L. Burke, Brian E. Cade, Qiuyin Cai, Neil E. Caporaso, Chris Carlson, John D. Carpten, Graham Casey, Stephen J. Chanock, Guanjie Chen, Minhui Chen, Yii-Der I. Chen, Wei‐Min Chen, Alessandra Chesi, Charleston W. K. Chiang, Lisa W. Chu, David V. Conti, Mary Cushman, Ellen W. Demerath, Sandra L. Deming, Latchezar Dimitrov, Jingzhong Ding, W. Ryan Diver, Qing Duan, Michele K. Evans, Adeyinka G. Falusi, Jessica D. Faul, Myriam Fornage, Caroline S. Fox, Barry I. Freedman, Melissa García, Elizabeth M. Gillanders, Phyllis J. Goodman, Omri Gottesman, Struan F.A. Grant, Xiuqing Guo, Håkon Håkonarson, Talin Haritunians, Tamara B. Harris, Curtis C. Harris, Brian E. Henderson, Anselm Hennis, Dena Hernández, Joel N. Hirschhorn, Lorna H. McNeill, Timothy D. Howard, Barbara V. Howard, Ann W. Hsing, Yu-Han H. Hsu, Jennifer J. Hu, Chad D. Huff, Dezheng Huo, Sue A. Ingles, Marguerite R. Irvin, Esther M. John, Karen Johnson, Joanne M. Jordan, Edmond K. Kabagambe, Sun Jung Kang, Sharon L.R. Kardia, Brendan J. Keating, Rick A. Kittles, Eric A. Klein, Suzanne Kolb, Laurence N. Kolonel, Charles Kooperberg, Lewis H. Kuller, Abdullah Kutlar, Leslie A. Lange, Carl D. Langefeld, Loı̈c Le Marchand, Hampton L. Leonard, Guillaume Lettre, Albert M. Levin, Yun Li, Jin Li, Ching‐Ti Liu, Youfang Liu, Simin Liu, Kurt Lohman, Vaneet Lotay, Yingchang Lu, William Maixner, JoAnn E. Manson, Barbara McKnight, Yan Meng, Keri L. Monda, Kris Monroe, Jason H. Moore, Thomas H. Mosley, Poorva Mudgal, Adam B. Murphy, Rajiv Nadukuru, Mike A. Nalls, Katherine L. Nathanson, Uma Nayak, Amidou N’Diaye, Barbara Nemesure, Christine Neslund‐Dudas, Marian L. Neuhouser, Sarah J. Nyante, Heather M. Ochs‐Balcom, Temidayo O. Ogundiran, Adesola Ogunniyi, Oladosu Ojengbede, Hayrettin Okut, Olufunmilayo I. Olopade, Andrew F. Olshan, Badri Padhukasahasram, Julie R. Palmer, Cameron D. Palmer, George Papanicolaou, Sanjay R. Patel, Curtis A. Pettaway, Patricia A. Peyser, Michael F. Press, D. C. Rao, Laura J. Rasmussen‐Torvik, Susan Redline, Alex P. Reiner, Suhn K. Rhie, Jorge L. Rodriguez‐Gil, Charles N. Rotimi, Jerome I. Rotter, Edward Ruiz-Narváez, Benjamin A. Rybicki, Babatunde Salako, Michèle M. Sale, Maureen Sanderson, Eric E. Schadt, Pamela J. Schreiner, Claudia Schurmann, Ann G. Schwartz, Daniel Shriner, Lisa B. Signorello, Andrew B. Singleton, David S. Siscovick, Jennifer A. Smith, Shad B. Smith, Elizabeth K. Speliotes, Margaret R. Spitz, Janet L. Stanford, Victoria L. Stevens, Alex Stram, Sara S. Strom, Lara Sucheston, Yan V. Sun, Salman M. Tajuddin, Herman A. Taylor, Kira C. Taylor, Bamidele O. Tayo, Michael J. Thun, Margaret A. Tucker, Dhananjay Vaidya, David J. Van Den Berg, Sailaja Vedantam, Mara Z. Vitolins, Erin B. Ware, Sylvia Wassertheil‐Smoller, David R. Weir, John K. Wiencke, Scott M. Williams, L. Keoki Williams, James G. Wilson, John S. Witte, Margaret Wrensch, Xifeng Wu, Jie Yao, Neil A. Zakai, Krista A. Zanetti, Babette S. Zemel, Wei Zhao, Jing Hua Zhao, Wei Zheng, Degui Zhi, Jie Zhou, Xiaofeng Zhu, Regina G. Ziegler, Joe Zmuda, Alan B. Zonderman, Bruce M. Psaty, Ingrid B. Borecki, L. Adrienne Cupples, Christopher A. Haiman, Ruth J. F. Loos, Maggie Ng, Kari E. North
Bibliographic record
VenueThe American Journal of Human Genetics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersU.S. Army Medical Research and Development CommandMedical Research and Materiel CommandNational Center for Research ResourcesNational Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Institute of Nursing ResearchNational Center for Advancing Translational SciencesWake Forest School of MedicineNational Human Genome Research InstituteNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Allergy and Infectious DiseasesSchool of Medicine, Vanderbilt UniversityNational Institute on AgingNational Cancer InstituteNational Institutes of HealthNational Heart, Lung, and Blood InstituteEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. Department of Defense
KeywordsGenome-wide association studyAncestry-informative markerGenotypingImputation (statistics)BiologyGenetics1000 Genomes ProjectSingle-nucleotide polymorphismGenetic genealogyAllele frequencyGenetic associationGenetic admixtureMinor allele frequencyEvolutionary biologyInternational HapMap ProjectAlleleDemographyGenotypePopulationGeneStatistics
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)0.005
metaresearch head score (Gemma)0.010
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 score0.007
Threshold uncertainty score0.027
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.000 |
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 head0.016
GPT teacher head0.275
Teacher spread0.260 · 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
Citations34
Published2021
Admission routes1
Has abstractno