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Enregistrement W2104382557 · doi:10.1038/nature11401

FTO genotype is associated with phenotypic variability of body mass index

2012· review· en· W2104382557 sur OpenAlexaff
Jian Yang, Ruth J. F. Loos, Joseph E. Powell, Sarah E. Medland, Elizabeth K. Speliotes, Daniel I. Chasman, Lynda M. Rose, Guðmar Þorleifsson, Valgerður Steinthórsdóttir, Reedik Mägi, Lindsay L. Waite, Albert V. Smith, Laura M. Yerges-Armstrong, Keri L. Monda, David Hadley, Anubha Mahajan, Li Guo, Karen Kapur, Véronique Vitart, Jennifer E. Huffman, Sophie R. Wang, Cameron D. Palmer, Tõnu Esko, Krista Fischer, Wei Zhao, Ayşe Demirkan, Aaron Isaacs, Mary F. Feitosa, Jian’an Luan, Nancy L. Heard‐Costa, Charles C. White, Anne Jackson, Michael Preuß, Andreas Ziegler, Joel Eriksson, Zoltán Kutalik, Francesca Frau, Ilja M. Nolte, Jana V. van Vliet‐Ostaptchouk, Jouke‐Jan Hottenga, Kevin B. Jacobs, Niek Verweij, Anuj Goel, Carolina Medina‐Gómez, Karol Estrada, Jennifer L. Bragg‐Gresham, Serena Sanna, Carlo Sidore, Jonathan P. Tyrer, Alexander Teumer, Inga Prokopenko, Massimo Mangino, Cecilia M. Lindgren, Themistocles L. Assimes, Alan R. Shuldiner, Jennie Hui, John Beilby, Wendy L. McArdle, Per Hall, Talin Haritunians, Lina Zgaga, Ivana Kolčić, Ozren Polašek, Tatijana Zemunik, Ben A. Oostra, Juhani Junttila, Henrik Grönberg, Stefan Schreiber, Annette Peters, Andrew A. Hicks, Jonathan Stephens, Nicola Foad, Jaana Laitinen, Anneli Pouta, Marika Kaakinen, Gonneke Willemsen, Jacqueline M. Vink, Sarah H. Wild, Gerjan Navis, Folkert W. Asselbergs, Georg Homuth, Ulrich John, Carlos Iribarren, Tamara Harris, Lenore J. Launer, Vilmundur Guðnason, Jeffrey R. O’Connell, Eric Boerwinkle, Gemma Cadby, Lyle J. Palmer, Arthur W. Musk, Erik Ingelsson, Bruce M. Psaty, J. Beckmann, Gérard Waeber, Péter Vollenweider, Caroline Hayward, Alan F. Wright, Igor Rudan, Leif Groop, Andres Metspalu, Kay‐Tee Khaw, Cornelia M. van Duijn, Ingrid B. Borecki, Michael A. Province, Nicholas J. Wareham, Jean‐Claude Tardif, Heikki V. Huikuri, L. Adrienne Cupples, Larry D. Atwood, Caroline S. Fox, Michael Boehnke, Francis S. Collins, Karen L. Mohlke, Jeanette Erdmann, Heribert Schunkert, Christian Hengstenberg, Klaus Stark, Mattias Lorentzon, Claes Ohlsson, Daniele Cusi, Jan A. Staessen, Melanie M. van der Klauw, Peter P. Pramstaller, Sekar Kathiresan, Jennifer D. Jolley, Samuli Ripatti, Marjo‐Riitta Järvelin, Eco J. C. de Geus, Dorret I. Boomsma, Brenda W.J.H. Penninx, James F. Wilson, Harry Campbell, Stephen J. Chanock, Pim van der Harst, Anders Hamsten, Hugh Watkins, Albert Hofman, Jacqueline C.M. Witteman, M. Carola Zillikens, André G. Uitterlinden, Fernando Rivadeneira, Lambertus A. Kiemeney, Sita H. Vermeulen, Gonçalo R. Abecasis, David Schlessinger, Sabine Schipf, Michael Stümvoll, Anke Tönjes, Tim D. Spector, Kari E. North, Guillaume Lettre, Mark I. McCarthy, Sonja I. Berndt, Andrew C. Heath, Pamela A. F. Madden, Dale R. Nyholt, Grant W. Montgomery, Nicholas G. Martin, Barbara McKnight, David P. Strachan, William Hill, Harold Snieder, Paul M. Ridker, Unnur Þorsteinsdóttir, Kāri Stefánsson, Timothy M. Frayling, Joel N. Hirschhorn, Michael E. Goddard, Peter M. Visscher

Notice bibliographique

RevueNature · 2012
Typereview
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetic Associations and Epidemiology
Établissements canadiensUniversité de MontréalOntario Institute for Cancer Research
Organismes subventionnairesNational Center for Research ResourcesU.S. National Library of MedicineNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Institute on Drug AbuseNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Cancer InstituteNational Institute on Alcohol Abuse and AlcoholismCancer Research UKNational Health and Medical Research CouncilNational Human Genome Research InstituteWellcome TrustAustralian Research CouncilNational Institute of Arthritis and Musculoskeletal and Skin DiseasesMedical Research CouncilNational Institutes of Health
Mots-clésBiologySingle-nucleotide polymorphismGeneticsGenetic variationPhenotypeQuantitative trait locusGenome-wide association studyGenotypeLocus (genetics)Genetic associationGenetic variabilityTraitSNPGenetic architectureEvolutionary biologyGene

Résumé

récupéré en direct d'OpenAlex

A meta-analysis of genome-wide association studies of phenotypic variation for height and body mass index in human populations using 170,000 samples shows that one single nucleotide polymorphism at the FTO locus, which is associated with obesity, is also associated with phenotypic variation. Genome-wide association studies have successfully detected thousands of single nucleotide polymorphisms (SNPs) associated with complex traits in human populations. These studies tested the associations between SNPs and a phenotype — a disease or quantitative trait — expressed as a mean of the trait. This study is different, testing for associations between SNPs and variations of the phenotype, using more than 100,000 samples on height and body mass index in human populations. The authors find that one SNP at the FTO locus, which is known to be associated with obesity, is also associated with phenotypic variability. These results demonstrate that it is possible to find genetic variants that associate with variability and that between-person variability in obesity can partly be explained by genotype at the FTO locus. However, most genetic variants are not associated with phenotypic variance, or their effects on variability are very small. There is evidence across several species for genetic control of phenotypic variation of complex traits1,2,3,4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5,6,7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9,10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,296
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations455
Publié2012
Routes d'admission1
Résumé présentnon

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