Döring, A. et al. SLC2A9 influences uric acid concentrations with pronounced sex-specific effects. Nat. Genet. 40, 430-436

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Nature Genetics (Impact Factor: 29.35). 05/2008; 40(4):430-6. DOI: 10.1038/ng.107
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Serum uric acid concentrations are correlated with gout and clinical entities such as cardiovascular disease and diabetes. In the genome-wide association study KORA (Kooperative Gesundheitsforschung in der Region Augsburg) F3 500K (n = 1,644), the most significant SNPs associated with uric acid concentrations mapped within introns 4 and 6 of SLC2A9, a gene encoding a putative hexose transporter (effects: -0.23 to -0.36 mg/dl per copy of the minor allele). We replicated these findings in three independent samples from Germany (KORA S4 and SHIP (Study of Health in Pomerania)) and Austria (SAPHIR; Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk), with P values ranging from 1.2 x 10(-8) to 1.0 x 10(-32). Analysis of whole blood RNA expression profiles from a KORA F3 500K subgroup (n = 117) showed a significant association between the SLC2A9 isoform 2 and urate concentrations. The SLC2A9 genotypes also showed significant association with self-reported gout. The proportion of the variance of serum uric acid concentrations explained by genotypes was about 1.2% in men and 6% in women, and the percentage accounted for by expression levels was 3.5% in men and 15% in women.

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Available from: Arne Pfeufer, Mar 25, 2014
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    • "Results from a series of GWAS studies (genome-wide association scans) revealed a significant correlation between genetic variants in the gene SLC2A9 and serum UA level, the excretion fraction of UA, gout and body mass index [9]–[11]. The importance of URAT1 and GLUT9 for regulating blood urate levels was confirmed by the finding of causal mutations in patients with idiopathic renal hypouricemia type 1 (OMIM #220150, RHUC1) and type 2 (OMIM #612076, RHUC2). "
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    ABSTRACT: Objective Using European descent Czech populations, we performed a study of SLC2A9 and SLC22A12 genes previously identified as being associated with serum uric acid concentrations and gout. This is the first study of the impact of non-synonymous allelic variants on the function of GLUT9 except for patients suffering from renal hypouricemia type 2. Methods The cohort consisted of 250 individuals (150 controls, 54 nonspecific hyperuricemics and 46 primary gout and/or hyperuricemia subjects). We analyzed 13 exons of SLC2A9 (GLUT9 variant 1 and GLUT9 variant 2) and 10 exons of SLC22A12 by PCR amplification and sequenced directly. Allelic variants were prepared and their urate uptake and subcellular localization were studied by Xenopus oocytes expression system. The functional studies were analyzed using the non-parametric Wilcoxon and Kruskall-Wallis tests; the association study used the Fisher exact test and linear regression approach. Results We identified a total of 52 sequence variants (12 unpublished). Eight non-synonymous allelic variants were found only in SLC2A9: rs6820230, rs2276961, rs144196049, rs112404957, rs73225891, rs16890979, rs3733591 and rs2280205. None of these variants showed any significant difference in the expression of GLUT9 and in urate transport. In the association study, eight variants showed a possible association with hyperuricemia. However, seven of these were in introns and the one exon located variant, rs7932775, did not show a statistically significant association with serum uric acid concentration. Conclusion Our results did not confirm any effect of SLC22A12 and SLC2A9 variants on serum uric acid concentration. Our complex approach using association analysis together with functional and immunohistochemical characterization of non-synonymous allelic variants did not show any influence on expression, subcellular localization and urate uptake of GLUT9.
    PLoS ONE 09/2014; 9(9). DOI:10.1371/journal.pone.0107902 · 3.23 Impact Factor
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    • ", p=3.19×10-23). Gender-specific associations between SLC2A9 polymorphisms and uric acid concentrations have been reported by others and are consistent with our observations with CNPs near SLC2A9[7,33-36]. Independent replication of the association between copy number and uric acid concentrations in FHS provides further support for our finding. "
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    ABSTRACT: Background Hyperuricemia is associated with multiple diseases, including gout, cardiovascular disease, and renal disease. Serum urate is highly heritable, yet association studies of single nucleotide polymorphisms (SNPs) and serum uric acid explain a small fraction of the heritability. Whether copy number polymorphisms (CNPs) contribute to uric acid levels is unknown. Results We assessed copy number on a genome-wide scale among 8,411 individuals of European ancestry (EA) who participated in the Atherosclerosis Risk in Communities (ARIC) study. CNPs upstream of the urate transporter SLC2A9 on chromosome 4p16.1 are associated with uric acid (χ2df2=3545, p=3.19×10-23). Effect sizes, expressed as the percentage change in uric acid per deleted copy, are most pronounced among women (3.974.935.87 [ 2.55097.5 denoting percentiles], p=4.57×10-23) and independent of previously reported SNPs in SLC2A9 as assessed by SNP and CNP regression models and the phasing SNP and CNP haplotypes (χ2df2=3190,p=7.23×10-08). Our finding is replicated in the Framingham Heart Study (FHS), where the effect size estimated from 4,089 women is comparable to ARIC in direction and magnitude (1.414.707.88, p=5.46×10-03). Conclusions This is the first study to characterize CNPs in ARIC and the first genome-wide analysis of CNPs and uric acid. Our findings suggests a novel, non-coding regulatory mechanism for SLC2A9-mediated modulation of serum uric acid, and detail a bioinformatic approach for assessing the contribution of CNPs to heritable traits in large population-based studies where technical sources of variation are substantial.
    BMC Genetics 07/2014; 15(1):81. DOI:10.1186/1471-2156-15-81 · 2.40 Impact Factor
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    • "Recently, genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with serum urate concentrations and gout, several of them located in genes coding for renal transport proteins (Doring et al. 2008; Kolz et al. 2009; Kottgen et al. 2013; Li et al. 2007; Vitart et al. 2008; Wallace et al. 2008; Yang et al. 2010). However, despite the success of these GWAS, detailed functional information on the underlying biological processes is still lacking. "
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    ABSTRACT: Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia. Electronic supplementary material The online version of this article (doi:10.1007/s11306-013-0565-2) contains supplementary material, which is available to authorized users.
    Metabolomics 02/2014; 10(1):141-151. DOI:10.1007/s11306-013-0565-2 · 3.86 Impact Factor
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