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Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies
Cathy E. Elks, John R. B. Perry, Patrick Sulem, Daniel I. Chasman, Nora Franceschini, Chunyan He, Kathryn L. Lunetta, Jenny A. Visser, Enda M. Byrne, Diana L. Cousminer, Daníel F. Guðbjartsson, Tõnu Esko, Bjarke Feenstra, Jouke‐Jan Hottenga, Daniel L. Koller, Zoltán Kutalik, Massimo Mangino, Mara Marongiu, Patrick F. McArdle, Albert V. Smith, Lisette Stolk, Sophie H van Wingerden, Jing Hua Zhao, Eva Albrecht, Tanguy Corre, Erik Ingelsson, Caroline Hayward, Patrik K. E. Magnusson, Erin N. Smith, Shelia Ulivi, Nicole M. Warrington, Lina Zgaga, Helen Alavere, Najaf Amin, Thor Aspelund, Stefania Bandinelli, Inês Barroso, Gerald S. Berenson, Sven Bergmann, Hannah Blackburn, Eric Boerwinkle, Julie E. Buring, Fabio Busonero, Harry Campbell, Stephen J. Chanock, Wei Chen, Marilyn C. Cornelis, David Couper, Andrea D. Coviello, Pio D’Adamo, Ulf dé Fairé, Eco J. C. de Geus, Panos Deloukas, Angela Döring, George Davey Smith, Douglas F. Easton, Guðný Eiríksdóttir, Valur Emilsson, Johan G. Eriksson, Luigi Ferrucci, Aaron R. Folsom, Tatiana Foroud, Melissa Garcia, Paolo Gasparini, Frank Geller, Christian Gieger, Vilmundur Guðnason, Per Hall, Susan E. Hankinson, Liana Ferreli, Andrew C. Heath, Dena G. Hernandez, Albert Hofman, Frank B. Hu, Thomas Illig, Marjo‐Riitta Järvelin, Andrew D. Johnson, David Karasik, Kay‐Tee Khaw, Douglas P. Kiel, Tuomas O. Kilpeläinen, Ivana Kolčić, Peter Kraft, Lenore J. Launer, Joop S.E. Laven, Shengxu Li, Jianjun Liu, Daniel Levy, Nicholas G. Martin, Wendy L. McArdle, Mads Melbye, Vincent Mooser, Jeffrey C. Murray, Sarah S. Murray, Michael A. Nalls, Pau Navarro, Mari Nelis, Kate Northstone, Ben A. Oostra, Munro Peacock, Lyle J. Palmer, Aarno Palotie, Guillaume Paré, Alex Parker, Nancy L. Pedersen, Leena Peltonen, Craig E. Pennell, Paul D.P. Pharoah, Ozren Polašek, Andrew Plump, Anneli Pouta, Eleonora Porcu, Þórunn Rafnar, John P. Rice, Susan M. Ring, Fernando Rivadeneira, Igor Rudan, Cinzia Sala, Veikko Salomaa, Serena Sanna, David Schlessinger, Nicholas J. Schork, Angelo Scuteri, Ayellet V. Segrè, Alan R. Shuldiner, Nicole Soranzo, Ulla Sovio, Sathanur R. Srinivasan, David P. Strachan, Mar-Liis Tammesoo, Emmi Tikkanen, Daniela Toniolo, Kim Tsui, Laufey Tryggvadóttír, Manuela Uda, Rob M. van Dam, Joyce B. J. van Meurs, Péter Vollenweider, Gérard Waeber, Nicholas J. Wareham, Dawn Waterworth, Michael N. Weedon, H.‐Erich Wichmann, Gonneke Willemsen, James F. Wilson, Alan F. Wright, Lauren Young, Guangju Zhai, Wei Zhuang, Laura J. Bierut, Dorret I. Boomsma, Heather A. Boyd, Laura Crisponi, Ellen W. Demerath, Cornelia M. van Duijn, Michael J. Econs, Tamara B. Harris, David J. Hunter, Ruth J. F. Loos, Andres Metspalu, Grant W. Montgomery, Paul M. Ridker, Tim D. Spector, Elizabeth A. Streeten, Kāri Stefánsson, Unnur Þorsteinsdóttir, André G. Uitterlinden, Elisabeth Widén, Joanne M. Murabito, Ken K. Ong, Anna Murray
Bibliographic record
VenueNature Genetics · 2010
Typereview
Languageen
FieldMedicine
TopicHypothalamic control of reproductive hormones
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute of Dental and Craniofacial ResearchNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Human Genome Research InstituteDanmarks GrundforskningsfondNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institute on Alcohol Abuse and AlcoholismMarch of Dimes FoundationHelmholtz Zentrum MünchenNational Health and Medical Research CouncilMedical Research CouncilNational Institutes of HealthU.S. Public Health ServiceCentre for Medical Systems BiologyHjartaverndUniversity of BristolEgmont FondenAmgenChinese Society of Clinical OncologyFondation LeenaardsCompagnia di San PaoloAugustinus FondenNational Institute on Drug AbuseHjärt-LungfondenFondazione CariploVetenskapsrådetScottish GovernmentMinistère de l'Education Nationale, de l'Enseignement Superieur et de la RechercheMinistero della SaluteEuropean Regional Development FundBundesministerium für Bildung und ForschungCancer Research UKWellcome TrustMünchner Zentrum für GesundheitswissenschaftenErasmus Medisch CentrumStiftelsen för Strategisk ForskningSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Research FoundationSvenska LäkaresällskapetNederlandse Organisatie voor Wetenschappelijk OnderzoekNational Institute on Minority Health and Health DisparitiesEuropean CommissionNational Cancer InstituteEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentGlaxoSmithKlineNational Science FoundationAmerican Heart AssociationCanadian Institutes of Health ResearchJuvenile Diabetes Research Foundation International
KeywordsBiologyMenarcheGenome-wide association studyGeneticsGeneGenetic associationBody mass indexGenomeGenotypeSingle-nucleotide polymorphismEndocrinology
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)0.002
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 score0.009
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.002 | 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 head0.114
GPT teacher head0.393
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 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
Citations511
Published2010
Admission routes1
Has abstractno