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      Genome-wide association study of clinically defined gout identifies multiple risk loci and its association with clinical subtypes

      1 , 2 , 3 , 1 , 4 , 1 , 5 , 1 , 6 , 6 , 7 , 8 , 9 , 10 , 11 , 1 , 1 , 1 , 1 , 1 , 1 , 12 , 13 , 12 , 12 , 12 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 10 , 8 , 18 , 21 , 22 , 23 , 24 , 3 , 25 , 22 , 26 , 14 , 27 , 1

      Annals of the Rheumatic Diseases

      BMJ Publishing Group

      Gout, Arthritis, Gene Polymorphism

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          Gout, caused by hyperuricaemia, is a multifactorial disease. Although genome-wide association studies (GWASs) of gout have been reported, they included self-reported gout cases in which clinical information was insufficient. Therefore, the relationship between genetic variation and clinical subtypes of gout remains unclear. Here, we first performed a GWAS of clinically defined gout cases only.

          Methods

          A GWAS was conducted with 945 patients with clinically defined gout and 1213 controls in a Japanese male population, followed by replication study of 1048 clinically defined cases and 1334 controls.

          Results

          Five gout susceptibility loci were identified at the genome-wide significance level (p<5.0×10 −8), which contained well-known urate transporter genes ( ABCG2 and SLC2A9) and additional genes: rs1260326 (p=1.9×10 −12; OR=1.36) of GCKR (a gene for glucose and lipid metabolism), rs2188380 (p=1.6×10 −23; OR=1.75) of MYL2-CUX2 (genes associated with cholesterol and diabetes mellitus) and rs4073582 (p=6.4×10 −9; OR=1.66) of CNIH-2 (a gene for regulation of glutamate signalling). The latter two are identified as novel gout loci. Furthermore, among the identified single-nucleotide polymorphisms (SNPs), we demonstrated that the SNPs of ABCG2 and SLC2A9 were differentially associated with types of gout and clinical parameters underlying specific subtypes (renal underexcretion type and renal overload type). The effect of the risk allele of each SNP on clinical parameters showed significant linear relationships with the ratio of the case–control ORs for two distinct types of gout (r=0.96 [p=4.8×10 −4] for urate clearance and r=0.96 [p=5.0×10 −4] for urinary urate excretion).

          Conclusions

          Our findings provide clues to better understand the pathogenesis of gout and will be useful for development of companion diagnostics.

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          Most cited references 38

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          Preliminary criteria for the classification of the acute arthritis of primary gout.

          The American Rheumatism Association sub-committe on classification criteria for gout analyzed data from more than 700 patients with gout, pseudogout, rheumatoid arthritis, or septic arthritis. Criteria for classifying a patient as having gout were a) the presence of characteristic urate crystals in the joint fluid, and/or b) a topus proved to contain urate crystals by chemical or polarized light microscopic means, and/or c) the presence of six of the twelve clinical, laboratory, and X-ray phenomena listed in Table 5.
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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

                Journal
                Ann Rheum Dis
                Ann. Rheum. Dis
                annrheumdis
                ard
                Annals of the Rheumatic Diseases
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                0003-4967
                1468-2060
                April 2016
                2 February 2015
                : 75
                : 4
                : 652-659
                Affiliations
                [1 ]Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College , Tokorozawa, Saitama, Japan
                [2 ]Department of Medical Chemistry, Kurume University School of Medicine , Kurume, Fukuoka, Japan
                [3 ]Division of Human Genetics, Department of Integrated Genetics, National Institute of Genetics , Mishima, Shizuoka, Japan
                [4 ]Medical Group, Headquarters, Iwo-to Air Base Group, Japan Air Self-Defense Force , Tokyo, Japan
                [5 ]Department of Dermatology, National Defense Medical College , Tokorozawa, Saitama, Japan
                [6 ]Laboratory for Statistical Analysis, Center for Integrative Medical Sciences, RIKEN , Yokohama, Kanagawa, Japan
                [7 ]Laboratory for Mathematics, National Defense Medical College , Tokorozawa, Saitama, Japan
                [8 ]Department of Preventive Medicine and Public Health, National Defense Medical College , Tokorozawa, Saitama, Japan
                [9 ]The Central Research Institute, National Defense Medical College , Tokorozawa, Saitama, Japan
                [10 ]Cell Engineering Division, RIKEN BioResource Center , Tsukuba, Ibaraki, Japan
                [11 ]Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University , Sendai, Miyagi, Japan
                [12 ]Department of Preventive Medicine, Nagoya University Graduate School of Medicine , Nagoya, Aichi, Japan
                [13 ]Department of Nutritional Sciences, Faculty of Health and Welfare, Seinan Jo Gakuin University , Fukuoka, Japan
                [14 ]Ryougoku East Gate Clinic , Tokyo, Japan
                [15 ]Department of Internal Medicine, National Defense Medical College , Tokorozawa, Saitama, Japan
                [16 ]Department of Pathology, National Defense Medical College , Tokorozawa, Saitama, Japan
                [17 ]Department of Internal Medicine, Self-Defense Forces Central Hospital , Tokyo, Japan
                [18 ]Department of Pharmacy, The University of Tokyo Hospital , Tokyo, Japan
                [19 ]Department of Biopharmaceutics, School of Pharmacy, Tokyo University of Pharmacy and Life Sciences , Tokyo, Japan
                [20 ]Faculty of Pharmacy, Kanazawa University , Kanazawa, Ishikawa, Japan
                [21 ]Division of Bio-system Pharmacology, Department of Pharmacology, Graduate School of Medicine, Osaka University , Osaka, Japan
                [22 ]Division of Kidney and Hypertension, Department of Internal Medicine, Jikei University School of Medicine , Tokyo, Japan
                [23 ]Department of Pathophysiology and Therapy in Chronic Kidney Disease, Jikei University School of Medicine , Tokyo, Japan
                [24 ]Department of Healthcare Administration, Nagoya University Graduate School of Medicine , Nagoya, Japan
                [25 ]Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN , Yokohama, Kanagawa, Japan
                [26 ]Department of Pathophysiology, Tokyo University of Pharmacy and Life Sciences , Tokyo, Japan
                [27 ]Midorigaoka Hospital , Osaka, Japan
                Author notes

                Handling editor Tore K Kvien

                [Correspondence to ] Dr Hirotaka Matsuo, Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama 359-8513, Japan; hmatsuo@ 123456ndmc.ac.jp

                HM, KY, HNakaoka, AN and MS contributed equally.

                Article
                annrheumdis-2014-206191
                10.1136/annrheumdis-2014-206191
                4819613
                25646370
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

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                Clinical and Epidemiological Research
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                Immunology

                arthritis, gene polymorphism, gout

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