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      Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

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          Abstract

          Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood ( n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation ( n = 1980) and epigenomic annotation data highlight 3 genes ( CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants.

          Abstract

          GWAS have so far identified 129 loci associated with type 2 diabetes (T2D). Here, the authors meta-analyse three large T2D GWA studies which uncovers 42 additional loci, further prioritize 33 functional genes using eQTL and mQTL data and propose regulatory mechanisms for three putative T2D genes.

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          Rare and common variants: twenty arguments.

          Genome-wide association studies have greatly improved our understanding of the genetic basis of disease risk. The fact that they tend not to identify more than a fraction of the specific causal loci has led to divergence of opinion over whether most of the variance is hidden as numerous rare variants of large effect or as common variants of very small effect. Here I review 20 arguments for and against each of these models of the genetic basis of complex traits and conclude that both classes of effect can be readily reconciled.
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            An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

            To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
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              The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes.

              Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.
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                Author and article information

                Contributors
                j.zeng@uq.edu.au
                jian.yang@uq.edu.au
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                27 July 2018
                27 July 2018
                2018
                : 9
                : 2941
                Affiliations
                [1 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, Institute for Molecular Bioscience, , The University of Queensland, ; Brisbane, Queensland 4072 Australia
                [2 ]ISNI 0000 0001 0348 3990, GRID grid.268099.c, The Eye Hospital, School of Ophthalmology & Optometry, , Wenzhou Medical University, ; Wenzhou, Zhejiang 325027 China
                [3 ]ISNI 0000 0001 0943 7661, GRID grid.10939.32, Estonian Genome Center, , Institute of Genomics, University of Tartu, ; Tartu, 51010 Estonia
                [4 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, Queensland Brain Institute, , The University of Queensland, ; Brisbane, Queensland 4072 Australia
                [5 ]ISNI 0000 0004 0626 690X, GRID grid.419890.d, Computational Biology, Ontario Institute for Cancer Research, ; Toronto, Ontario M5G 0A3 Canada
                [6 ]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Department of Public Health Sciences, , University of Chicago, ; Chicago, IL 60637 USA
                [7 ]ISNI 0000 0004 0637 0221, GRID grid.185448.4, Singapore Immunology Network, Agency for Science, , Technology and Research, ; Singapore, 138648 Singapore
                [8 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Computer Science, , Johns Hopkins University, ; Baltimore, MD 21218 USA
                [9 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Heart Center Leipzig, , Universität Leipzig, ; 04289 Leipzig, Germany
                [10 ]ISNI 0000 0000 9558 4598, GRID grid.4494.d, Department of Genetics, , University Medical Centre Groningen, ; 9713 GZ Groningen, The Netherlands
                [11 ]ISNI 0000 0004 1754 9227, GRID grid.12380.38, Faculty of Genes, Behavior and Health, , Vrije Universiteit Amsterdam, ; 1081 HV Amsterdam, The Netherlands
                [12 ]ISNI 0000000122986657, GRID grid.34477.33, Cardiovascular Health Research Unit, , University of Washington, ; Seattle, WA 98195 United States of America
                [13 ]ISNI 0000 0001 0943 7661, GRID grid.10939.32, Estonian Genome Center, , University of Tartu, ; 50090 Tartu, Estonia
                [14 ]ISNI 0000 0004 1936 8024, GRID grid.8391.3, Exeter Medical School, , University of Exeter, ; Exeter, EX4 4QD UK
                [15 ]ISNI 0000000122986657, GRID grid.34477.33, Department of Medicine, , University of Washington, ; Seattle, WA 98195 USA
                [16 ]ISNI 0000 0001 2097 4943, GRID grid.213917.f, School of Biological Sciences, , Georgia Tech, ; Atlanta, GA 30332 USA
                [17 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, MRC Integrative Epidemiology Unit, , University of Bristol, ; Bristol, BS8 1TH UK
                [18 ]ISNI 0000 0004 0628 2985, GRID grid.412330.7, Department of Clinical Physiology, , Tampere University Hospital, ; 33521 Tampere, Finland
                [19 ]ISNI 0000 0001 2314 6254, GRID grid.5509.9, Faculty of Medicine and Life Sciences, , University of Tampere, ; 33100 Tampere, Finland
                [20 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, National Institute for Health and Welfare, , University of Helsinki, ; 00100 Helsinki, Finland
                [21 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Institut für Medizinische InformatiK, Statistik und Epidemiologie, LIFE – Leipzig Research Center for Civilization Diseases, , Universität Leipzig, ; 04103 Leipzig, Germany
                [22 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, IFB Adiposity Diseases, Department of Medicine, , Universität Leipzig, ; 04103 Leipzig, Germany
                [23 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Interdisciplinary Center for Clinical Research, Faculty of Medicine, , Universität Leipzig, ; 04103 Leipzig, Germany
                [24 ]ISNI 0000 0001 0423 4662, GRID grid.8515.9, Lausanne University Hospital, ; 1011 Lausanne, Switzerland
                [25 ]ISNI 0000 0001 2314 6254, GRID grid.5509.9, Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences, , University of Tampere, ; 33110 Tampere, Finland
                [26 ]ISNI 0000 0004 0483 2525, GRID grid.4567.0, Institute of Genetic Epidemiology, , Helmholtz Zentrum München, ; 81377 München, Germany
                [27 ]GRID grid.5603.0, Institute of Clinical Chemistry and Laboratory Medicine, , University Medicine Greifswald, ; 17489 Greifswald, Germany
                [28 ]ISNI 0000 0004 0483 2525, GRID grid.4567.0, Institute of Human Genetics, , Helmholtz Zentrum München, ; 81675 München, Germany
                [29 ]ISNI 0000000122986657, GRID grid.34477.33, Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine, and Health Services, , University of Washington, ; Seattle, WA 98195 USA
                [30 ]ISNI 0000 0004 0628 215X, GRID grid.410552.7, Department of Clinical Physiology and Nuclear Medicine, , Turku University Hospital, ; 20521 Turku, Finland
                [31 ]ISNI 0000 0001 2097 1371, GRID grid.1374.1, University of Turku, ; 20500 Turku, Finland
                [32 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, School of Social and Community Medicine, , University of Bristol, ; Bristol, BS8 1TH UK
                [33 ]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Department of Medical Epidemiology and Biostatistics, , Karolinska Institute, ; 171 77 Solna, Sweden
                [34 ]GRID grid.5603.0, Institute for Community Medicine, , University Medicine Greifswald, ; 17489 Greifswald, Germany
                [35 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Institute for Laboratory Medicine, LIFE – Leipzig Research Center for Civilization Diseases, , Universität Leipzig, ; 04107 Leipzig, Germany
                [36 ]ISNI 0000 0001 2230 9752, GRID grid.9647.c, Division of Endocrinology and Nephrology, Department of Medicine, , Universität Leipzig, ; 04103 Leipzig, Germany
                [37 ]ISNI 000000040459992X, GRID grid.5645.2, Department of Internal Medicine, , Erasmus Medical Centre, ; 3015 CE Rotterdam, The Netherlands
                [38 ]GRID grid.5603.0, Interfaculty Institute for Genetics and Functional Genomics, , University Medicine Greifswald, ; 17489 Greifswald, Germany
                Author information
                http://orcid.org/0000-0002-0285-0426
                http://orcid.org/0000-0002-0128-7280
                http://orcid.org/0000-0002-2143-8760
                http://orcid.org/0000-0003-2001-2474
                Article
                4951
                10.1038/s41467-018-04951-w
                6063971
                30054458
                ca03a6e1-6849-457d-ae0e-d80bcfcb6784
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 March 2018
                : 5 June 2018
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