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      Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis

      research-article
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          Abstract

          Background

          Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

          Methods & findings

          Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts ( N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04–1.06, per HbA1c-raising allele, p = 3 × 10 −29); whereas GS-E was not (OR = 1.00, 95% CI 0.99–1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66–0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38–0.97) in homozygous women. The G6PD variant may cause approximately 2% ( N = 0.65 million, 95% CI 0.55–0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

          Conclusions

          As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

          Abstract

          Ines Barroso and colleagues identify a genetic variant that leads to reduced levels of HbA1c in African American adults; 2% of this population are at risk of missed diagnosis for diabetes.

          Author summary

          Why was this study done?
          • Blood glucose binds in an irreversible manner to circulating hemoglobin in red blood cells (RBCs), generating “glycated hemoglobin,” called HbA1c. HbA1c is used to diagnose and monitor diabetes.

          • Previous large-scale human genetic studies have demonstrated that HbA1c is influenced by genetic variants. Some variants are thought to influence the function, structure, and lifespan of the red blood itself (“erythrocytic variants”), while others are thought to influence blood glucose control (“glycemic variants”). This study aimed to identify additional variants influencing HbA1c levels, and investigate the extent to which variants affecting this measurement independently of blood glucose concentration may lead to misdiagnosis, mistreatment, and human health disparities.

          What did the researchers do and find?
          • We studied genetic variants and their association with HbA1c levels in almost 160,000 people from European, African, East Asian, and South Asian ancestry from 82 separate studies worldwide. We found 60 genetic variants influencing HbA1c, of which 42 variants were new. Of the 60 variants, we found 19 glycemic variants and 22 erythrocytic variants.

          • In approximately 33,000 people from 5 ancestry groups followed carefully over time, we found that the more glycemic variants a person had, the higher their risk to get diabetes (OR = 1.05 per HbA1c-raising allele, p = 3 × 10 −29). However, more erythrocytic variants did not lead to a higher risk of diabetes, meaning erythrocytic variants that lower HbA1c levels independently from glucose concentration could lead to missed diagnosis of diabetes.

          • Next, we found that in everyone but those of African ancestry, those with more versus those with less of the 60 HbA1c genetic variants had a fairly small difference in HbA1c (about 0.2 units), while those of African ancestry had a larger difference (about 0.8 units, a fairly large number for this medical test).

          • This difference in African ancestry was explained by one erythrocytic variant on the X chromosome. This variant mutates the protein made by the gene “glucose-6-phosphate dehydrogenase” ( G6PD), which can shorten RBC lifespan, and thus lower HbA1c levels, no matter the blood glucose level.

          • About 11% of people of African American ancestry carry at least one copy of this G6PD variant, while almost no one of any other ancestry does. We estimated that if we tested all Americans for diabetes using HbA1c, about 650,000 African Americans would be missed because of these genetically lowered HbA1c levels.

          What do these findings mean?
          • We may want to investigate the benefits of screening for the G6PD genotype in specific communities or perform additional diagnostic tests to avoid health disparities between communities.

          • It will also be important to follow up with additional studies to check whether new standardized thresholds for diagnoses should be recommended for those that have this G6PD variant.

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          Most cited references43

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

          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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            METAL: fast and efficient meta-analysis of genomewide association scans

            Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: goncalo@umich.edu
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              Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits.

              We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.
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                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                12 September 2017
                September 2017
                : 14
                : 9
                : e1002383
                Affiliations
                [1 ] Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, United Kingdom
                [2 ] Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, United States of America
                [3 ] Harvard Medical School, Boston, MA, United States of America
                [4 ] Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
                [5 ] Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, United States of America
                [6 ] Massachusetts General Hospital, Boston, MA, United States of America
                [7 ] Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
                [8 ] Centre for Molecular Medicine, Karolinska Universitetsjukhuset, Solna, Sweden
                [9 ] MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
                [10 ] Department of Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
                [11 ] Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
                [12 ] Division of Nephrology, University of Utah, Salt Lake City, UT, United States of America
                [13 ] Department of Human Genetics, University of Utah, Salt Lake City, UT, United States of America
                [14 ] Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, United States of America
                [15 ] Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
                [16 ] National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States of America
                [17 ] Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America
                [18 ] Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
                [19 ] Department of Cardiology, Ealing Hospital NHS Trust, Southall, Middlesex, United Kingdom
                [20 ] Life Sciences Institute, National University of Singapore, Singapore, Singapore
                [21 ] Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, United States of America
                [22 ] Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, Jilin, China
                [23 ] College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
                [24 ] Division of General Internal Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
                [25 ] Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins University, Baltimore, MD, United States of America
                [26 ] Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States of America
                [27 ] Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
                [28 ] University of Virginia Center for Public Health Genomics, Charlottesville, VA, United States of America
                [29 ] Personalised Healthcare & Biomarkers, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Cambridge, United Kingdom
                [30 ] California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
                [31 ] Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
                [32 ] Division of Structural and Functional Genomics, Center for Genome Science, Korean National Institute of Health, Osong, Chungchungbuk-do, South Korea
                [33 ] Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
                [34 ] The Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, People’s Republic of China
                [35 ] Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States of America
                [36 ] William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
                [37 ] Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
                [38 ] Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
                [39 ] Lund University Diabetes Centre, Lund University, Lund, Sweden
                [40 ] University of Lille, CNRS, Institut Pasteur of Lille, UMR 8199—EGID, Lille, France
                [41 ] Singapore Eye Research Institute, The Academia Level 6, Discovery Tower, Singapore, Singapore
                [42 ] The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [43 ] The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [44 ] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
                [45 ] Institute of Epidemiology II, Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
                [46 ] German Center for Diabetes Research (DZD e.V.), Partner Munich, Munich, Germany
                [47 ] Data Tecnica International, Glen Echo, MD, United States of America
                [48 ] Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, United States of America
                [49 ] MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland
                [50 ] Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
                [51 ] Data Coordinating Center, Boston University School of Public Health, Boston, MA, United States of America
                [52 ] Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
                [53 ] Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States of America
                [54 ] Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
                [55 ] Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
                [56 ] MRC Unit for Lifelong Health & Ageing, London, United Kingdom
                [57 ] Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
                [58 ] Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
                [59 ] Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
                [60 ] National Institute for Health and Welfare (THL), Helsinki, Finland
                [61 ] University of Helsinki, Institute for Molecular Medicine, Finland (FIMM) and Diabetes and Obesity Research Program, Helsinki, Finland
                [62 ] Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, United States of America
                [63 ] Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
                [64 ] Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Netherlands
                [65 ] Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
                [66 ] Integrated Research and Treatment (IFB) Center Adiposity Diseases, University of Leipzig, Leipzig, Germany
                [67 ] Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
                [68 ] Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD, United States of America
                [69 ] School of Chinese Medicine, China Medical University, Taichung City, Taiwan
                [70 ] Department of Biomedical Science, Hallym University, Chuncheon, Gangwon-do, South Korea
                [71 ] Department of Nutrition Sciences, University of Alabama at Birmingham and the Birmingham Veterans Affairs Medical Center, Birmingham, AL, United States of America
                [72 ] Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
                [73 ] Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
                [74 ] Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
                [75 ] German Center for Diabetes Research (DZD), München-Neuherberg, Germany
                [76 ] Division of Endocrinology, Diabetes, Metabolism, Department of Internal Medicine, Wexner Medical Center, The Ohio State University, Columbus, OH, United States of America
                [77 ] Boston VA Research Institute, Inc., Boston, MA, United States of America
                [78 ] Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Ehime, Japan
                [79 ] Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
                [80 ] Department of Geriatric Medicine and Nephrology, Osaka University Graduate School of Medicine, Suita, Japan
                [81 ] Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
                [82 ] Center of Pediatric Research, University Hospital for Children & Adolescents, Dept. of Women's & Child Health, University of Leipzig, Leipzig, Germany
                [83 ] LIFE Child, LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
                [84 ] Faculty of Collaborative Regional Innovation, Ehime University, Ehime, Japan
                [85 ] Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
                [86 ] Institute of Human Genetics, Technische Universität München, Munich, Germany
                [87 ] Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
                [88 ] Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
                [89 ] Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States of America
                [90 ] Center for Evidence-based Healthcare, University Hospital and Medical Faculty Carl Gustav Carus, Dresden, Germany
                [91 ] Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
                [92 ] Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-Universität, Munich, Germany
                [93 ] DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
                [94 ] Laboratory of Genetics, National Institute on Aging, Baltimore, MD, United States of America
                [95 ] Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
                [96 ] Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, United States of America
                [97 ] University of Split, Split, Croatia
                [98 ] Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
                [99 ] Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
                [100 ] Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom
                [101 ] Department of Medicine, Medical University of South Carolina, Charleston, SC, United States of America
                [102 ] Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
                [103 ] Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, United States of America
                [104 ] Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
                [105 ] Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Düsseldorf, Germany
                [106 ] INSERM, UMR_S 1138, Centre de Recherche des Cordelier, Paris, France
                [107 ] Université Paris Diderot, Sorbonne Paris Cité, UFR de Médecine, Paris, France
                [108 ] Assistance Publique Hôpitaux de Paris, Bichat Hospital, DHU FIRE, Department of Diabetology, Endocrinology and Nutrition, Paris, France
                [109 ] University of Edinburgh, Edinburgh, United Kingdom
                [110 ] Science for life laboratory, Karolinska Institutet, Solna, Sweden
                [111 ] The New York Academy of Medicine, New York, NY, United States of America
                [112 ] Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
                [113 ] Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
                [114 ] Health Disparities Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
                [115 ] Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
                [116 ] NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
                [117 ] Department of Medicine; University of Leipzig, Leipzig, Germany
                [118 ] Dept of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
                [119 ] Institute of Cardiovascular Science, University College London, London, United Kingdom
                [120 ] Department of Vascular Medicine, Academic Medical Center, Amsterdam, Netherlands
                [121 ] Department of Epidemiology and Public Health, University College London, London, United Kingdom
                [122 ] Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom
                [123 ] Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Medical Research Institute, Ninewells Hospital and Medical School, Dundee, United Kingdom
                [124 ] Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
                [125 ] Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
                [126 ] Singapore National Eye Centre, Singapore, Singapore
                [127 ] Dept of Medicine III, University of Dresden, Medical Faculty Carl Gustav Carus, Dresden, Germany
                [128 ] Imperial College Healthcare NHS Trust, London, United Kingdom
                [129 ] Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America
                [130 ] Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
                [131 ] Dipartimento di Scienze Biomediche, Università di Sassari, Italy
                [132 ] Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
                [133 ] Brown Foundation Institute of Molecular Medicine, Division of Epidemiology, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America
                [134 ] Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
                [135 ] CNRS 8199-Lille University, France
                [136 ] Finnish Institute for Molecular Medicine (FIMM), Helsinki, Finland
                [137 ] Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
                [138 ] National Institute on Aging, Bethesda, MD, United States of America
                [139 ] Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
                [140 ] Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
                [141 ] Khoo Teck Puat-National University Children’s Medical Institute, National University Health System, Singapore, Singapore
                [142 ] Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
                [143 ] Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
                [144 ] Duke-NUS Medical School Singapore, Singapore
                [145 ] National Heart and Lung Institute, Imperial College London, Hammersmith Hospital Campus, London, United Kingdom
                [146 ] Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
                [147 ] Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC, United States of America
                [148 ] The Mindich Child Health Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [149 ] Department of Medical Epidemiology and Biostatistics, Karolinska Insitutet, Stockholm, Sweden
                [150 ] Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
                [151 ] Synlab Academy, Synlab Services GmbH, Mannheim, Germany
                [152 ] Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, United Kingdom
                [153 ] Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America
                [154 ] Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, United States of America
                [155 ] Center for Non-Communicable Diseases, Karachi, Pakistan
                [156 ] Department of Medicine, Central Hospital, Central Finland, Jyväskylä, Finland
                [157 ] Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
                [158 ] School of Medicine, National Yang-Ming University, Taipei, Taiwan
                [159 ] School of Medicine, National Defense Medical Center, Taipei, Taiwan
                [160 ] Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
                [161 ] Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
                [162 ] Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
                [163 ] Dasman Diabetes Institute, Dasman, Kuwait
                [164 ] Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
                [165 ] Saudi Diabetes Research Group, King Abdulaziz University, Fahd Medical Research Center, Jeddah, Saudi Arabia
                [166 ] Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, United States of America
                [167 ] Division of Cancer Control and Population Sciences,University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States of America
                [168 ] Laboratory of Epidemiology & Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
                [169 ] Department of Haematology, University of Cambridge, Cambridge, United Kingdom
                [170 ] The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics at the University of Cambridge, United Kingdom
                [171 ] Biomedical Research Centre Oxford Haematology Theme and Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Headley Way, Headington, Oxford, United Kingdom
                [172 ] NHS Blood and Transplant, Headington, Oxford, United Kingdom
                [173 ] Diabetes Unit and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, United States of America
                [174 ] Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, United States of America
                [175 ] Department of Medicine, McGill University, Montreal, Quebec, Canada
                [176 ] Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom
                [177 ] Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
                [178 ] Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
                Centers for Disease Control and Prevention, UNITED STATES
                Author notes

                We have read the journal's policy and the authors of this manuscript have the following competing interests: AYC is an employee of Merck, however all work for the manuscript was completed before the start of employment. CEE is a current employee of AstraZeneca. CLan receives a stipend as a specialty consulting editor for PLOS Medicine and serves on the journal's editorial board. EI is a scientific advisor for Precision Wellness, Cellink and Olink Proteomics for work unrelated to the present project. GKH declared institution support from Amgen, AstraZeneca, Cerenis, Ionis, Regeneron Pharmaceuticals, Inc. and Sanofi, Synageva. He has served as a consultant and received speaker fees from Aegerion, Amgen, Sanofi, Regeneron Pharmaceuticals, Inc., and Pfizer. IB and spouse own stock in GlaxoSmithKline and Incyte Corporation. JD declared grants from the National Heart, Lung, and Blood Institute (NHLBI) of the National Institute of Health (NIH) during the course of this study. JIR declared funding from NIH grants. MAN consults for Illumina Inc, the Michael J. Fox Foundation and University of California Healthcare among others. MBl receives speaker’s honoraria and/or compensation for participation in advisory boards from: Astra Zeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis, MSD, Pfizer, Riemser and Sanofi. MIM was a member of the editorial board of PLOS Medicine at the time this manuscript was submitted. RAS is an employee and shareholder in GlaxoSmithKline.

                ‡ EW and AL also contributed equally to this work.

                ¶ Membership of the EPIC-CVD Consortium, EPIC-InterAct Consortium, and Lifelines Cohort Study is provided in the Acknowledgments

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                Article
                PMEDICINE-D-17-00599
                10.1371/journal.pmed.1002383
                5595282
                28898252
                616d8198-06ef-401a-b1d6-96dfdf04d0b0

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 17 February 2017
                : 3 August 2017
                Page count
                Figures: 5, Tables: 2, Pages: 30
                Funding
                Please refer to the supporting information file S1 Financial Disclosure for full information with regard to funding and financial support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and health sciences
                Diagnostic medicine
                Diabetes diagnosis and management
                HbA1c
                Biology and life sciences
                Biochemistry
                Proteins
                Hemoglobin
                HbA1c
                People and places
                Population groupings
                Ethnicities
                African Americans
                Medicine and Health Sciences
                Diagnostic Medicine
                Diabetes Diagnosis and Management
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Human Genetics
                Genome-Wide Association Studies
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Biology and Life Sciences
                Genetics
                Human Genetics
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Custom metadata
                The ancestry-specific and transethnic genome-wide meta-analysis summary statistics for association with HbA1c, and published data included in this study, are available to download from the MAGIC website, www.magicinvestigators.org/downloads. Uniform analysis plan(s) showing the QC and data analysis steps in detail are provided in the supporting information file S1 Analysis Plans.

                Medicine
                Medicine

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