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Item does not contain fulltext OBJECTIVE: To determine whether a gout polygenic risk score (PRS) is associated with age at gout onset and tophaceous disease in European, East Polynesian, and West Polynesian men and women with gout. METHODS: A 19-variant gout PRS was produced in 7 European gout cohorts (N = 4,016), 2 East Polynesian gout cohorts (N = 682), and 1 West Polynesian gout cohort (N = 490). Sex-stratified regression models were used to estimate the relationship between the PRS and age at gout onset and tophaceous disease. RESULTS: The PRS was associated with earlier age at gout onset in men (β = -3.61 in years per unit PRS [95% confidence interval (95% CI) -4.32, -2.90] in European men; β = -6.35 [95% CI -8.91, -3.80] in East Polynesian men; β = -3.51 [95% CI -5.46, -1.57] in West Polynesian men) but not in women (β = 0.07 [95% CI -2.32, 2.45] in European women; β = 0.20 [95% CI -7.21, 7.62] in East Polynesian women; β -3.33 [95% CI -9.28, 2.62] in West Polynesian women). The PRS showed a positive association with tophaceous disease in men (odds ratio [OR] for the association 1.15 [95% CI 1.00, 1.31] in European men; OR 2.60 [95% CI 1.66, 4.06] in East Polynesian men; OR 1.53 [95% CI 1.07, 2.19] in West Polynesian men) but not in women (OR for the association 0.68 [95% CI 0.42, 1.10] in European women; OR 1.45 [95% CI 0.39, 5.36] in East Polynesian women). The PRS association with age at gout onset was robust to the removal of ABCG2 variants from the PRS in European and East Polynesian men (β = -2.42 [95% CI -3.37, -1.46] and β = -6.80 [95% CI -10.06, -3.55], respectively) but not in West Polynesian men (β = -1.79 [95% CI -4.74, 1.16]). CONCLUSION: Genetic risk variants for gout also harbor risk for earlier age at gout onset and tophaceous disease in European and Polynesian men. Our findings suggest that earlier gout onset involves the accumulation of gout risk alleles in men but perhaps not in women, and that this genetic risk is shared across multiple ancestral groups.

Gout is of particularly high prevalence in the Māori 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.

Gout is a form of arthritis, resulting from an inflammatory reaction to the deposition of monosodium urate (MSU) crystals in the synovial fluid of the joint space. It is characterised by periods of acute inflammation in the affected joint, or joints (known as gout flares), separated by asymptomatic periods. There seems to be substantial overlap between environmental triggers of gout flares and common environmental modifiers (diet, pharmaceuticals, and stress) of epigenetic markers (DNA methylation, histone modifications, and ncRNA). Very few studies have looked at whether environment is influencing gout through epigenetic mechanisms. The pathogenesis of gouty inflammation is well understood but understanding the variation of response to hyperuricaemia in terms of gout flare initiation is less well known. In this review, we will examine the potential of epigenomics in understanding how gout flares may occur, both in terms of development of hyperuricaemia and the inflammatory response. Looking at the epigenome and its intersection with lifestyle could help identify new targets and strategies for effective management of gout flares.

ObjectiveThe Māori and Pacific (Polynesian) population of Aotearoa New Zealand has a high prevalence of gout. Our aim was to identify potentially functional missense genetic variants in candidate inflammatory genes amplified in frequency that may underlie the increased prevalence of gout in Polynesian populations.MethodsA list of 712 inflammatory disease-related genes was generated. An in silico targeted exome set was extracted from whole genome sequencing data in people with gout of various ancestral groups (Polynesian, European, East Asian; n = 55, 780, 135, respectively) to identify Polynesian-amplified common missense variants (minor allele frequency > 0.05). Candidate functional variants were tested for association with gout by multivariable-adjusted regression analysis in 2528 individuals of Polynesian ancestry.ResultsWe identified 26 variants common in the Polynesian population and uncommon in the European and East Asian populations. Three of the 26 population-amplified variants were nominally associated with the risk of gout (rs1635712 [KIAA0319], ORmeta = 1.28, Pmeta = 0.03; rs16869924 [CLNK], ORmeta = 1.37, Pmeta = 0.002; rs2070025 [fibrinogen A alpha chain (FGA)], ORmeta = 1.34, Pmeta = 0.02). The CLNK variant, within the established SLC2A9 gout locus, was genetically independent of the association signal at SLC2A9.ConclusionWe provide nominal evidence for the existence of population-amplified genetic variants conferring risk of gout in Polynesian populations. Polymorphisms in CLNK have previously been associated with gout in other populations, supporting our evidence for the association of this gene with gout.

BackgroundThe Pacific-specific minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor (CREBRF), is associated with several cardiometabolic phenotypes in Polynesian peoples, but the variant’s function remains poorly understood. To broaden our understanding of this variant, we used joint multivariate and network analyses to examine the relationships between rs373863828 and a panel of correlated anthropometric and lipid phenotypes.MethodsWe tested the association of rs373863828 with a panel of phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) under a multivariate Bayesian association model in a cohort from Samoa (N = 1 632), a Māori and Pacific Island (Polynesian) cohort from Aotearoa New Zealand (N = 1 419), and the combined cohort (N = 2 976). An expanded set of phenotypes (adding estimated fat and fat-free mass, abdominal circumference, hip circumference, and abdominal-hip ratio) was also tested in the Samoa cohort (N = 1 496). Bayesian networks were learned to further understand the structure of the relationships.ResultsIn the Samoa cohort, significant associations (log10 Bayes factor ≥5.0) were found between rs373863828 and the overall phenotype panel (7.97), weight (8.35) and BMI (6.39). In the Aotearoa New Zealand cohort, suggestive associations (log10 Bayes factor between 1.5 and 5) were found between rs373863828 and the overall phenotype panel (3.64), weight (3.30), and BMI (1.79). In the combined cohort, concordant signals with stronger magnitudes were observed. In the expanded phenotype analyses among the Samoa cohort, significant associations were also observed between rs373863828 and fat mass (5.68), abdominal circumference (5.37), and hip circumference (5.15).Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI.ConclusionsWhen correlation structures were considered, multivariate Bayesian analyses provided additional evidence of rs373863828’s pleiotropic effects and highlighted a strong direct effect only on weight.

ObjectivesGenome-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.MethodsTwo 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.ResultsIn addition to the eight loci we reported previously, two novel loci, PIBF1 and ACSM2B, were identified at a genome-wide significance level (p–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.ConclusionsOur 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.

Sequencing ofCETPin Māori and Pacific peoples identified a common (MAF ∼2.4%-5.4%) population-specific missense variant (rs1597000001,CETP:c.530C>T p.Pro177Leu) that associates with higher HDL-C levels ([95% CI 0.211; 0.260]) and lower LDL-C ([95% CI -0.209; -0.058]). In a subsample of the study cohort (n = 11), heterozygous carriers of the population-specific variant had lower plasma CETP activity (P= 0.028). Our study identifies a population-specific missense variant inCETPwhich lowers CETP activity with an effect on HDL-C that is comparable to MendelianCETPloss-of-function mutations.

Objectives: Some studies suggest that current-smoking may be protective against gout and smoking cessation associated with higher incidence of gout. Our study assessed potential interactions between smoking, genetic variants and gout prevalence. Methods: Four loci (ABCG2, GCKR, TRIM46, HNF4G) with evidence of smoking-influenced associations with serum urate were tested for non-additive interaction with current-smoker or ex-smoker status that associates with gout in Aotearoa New Zealand (NZ) East and West Polynesian participants with (n=520) and without (n=629) gout. Results: Ex-smoker status was associated with higher prevalence of gout in people with East Polynesian but not West Polynesian ancestry. No association was detected between current smoking and gout. An interaction between TRIM46 (rs11264341) and ex-smoker status that associates with gout was observed in meta-analysis of NZ East and West Polynesians [ORInteraction= 0.58 (0.37-0.92)]. Never-smokers who were homozygous for the rs11264341 C-allele had higher odds of gout [OR= 2.43 (1.27; 4.64)], but not never-smoker heterozygotes [1.20 (0.73; 1.97]. The C allele was not associated with gout in ex-smokers [0.73 (0.36-1.47)]. No interactions involving current-smoker status were detected.Conclusions: We provide evidence for a non-additive interaction between TRIM46 (rs11264341) and ex-smoker status that associated with gout prevalence. MUC1, which encodes a transmembrane mucin in the lungs affected by cigarette smoke, is a possible candidate gene at this locus. No interaction involving current-smoker status was observed raising uncertainties about the relevance of an interaction specific to ex-smokers.

Background Prevention of hyperuricaemia (HU) is critical to the prevention of gout. Understanding causal relationships and relative contributions of various risk factors to hyperuricemia is therefore important in the prevention of gout. Here, we use attributable fraction to compare the relative contribution of genetic, dietary, urate-lowering therapy (ULT) and other exposures to HU. We use Mendelian randomisation to test for the causality of diet in urate levels. Methods Four European-ancestry sample sets, three from the general population (n = 419,060) and one of people with gout (n = 6781) were derived from the Database of Genotypes and Phenotypes (ARIC, FHS, CARDIA, CHS) and UK Biobank. Dichotomised exposures to diet, genetic risk variants, BMI, alcohol, diuretic treatment, sex and age were used to calculate adjusted population and average attributable fractions (PAF/AAF) for HU (≥0.42 mmol/L [≥7 mg/dL]). Exposure to ULT was also assessed in the gout cohort. Two sample Mendelian randomisation was done in the UK Biobank using dietary pattern-associated genetic variants as exposure and serum urate levels as outcome. Results Adherence to dietary recommendations, BMI (2), and absence of the SLC2A9 rs12498742 urate-raising allele produced PAFs for HU of 20 to 24%, 59 to 69%, and 57 to 64%, respectively, in the three non-gout cohorts. In the gout cohort, diet, BMI, SLC2A9 rs12498742 and ULT PAFs for HU were 12%, 49%, 48%, and 63%, respectively. Mendelian randomisation demonstrated weak causal effects of four dietary habits on serum urate levels (e.g. preferentially drinking skim milk increased urate, β = 0.047 mmol/L, P = 3.78 × 10−8). These effects were mediated by BMI, and they were not significant (P ≥ 0.06) in multivariable models assessing the BMI-independent effect of diet on urate. Conclusions Diet has a relatively minor role in determining serum urate levels and HU. In gout, the use of ULT was the largest attributable fraction tested for HU.

ObjectiveThe minor allele of rs373863828 in CREBRF is associated with higher BMI, lower fasting glucose, and lower odds of type 2 diabetes. We examined the associations between BMI and rs373863828 on type 2 diabetes and fasting glucose with a large sample of adult Polynesians from Samoa, American Samoa and Aotearoa New Zealand and estimated direct and indirect (via BMI) effects of rs373863828 on type 2 diabetes and fasting glucose.Research Design and MethodsWe regressed type 2 diabetes and fasting glucose on BMI and rs373863828 stratified by obesity, regressed type 2 diabetes and fasting glucose on BMI stratified by rs373863828 genotype, and assessed the effects of rs373863828 on type 2 diabetes and fasting glucose with path analysis.ResultsAssociation of BMI with fasting glucose was greater in those without obesity than in those with obesity. We did not observe evidence of differences by genotype. In the path analysis, the minor allele has direct negative and indirect positive effects on type 2 diabetes risk and fasting glucose, with the indirect effect mediated through a direct positive effect on BMI.ConclusionsThere may be a stronger effect of BMI on fasting glucose in Polynesians without obesity than in those with obesity. Carrying the rs373863828 minor allele does not decouple higher BMI from odds of type 2 diabetes. Given the current cost of genotyping compared to the accessibility of measuring BMI, including rs373863828 as a clinical predictor of type 2 diabetes may not be indicated.

Background: Epidemiological and prospective studies suggest that current-smoking may be protective against developing gout and that smoking cessation may increase risk. The aim of this study was to identify interactions between smoking, genetic risk variants and the risk of gout. Methods: A cohort of 520 New Zealand (NZ) East and West Polynesian participants with and 629 without gout were included in our discovery analysis. A cohort of European participants (7576 with and 364,445 without) and South Asian participants (156 with and 7504 without gout) of the UK Biobank were used for replication. Five loci with previous evidence of smoking-influenced associations with serum urate levels were tested for their interaction with smoking status (current-smoker or ex-smoker vs. never-smoker as the reference group) in determining gout risk. The 5 loci were in genes, SLC2A9, ABCG2, GCKR, TRIM46, and HNF4G.Results: A non-additive interaction between genotype and smoking on gout risk was observed between ex-smoker status and TRIM46 (rs11264341) in NZ East and West Polynesian people [interaction ORmeta = 0.58 (0.37-0.92), p = 0.021], but not in European (OR = 0.94 (0.88-1.01), p = 0.10) or South Asian (0.96 (0.55-1.66), p = 0.88) participants of the UK Biobank. TRIM46 (rs11264341) interacted with current-smoker status in the Asian UK Biobank cohort [interaction OR = 2.68 (1.26-5.68), p = 0.010]. In smoking status subgroups the C-allele of rs11264341 increased risk of gout specifically in never-smokers (OR= 1.41 (1.04-1.92), p = 0.029) of the NZ Polynesian sample set and in current-smokers (2.39 (1.13-5.05), p=0.022) of the South Asian sample set. There was no evidence of interaction between smoking-status and the 4 remaining loci in 2 or more of the ancestral populations analysed in this study.Conclusion: We provide evidence for a non-additive interaction between TRIM46 (rs11264341) and smoking behaviour associated with gout risk in a NZ Polynesian sample set and a South Asian sample set, but not in a European sample set. MUC1, that encodes a transmembrane mucin in the lungs whose expression and function is affected by cigarette smoke, is a possible candidate gene at the TRIM46 locus.

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.

IntroductionThe minor allele of a missense variant, rs373863828, in CREBRF is associated with higher body mass index (BMI), lower fasting glucose, and lower odds of type 2 diabetes. rs373863828 is common in Pacific Island populations (minor allele frequency (MAF) 0.096–0.259) but rare in non-Pacific Island populations (MAF Research design and methodsWe regressed type 2 diabetes and fasting glucose on BMI and rs373863828 stratified by obesity, regressed type 2 diabetes and fasting glucose on BMI stratified by rs373863828 genotype, and assessed the effects of rs373863828 on type 2 diabetes and fasting glucose with path analysis. The regression analyses were completed separately in four samples that were recruited during different time periods between 1990 and 2010 and then the results were meta-analyzed. All samples were pooled for the path analysis.ResultsAssociation of BMI with type 2 diabetes and fasting glucose may be greater in those without obesity (OR=7.77, p=0.015 and β=0.213, p=9.53×10−5, respectively) than in those with obesity (OR=5.01, p=1.12×10−9 and β=0.162, p=5.63×10−6, respectively). We did not observe evidence of differences in the association of BMI with type 2 diabetes or fasting glucose by genotype. In the path analysis, the minor allele has direct negative (lower odds of type 2 diabetes and fasting glucose) and indirect positive (higher odds of type 2 diabetes and fasting glucose) effects on type 2 diabetes risk and fasting glucose, with the indirect effects mediated through a direct positive effect of rs373863828 on BMI.ConclusionsThere may be a stronger effect of BMI on fasting glucose in Polynesian individuals without obesity than in those with obesity. Carrying the rs373863828 minor allele does not decouple higher BMI from higher odds of type 2 diabetes.

Subjects with hypertension are frequently obese or insulin resistant, both conditions in which hyperuricemia is common. Obese and insulin-resistant subjects are also known to have blood pressure that is more sensitive to changes in dietary sodium intake. Whether hyperuricemia is a resulting consequence, moderating or contributing factor to the development of hypertension has not been fully evaluated and very few studies have reported interactions between sodium intake and serum uric acid. We performed further analysis of our randomized controlled clinical trials (Australian New Zealand Clinical Trials Registry #12609000161224 and #12609000292279) designed to assess the effects of modifying sodium intake on concentrations of serum markers, including uric acid. Uric acid and other variables (including blood pressure, renin, and aldosterone) were measured at baseline and 4 weeks following the commencement of low (60 mmol/day), moderate (150 mmol/day), and high (200-250 mmol/day) dietary sodium intake. The median aldosterone-to-renin ratio was 1.90 [pg/ml]/[pg/ml] (range 0.10-11.04). Serum uric acid fell significantly in both the moderate and high interventions compared to the low sodium intervention. This pattern of response occurred when all subjects were analyzed, and when normotensive or hypertensive subjects were analyzed alone. Although previously reported in hypertensive subjects, these data provide evidence in normotensive subjects of an interaction between dietary sodium intake and serum uric acid. As this interaction is present in the absence of hypertension, it is possible it could play a role in hypertension development, and will need to be considered in future trials of dietary sodium intake. The trials were registered with the Australian and New Zealand Clinical Trials Registry as ACTRN12609000161224 and ACTRN1260.

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.

BackgroundThe ABCG2 Q141K (rs2231142) andrs10011796variants associate with hyperuricaemia (HU). The effect size ofABCG2 rs2231142on urate is ∼60% that ofSLC2A9, 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 ofABCG2 rs2231142andrs10011796with gout using HU controls.MethodsWe analysed 1,699 European gout cases and 14,350 normourciemic (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.ResultsIn Europeans and Polynesians, theABCG2141K (T) allele was associated with gout using HU controls (OR=1.85,P=3.8E-21and 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). ForSLC2A9 rs11942223, the T allele associated with gout in the presence of HU in European (OR=1.37,P=4.7E-06), however significantly weaker thanABCG2 rs2231142141K (PHet=0.0023). In Western Polynesian and European, there was epistatic interaction betweenABCG2 rs2231142and the genetically-independentrs10011796. Combining the presence of the 141K allele with thers10011796CC-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 positively associated with flare frequency in Polynesian (Pmeta=2.5E-03).ConclusionThese data are consistent with a role forABCG2141K in gout in the presence of established HU.

Serum urate is the end-product of purine metabolism. Elevated serum urate is causal of gout and a predictor of renal disease, cardiovascular disease and other metabolic conditions. Genome-wide association studies (GWAS) have reported dozens of loci associated with serum urate control, however there has been little progress in understanding the molecular basis of the associated loci. Here we employed trans-ancestral meta-analysis using data from European and East Asian populations to identify ten new loci for serum urate levels. Genome-wide colocalization withcis-expression quantitative trait loci (eQTL) identified a further five new loci. Bycis-andtrans-eQTL colocalization analysis we identified 24 and 20 genes respectively where the causal eQTL variant has a high likelihood that it is shared with the serum urate-associated locus. One new locus identified wasSLC22A9that encodes organic anion transporter 7 (OAT7). We demonstrate that OAT7 is a very weak urate-butyrate exchanger. Newly implicated genes identified in the eQTL analysis include those encoding proteins that make up the dystrophin complex, a scaffold for signaling proteins and transporters at the cell membrane;MLXIPthat, with the previously identifiedMLXIPL, is a transcription factor that may regulate serum urate via the pentose-phosphate pathway; andMRPS7andIDH2that encode proteins necessary for mitochondrial function. Trans-ancestral functional fine-mapping identified six loci (RREB1, INHBC, HLF, UBE2Q2, SFMBT1, HNF4G) with colocalized eQTL that contained putative causal SNPs (posterior probability of causality > 0.8). This systematic analysis of serum urate GWAS loci has identified candidate causal genes at 19 loci and a network of previously unidentified genes likely involved in control of serum urate levels, further illuminating the molecular mechanisms of urate control.Author SummaryHigh serum urate is a prerequisite for gout and a risk factor for metabolic disease. Previous GWAS have identified numerous loci that are associated with serum urate control, however, only a small handful of these loci have known molecular consequences. The majority of loci are within the non-coding regions of the genome and therefore it is difficult to ascertain how these variants might influence serum urate levels without tangible links to gene expression and / or protein function. We have applied a novel bioinformatic pipeline where we combined population-specific GWAS data with gene expression and genome connectivity information to identify putative causal genes for serum urate associated loci. Overall, we identified 15 novel serum urate loci and show that these loci along with previously identified loci are linked to the expression of 44 genes. We show that some of the variants within these loci have strong predicted regulatory function which can be further tested in functional analyses. This study expands on previous GWAS by identifying further loci implicated in serum urate control and new causal mechanisms supported by gene expression changes.

Objective To systematically test dietary components for association with serum urate levels and to evaluate the relative contributions of estimates of diet pattern and inherited genetic variants to population variance in serum urate levels. Design Meta-analysis of cross sectional data from the United States. Data sources Five cohort studies. Review methods 16 760 individuals of European ancestry (8414 men and 8346 women) from the US were included in analyses. Eligible individuals were aged over 18, without kidney disease or gout, and not taking urate lowering or diuretic drugs. All participants had serum urate measurements, dietary survey data, information on potential confounders (sex, age, body mass index, average daily calorie intake, years of education, exercise levels, smoking status, and menopausal status), and genome wide genotypes. The main outcome measures were average serum urate levels and variance in serum urate levels. β values (95% confidence intervals) and Bonferroni corrected P values from multivariable linear regression analyses, along with regression partial R 2 values, were used to quantitate associations. Results Seven foods were associated with raised serum urate levels (beer, liquor, wine, potato, poultry, soft drinks, and meat (beef, pork, or lamb)) and eight foods were associated with reduced serum urate levels (eggs, peanuts, cold cereal, skim milk, cheese, brown bread, margarine, and non-citrus fruits) in the male, female, or full cohorts. Three diet scores, constructed on the basis of healthy diet guidelines, were inversely associated with serum urate levels and a fourth, data driven diet pattern positively associated with raised serum urate levels, but each explained ≤0.3% of variance in serum urate. In comparison, 23.9% of variance in serum urate levels was explained by common, genome wide single nucleotide variation. Conclusion In contrast with genetic contributions, diet explains very little variation in serum urate levels in the general population.

Background Increased coffee intake is associated with reduced serum urate concentrations and lower risk of gout. Specific alleles of the GCKR, ABCG2, MLXIPL, and CYP1A2 genes have been associated with both reduced coffee intake and increased serum urate in separate genome-wide association studies (GWAS). The aim of this study was to determine whether these single nucleotide polymorphisms (SNPs) influence the risk of gout through their effects on coffee consumption. Methods This research was conducted using the UK Biobank Resource. Data were available for 130,966 European participants aged 40–69 years. Gout status and coffee intake were tested for association with four urate-associated SNPs: GCKR (rs1260326), ABCG2 (rs2231142), MLXIPL (rs1178977), and CYP1A2 (rs2472297). Multiple regression and path analysis were used to examine whether coffee consumption mediated the effect of the SNPs on gout risk. Results Coffee consumption was inversely associated with gout (multivariate adjusted odds ratio (95% confidence interval (CI)) for any coffee consumption 0.75 (0.67–0.84, P = 9 × 10−7)). There was also evidence of a dose-effect with multivariate adjusted odds ratio (95% CI) per cup consumed per day of 0.85 (0.82–0.87, P = 9 × 10−32). The urate-increasing GCKR, ABCG2, MLXIPL, and CYP1A2 alleles were associated with reduced daily coffee consumption, with the strongest associations for CYP1A2 (beta −0.30, P = 8 × 10−40), and MLXIPL (beta −0.17, P = 3 × 10−8), and weaker associations for GCKR (beta −0.07, P = 3 × 10−10) and ABCG2 (beta −0.09, P = 2 × 10−9). The urate-increasing GCKR and ABCG2 alleles were associated with gout (multivariate adjusted p

A central aspect of the pathogenesis of gout is elevated urate concentrations, which lead to the formation of monosodium urate crystals. The clinical features of gout result from an individual's immune response to these deposited crystals. Genome-wide association studies (GWAS) have confirmed the importance of urate excretion in the control of serum urate levels and the risk of gout and have identified the kidneys, the gut and the liver as sites of urate regulation. The genetic contribution to the progression from hyperuricaemia to gout remains relatively poorly understood, although genes encoding proteins that are involved in the NLRP3 (NOD-, LRR- and pyrin domain-containing 3) inflammasome pathway play a part. Genome-wide and targeted sequencing is beginning to identify uncommon population-specific variants that are associated with urate levels and gout. Mendelian randomization studies using urate-associated genetic variants as unconfounded surrogates for lifelong urate exposure have not supported claims that urate is causal for metabolic conditions that are comorbidities of hyperuricaemia and gout. Genetic studies have also identified genetic variants that predict responsiveness to therapies (for example, urate-lowering drugs) for treatment of hyperuricaemia. Future research should focus on large GWAS (that include asymptomatic hyperuricaemic individuals) and on increasing the use of whole-genome sequencing data to identify uncommon genetic variants with increased penetrance that might provide opportunities for clinical translation.

The A (minor) allele of CREBRF rs373863828 has been associated with increased BMI and reduced risk of type 2 diabetes in the Samoan populations of Samoa and American Samoa. Our aim was to test rs373863828 for associations with BMI and the odds of type 2 diabetes, gout and chronic kidney disease (CKD) in Māori and Pacific (Polynesian) people living in Aotearoa/New Zealand. Linear and logistic regression models were used to analyse the association of the A allele of CREBRF rs373863828 with BMI, log-transformed BMI, waist circumference, type 2 diabetes, gout and CKD in 2286 adults. The primary analyses were adjusted for age, sex, the first four genome-wide principal components and (where appropriate) BMI, waist circumference and type 2 diabetes. The primary analysis was conducted in ancestrally defined groups and association effects were combined using meta-analysis. For the A allele of rs373863828, the effect size was 0.038 (95% CI 0.022, 0.055, p = 4.8 × 10−6) for log-transformed BMI, with OR 0.59 (95% CI 0.47, 0.73, p = 1.9 × 10−6) for type 2 diabetes. There was no evidence for an association of genotype with variance in BMI (p = 0.13), and nor was there evidence for associations with serum urate (β = 0.012 mmol/l, pcorrected = 0.10), gout (OR 1.00, p = 0.98) or CKD (OR 0.91, p = 0.59). Our results in New Zealand Polynesian adults replicate, with very similar effect sizes, the association of the A allele of rs373863828 with higher BMI but lower odds of type 2 diabetes among Samoan adults living in Samoa and American Samoa.

Aim/HypothesesThe minor allele of CREBRF rs373863828 associates with increased body mass index (BMI) and reduced risk of type 2 diabetes (T2D) in the Samoan population of Samoa and American Samoa. Our aim was to test rs373863828 for association with BMI and odds of T2D, gout and chronic kidney disease (CKD) in Māori and Pacific (Polynesian) people living in Aotearoa New Zealand in 2,286 adults.MethodsAssociation analyses were performed by linear and logistic regression with BMI, log-transformed BMI, waist circumference, T2D, gout and CKD. Analyses were adjusted for age, sex, the first four genome-wide principal components, and (when appropriate) BMI, waist circumference and T2D.ResultsFor the minor allele of rs373863828 the effect size for log-transformed BMI was 0.038 (95% CI [0.022-0.055], P=4.8x10−6) and for T2D was OR=0.59 (95% CI [0.47-0.73], P=1.9x10−6). There was no evidence for association of genotype with variance in BMI (P=0.13). Nor was there evidence for association with serum urate (β=0.012 mmol/L, Pc=0.10), gout (OR=1.00, P=0.98) or CKD (OR=0.91, P=0.59).Conclusions/interpretationOur results replicated, with very similar effect sizes, association of the minor allele of rs373863828 with higher BMI but lower odds of T2D among New Zealand Polynesian adults, as in Samoan adults living in Samoa and American Samoa.