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Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

115Citations signalées, ce qui n’est pas une note de qualité
55Institutions déclarées
11Pays d’affiliation déclarés

Rattachement africain : gb, us, dk, ca, se, au, fi, at, sa, es, ee. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus
Date Crossref
27/01/2015
Éditeur
Public Library of Science (PLoS)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Centre for Human GeneticsUniversity of OxfordUniversity of MichiganMichigan UnitedOxford Centre for Diabetes, Endocrinology and MetabolismBroad InstituteThe University of Texas Health Science Center at HoustonUniversity of CopenhagenNovo Nordisk FoundationUniversity of ChicagoMcGill University and Génome Québec Innovation CentreMcGill UniversityMassachusetts General HospitalWellcome Sanger InstituteLund UniversityGenomics (United Kingdom)King's College LondonUppsala UniversityScience for Life LaboratoryTexas Biomedical Research InstituteUniversity of California, San FranciscoBlood Systems Research InstituteJackson Memorial HospitalUniversity of Mississippi Medical CenterVejle SygehusUniversity of Southern DenmarkRegion of Southern DenmarkNinewells HospitalGlostrup HospitalDepartment of Social ServicesFolkhälsans ForskningscentrumHelsinki University HospitalSteno Diabetes CentersAalborg UniversityUniversity of Eastern FinlandKuopio University HospitalFinnish Institute for Health and WelfareNational Institutes of HealthNational Human Genome Research InstituteUniversity of North Carolina at Chapel HillCedars-Sinai Medical CenterUniversität für Weiterbildung KremsKing Abdulaziz UniversityHospital La Paz Institute for Health ResearchUniversidad Autónoma de MadridUniversity of Southern CaliforniaImperial College LondonBoston UniversityNational Heart, Lung, and Blood InstituteFramingham Heart StudyOxford BioMedica (United Kingdom)Harvard UniversityUniversity of LiverpoolUniversity of TartuMassachusetts Institute of Technology

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksGenetic Mapping and Diversity in Plants and Animals

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