The development and evaluation of dose-prediction tools for allopurinol therapy (Easy-Allo tools).

AIMS: Dose escalation at the initiation of allopurinol therapy can be protracted and resource intensive. Tools to predict the allopurinol doses required to achieve target serum urate concentrations would facilitate the implementation of more efficient dose-escalation strategies. The aim of this research was to develop and externally evaluate allopurinol dosing tools, one for use when the pre-urate-lowering therapy serum urate is known (Easy-Allo1) and one for when it is not known (Easy-Allo2). METHODS: A revised population pharmacokinetic-pharmacodynamic model was developed using data from 653 people with gout. Maintenance doses to achieve the serum urate target of <0.36 mmol L-1 in >80% of individuals were simulated and evaluated against external data. The predicted and observed allopurinol doses were compared using the mean prediction error (MPE) and root mean square error (RMSE). The proportion of Easy-Allo predicted doses within 100 mg of the observed was quantified. RESULTS: Allopurinol doses were predicted by total body weight, baseline urate, ethnicity and creatinine clearance. Easy-Allo1 produced unbiased and suitably precise dose predictions (MPE 2 mg day-1 95% confidence interval [CI] -13-17, RMSE 91%, 90% within 100 mg of the observed dose). Easy-Allo2 was positively biased by about 70 mg day-1 and slightly less precise (MPE 70 mg day-1 95% CI 52-88, RMSE 131%, 71% within 100 mg of the observed dose). CONCLUSIONS: The Easy-Allo tools provide a guide to the allopurinol maintenance dose requirement to achieve the serum urate target of <0.36 mmol L-1 and will aid in the development of novel dose-escalation strategies for allopurinol therapy.

The impact of genetic variability in urate transporters on oxypurinol pharmacokinetics.

The genetic determinants of the allopurinol dose-concentration relationship have not been extensively studied. We aimed to clarify what factors, including genetic variation in urate transporters, influence oxypurinol pharmacokinetics (PKs). A population PK model for oxypurinol was developed with NONMEM (version 7.3). The influence of urate transporter genetic variants for ABCG2 (rs2231142 and rs10011796), SLC2A9/GLUT9 (rs11942223), SLC17A1/NPT1 (rs1183201), SLC22A12/URAT1 (rs3825018), SLC22A11/OAT4 (rs17300741), and ABCC4/MRP4 (rs4148500), as well as other participant factors on oxypurinol PKs was assessed. Data from 325 people with gout were available. The presence of the T allele for ABCG2 (rs2231142) and SLC17A1/NPT1 (rs1183201) was associated with a 24% and 22% increase in oxypurinol clearance, respectively, in univariate analysis. This effect was not significant in the multivariate analysis. In the final model, oxypurinol PKs were predicted by creatinine clearance, diuretic use, ethnicity, and body weight. We have found that genetic variability in the transporters examined does not appear to influence oxypurinol PKs.

An allopurinol adherence tool using plasma oxypurinol concentrations.

AIMS: This study aimed to develop and evaluate an allopurinol adherence tool based on steady-state oxypurinol plasma concentrations, allopurinol's active metabolite. METHODS: Plasma oxypurinol concentrations were simulated stochastically from an oxypurinol pharmacokinetic model for allopurinol doses of 100-800 mg daily, accounting for differences in renal function, diuretic use and ethnicity. For each scenario, the 20th percentile for peak and trough concentrations defined the adherence threshold, below which imperfect adherence was assumed. Predictive performance was evaluated using both simulated low adherence and against data from 146 individuals with paired oxypurinol plasma concentrations and adherence measures. Sensitivity and specificity (S&S), negative and positive predictive values (NPV, PPV) and receiver operating characteristic (ROC) area under the curve (AUC) were determined. The predictive performance of the tool was evaluated using adherence data from an external study (CKD-FIX). RESULTS: The allopurinol adherence tool produced S&S values for trough thresholds of 89-98% and 76-84%, respectively, and 90%-98% and 76-83% for peak thresholds. PPV and NPV were 79-84% and 88-94%, respectively, for trough and 80-85% and 89-98%, respectively, for peak concentrations. The ROC AUC values ranged from 0.84 to 0.88 and from 0.86 to 0.89 for trough and peak concentrations, respectively. S&S values for the external evaluation were found to be 75.8% and 86.5%, respectively, producing an ROC AUC of 0.8113. CONCLUSION: A tool to identify people with gout who require additional support to maintain adherence using plasma oxypurinol concentrations was developed and evaluated. The predictive performance of the tool is suitable for adherence screening in clinical trials and may have utility in some clinical practice settings.

A Polynesian-specific copy number variant encompassing the MICA gene associates with gout.

Gout is of particularly high prevalence in the Maori and Pacific (Polynesian) populations of Aotearoa New Zealand (NZ). Here, we investigated the contribution of common population-specific copy number variation (CNV) to gout in the Aotearoa NZ Polynesian population. Microarray-generated genome-wide genotype data from Aotearoa NZ Polynesian individuals with (n = 1196) and without (n = 1249) gout were analyzed. Comparator population groups were 552 individuals of European ancestry and 1962 of Han Chinese ancestry. Levels of circulating major histocompatibility complex (MHC) class I polypeptide-related sequence A (MICA) were measured by enzyme-linked immunosorbent assay. Fifty-four CNV regions (CNVRs) appearing in at least 10 individuals were detected, of which seven common (>2%) CNVRs were specific to or amplified in Polynesian people. A burden test of these seven revealed associations of insertion/deletion with gout (odds ratio (OR) 95% confidence interval [CI] = 1.80 [1.01; 3.22], P = 0.046). Individually testing of the seven CNVRs for association with gout revealed nominal association of CNVR1 with gout in Western Polynesian (Chr6: 31.36-31.45 Mb, OR = 1.72 [1.03; 2.92], P = 0.04), CNVR6 in the meta-analyzed Polynesian sample sets (Chr1: 196.75-196.92 Mb, OR = 1.86 [1.16; 3.00], P = 0.01) and CNVR9 in Western Polynesian (Chr1: 189.35-189.54 Mb, OR = 2.75 [1.15; 7.13], P = 0.03). Analysis of European gout genetic association data demonstrated a signal of association at the CNVR1 locus that was an expression quantitative trait locus for MICA. The most common CNVR (CNVR1) includes deletion of the MICA gene, encoding an immunomodulatory protein. Expression of MICA was reduced in the serum of individuals with the deletion. In summary, we provide evidence for the association of CNVR1 containing MICA with gout in Polynesian people, implicating class I MHC-mediated antigen presentation in gout.

Trans-ancestral dissection of urate- and gout-associated major loci SLC2A9 and ABCG2 reveals primate-specific regulatory effects.

Gout is a complex inflammatory arthritis affecting ~20% of people with an elevated serum urate level (hyperuricemia). Gout and hyperuricemia are essentially specific to humans and other higher primates, with varied prevalence across ancestral groups. SLC2A9 and ABCG2 are major loci associated with both urate and gout in multiple ancestral groups. However, fine mapping has been challenging due to extensive linkage disequilibrium underlying the associated regions. We used trans-ancestral fine mapping integrated with primate-specific genomic information to address this challenge. Trans-ancestral meta-analyses of GWAS cohorts of either European (EUR) or East Asian (EAS) ancestry resulted in single-variant resolution mappings for SLC2A9 (rs3775948 for urate and rs4697701 for gout) and ABCG2 (rs2622621 for gout). Tests of colocalization of variants in both urate and gout suggested existence of a shared candidate causal variant for SLC2A9 only in EUR and for ABCG2 only in EAS. The fine-mapped gout variant rs4697701 was within an ancient enhancer, whereas rs2622621 was within a primate-specific transposable element, both supported by functional evidence from the Roadmap Epigenomics project in human primary tissues relevant to urate and gout. Additional primate-specific elements were found near both loci and those adjacent to SLC2A9 overlapped with known statistical epistatic interactions associated with urate as well as multiple super-enhancers identified in urate-relevant tissues. We conclude that by leveraging ancestral differences trans-ancestral fine mapping has identified ancestral and functional variants for SLC2A9 or ABCG2 with primate-specific regulatory effects on urate and gout.

The ABCG2 Q141K hyperuricemia and gout associated variant illuminates the physiology of human urate excretion.

The pathophysiological nature of the common ABCG2 gout and hyperuricemia associated variant Q141K (rs2231142) remains undefined. Here, we use a human interventional cohort study (ACTRN12615001302549) to understand the physiological role of ABCG2 and find that participants with the Q141K ABCG2 variant display elevated serum urate, unaltered FEUA, and significant evidence of reduced extra-renal urate excretion. We explore mechanisms by generating a mouse model of the orthologous Q140K Abcg2 variant and find male mice have significant hyperuricemia and metabolic alterations, but only subtle alterations of renal urate excretion and ABCG2 abundance. By contrast, these mice display a severe defect in ABCG2 abundance and function in the intestinal tract. These results suggest a tissue specific pathobiology of the Q141K variant, support an important role for ABCG2 in urate excretion in both the human kidney and intestinal tract, and provide insight into the importance of intestinal urate excretion for serum urate homeostasis.

Pleiotropic effect of the ABCG2 gene in gout: involvement in serum urate levels and progression from hyperuricemia to gout.

BACKGROUND: The ABCG2 Q141K (rs2231142) and rs10011796 variants associate with hyperuricaemia (HU). The effect size of ABCG2 rs2231142 on urate is ~ 60% that of SLC2A9, yet the effect size on gout is greater. We tested the hypothesis that ABCG2 plays a role in the progression from HU to gout by testing for association of ABCG2 rs2231142 and rs10011796 with gout using HU controls. METHODS: We analysed 1699 European gout cases and 14,350 normouricemic (NU) and HU controls, and 912 New Zealand (NZ) Polynesian (divided into Eastern and Western Polynesian) gout cases and 696 controls. Association testing was performed using logistic and linear regression with multivariate adjusting for confounding variables. RESULTS: In Europeans and Polynesians, the ABCG2 141K (T) allele was associated with gout using HU controls (OR = 1.85, P = 3.8E- 21 and ORmeta = 1.85, P = 1.3E- 03, respectively). There was evidence for an effect of 141K in determining HU in European (OR = 1.56, P = 1.7E- 18) but not in Polynesian (ORmeta = 1.49, P = 0.057). For SLC2A9 rs11942223, the T allele associated with gout in the presence of HU in European (OR = 1.37, P = 4.7E- 06), however significantly weaker than ABCG2 rs2231142 141K (PHet = 0.0023). In Western Polynesian and European, there was epistatic interaction between ABCG2 rs2231142 and rs10011796. Combining the presence of the 141K allele with the rs10011796 CC-genotype increased gout risk, in the presence of HU, 21.5-fold in Western Polynesian (P = 0.009) and 2.6-fold in European (P = 9.9E- 06). The 141K allele of ABCG2 associated with increased gout flare frequency in Polynesian (Pmeta = 2.5E- 03). CONCLUSION: These data are consistent with a role for ABCG2 141K in gout in the presence of established HU.

Systematic genetic analysis of early-onset gout: ABCG2 is the only associated locus.

OBJECTIVE: The aim of this study was to examine whether serum urate-associated genetic variants are associated with early-onset gout. METHODS: Participants with gout in the Genetics of Gout in Aotearoa study with available genotyping were included (n = 1648). Early-onset gout was defined as the first presentation of gout <40 years of age. Single nucleotide polymorphisms (SNPs) for the 10 loci most strongly associated with serum urate were genotyped. Allelic association of the SNPs with early-onset gout was tested using logistic regression in an unadjusted model and in a model adjusted for sex, body mass index, tophus presence, flare frequency, serum creatinine and highest serum urate. The analysis was also done in two replication cohorts: Eurogout (n = 704) and Ardea (n = 755), and data were meta-analysed. RESULTS: In the Genetics of Gout in Aotearoa study, there were 638 (42.4%) participants with early-onset gout. The ABCG2 rs2231142 gout risk T-allele was present more frequently in participants with early-onset gout compared with the later-onset group. For the other SNPs tested, no differences in risk allele number were observed. In the allelic association analysis, the ABCG2 rs2231142 T-allele was associated with early-onset gout in unadjusted and adjusted models. Analysis of the replication cohorts confirmed the association of early-onset gout with the ABCG2 rs2231142 T-allele, but not with other serum urate-associated SNPs. In the meta-analysis, the odds ratio (95% CI) for early-onset gout for the ABCG2 rs2231142 T-allele was 1.60 (1.41, 1.83). CONCLUSION: In contrast to other serum urate-raising variants, the ABCG2 rs2231142 T-allele is strongly associated with early-onset gout.

Differential DNA Methylation of Networked Signaling, Transcriptional, Innate and Adaptive Immunity, and Osteoclastogenesis Genes and Pathways in Gout.

OBJECTIVE: In gout, autoinflammatory responses to urate crystals promote acute arthritis flares, but the pathogeneses of tophi, chronic synovitis, and erosion are less well understood. Defining the pathways of epigenomic immunity training can reveal novel pathogenetic factors and biomarkers. The present study was undertaken to seminally probe differential DNA methylation patterns utilizing epigenome-wide analyses in patients with gout. METHODS: Peripheral blood mononuclear cells (PBMCs) were obtained from a San Diego cohort of patients with gout (n = 16) and individually matched healthy controls (n = 14). PBMC methylome data were processed with ChAMP package in R. ENCODE data and Taiji data analysis software were used to analyze transcription factor (TF)-gene networks. As an independent validation cohort, whole blood DNA samples from New Zealand Maori subjects (n = 13 patients with gout, n = 16 control subjects without gout) were analyzed. RESULTS: Differentially methylated loci clearly separated gout patients from controls, as determined by hierarchical clustering and principal components analyses. IL23R, which mediates granuloma formation and cell invasion, was identified as one of the multiple differentially methylated gout risk genes. Epigenome-wide analyses revealed differential methylome pathway enrichment for B and T cell receptor signaling, Th17 cell differentiation and interleukin-17 signaling, convergent longevity regulation, circadian entrainment, and AMP-activated protein kinase signaling, which are pathways that impact inflammation via insulin-like growth factor 1 receptor, phosphatidylinositol 3-kinase/Akt, NF-κB, mechanistic target of rapamycin signaling, and autophagy. The gout cohorts overlapped for 37 (52.9%) of the 70 TFs with hypomethylated sequence enrichment and for 30 (78.9%) of the 38 enriched KEGG pathways identified via TFs. Evidence of shared differentially methylated gout TF-gene networks, including the NF-κB activation-limiting TFs MEF2C and NFATC2, pointed to osteoclast differentiation as the most strongly weighted differentially methylated pathway that overlapped in both gout cohorts. CONCLUSION: These findings of differential DNA methylation of networked signaling, transcriptional, innate and adaptive immunity, and osteoclastogenesis genes and pathways suggest that they could serve as novel therapeutic targets in the management of flares, tophi, chronic synovitis, and bone erosion in patients with gout.

A non-coding genetic variant maximally associated with serum urate levels is functionally linked to HNF4A-dependent PDZK1 expression.

The precise molecular mechanisms by which urate-associated genetic variants affect urate levels are unknown. Here, we tested for functional linkage of the maximally associated genetic variant rs1967017 at the PDZK1 locus to elevated PDZK1 expression. We performed expression quantitative trait loci (eQTL) and likelihood analyses and gene expression assays. Zebrafish were used to evaluate tissue-specific gene expression. Luciferase assays in HEK293 and HepG2 cells measured the effect of rs1967017 on transcription amplitude. Probabilistic Annotation Integrator analysis revealed rs1967017 as most likely to be causal and rs1967017 was an eQTL for PDZK1 in the intestine. The region harboring rs1967017 was capable of directly driving green fluorescent protein expression in the kidney, liver and intestine of zebrafish embryos, consistent with a conserved ability to confer tissue-specific expression. Small interfering RNA depletion of HNF4A reduced endogenous PDZK1 expression in HepG2 cells. Luciferase assays showed that the T allele of rs1967017 gains enhancer activity relative to the urate-decreasing C allele, with T allele enhancer activity abrogated by HNF4A depletion. HNF4A physically binds the rs1967017 region, suggesting direct transcriptional regulation of PDZK1 by HNF4A. Computational prediction of increased motif strength, together with our functional assays, suggests that the urate-increasing T allele of rs1967017 strengthens a binding site for the transcription factor HNF4A. Our and other data predict that the urate-raising T allele of rs1967017 enhances HNF4A binding to the PDZK1 promoter, thereby increasing PDZK1 expression. As PDZK1 is a scaffold protein for many ion channel transporters, increased expression can be predicted to increase activity of urate transporters and alter excretion of urate.

The impact of diuretic use and ABCG2 genotype on the predictive performance of a published allopurinol dosing tool.

AIM: This research aims to evaluate the predictive performance of a published allopurinol dosing tool. METHODS: Allopurinol dose predictions were compared to the actual dose required to achieve serum urate (SU) <0.36 mmol l-1 using mean prediction error. The influence of patient factors on dose predictions was explored using multilinear regression. RESULTS: Allopurinol doses were overpredicted by the dosing tool; however, this was minimal in patients without diuretic therapy (MPE 63 mg day-1 , 95% CI 40-87) compared to those receiving diuretics (MPE 295 mg day-1 , 95% CI 260-330, P < 0.0001). ABCG2 genotype (rs2231142, G>T) had an important impact on the dose predictions (MPE 201, 107, 15 mg day-1 for GG, GT and TT, respectively, P < 0.0001). Diuretic use and ABCG2 genotype explained 53% of the variability in prediction error (R2  = 0.53, P = 0.0004). CONCLUSIONS: The dosing tool produced acceptable maintenance dose predictions for patients not taking diuretics. Inclusion of ABCG2 genotype and a revised adjustment for diuretics would further improve the performance of the dosing tool.

Population-specific association between ABCG2 variants and tophaceous disease in people with gout.

BACKGROUND: Tophi contribute to musculoskeletal disability, joint damage and poor health-related quality of life in people with gout. The aim of this study was to examine the role of SLC2A9 and ABCG2 variants in tophaceous disease in people with gout. METHODS: Participants (n = 1778) with gout fulfilling the 1977 American Rheumatism Association (ARA) classification criteria, who were recruited from primary and secondary care, attended a detailed study visit. The presence of palpable tophi was recorded. SLC2A9 rs11942223, ABCG2 rs2231142 and ABCG2 rs10011796 were genotyped. Data were analysed according to tophus status. RESULTS: Compared to participants without tophi, those with tophi were older, had longer disease duration and higher serum creatinine, and were more likely to be of Maori or Pacific (Polynesian) ancestry. SLC2A9 rs11942223 was not associated with tophi. However, the risk alleles for both ABCG2 single nucleotide polymorphisms (SNPs) were present more frequently in those with tophi (OR (95% CI) 1.24 (1.02-1.51) for rs2231142 and 1.33 (1.01-1.74) for rs10011796, p < 0.05 for both). The effect of rs2231142 was limited to participants of Maori or Pacific ancestry (OR 1.50 (1.14-1.99), p = 0.004), with a significant effect observed in those of Western Polynesian ancestry only (OR 1.71 (1.07-2.72), p = 0.017). The rs10011796 risk allele was strongly associated with tophi in the Western Polynesian group (OR 3.76 (1.61-8.77), p = 0.002), but not in the Eastern Polynesian group (OR 0.87 (0.52-1.46), p = 0.60) nor in the non-Polynesian group (OR 1.16 (0.81-1.66), p = 0.32). The ABCG2 associations persisted in the Western Polynesian group after adjusting for serum urate, creatinine, and disease duration, and when including both ABCG2 variants in the regression models. CONCLUSIONS: Variation in ABCG2 function may play a role in the development of tophaceous disease in some populations with high prevalence of severe gout.

Clinical and genetic features of diuretic-associated gout: a case-control study.

OBJECTIVE: Hyperuricaemia and gout are well-recognized complications of diuretic use. The aim of this study was to examine the clinical and genetic features of diuretic-associated gout. METHODS: Participants (n = 1365) fulfilling the 1977 ARA gout classification criteria, recruited from primary and secondary care, attended a study visit that included a detailed clinical assessment. Use of diuretic therapy was recorded during the study visit, and was confirmed by electronic dispensing data [n = 426 (31.2%) on diuretics]. Gout-associated single nucleotide polymorphisms were genotyped. Clinical and genetic features of diuretic-associated gout were analysed using a case-control study design (diuretics vs no diuretics). RESULTS: In the diuretic group there were more women, higher rates of comorbid conditions, higher BMI and lower estimated glomerular filtration rate compared with those not taking diuretics. Gout disease duration, frequency of gout flares and presence of tophi were similar in the two groups. Patients on diuretics had higher age of gout presentation and higher recorded serum urate. The ABCG2 rs2231142 risk allele was present less frequently in the diuretic group (36.1%) compared with those not on diuretics (47.6%, P = 1.2 × 10(-4)). The differences in ABCG2 were observed in both men and women with gout. CONCLUSION: Diuretic-associated gout represents a medically complex condition. Although age of gout onset is later and serum urate concentrations are higher in those on diuretics, other clinical features of gout are similar. The observed differences in the ABCG2 risk allele frequency suggest that some genetic factors play a less dominant role in diuretic-associated gout compared with primary gout.

Hyperuricaemia: contributions of urate transporter ABCG2 and the fractional renal clearance of urate.

OBJECTIVE: To investigate the contributions towards hyperuricaemia of known risk factors, focusing on fractional (renal) clearance of urate (FCU) and variation in the ATP-binding cassette transporter, sub-family G 2 (ABCG2) gene. METHODS: The contributions of age, sex, ancestry, Q141K genotype for ABCG2, FCU, sugar-sweetened beverage and alcohol consumption, metabolic syndrome disorders and measures of renal function to the risk of hyperuricaemia were evaluated by comparing hyperuricaemic (serum urate≥0.42 mmol/L, n=448) with normouricaemic (serum urate<0.42 mmol/L, n=344) participants using stepwise logistic regression. Model performance was evaluated using the area under the receiver operator characteristic curve (AUROC). RESULTS: ABCG2 genotype, FCU, male sex, body mass index, serum triglyceride concentrations, estimated glomerular filtration rate and consumption of alcohol were the best predictors of hyperuricaemia (AUROC 0.90, 81% accuracy). Homozygosity in the 141K variant for ABCG2 conferred an adjusted OR of 10.5 for hyperuricaemia (95% CI 2.4 to 46.2). For each 1% decrease of FCU, the adjusted OR increased by 51% (OR 1.51, 95% CI 1.37 to 1.66). There was no association between ABCG2 genotype and FCU (r=0.02, p=0.83). CONCLUSIONS: The ABCG2 141K variant and the FCU contribute strongly but independently to hyperuricaemia. These findings provide further evidence for a significant contribution of ABCG2 to extra-renal (gut) clearance of urate.

Gout Is a Chronic Inflammatory Disease in Which High Levels of Interleukin-8 (CXCL8), Myeloid-Related Protein 8/Myeloid-Related Protein 14 Complex, and an Altered Proteome Are Associated With Diabetes Mellitus and Cardiovascular Disease.

OBJECTIVE: The frequent association of gout with metabolic syndrome and cardiovascular disease (CVD) suggests that it has a systemic component. Our objective was to study whether circulating proinflammatory cytokines are associated with comorbidities in gout patients. METHODS: We studied 330 gout patients from 3 independent cohorts and compared them with 144 healthy individuals and 276 disease controls. We measured circulating levels of interleukin-8 (IL-8)/CXCL8, IL-1ß, IL-6, IL-10, IL-12, and tumor necrosis factor, after which we performed proteome-wide analysis in a selection of samples to identify proteins that were possibly prognostic for the development of comorbidities. Replication analysis was performed specifically for myeloid-related protein 8 (MRP-8)/MRP-14 complex. RESULTS: Compared to healthy controls and disease control patients, patients with gouty arthritis (n = 48) had significantly higher mean levels of CXCL8 (P < 0.001), while other cytokines were almost undetectable. Similarly, patients with intercritical gout showed high levels of CXCL8. CXCL8 was independently associated with diabetes mellitus in patients with intercritical gout (P < 0.0001). Proteome-wide analysis in gouty arthritis (n = 18) and intercritical gout (n = 39) revealed MRP-8 and MRP-14 as the proteins with the greatest differential expression between low and high levels of CXCL8 and also showed a positive correlation of MRP8/MRP14 complex with CXCL8 levels (R(2) = 0.49, P < 0.001). These findings were replicated in an independent cohort. The proteome of gout patients with high levels of CXCL8 was associated with diabetes mellitus (odds ratio 16.5 [95% confidence interval 2.8-96.6]) and CVD (odds ratio 3.9 [95% confidence interval 1.0-15.3]). CONCLUSION: Circulating levels of CXCL8 are increased during both the acute and intercritical phases of gout, and they coincide with a specific circulating proteome that is associated with risk of diabetes mellitus and CVD. Further research focused on the roles of CXCL8 and MRP8/MRP14 complex in patients with gout is warranted.

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.

Influence of the ABCG2 gout risk 141 K allele on urate metabolism during a fructose challenge.

INTRODUCTION: Both genetic variation in ATP-binding cassette sub-family G member 2 (ABCG2) and intake of fructose-containing beverages are major risk factors for hyperuricemia and gout. This study aimed to test the hypothesis that the ABCG2 gout risk allele 141 K promotes the hyperuricaemic response to fructose loading. METHODS: Healthy volunteers (n = 74) provided serum and urine samples immediately before and 30, 60, 120 and 180 minutes after ingesting a 64 g fructose solution. Data were analyzed based on the presence or absence of the ABCG2 141 K gout risk allele. RESULTS: The 141 K risk allele was present in 23 participants (31%). Overall, serum urate (SU) concentrations during the fructose load were similar in those with and without the 141 K allele (PSNP = 0.15). However, the 141 K allele was associated with a smaller increase in SU following fructose intake (PSNP <0.0001). Those with the 141 K allele also had a smaller increase in serum glucose following the fructose load (PSNP = 0.002). Higher fractional excretion of uric acid (FEUA) at baseline and throughout the fructose load was observed in those with the 141 K risk allele (PSNP <0.0001). However, the change in FEUA in response to fructose was not different in those with and without the 141 K risk allele (PSNP = 0.39). The 141 K allele effects on serum urate and glucose were more pronounced in Polynesian participants and in those with a body mass index ≥25 kg/m². CONCLUSIONS: In contrast to the predicted responses for a hyperuricemia/gout risk allele, the 141 K allele is associated with smaller increases in SU and higher FEUA following a fructose load. The results suggest that ABCG2 interacts with extra-renal metabolic pathways in a complex manner to regulate SU and gout risk. CLINICAL TRIALS REGISTRATION: The study was registered by the Australian Clinical Trials Registry (ACTRN12610001036000).

Association analysis of the SLC22A11 (organic anion transporter 4) and SLC22A12 (urate transporter 1) urate transporter locus with gout in New Zealand case-control sample sets reveals multiple ancestral-specific effects.

INTRODUCTION: There is inconsistent association between urate transporters SLC22A11 (organic anion transporter 4 (OAT4)) and SLC22A12 (urate transporter 1 (URAT1)) and risk of gout. New Zealand (NZ) Maori and Pacific Island people have higher serum urate and more severe gout than European people. The aim of this study was to test genetic variation across the SLC22A11/SLC22A12 locus for association with risk of gout in NZ sample sets. METHODS: A total of 12 single nucleotide polymorphism (SNP) variants in four haplotype blocks were genotyped using TaqMan® and Sequenom MassArray in 1003 gout cases and 1156 controls. All cases had gout according to the 1977 American Rheumatism Association criteria. Association analysis of single markers and haplotypes was performed using PLINK and Stata. RESULTS: A haplotype block 1 SNP (rs17299124) (upstream of SLC22A11) was associated with gout in less admixed Polynesian sample sets, but not European Caucasian (odds ratio; OR = 3.38, P = 6.1 × 10-4; OR = 0.91, P = 0.40, respectively) sample sets. A protective block 1 haplotype caused the rs17299124 association (OR = 0.28, P = 6.0 × 10-4). Within haplotype block 2 (SLC22A11) we could not replicate previous reports of association of rs2078267 with gout in European Caucasian (OR = 0.98, P = 0.82) sample sets, however this SNP was associated with gout in Polynesian (OR = 1.51, P = 0.022) sample sets. Within haplotype block 3 (including SLC22A12) analysis of haplotypes revealed a haplotype with trans-ancestral protective effects (OR = 0.80, P = 0.004), and a second haplotype conferring protection in less admixed Polynesian sample sets (OR = 0.63, P = 0.028) but risk in European Caucasian samples (OR = 1.33, P = 0.039). CONCLUSIONS: Our analysis provides evidence for multiple ancestral-specific effects across the SLC22A11/SLC22A12 locus that presumably influence the activity of OAT4 and URAT1 and risk of gout. Further fine mapping of the association signal is needed using trans-ancestral re-sequence data.

The renal urate transporter SLC17A1 locus: confirmation of association with gout.

INTRODUCTION: Two major gout-causing genes have been identified, the urate transport genes SLC2A9 and ABCG2. Variation within the SLC17A1 locus, which encodes sodium-dependent phosphate transporter 1, a renal transporter of uric acid, has also been associated with serum urate concentration. However, evidence for association with gout is equivocal. We investigated the association of the SLC17A1 locus with gout in New Zealand sample sets. METHODS: Five variants (rs1165196, rs1183201, rs9358890, rs3799344, rs12664474) were genotyped across a New Zealand sample set totaling 971 cases and 1,742 controls. Cases were ascertained according to American Rheumatism Association criteria. Two population groups were studied: Caucasian and Polynesian. RESULTS: At rs1183201 (SLC17A1), evidence for association with gout was observed in both the Caucasian (odds ratio (OR) = 0.67, P = 3.0 × 10-6) and Polynesian (OR = 0.74, P = 3.0 × 10-3) groups. Meta-analysis confirmed association of rs1183201 with gout at a genome-wide level of significance (OR = 0.70, P = 3.0 × 10-8). Haplotype analysis suggested the presence of a common protective haplotype. CONCLUSION: We confirm the SLC17A1 locus as the third associated with gout at a genome-wide level of significance.

A strong role for the ABCG2 gene in susceptibility to gout in New Zealand Pacific Island and Caucasian, but not Maori, case and control sample sets.

Genetic variation in ABCG2 (rs2231142, Q141K), encoding a uric acid transporter, is associated with gout in diverse populations. The aim of this study was to examine a role for ABCG2 in gout susceptibility in New Zealand Maori, Pacific Island and Caucasian samples. Patients (n = 185, 173 and 214, for Maori, Pacific Island and Caucasian, respectively) satisfied the American College of Rheumatology gout classification criteria. The comparison samples comprised 284, 129 and 562 individuals, respectively, without gout. rs2231142 was genotyped and stratification accounted for using genomic control markers. Association of the minor allele of rs2231142 with gout was observed in the Pacific Island samples (OR = 2.80, P(STRAT) < 0.001 after accounting for effects of population structure), but not in the Maori samples (OR = 1.08, P(STRAT)= 0.70), with heterogeneity in association evident between the Maori and Pacific Island datasets (P(HET) = 0.001). A similar dichotomy in association was observed when samples were stratified into Western (Tonga, Samoa, Niue, Tokelau) versus Eastern Polynesian (Maori, Cook Island) origin (OR = 2.59, P(STRAT) < 0.001; OR = 1.12, P(STRAT)= 0.48, respectively; P(HET) = 0.005). Association with gout was observed in the Caucasian samples (OR = 2.20, P = 3.2 × 10(-8)). Unlike SLC2A9, which is a strong risk factor for gout in both Maori and Pacific Island people, ABCG2 rs2231142 has a strong effect only in people of Western Polynesian ancestry. Our results emphasize the need to account for sub-population differences when undertaking biomedical genetic research in a group defined by a geographical region and shared ancestry but characterized by migratory events that create bottlenecks and altered genetic structure in the founder populations.