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Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis
Eleanor Wheeler, Aaron Leong, Ching‐Ti Liu, Marie‐France Hivert, Rona J. Strawbridge, Clara Podmore, Man Li, Jie Yao, Xueling Sim, Jaeyoung Hong, Audrey Y. Chu, Weihua Zhang, Xu Wang, Peng Chen, Nisa M. Maruthur, Bianca Porneala, Stephen J. Sharp, Yucheng Jia, Edmond K. Kabagambe, Li-Ching Chang, Wei‐Min Chen, Cathy E. Elks, Daniel S. Evans, Qiao Fan, Franco Giulianini, Min Jin Go, Jouke‐Jan Hottenga, Yao Hu, Anne Jackson, Stavroula Kanoni, Young Jin Kim, Marcus E. Kleber, Claes Ladenvall, Cécile Lecœur, Sing-Hui Lim, Yingchang Lu, Anubha Mahajan, Carola Marzi, Mike A. Nalls, Pau Navarro, Ilja M. Nolte, Lynda M. Rose, Denis Rybin, Serena Sanna, Yuan Shi, Daniel O. Stram, Fumihiko Takeuchi, Peter J. van der Most, Jana V. van Vliet‐Ostaptchouk, Andrew Wong, Loïc Yengo, Wanting Zhao, Anuj Goel, Maria Teresa Martínez Larrad, Dörte Radke, Perttu Salo, Toshiko Tanaka, Erik P.A. van Iperen, Gonçalo R. Abecasis, Saima Afaq, Behrooz Z. Alizadeh, Alain G. Bertoni, Amélie Bonnefond, Yvonne Böttcher, Erwin P. Böttinger, Harry Campbell, Olga D. Carlson, Chien-Hsiun Chen, Yoon Shin Cho, W. Timothy Garvey, Christian Gieger, Mark O. Goodarzi, Harald Grallert, Anders Hamsten, Catharina A. Hartman, Christian Herder, Chao A. Hsiung, Jie Huang, Michiya Igase, Masato Isono, Tomohiro Katsuya, Chiea Chuen Khor, Wieland Kieß, Katsuhiko Kohara, Péter Kovács, Juyoung Lee, Wen‐Jane Lee, Benjamin Lehne, Huaixing Li, Jianjun Liu, Stéphane Lobbens, Jian’an Luan, Valeriya Lyssenko, Thomas Meitinger, Tetsuro Miki, Iva Miljkovic, Sanghoon Moon, Antonella Mulas, Gabriele Müller, Martina Müller‐Nurasyid, Ramaiah Nagaraja, Matthias Nauck, James S. Pankow, Ozren Polašek, Inga Prokopenko, Paula S. Ramos, Laura J. Rasmussen‐Torvik, Wolfgang Rathmann, Stephen S. Rich, Neil R. Robertson, Michael Roden, Ronan Roussel, Igor Rudan, Robert A. Scott, William R. Scott, Bengt Sennblad, David S. Siscovick, Konstantin Strauch, Liang Sun, Morris A. Swertz, Salman M. Tajuddin, Kent D. Taylor, Yik‐Ying Teo, Yih Chung Tham, Anke Tönjes, Nicholas J. Wareham, Gonneke Willemsen, Tom Wilsgaard, Aroon D. Hingorani, Josephine Egan, Luigi Ferrucci, G. Kees Hovingh, Antti Jula, Mika Kivimäki, Meena Kumari, Inger Njølstad, Manuel Serrano‐Ríos, Michael Stümvoll, Hugh Watkins, Tin Aung, Matthias Blüher, Michael Boehnke, Dorret I. Boomsma, Stefan R. Bornstein, John C. Chambers, Daniel I. Chasman, Yii‐Der Ida Chen, Yduan-Tsong Chen, Ching‐Yu Cheng, Francesco Cucca, Eco J. C. de Geus, Panos Deloukas, Michele K. Evans, Myriam Fornage, Yechiel Friedlander, Philippe Froguel, Leif Groop, Myron D. Gross, Tamara B. Harris, Caroline Hayward, Chew‐Kiat Heng, Erik Ingelsson, Norihiro Kato, Bong-Jo Kim, Woon-Puay Koh, Jaspal S. Kooner, Antje Körner, Diana Kuh, Johanna Kuusisto, Markku Laakso, Lin Xu, Ruth J. F. Loos, Patrik K. E. Magnusson, Winfried März, Mark I. McCarthy, Albertine J. Oldehinkel, Ken K. Ong, Nancy L. Pedersen, Mark A. Pereira, Annette Peters, Paul M. Ridker, Charumathi Sabanayagam, Michèle M. Sale, Danish Saleheen, Juha Saltevo, Peter E. H. Schwarz, Wayne H.-H. Sheu, Harold Snieder, Timothy D. Spector, Yasuharu Tabara, Jaakko Tuomilehto, Rob M. van Dam, James G. Wilson, James F. Wilson, Bruce H. R. Wolffenbuttel, Tien Yin Wong, Jer‐Yuarn Wu, Jian‐Min Yuan, Alan B. Zonderman, Nicole Soranzo, Xiuqing Guo, David J. Roberts, José C. Florez, Robert Sladek, Josée Dupuis, Andrew P. Morris, E Shyong Tai, Elizabeth Selvin, Jerome I. Rotter, Claudia Langenberg, Inês Barroso, James B. Meigs
Bibliographic record
VenuePLoS Medicine · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill UniversityCentre for Global Health Research
FundersMedical Research CouncilUniversität LeipzigCentre National de la Recherche ScientifiqueInstitut National de la Santé et de la Recherche MédicaleNational Institutes of HealthKidney Research UKNational Cancer InstituteBritish Heart FoundationIncyteNovo NordiskNational Institute for Health and Care ResearchRegeneron PharmaceuticalsSanofiGlaxoSmithKlineMichael J. Fox Foundation for Parkinson's ResearchAmgenNational Heart, Lung, and Blood InstitutePfizerAstraZenecaEli Lilly and Company
KeywordsGenome-wide association studyGlycemicType 2 diabetesBiologyGeneticsGenetic associationGlycated hemoglobinDiabetes mellitusMedicineInternal medicineGenotypeSingle-nucleotide polymorphismEndocrinologyGene
Abstract
OpenAlex records an abstract for this work, but it could not be fetched just now.
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)0.011
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.057
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.024 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 head0.233
GPT teacher head0.428
Teacher spread0.196 · 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.
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
Citations441
Published2017
Admission routes1
Has abstractyes