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Record W3086046259 · doi:10.2337/db20-0070

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

2020· article· en· W3086046259 on OpenAlexaff
Hanieh Yaghootkar, Yiying Zhang, Cassandra N. Spracklen, Tugce Karaderi, Lam Opal Huang, Jonathan P. Bradfield, Claudia Schurmann, Rebecca S. Fine, Michael Preuß, Zoltán Kutalik, Laura B. L. Wittemans, Yingchang Lu, Sophia Metz, Sara M. Willems, Ruifang Li‐Gao, Niels Grarup, Shuai Wang, Sophie Molnos, América A. Sandoval-Zárate, Mike A. Nalls, Leslie A. Lange, Jeffrey Haesser, Xiuqing Guo, Leo‐Pekka Lyytikäinen, Mary F. Feitosa, Colleen M. Sitlani, Cristina Venturini, Anubha Mahajan, Tim Kacprowski, Carol A. Wang, Daniel I. Chasman, Najaf Amin, Linda Broer, Neil Robertson, Kristin L. Young, Matthew Allison, Paul L. Auer, Matthias Blüher, Judith B. Borja, Jette Bork‐Jensen, Germán D. Carrasquilla, Paraskevi Christofidou, Ayşe Demirkan, Claudia A. Doege, Melissa E. Garcia, Mariaelisa Graff, Kaiying Guo, Håkon Håkonarson, Jaeyoung Hong, Yii-Der Ida Chen, Rebecca D. Jackson, Hermina Jakupović, Pekka Jousilahti, Anne E. Justice, Mika Kähönen, Jorge R. Kizer, Jennifer Kriebel, Charles A. LeDuc, Jin Li, Lars Lind, Jian’an Luan, David A. Mackey, Massimo Mangino, Satu Männistö, Jayne F. Martin Carli, Carolina Medina‐Gómez, Dennis O. Mook‐Kanamori, Andrew P. Morris, Renée de Mutsert, Matthias Nauck, Ivana Nedeljković, Craig E. Pennell, Arund D. Pradhan, Bruce M. Psaty, Olli T. Raitakari, Robert A. Scott, Tea Skaaby, Konstantin Strauch, Kent D. Taylor, Alexander Teumer, André G. Uitterlinden, Ying Wu, Jie Yao, Mark Walker, Kari E. North, Péter Kovács, M. Arfan Ikram, Cornelia M. van Duijn, Paul M. Ridker, Stephen J. Lye, Georg Homuth, Erik Ingelsson, Tim D. Spector, Barbara McKnight, Michael A. Province, Terho Lehtimäki, Linda S. Adair, Jerome I. Rotter, Alex P. Reiner, James G. Wilson, Tamara B. Harris, Samuli Ripatti, Harald Grallert, James B. Meigs, Veikko Salomaa, Torben Hansen, Ko Willems van Dijk, Nicholas J. Wareham, Struan F.A. Grant, Claudia Langenberg, Timothy M. Frayling, Cecilia M. Lindgren, Karen L. Mohlke, Rudolph L. Leibel, Ruth J. F. Loos, Tuomas O. Kilpeläinen

Bibliographic record

VenueDiabetes · 2020
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteMünchner Zentrum für GesundheitswissenschaftenNIHR Oxford Biomedical Research CentreHelmholtz Zentrum MünchenNational Institutes of HealthDiabetesforeningenNovo Nordisk Foundation Center for Basic Metabolic ResearchFP7 Ideas: European Research CouncilTaysNovo Nordisk FondenDiabetesliittoSydäntutkimussäätiöEmil Aaltosen SäätiöNational Center for Advancing Translational SciencesMedical Research CouncilSigne ja Ane Gyllenbergin SäätiöAmerican Heart AssociationJuho Vainion SäätiöZonMwSuomen KulttuurirahastoYrjö Jahnssonin SäätiöDiabetes UKBundesministerium für GesundheitNational Institute on Minority Health and Health DisparitiesTampereen TuberkuloosisäätiöKelaJohns Hopkins UniversityEuropean CommissionLi Ka Shing FoundationFoundation for Cardiovascular ResearchAugustinus FondenPaavo Nurmen SäätiöNovo NordiskBundesministerium für Bildung und ForschungNational Institute on AgingNational Institute for Health and Care ResearchWellcome TrustHjerteforeningenDanmarks Frie Forskningsfond
KeywordsLeptinInternal medicineEndocrinologyAdipokineBiologyMedicineObesity

Abstract

fetched live from OpenAlex

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10−16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.283
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations56
Published2020
Admission routes1
Has abstractyes

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