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      Metabolic Syndrome, Alcohol Consumption and Genetic Factors Are Associated with Serum Uric Acid Concentration

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          Abstract

          Objective

          Uric acid is the end product of purine metabolism in humans, and increased serum uric acid concentrations lead to gout. The objective of the current study was to identify factors that are independently associated with serum uric acid concentrations in a cohort of Czech control individuals.

          Methods

          The cohort consisted of 589 healthy subjects aged 18–65 years. We studied the associations between the serum uric acid concentration and the following: (i) demographic, anthropometric and other variables previously reported to be associated with serum uric acid concentrations; (ii) the presence of metabolic syndrome and the levels of metabolic syndrome components; and (iii) selected genetic variants of the MTHFR (c.665C>T, c.1286A>C), SLC2A9 (c.844G>A, c.881G>A) and ABCG2 genes (c.421C>A). A backward model selection procedure was used to build two multiple linear regression models; in the second model, the number of metabolic syndrome criteria that were met replaced the metabolic syndrome-related variables.

          Results

          The models had coefficients of determination of 0.59 and 0.53. The serum uric acid concentration strongly correlated with conventional determinants including male sex, and with metabolic syndrome-related variables. In the simplified second model, the serum uric acid concentration positively correlated with the number of metabolic syndrome criteria that were met, and this model retained the explanatory power of the first model. Moderate wine drinking did not increase serum uric acid concentrations, and the urate transporter ABCG2, unlike MTHFR, was a genetic determinant of serum uric acid concentrations.

          Conclusion

          Metabolic syndrome, moderate wine drinking and the c.421C>A variant in the ABCG gene are independently associated with the serum uric acid concentration. Our model indicates that uric acid should be clinically monitored in persons with metabolic syndrome.

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          Most cited references45

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          Molecular identification of a renal urate anion exchanger that regulates blood urate levels.

          Urate, a naturally occurring product of purine metabolism, is a scavenger of biological oxidants implicated in numerous disease processes, as demonstrated by its capacity of neuroprotection. It is present at higher levels in human blood (200 500 microM) than in other mammals, because humans have an effective renal urate reabsorption system, despite their evolutionary loss of hepatic uricase by mutational silencing. The molecular basis for urate handling in the human kidney remains unclear because of difficulties in understanding diverse urate transport systems and species differences. Here we identify the long-hypothesized urate transporter in the human kidney (URAT1, encoded by SLC22A12), a urate anion exchanger regulating blood urate levels and targeted by uricosuric and antiuricosuric agents (which affect excretion of uric acid). Moreover, we provide evidence that patients with idiopathic renal hypouricaemia (lack of blood uric acid) have defects in SLC22A12. Identification of URAT1 should provide insights into the nature of urate homeostasis, as well as lead to the development of better agents against hyperuricaemia, a disadvantage concomitant with human evolution.
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            SLC2A9 is a newly identified urate transporter influencing serum urate concentration, urate excretion and gout.

            Uric acid is the end product of purine metabolism in humans and great apes, which have lost hepatic uricase activity, leading to uniquely high serum uric acid concentrations (200-500 microM) compared with other mammals (3-120 microM). About 70% of daily urate disposal occurs via the kidneys, and in 5-25% of the human population, impaired renal excretion leads to hyperuricemia. About 10% of people with hyperuricemia develop gout, an inflammatory arthritis that results from deposition of monosodium urate crystals in the joint. We have identified genetic variants within a transporter gene, SLC2A9, that explain 1.7-5.3% of the variance in serum uric acid concentrations, following a genome-wide association scan in a Croatian population sample. SLC2A9 variants were also associated with low fractional excretion of uric acid and/or gout in UK, Croatian and German population samples. SLC2A9 is a known fructose transporter, and we now show that it has strong uric acid transport activity in Xenopus laevis oocytes.
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              Association of three genetic loci with uric acid concentration and risk of gout: a genome-wide association study.

              Hyperuricaemia, a highly heritable trait, is a key risk factor for gout. We aimed to identify novel genes associated with serum uric acid concentration and gout. Genome-wide association studies were done for serum uric acid in 7699 participants in the Framingham cohort and in 4148 participants in the Rotterdam cohort. Genome-wide significant single nucleotide polymorphisms (SNPs) were replicated in white (n=11 024) and black (n=3843) individuals who took part in the study of Atherosclerosis Risk in Communities (ARIC). The SNPs that reached genome-wide significant association with uric acid in either the Framingham cohort (p<5.0 x 10(-8)) or the Rotterdam cohort (p<1.0 x 10(-7)) were evaluated with gout. The results obtained in white participants were combined using meta-analysis. Three loci in the Framingham cohort and two in the Rotterdam cohort showed genome-wide association with uric acid. Top SNPs in each locus were: missense rs16890979 in SLC2A9 (p=7.0 x 10(-168) and 2.9 x 10(-18) for white and black participants, respectively); missense rs2231142 in ABCG2 (p=2.5 x 10(-60) and 9.8 x 10(-4)), and rs1165205 in SLC17A3 (p=3.3 x 10(-26) and 0.33). All SNPs were direction-consistent with gout in white participants: rs16890979 (OR 0.59 per T allele, 95% CI 0.52-0.68, p=7.0 x 10(-14)), rs2231142 (1.74, 1.51-1.99, p=3.3 x 10(-15)), and rs1165205 (0.85, 0.77-0.94, p=0.002). In black participants of the ARIC study, rs2231142 was direction-consistent with gout (1.71, 1.06-2.77, p=0.028). An additive genetic risk score of high-risk alleles at the three loci showed graded associations with uric acid (272-351 mumol/L in the Framingham cohort, 269-386 mumol/L in the Rotterdam cohort, and 303-426 mumol/L in white participants of the ARIC study) and gout (frequency 2-13% in the Framingham cohort, 2-8% in the Rotterdam cohort, and 1-18% in white participants in the ARIC study). We identified three genetic loci associated with uric acid concentration and gout. A score based on genes with a putative role in renal urate handling showed a substantial risk for gout.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                14 May 2014
                : 9
                : 5
                : e97646
                Affiliations
                [1]Institute of Inherited Metabolic Disorders, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
                University of Maryland School of Medicine, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: BS MP VK. Performed the experiments: BS JS. Analyzed the data: VK BS MP JS. Contributed reagents/materials/analysis tools: BS VK JS. Wrote the paper: BS VK MP.

                Article
                PONE-D-14-05691
                10.1371/journal.pone.0097646
                4020828
                24827988
                3c97e00d-dcf9-41fb-8ce7-5e6d3da964fe
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 February 2014
                : 22 April 2014
                Page count
                Pages: 9
                Funding
                This study was supported by a grant from the Czech Republic Ministry of Health (IGA MZ NT/11322–4/2010 and RVO VFN64165) and by institutional support from a program at Charles University in Prague (PRVOUK-P24/LF1/3). 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
                Public and Occupational Health
                Preventive Medicine
                Research and Analysis Methods
                Research Design
                Clinical Research Design
                Cohort Studies
                Simulation and Modeling

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