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Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.
M. Carola Zillikens, Serkalem Demissie, Yi‐Hsiang Hsu, Laura M. Yerges-Armstrong, Wen‐Chi Chou, Lisette Stolk, Gregory Livshits, Linda Broer, Toby Johnson, Daniel L. Koller, Z. Kutalik, Jian’an Luan, Ida Malkin, Janina S. Ried, Albert V. Smith, Guðmar Þorleifsson, Liesbeth Vandenput, Jing Hua Zhao, Weihua Zhang, Ali A. Aghdassi, Kristina Åkesson, Najaf Amin, Leslie J. Baier, Inês Barroso, David A. Bennett, Lars Bertram, Rainer Biffar, Murielle Bochud, Michael Boehnke, Ingrid B. Borecki, Aron S. Buchman, Liisa Byberg, Harry Campbell, Natalia Campos Obanda, Jane A. Cauley, Peggy M. Cawthon, Henna Cederberg, Zhao Chen, Nam H. Cho, Hyung Jin Choi, Melina Claussnitzer, Francis S. Collins, Steven R. Cummings, Philip L. De Jager, Ilja Demuth, R.A.M. Dhonukshe-Rutten, Luda Diatchenko, Guðný Eiríksdóttir, Anke W. Enneman, Mike Erdos, Johan G. Eriksson, Joel Eriksson, Karol Estrada, Daniel S. Evans, Mary F. Feitosa, Mao Fu, Melissa Garcia, Christian Gieger, Thomas Girke, Nicole L. Glazer, Harald Grallert, Jagvir Grewal, Bok‐Ghee Han, Robert L. Hanson, Caroline Hayward, Albert Hofman, Eric P. Hoffman, Georg Homuth, Wen-Chi Hsueh, Monica J. Hubal, Alan Hubbard, Kim M. Huffman, Lise B. Husted, Thomas Illig, Erik Ingelsson, Till Ittermann, John‐Olov Jansson, Joanne M. Jordan, Antti Jula, Magnus K. Karlsson, Kay‐Tee Khaw, Tuomas O. Kilpainen, Norman Klopp, Jacqueline S. L. Kloth, Heikki A. Koistinen, William E. Kraus, Stephen B. Kritchevsky, Teemu Kuulasmaa, Johanna Kuusisto, Markku Laakso, Jari Lahti, Thomas Lang, Bente Langdahl, Lenore J. Launer, Jong‐Young Lee, Markus M. Lerch, Joshua R. Lewis, Lars Lind, Cecilia M. Lindgren, Ching‐Ti Liu, Tian Liu, Youfang Liu, Östen Ljunggren, Mattias Lorentzon, Robert Luben, William Maixner, Fiona E. McGuigan, Carolina Medina‐Gómez, Thomas Meitinger, Håkan Melhus, Dan Mellström, Simon Melov, Karl Michaëlsson, Braxton D. Mitchell, Andrew P. Morris, Leif Mosekilde, Anne B. Newman, Carrie M. Nielson, Jeffrey R. O’Connell, Ben A. Oostra, Eric Orwoll, Aarno Palotie, Stephan Parker, Munro Peacock, Markus Perola, Annette Peters, Ozren Polašek, Richard L. Prince, Katri Räikkönen, Stuart H. Ralston, Samuli Ripatti, John A. Robbins, Jerome I. Rotter, Igor Rudan, Veikko Salomaa, Suzanne Satterfield, Eric E. Schadt, Sabine Schipf, Laura J. Scott, Joban Sehmi, Jian Shen, Chan Soo Shin, Gunnar Sigurðsson, Shad B. Smith, Nicole Soranzo, Alena Stančáková, Elisabeth Steinhagen–Thiessen, Elizabeth A. Streeten, Unnur Styrkársdóttir, Karin M. A. Swart, Mark A. Tarnopolsky, Cynthia A. Thomson, Unnur Þorsteinsdóttir, Emmi Tikkanen, Gregory J. Tranah, Jaakko Tuomilehto, Natasja M. van Schoor, Arjun Verma, Péter Vollenweider, Jean Wactawski‐Wende, Mark Walker, Michael N. Weedon, Ryan Welch, H. Erich Wichman, Elisabeth Widén, Frances M. K. Williams, James F. Wilson, Nicole C. Wright, Weijia Xie, Lei Yu, Yanhua Zhou, John C. Chambers, Angela Döring, Cornelia M. van Duijn, Michael J. Econs, Vilmundur Guðnason, Jaspal S. Kooner, Bruce M. Psaty, Timothy D. Spector, Kāri Stefánsson, Fernando Rivadeneira, André G. Uitterlinden, Nicholas J. Wareham, Vicky Ossowski, Dawn Waterworth, Ruth J. F. Loos, David Karasik, Tamara B. Harris, Claes Ohlsson, Douglas P. Kiel
Bibliographic record
VenueMPG.PuRe (Max Planck Society) · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesU.S. National Library of MedicineNational Institute of Neurological Disorders and StrokeNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingMünchner Zentrum für GesundheitswissenschaftenWageningen University and ResearchKorea Centers for Disease Control and PreventionNational Health and Medical Research CouncilCanadian Institutes of Health ResearchNational Center for Research ResourcesCenters for Disease Control and PreventionNational Institutes of HealthArmy Research OfficeUniversität GreifswaldChinese Society of Clinical OncologyMedical Research CouncilUppsala UniversitetNational Institute of Arthritis and Musculoskeletal and Skin DiseasesGreta och Johan Kocks stiftelserGöteborgs LäkaresällskapSydäntutkimussäätiöAkademiska SjukhusetKidney Research UKDanmarks Frie ForskningsfondVetenskapsrådetU.S. Department of Health and Human ServicesGlaxoSmithKlineSigne ja Ane Gyllenbergin SäätiöCentre for Medical Systems BiologyGenome CanadaNovo NordiskFP7 People: Marie-Curie ActionsAmerican Diabetes AssociationVrije Universiteit AmsterdamKaren Elise Jensens FondSvenska LäkaresällskapetDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekBritish Heart FoundationBundesministerium für Bildung und ForschungJohns Hopkins UniversityUniversität zu LübeckKing's College LondonAcademy of FinlandMinisterie van Economische Zaken, Landbouw en InnovatieDiabetestutkimussäätiöZonMwSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNederlandse Zuivel OrganisatieErasmus Medisch CentrumMax-Planck-Institut für BildungsforschungStiftelsen för Strategisk ForskningHealthwayMalmö HögskolaEuropean Science FoundationNational Institute for Health and Care ResearchWellcome TrustNational Heart, Lung, and Blood InstituteItä-Suomen YliopistoFoundation for Cardiovascular ResearchFinska LäkaresällskapetYrjö Jahnssonin SäätiöAstraZenecaEuropean CommissionHelsingin YliopistoSchool of Medicine, Boston UniversityChronic Disease Research FoundationKuopion Yliopistollinen SairaalaWake Forest UniversityScottish GovernmentHjartaverndIllinois Department of Public HealthCedars-Sinai Medical CenterMinistry of Cultural AffairsEmil Aaltosen SäätiöRoyal SocietyNational Science FoundationJuho Vainion SäätiöNovo Nordisk FondenAmerican Heart Association
KeywordsLean body massGenome-wide association studyAssociation (psychology)BiologyGeneticsComputational biologyGeneBody weightPsychologyGenotypeSingle-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)0.007
metaresearch head score (Gemma)0.016
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 head0.048
GPT teacher head0.324
Teacher spread0.276 · 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
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".
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Citations0
Published2017
Admission routes1
Has abstractno