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Meta-Analysis
, 44 (9), 991-1005

Large-scale Association Analyses Identify New Loci Influencing Glycemic Traits and Provide Insight Into the Underlying Biological Pathways

Robert A Scott  1 Vasiliki LagouRyan P WelchEleanor WheelerMay E MontasserJian'an LuanReedik MägiRona J StrawbridgeEmil RehnbergStefan GustafssonStavroula KanoniLaura J Rasmussen-TorvikLoïc YengoCecile LecoeurDmitry ShunginSerena SannaCarlo SidorePaul C D JohnsonJ Wouter JukemaToby JohnsonAnubha MahajanNiek VerweijGudmar ThorleifssonJouke-Jan HottengaSonia ShahAlbert V SmithBengt SennbladChristian GiegerPerttu SaloMarkus PerolaNicholas J TimpsonDavid M EvansBeate St PourcainYing WuJeanette S AndrewsJennie HuiLawrence F BielakWei ZhaoMomoko HorikoshiPau NavarroAaron IsaacsJeffrey R O'ConnellKathleen StirrupsVeronique VitartCaroline HaywardTõnu EskoEvelin MihailovRoss M FraserTove FallBenjamin F VoightSoumya RaychaudhuriHan ChenCecilia M LindgrenAndrew P MorrisNigel W RaynerNeil RobertsonDenis RybinChing-Ti LiuJacques S BeckmannSara M WillemsPeter S ChinesAnne U JacksonHyun Min KangHeather M StringhamKijoung SongToshiko TanakaJohn F PedenAnuj GoelAndrew A HicksPing AnMartina Müller-NurasyidAnders Franco-CerecedaLasse FolkersenLetizia MarulloHanneke JansenAlbertine J OldehinkelMarcel BruinenbergJames S PankowKari E NorthNita G ForouhiRuth J F LoosSarah EdkinsTibor V VargaGöran HallmansHeikki OksaMulas AntonellaRamaiah NagarajaStella TrompetIan FordStephan J L BakkerAugustine KongMeena KumariBruna GiganteChristian HerderPatricia B MunroeMark CaulfieldJula AnttiMassimo ManginoKerrin SmallIva MiljkovicYongmei LiuMustafa AtalayWieland KiessAlan L JamesFernando RivadeneiraAndre G UitterlindenColin N A PalmerAlex S F DoneyGonneke WillemsenJohannes H SmitSusan CampbellOzren PolasekLori L BonnycastleSerge HercbergMaria DimitriouJennifer L BoltonGerard R FowkesPeter KovacsJaana LindströmTatijana ZemunikStefania BandinelliSarah H WildHanneke V BasartWolfgang RathmannHarald GrallertDIAbetes Genetics Replication and Meta-analysis (DIAGRAM) ConsortiumWinfried MaerzMarcus E KleberBernhard O BoehmAnnette PetersPeter P PramstallerMichael A ProvinceIngrid B BoreckiNicholas D HastieIgor RudanHarry CampbellHugh WatkinsMartin FarrallMichael StumvollLuigi FerrucciDawn M WaterworthRichard N BergmanFrancis S CollinsJaakko TuomilehtoRichard M WatanabeEco J C de GeusBrenda W PenninxAlbert HofmanBen A OostraBruce M PsatyPeter VollenweiderJames F WilsonAlan F WrightG Kees HovinghAndres MetspaluMatti UusitupaPatrik K E MagnussonKirsten O KyvikJaakko KaprioJackie F PriceGeorge V DedoussisPanos DeloukasPierre MenetonLars LindMichael BoehnkeAlan R ShuldinerCornelia M van DuijnAndrew D MorrisAnke ToenjesPatricia A PeyserJohn P BeilbyAntje KörnerJohanna KuusistoMarkku LaaksoStefan R BornsteinPeter E H SchwarzTimo A LakkaRainer RauramaaLinda S AdairGeorge Davey SmithTim D SpectorThomas IlligUlf de FaireAnders HamstenVilmundur GudnasonMika KivimakiAroon HingoraniSirkka M Keinanen-KiukaanniemiTimo E SaaristoDorret I BoomsmaKari StefanssonPim van der HarstJosée DupuisNancy L PedersenNaveed SattarTamara B HarrisFrancesco CuccaSamuli RipattiVeikko SalomaaKaren L MohlkeBeverley BalkauPhilippe FroguelAnneli PoutaMarjo-Riitta JarvelinNicholas J WarehamNabila Bouatia-NajiMark I McCarthyPaul W FranksJames B MeigsTanya M TeslovichJose C FlorezClaudia LangenbergErik IngelssonInga ProkopenkoInês Barroso
Affiliations
Meta-Analysis

Large-scale Association Analyses Identify New Loci Influencing Glycemic Traits and Provide Insight Into the Underlying Biological Pathways

Robert A Scott et al. Nat Genet.

Abstract

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

Figures

Figure 1
Figure 1
Associations between glycemic loci and T2D, HDL-cholesterol and triglycerides, BMI and WHR. Loci associated with the above traits (P < 0.05) are highlighted. Those with positively correlated effect directions are colored yellow, and those with negative correlations are colored blue. Those which did not reach a q-value < 0.05 in FDR analyses are also marked.
Figure 2
Figure 2
Per-allele beta-coefficients for glucose and insulin concentrations vs. odds ratios for T2D. (a) Fasting glucose vs. T2D. (b) Fasting insulin vs. T2D. (c) Fasting insulin adjusted for BMI vs. T2D. (d) 2-h glucose vs. T2D.
Figure 2
Figure 2
Per-allele beta-coefficients for glucose and insulin concentrations vs. odds ratios for T2D. (a) Fasting glucose vs. T2D. (b) Fasting insulin vs. T2D. (c) Fasting insulin adjusted for BMI vs. T2D. (d) 2-h glucose vs. T2D.
Figure 2
Figure 2
Per-allele beta-coefficients for glucose and insulin concentrations vs. odds ratios for T2D. (a) Fasting glucose vs. T2D. (b) Fasting insulin vs. T2D. (c) Fasting insulin adjusted for BMI vs. T2D. (d) 2-h glucose vs. T2D.
Figure 2
Figure 2
Per-allele beta-coefficients for glucose and insulin concentrations vs. odds ratios for T2D. (a) Fasting glucose vs. T2D. (b) Fasting insulin vs. T2D. (c) Fasting insulin adjusted for BMI vs. T2D. (d) 2-h glucose vs. T2D.

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