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Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes.

ABSTRACT: To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis.

SUBMITTER: Morris AP

PROVIDER: S-EPMC3442244 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes.

Morris Andrew P AP Voight Benjamin F BF Teslovich Tanya M TM Ferreira Teresa T Segrè Ayellet V AV Steinthorsdottir Valgerdur V Strawbridge Rona J RJ Khan Hassan H Grallert Harald H Mahajan Anubha A Prokopenko Inga I Kang Hyun Min HM Dina Christian C Esko Tonu T Fraser Ross M RM Kanoni Stavroula S Kumar Ashish A Lagou Vasiliki V Langenberg Claudia C Luan Jian'an J Lindgren Cecilia M CM Müller-Nurasyid Martina M Pechlivanis Sonali S Rayner N William NW Scott Laura J LJ Wiltshire Steven S Yengo Loic L Kinnunen Leena L Rossin Elizabeth J EJ Raychaudhuri Soumya S Johnson Andrew D AD Dimas Antigone S AS Loos Ruth J F RJ Vedantam Sailaja S Chen Han H Florez Jose C JC Fox Caroline C Liu Ching-Ti CT Rybin Denis D Couper David J DJ Kao Wen Hong L WH Li Man M Cornelis Marilyn C MC Kraft Peter P Sun Qi Q van Dam Rob M RM Stringham Heather M HM Chines Peter S PS Fischer Krista K Fontanillas Pierre P Holmen Oddgeir L OL Hunt Sarah E SE Jackson Anne U AU Kong Augustine A Lawrence Robert R Meyer Julia J Perry John R B JR Platou Carl G P CG Potter Simon S Rehnberg Emil E Robertson Neil N Sivapalaratnam Suthesh S Stančáková Alena A Stirrups Kathleen K Thorleifsson Gudmar G Tikkanen Emmi E Wood Andrew R AR Almgren Peter P Atalay Mustafa M Benediktsson Rafn R Bonnycastle Lori L LL Burtt Noël N Carey Jason J Charpentier Guillaume G Crenshaw Andrew T AT Doney Alex S F AS Dorkhan Mozhgan M Edkins Sarah S Emilsson Valur V Eury Elodie E Forsen Tom T Gertow Karl K Gigante Bruna B Grant George B GB Groves Christopher J CJ Guiducci Candace C Herder Christian C Hreidarsson Astradur B AB Hui Jennie J James Alan A Jonsson Anna A Rathmann Wolfgang W Klopp Norman N Kravic Jasmina J Krjutškov Kaarel K Langford Cordelia C Leander Karin K Lindholm Eero E Lobbens Stéphane S Männistö Satu S Mirza Ghazala G Mühleisen Thomas W TW Musk Bill B Parkin Melissa M Rallidis Loukianos L Saramies Jouko J Sennblad Bengt B Shah Sonia S Sigurðsson Gunnar G Silveira Angela A Steinbach Gerald G Thorand Barbara B Trakalo Joseph J Veglia Fabrizio F Wennauer Roman R Winckler Wendy W Zabaneh Delilah D Campbell Harry H van Duijn Cornelia C Uitterlinden Andre G AG Hofman Albert A Sijbrands Eric E Abecasis Goncalo R GR Owen Katharine R KR Zeggini Eleftheria E Trip Mieke D MD Forouhi Nita G NG Syvänen Ann-Christine AC Eriksson Johan G JG Peltonen Leena L Nöthen Markus M MM Balkau Beverley B Palmer Colin N A CN Lyssenko Valeriya V Tuomi Tiinamaija T Isomaa Bo B Hunter David J DJ Qi Lu L Shuldiner Alan R AR Roden Michael M Barroso Ines I Wilsgaard Tom T Beilby John J Hovingh Kees K Price Jackie F JF Wilson James F JF Rauramaa Rainer R Lakka Timo A TA Lind Lars L Dedoussis George G Njølstad Inger I Pedersen Nancy L NL Khaw Kay-Tee KT Wareham Nicholas J NJ Keinanen-Kiukaanniemi Sirkka M SM Saaristo Timo E TE Korpi-Hyövälti Eeva E Saltevo Juha J Laakso Markku M Kuusisto Johanna J Metspalu Andres A Collins Francis S FS Mohlke Karen L KL Bergman Richard N RN Tuomilehto Jaakko J Boehm Bernhard O BO Gieger Christian C Hveem Kristian K Cauchi Stephane S Froguel Philippe P Baldassarre Damiano D Tremoli Elena E Humphries Steve E SE Saleheen Danish D Danesh John J Ingelsson Erik E Ripatti Samuli S Salomaa Veikko V Erbel Raimund R Jöckel Karl-Heinz KH Moebus Susanne S Peters Annette A Illig Thomas T de Faire Ulf U Hamsten Anders A Morris Andrew D AD Donnelly Peter J PJ Frayling Timothy M TM Hattersley Andrew T AT Boerwinkle Eric E Melander Olle O Kathiresan Sekar S Nilsson Peter M PM Deloukas Panos P Thorsteinsdottir Unnur U Groop Leif C LC Stefansson Kari K Hu Frank F Pankow James S JS Dupuis Josée J Meigs James B JB Altshuler David D Boehnke Michael M McCarthy Mark I MI

Nature genetics 20120812 9

To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation ...[more]

PMID: 22885922

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Project description:BackgroundLong QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility.MethodsWe conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score.ResultsGenome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance (P<5×10-8) near NOS1AP, KCNQ1, and KLF12, and 1 missense variant in KCNE1(p.Asp85Asn) at the suggestive threshold (P<10-6). Heritability analyses showed that ≈15% of variance in overall LQTS susceptibility was attributable to common genetic variation (h2SNP 0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (rg=0.40; P=3.2×10-3). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls (P<10-13), and it is notable that, among patients with LQTS, this polygenic risk score was greater in patients who were genotype negative compared with those who were genotype positive (P<0.005).ConclusionsThis work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.

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Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes.

Publications

Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes.

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