What lies behind serum urate concentration? Insights from genetic and genomic studies

Many factors, including genetic components and acquired factors such as obesity and alcohol consumption, influence serum uric acid (urate) concentrations. Since serum urate concentrations are determined by the balance between renal urate excretion and the volume of urate produced via purine metabolism, urate transporter genes as well as genes coding for enzymes involved in purine metabolism affect serum urate concentrations. URAT1 was the first transporter affecting serum urate concentrations to be identified. Using the characterization of this transporter as an indicator, several transporters have been shown to transport urate, allowing the construction of a synoptic renal urate transport model. Notable re-absorptive urate transporters are URAT1 at apical membranes and GLUT9 at basolateral membranes, while ABCG2, MRP4 (multidrug resistance protein 4) and NPT1 are secretive transporters at apical membranes. Recent genome-wide association studies have led to validation of the in vitro model constructed from each functional analysis of urate transporters, and identification of novel candidate genes related to urate metabolism and transport proteins, such as glucokinase regulatory protein (GKRP), PDZK1 and MCT9. However, the function and physiologic roles of several candidates, as well as the influence of acquired factors such as obesity, foods, or alcoholic beverages, remain unclear

Allopurinol and oxypurinol differ in their strength and mechanisms of inhibition of xanthine oxidoreductase

Xanthine oxidoreductase is a metalloenzyme that catalyzes the final steps in purine metabolism by converting hypoxanthine to xanthine and then uric acid. Allopurinol, an analog of hypoxanthine, is widely used as an antigout drug, as xanthine oxidoreductase-mediated metabolism of allopurinol to oxypurinol leads to oxypurinol rotation in the enzyme active site and reduction of the molybdenum Mo(VI) active center to Mo(IV), inhibiting subsequent urate production. However, when oxypurinol is administered directly to a mouse model of hyperuricemia, it yields a weaker urate-lowering effect than allopurinol. To better understand its mechanism of inhibition and inform patient dosing strategies, we performed kinetic and structural analyses of the inhibitory activity of oxypurinol. Our results demonstrated that oxypurinol was less effective than allopurinol both in vivo and in vitro. We show that upon reoxidation to Mo(VI), oxypurinol binding is greatly weakened, and reduction by xanthine, hypoxanthine, or allopurinol is required for reformation of the inhibitor-enzyme complex. In addition, we show oxypurinol only weakly inhibits the conversion of hypoxanthine to xanthine and is therefore unlikely to affect the feedback inhibition of de novo purine synthesis. Furthermore, we observed weak allosteric inhibition of purine nucleoside phosphorylase by oxypurinol which has potentially adverse effects for patients. Considering these results, we propose the single-dose method currently used to treat hyperuricemia can result in unnecessarily high levels of allopurinol. While the short half-life of allopurinol in blood suggests that oxypurinol is responsible for enzyme inhibition, we anticipate multiple, smaller doses of allopurinol would reduce the total allopurinol patient load

Analysis of Purine Metabolism to Elucidate the Pathogenesis of Acute Kidney Injury in Renal Hypouricemia

博士（医学）甲日本医科大学202

A Proposal for Practical Diagnosis of Renal Hypouricemia : Evidenced from Genetic Studies of Nonfunctional Variants of URAT1/SLC22A12 among 30,685 Japanese Individuals

Background: Renal hypouricemia (RHUC) is characterized by a low serum uric acid (SUA) level and high fractional excretion of uric acid (FEUA). Further studies on FEUA in hypouricemic individuals are needed for a more accurate diagnosis of RHUC. Methods: In 30,685 Japanese health-examination participants, we genotyped the two most common nonfunctional variants of URAT1 (NFV-URAT1), W258X (rs121907892) and R90H (rs121907896), in 1040 hypouricemic individuals (SUA ≤ 3.0 mg/dL) and 2240 individuals with FEUA data. The effects of NFV-URAT1 on FEUA and SUA were also investigated using linear and multiple regression analyses. Results: Frequency of hypouricemic individuals (SUA ≤ 3.0 mg/dL) was 0.97% (male) and 6.94% (female) among 30,685 participants. High frequencies of those having at least one allele of NFV-URAT1 were observed in 1040 hypouricemic individuals. Furthermore, NFV-URAT1 significantly increased FEUA and decreased SUA, enabling FEUA and SUA levels to be estimated. Conversely, FEUA and SUA data of hypouricemic individuals are revealed to be useful to predict the number of NFV-URAT1. Conclusions: Our findings reveal that specific patterns of FEUA and SUA data assist with predicting the number of nonfunctional variants of causative genes for RHUC, and can also be useful for practical diagnosis of RHUC even before genetic tests

A common variant of leucine-rich repeat-containing 16A (LRRC16A) gene is associated with gout susceptibility

Gout is a common disease resulting from hyperuricemia which causes acute arthritis. Recently, genome-wide association studies revealed an association between serum uric acid levels and a common variant of leucine-rich repeat-containing 16A (LRRC16A) gene. However, it remains to be clarified whether LRRC16A contributes to the susceptibility to gout. In this study, we investigated the relationship between rs742132 in LRRC16A and gout. A total of 545 Japanese male gout cases and 1,115 male individuals as a control group were genotyped. rs742132 A/A genotype significantly increased the risk of gout, conferring an odds ratio of 1.30 (95 % CI 1.05–1.60; p = 0.015). LRRC16A encodes a protein called capping protein ARP2/3 and myosin-I linker (CARMIL), which serves as an inhibitor of the actin capping protein (CP). CP is an essential element of the actin cytoskeleton, which binds to the barbed end of the actin filament and regulates its polymerization. In the apical membrane of proximal tubular cells in the human kidney, the urate-transporting multimolecular complex (urate transportsome) is proposed to consist of several urate transporters and scaffolding proteins, which interact with the actin cytoskeleton. Thus, if there is a CARMIL dysfunction and regulatory disability in actin polymerization, urate transportsome may be unable to operate appropriately. We have shown for the first time that CARMIL/LRRC16A was associated with gout, which could be due to urate transportsome failure. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13577-013-0081-8) contains supplementary material, which is available to authorized users

Genome-wide association study revealed novel loci which aggravate asymptomatic hyperuricaemia into gout

Objective The first ever genome-wide association study (GWAS) of clinically defined gout cases and asymptomatic hyperuricaemia (AHUA) controls was performed to identify novel gout loci that aggravate AHUA into gout. Methods We carried out a GWAS of 945 clinically defined gout cases and 1003 AHUA controls followed by 2 replication studies. In total, 2860 gout cases and 3149 AHUA controls (all Japanese men) were analysed. We also compared the ORs for each locus in the present GWAS (gout vs AHUA) with those in the previous GWAS (gout vs normouricaemia). Results This new approach enabled us to identify two novel gout loci (rs7927466 of CNTN5 and rs9952962 of MIR302F) and one suggestive locus (rs12980365 of ZNF724) at the genome-wide significance level (p<5.0×10– 8). The present study also identified the loci of ABCG2, ALDH2 and SLC2A9. One of them, rs671 of ALDH2, was identified as a gout locus by GWAS for the first time. Comparing ORs for each locus in the present versus the previous GWAS revealed three ‘gout vs AHUA GWAS’-specific loci (CNTN5, MIR302F and ZNF724) to be clearly associated with mechanisms of gout development which distinctly differ from the known gout risk loci that basically elevate serum uric acid level. Conclusions This meta-analysis is the first to reveal the loci associated with crystal-induced inflammation, the last step in gout development that aggravates AHUA into gout. Our findings should help to elucidate the molecular mechanisms of gout development and assist the prevention of gout attacks in high-risk AHUA individuals

Subtype-specific gout susceptibility loci and enrichment of selection pressure on ABCG2 and ALDH2 identified by subtype genome-wide meta-analyses of clinically defined gout patients

Objectives Genome-wide meta-analyses of clinically defined gout were performed to identify subtype-specific susceptibility loci. Evaluation using selection pressure analysis with these loci was also conducted to investigate genetic risks characteristic of the Japanese population over the last 2000–3000 years. Methods Two genome-wide association studies (GWASs) of 3053 clinically defined gout cases and 4554 controls from Japanese males were performed using the Japonica Array and Illumina Array platforms. About 7.2 million single-nucleotide polymorphisms were meta-analysed after imputation. Patients were then divided into four clinical subtypes (the renal underexcretion type, renal overload type, combined type and normal type), and meta-analyses were conducted in the same manner. Selection pressure analyses using singleton density score were also performed on each subtype. Results In addition to the eight loci we reported previously, two novel loci, PIBF1 and ACSM2B, were identified at a genome-wide significance level (p<5.0×10–8) from a GWAS meta-analysis of all gout patients, and other two novel intergenic loci, CD2-PTGFRN and SLC28A3-NTRK2, from normal type gout patients. Subtype-dependent patterns of Manhattan plots were observed with subtype GWASs of gout patients, indicating that these subtype-specific loci suggest differences in pathophysiology along patients’ gout subtypes. Selection pressure analysis revealed significant enrichment of selection pressure on ABCG2 in addition to ALDH2 loci for all subtypes except for normal type gout. Conclusions Our findings on subtype GWAS meta-analyses and selection pressure analysis of gout will assist elucidation of the subtype-dependent molecular targets and evolutionary involvement among genotype, phenotype and subtype-specific tailor-made medicine/prevention of gout and hyperuricaemia