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Record W4240622323 · doi:10.2337/figshare.12933737.v1

Genetic studies of leptin concentrations implicate leptin in the regulation of early adiposity

2020· preprint· en· W4240622323 on OpenAlexfundno aff
Ada Admin, Hanieh Yaghootkar, Yiying Zhang, Cassandra N. Spracklen, Tugce Karaderi, Lam Opal Huang, Jonathan P. Bradfield, Claudia Schurmann, Rebecca S. Fine, Michael H Preuss, Zoltán Kutalik, Laura BL 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, 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, Jae‐Young Hong, Yii‐Der Ida Chen, Rebecca D. Jackson, Hermina Jakupović, Pekka Jousilahti, Anne E. Justice, Mika Kähönen, Jorge R. Kizer, Jennifer Kriebe, 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 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

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsnot available
FundersFP7 Ideas: European Research CouncilNational Institute of Neurological Disorders and StrokeNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingNIHR Oxford Biomedical Research CentreNational Institutes of HealthDiabetesforeningenCotswold FoundationAcademy of FinlandTerveyden ja hyvinvoinnin laitosAmerican Heart AssociationNovo Nordisk FondenNational Institute of General Medical SciencesDiabetesliittoNational Human Genome Research InstituteDanmarks Frie ForskningsfondAugustinus FondenEmil Aaltosen SäätiöMedical Research CouncilGlaxoSmithKlineSigne ja Ane Gyllenbergin SäätiöPaavo Nurmen SäätiöCentre for Medical Systems BiologyLi Ka Shing FoundationNovo NordiskMurdoch UniversityNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversity of Notre DameNovo Nordisk Foundation Center for Basic Metabolic ResearchTaysNational Health and Medical Research CouncilSuomen KulttuurirahastoEdith Cowan UniversitySydäntutkimussäätiöMünchner Zentrum für GesundheitswissenschaftenCurtin University of TechnologyNational Institute on Minority Health and Health DisparitiesEuropean CommissionDiabetes UKCanadian Institutes of Health ResearchNational Heart, Lung, and Blood InstituteBundesministerium für GesundheitYrjö Jahnssonin SäätiöNational Institute for Health and Care ResearchFoundation for Cardiovascular ResearchNational Center for Advancing Translational SciencesHjerteforeningenTampereen TuberkuloosisäätiöKelaZonMwRaine Medical Research FoundationJohns Hopkins UniversityRussian Foundation for Basic ResearchBundesministerium für Bildung und ForschungWomen and Infants Research FoundationWake Forest UniversityChildren's Hospital of PhiladelphiaWellcome TrustJuho Vainion Säätiö
KeywordsLeptinMissense mutationEndocrinologyInternal medicineAlleleObesityBiologyExomeExome sequencingGeneticsMedicineMutationGene

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=2x10-16, 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 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 machine prediction

Teacher imitation

Not 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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.102
GPT teacher head0.329
Teacher spread0.226 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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