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

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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 involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further 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 signalling and cell cycle regulation, in diabetes pathogenesis.

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Most cited references 61

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GCTA: a tool for genome-wide complex trait analysis.

Jian Yang, S. Lee, Michael E Goddard … (2011)

For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.

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Article: not found

SIFT: Predicting amino acid changes that affect protein function.

P C Ng (2003)

Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We have shown that SIFT can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms. SIFT is available at http://blocks.fhcrc.org/sift/SIFT.html.

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Is Open Access

A map of human genome variation from population-scale sequencing.

Amit Indap, Carlo Sidore (2011)

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

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Author and article information

Journal

Journal ID (nlm-journal-id): 9216904

Journal ID (pubmed-jr-id): 2419

Journal ID (nlm-ta): Nat Genet

Journal ID (iso-abbrev): Nat. Genet.

Title: Nature genetics

ISSN (Print): 1061-4036

ISSN (Electronic): 1546-1718

Publication date Nihms-submitted: 26 July 2012

Publication date (Electronic): 12 August 2012

Publication date (Print): September 2012

Publication date PMC-release: 12 February 2013

Volume: 44

Issue: 9

Pages: 981-990

Affiliations

[1 ]Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

[2 ]Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA.

[3 ]University of Pennsylvania - Perelman School of Medicine, Department of Pharmacology, Philadelphia, Pennsylvania, USA.

[4 ]Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

[5 ]Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA.

[6 ]Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.

[7 ]deCODE Genetics, Reykjavik, Iceland.

[8 ]Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.

[9 ]Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden.

[10 ]Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

[11 ]Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, Neuherberg, Germany.

[12 ]Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.

[13 ]Inserm UMR 1087, Nantes, France.

[14 ]CNRS UMR 6291, Nantes, France.

[15 ]Nantes University, Nantes, France.

[16 ]Estonian Genome Center, University of Tartu, Tartu, Estonia.

[17 ]Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.

[18 ]Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK.

[19 ]Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.

[20 ]MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK.

[21 ]Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.

[22 ]Institute of Genetic Epidemiology, Helmholtz Zentrum Muenchen, Neuherberg, Germany.

[23 ]Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-University, Munich, Germany.

[24 ]Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.

[25 ]CNRS-UMR-8199, Institute of Biology and Lille 2 University, Pasteur Institute, Lille, France.

[26 ]University Lille 1, Laboratory of Mathematics, CNRS-UMR 8524, MODAL team, INRIA Lille Nord-Europe, Lille, France.

[27 ]Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland.

[28 ]Health Science and Technology MD Program, Harvard University and Massachusetts Institute of Technology, Boston, Massachusetts, USA.

[29 ]Harvard Biological and Biomedical Sciences Program, Harvard University, Boston, Massachusetts, USA.

[30 ]Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.

[31 ]Partners Center for Personalized Genomic Medicine, Boston, Massachusetts, USA.

[32 ]National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA.

[33 ]Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.

[34 ]Biomedical Sciences Research Center Al. Fleming, Vari, Greece.

[35 ]Charles R. Bronfman Institute for Personalized Medicine, Mount Sinai School of Medicine, New York, New York, USA.

[36 ]Child Health and Development Institute, Mount Sinai School of Medicine, New York, New York, USA.

[37 ]Department of Preventive Medicine, Mount Sinai School of Medicine, New York, New York, USA.

[38 ]Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA.

[39 ]Division of Genetics and Endocrinology, Children’s Hospital, Boston, Massachusetts, USA.

[40 ]Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.

[41 ]Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.

[42 ]Division of Endocrinology and Metabolism, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA.

[43 ]Boston University Data Coordinating Center, Boston, Massachusetts, USA.

[44 ]Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

[45 ]Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

[46 ]Department of Nutrition and Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.

[47 ]Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.

[48 ]Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA.

[49 ]Saw Swee Hock School of Public Health, National University of Singapore, Singapore.

[50 ]National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.

[51 ]HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway.

[52 ]Centre for Genetic Epidemiology and Biostatistics, The University of Western Australia, Nedlands, Australia.

[53 ]Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, University of Exeter, Magdalen Road, Exeter, UK.

[54 ]Department of Internal Medicine, Levanger Hospital, Nord-Trøndelag Health Trust, Levanger, Norway.

[55 ]Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

[56 ]Department of Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

[57 ]Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.

[58 ]Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland.

[59 ]Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.

[60 ]Lund University Diabetes Centre, Department of Clinical Science Malmö, Scania University Hospital, Lund University, Malmö, Sweden.

[61 ]Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio Campus, Kuopio, Finland.

[62 ]Faculty of Medicine, University of Iceland, Reykjavík, Iceland.

[63 ]Landspitali University Hospital, Reykjavík, Iceland.

[64 ]Endocrinology-Diabetology Unit, Corbeil-Essonnes Hospital, Corbeil-Essonnes, France.

[65 ]Diabetes Research Centre, Biomedical Research Institute, University of Dundee, Ninewells Hospital, Dundee, UK.

[66 ]Pharmacogenomics Centre, Biomedical Research Institute, University of Dundee, Ninewells Hospital, Dundee, UK.

[67 ]Icelandic Heart Association, Kopavogur, Iceland.

[68 ]Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland.

[69 ]Vaasa Health Care Centre, Vaasa, Finland.

[70 ]Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

[71 ]Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

[72 ]Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Australia.

[73 ]PathWest Laboratory Medicine of Western Australia, QEII Medical Centre, Nedlands, Australia.

[74 ]School of Pathology and Laboratory Medicine, The University of Western Australia, Nedlands, Australia.

[75 ]School of Population Health, The University of Western Australia, Nedlands, Australia.

[76 ]Department of Pulmonary Physiology and Sleep Medicine, West Australian Sleep Disorders Research Institute, Queen Elizabeth II Medical Centre, Hospital Avenue, Nedlands, Australia.

[77 ]School of Medicine and Pharmacology, University of Western Australia, Nedlands, Australia.

[78 ]Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

[79 ]Institute of Human Genetics, University of Bonn, Bonn, Germany.

[80 ]Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany.

[81 ]Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Australia.

[82 ]University General Hospital Attikon, Athens, Greece.

[83 ]South Karelia Central Hospital, Lappeenranta, Finland.

[84 ]UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.

[85 ]Department of Clinical Chemistry and Central Laboratory, University of Ulm, Ulm, Germany.

[86 ]Institute of Epidemiology II, Helmholtz Zentrum Muenchen, Neuherberg, Germany.

[87 ]Centro Cardiologico Monzino, IRCCS, Milan, Italy.

[88 ]MRC Institute of Genetics and Molecular Medicine at the University of Edinburgh, Western General Hospital, Edinburgh, UK.

[89 ]Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.

[90 ]Netherland Genomics Initiative, Netherlands Consortium for Healthy Ageing and Centre for Medical Systems Biology, Rotterdam, The Netherlands.

[91 ]Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.

[92 ]Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, UK.

[93 ]Molecular Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

[94 ]Unit of General Practice, Helsinki University General Hospital, Helsinki, Finland.

[95 ]Folkhälsan Research Center, Helsinki, Finland.

[96 ]INSERM CESP U1018, Villejuif, France.

[97 ]University Paris Sud 11, UMRS 1018, Villejuif, France.

[98 ]Department of Medicine, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.

[99 ]Department of Social Services and Health Care, Jakobstad, Finland.

[100 ]The members of these consortia are listed in the Supplementary Note

[101 ]Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, USA.

[102 ]Geriatric Research Education and Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, Maryland, USA.

[103 ]Program in Personalised and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.

[104 ]Department of Medicine/Metabolic Diseases, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

[105 ]University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK.

[106 ]NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK.

[107 ]Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway.

[108 ]Kuopio Research Institute of Exercise Medicine, Kuopio, Finland.

[109 ]Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland.

[110 ]Department of Medical Sciences, Uppsala University, Akademiska Sjukhuset, Uppsala, Sweden.

[111 ]Department of Dietetics-Nutrition, Harokopio University, Athens, Greece.

[112 ]Faculty of Medicine, Institute of Health Sciences, University of Oulu, Oulu, Finland.

[113 ]Unit of General Practice, Oulu University Hospital, Oulu, Finland.

[114 ]Finnish Diabetes Association, Tampere, Finland.

[115 ]Pirkanmaa Hospital District, Tampere, Finland.

[116 ]South Ostrobothnia Central Hospital, Seinäjoki, Finland.

[117 ]Department of Medicine, Central Finland Central Hospital, Jyväskylä, Finland.

[118 ]Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA.

[119 ]Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.

[120 ]Red RECAVA Grupo RD06/0014/0015, Hospital Universitario La Paz, Madrid, Spain.

[121 ]Centre for Vascular Prevention, Danube-University Krems, Krems, Austria.

[122 ]Division of Endocrinology and Diabetes, Department of Internal Medicine, University Medical Centre Ulm, Ulm, Germany.

[123 ]Genomic Medicine, Imperial College London, Hammersmith Hospital, London, UK.

[124 ]Department of Pharmacological Sciences, University of Milan, Milan, Italy.

[125 ]Institute of Cardiovascular Science, University College London, London, UK.

[126 ]Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan.

[127 ]Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.

[128 ]Hannover Unified Biobank, Hannover Medical School, Hannover, Germany.

[129 ]Department of Statistics, University of Oxford, Oxford, UK.

[130 ]Diabetes Genetics, Institute of Biomedical and Clinical Science, Peninsula Medical School, University of Exeter, Exeter, UK.

[131 ]Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, USA.

[132 ]Human Genome Sequencing Center at Baylor College of Medicine, Houston, Texas, USA.

[133 ]Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA.

[134 ]Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA.

[135 ]General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA.

[136 ]Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.

[137 ]Department of Molecular Biology, Harvard Medical School, Boston, Massachusetts, USA.

[138 ]Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.

Author notes

Correspondence should be addressed to A.P.M. ( amorris@ 123456well.ox.ac.uk ), M.B. ( boehnke@ 123456umich.edu ) or M.I.M. ( mark.mccarthy@ 123456drl.ox.ac.uk ).

[139]

Deceased.

[140]

These authors contributed equally to this work.

[141]

These authors jointly supervised the work.

Article

Manuscript ID: UKMS49214

DOI: 10.1038/ng.2383

PMC ID: 3442244

PubMed ID: 22885922

SO-VID: 3e107668-c071-479b-8c81-29daf0c890ca

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Funding

Funded by: Wellcome Trust :

Award ID: 081682 || WT

Funded by: Wellcome Trust :

Award ID: 064890 || WT

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

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UCL: UN SDG 03 Good Health and Well-Being

Most cited references 61

GCTA: a tool for genome-wide complex trait analysis.

SIFT: Predicting amino acid changes that affect protein function.

A map of human genome variation from population-scale sequencing.

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Cited by 749

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