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      Genetic and Functional Assessment of the Role of the rs13431652-A and rs573225-A Alleles in the G6PC2 Promoter That Are Strongly Associated With Elevated Fasting Glucose Levels

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          Abstract

          OBJECTIVE

          Genome-wide association studies have identified a single nucleotide polymorphism (SNP), rs560887, located in a G6PC2 intron that is highly correlated with variations in fasting plasma glucose (FPG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit. This study examines the contribution of two G6PC2 promoter SNPs, rs13431652 and rs573225, to the association signal.

          RESEARCH DESIGN AND METHODS

          We genotyped 9,532 normal FPG participants (FPG <6.1 mmol/l) for three G6PC2 SNPs, rs13431652 (distal promoter), rs573225 (proximal promoter), rs560887 (3rd intron). We used regression analyses adjusted for age, sex, and BMI to assess the association with FPG and haplotype analyses to assess comparative SNP contributions. Fusion gene and gel retardation analyses characterized the effect of rs13431652 and rs573225 on G6PC2 promoter activity and transcription factor binding.

          RESULTS

          Genetic analyses provide evidence for a strong contribution of the promoter SNPs to FPG variability at the G6PC2 locus (rs13431652: β = 0.075, P = 3.6 × 10 −35; rs573225 β = 0.073 P = 3.6 × 10 −34), in addition to rs560887 (β = 0.071, P = 1.2 × 10 −31). The rs13431652-A and rs573225-A alleles promote increased NF-Y and Foxa2 binding, respectively. The rs13431652-A allele is associated with increased FPG and elevated promoter activity, consistent with the function of G6PC2 in pancreatic islets. In contrast, the rs573225-A allele is associated with elevated FPG but reduced promoter activity.

          CONCLUSIONS

          Genetic and in situ functional data support a potential role for rs13431652, but not rs573225, as a causative SNP linking G6PC2 to variations in FPG, though a causative role for rs573225 in vivo cannot be ruled out.

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          Most cited references42

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          A genome-wide association study identifies novel risk loci for type 2 diabetes.

          Type 2 diabetes mellitus results from the interaction of environmental factors with a combination of genetic variants, most of which were hitherto unknown. A systematic search for these variants was recently made possible by the development of high-density arrays that permit the genotyping of hundreds of thousands of polymorphisms. We tested 392,935 single-nucleotide polymorphisms in a French case-control cohort. Markers with the most significant difference in genotype frequencies between cases of type 2 diabetes and controls were fast-tracked for testing in a second cohort. This identified four loci containing variants that confer type 2 diabetes risk, in addition to confirming the known association with the TCF7L2 gene. These loci include a non-synonymous polymorphism in the zinc transporter SLC30A8, which is expressed exclusively in insulin-producing beta-cells, and two linkage disequilibrium blocks that contain genes potentially involved in beta-cell development or function (IDE-KIF11-HHEX and EXT2-ALX4). These associations explain a substantial portion of disease risk and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits.
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            MatInd and MatInspector: new fast and versatile tools for detection of consensus matches in nucleotide sequence data.

            The identification of potential regulatory motifs in new sequence data is increasingly important for experimental design. Those motifs are commonly located by matches to IUPAC strings derived from consensus sequences. Although this method is simple and widely used, a major drawback of IUPAC strings is that they necessarily remove much of the information originally present in the set of sequences. Nucleotide distribution matrices retain most of the information and are thus better suited to evaluate new potential sites. However, sufficiently large libraries of pre-compiled matrices are a prerequisite for practical application of any matrix-based approach and are just beginning to emerge. Here we present a set of tools for molecular biologists that allows generation of new matrices and detection of potential sequence matches by automatic searches with a library of pre-compiled matrices. We also supply a large library (> 200) of transcription factor binding site matrices that has been compiled on the basis of published matrices as well as entries from the TRANSFAC database, with emphasis on sequences with experimentally verified binding capacity. Our search method includes position weighting of the matrices based on the information content of individual positions and calculates a relative matrix similarity. We show several examples suggesting that this matrix similarity is useful in estimating the functional potential of matrix matches and thus provides a valuable basis for designing appropriate experiments.
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              Variants in MTNR1B influence fasting glucose levels.

              To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.
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                Author and article information

                Journal
                Diabetes
                diabetes
                diabetes
                Diabetes
                Diabetes
                American Diabetes Association
                0012-1797
                1939-327X
                October 2010
                9 July 2010
                : 59
                : 10
                : 2662-2671
                Affiliations
                [1] 1CNRS-UMR-8199, Institut Pasteur de Lille, Lille, France;
                [2] 2University Lille Nord de France, Lille, France;
                [3] 3Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee;
                [4] 4Department of Endocrinology and Metabolism, University of Pisa, Pisa, Italy;
                [5] 5INSERM U859, Université de Lille-Nord de France, Centre Hospitalier Regional et Universitaire de Lille, Lille, France;
                [6] 6Institut Inter-Régional pour la Santé, La Riche, France;
                [7] 7INSERM U780, Villejuif; University Paris-Sud, Orsay, France;
                [8] 8Department of Endocrinology, Diabetology and Nutrition, Bichat-Claude Bernard University Hospital, Assistance Publique des Hôpitaux de Paris, Paris, France; INSERM U695, Université Paris 7, Paris, France;
                [9] 9INSERM U690, Robert Debré Hospital, Paris; Paris Diderot University, Paris, France;
                [10] 10Department of Epidemiology and Public Health, Imperial College London, London, U.K.;
                [11] 11Institute of Health Sciences, University of Oulu, Department of Child and Adolescent Health, National Public Health Institute, Biocenter Oulu, University of Oulu, Oulu, Finland;
                [12] 12Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, U.K.
                Author notes
                Corresponding author: Richard M. O'Brien, richard.obrien@ 123456vanderbilt.edu .

                The present address for C.D. is INSERM UMR915 and CNRS ERL3147, Institut du Thorax, Nantes, France.

                N.B.-N. and A.B. contributed equally to this work.

                Article
                0389
                10.2337/db10-0389
                3279535
                20622168
                ad2eb220-1e55-4d5d-a203-554bb6095f7b
                © 2010 by the American Diabetes Association.

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

                History
                : 22 March 2010
                : 27 June 2010
                Funding
                Funded by: National Institutes of Health
                Award ID: DA-027002
                Award ID: P60 DK-20593
                Categories
                Genetics

                Endocrinology & Diabetes
                Endocrinology & Diabetes

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