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This review focuses on the post-genome-wide association study (GWAS) era in gout, i.e., the translation of GWAS genetic association signals into biologically informative knowledge. Analytical and experimental follow-up of individual loci, based on the identification of causal genetic variants, reveals molecular pathogenic pathways. We summarize in detail the largest GWAS in urate to date, then we review follow-up studies and molecular insights from ABCG2, HNF4A, PDZK1, MAF, GCKR, ALDH2, ALDH16A1, SLC22A12, SLC2A9, ABCC4, and SLC22A13, including the role of insulin signaling. One common factor in these pathways is the importance of transcriptional control, including the HNF4α transcription factor. The new molecular knowledge reveals new targets for intervention to manage urate levels and prevent gout.

BackgroundData on outcomes for people with gout and COVID-19 are extremely few. Our primary objective was to assess whether gout is a risk factor for diagnosis of COVID-19 and death related to COVID-19. The secondary objectives were to test for sex- and drug-specific differences in risk.MethodsWe used data from the UK Biobank that included 15,560 people with gout. Multivariable-adjusted logistic regression was employed in the following analyses using a case-control study design: Analysis A, to test for association between gout and COVID-19 diagnosis (n=459,837); Analysis B, to test for association between gout and death related to COVID-19 in a case-control cohort of people who died or survived with COVID-19 (n=16,336); Analysis C, to test for association between gout and death related to COVID-19 in the entire UK Biobank cohort (n=459,837); Analysis D, to stratify by prescription of urate-lowering therapy (ULT) and colchicine on the risk of death related to COVID-19 in a subset of the UK Biobank cohort with medication data (n=341,398).FindingsGout was associated with diagnosis of COVID-19 in analysis A (OR=1.2 [1.1 ; 1.3]) but not with risk of death in the COVID-19-diagnosed group in analysis B. In analysis C gout associated with risk of death related to COVID-19 in the unadjusted model (OR=3.9 [3.3 ; 4.7]), in Model 1 adjusted for demographic factors (OR=1.8 [1.5 ; 2.1]) and in the fully adjusted Model 2 (OR=1.3 [1.1 ; 1.6]). In Analysis C risk was higher in women than men in Model 1 adjusted for demographic factors (OR=3.5 [2.4 ; 5.0] and OR=1.5 [1.2 ; 1.8], respectively) with the difference maintained after additional adjustment for eight metabolic co-morbidities (ORMen=1.2 [0.9 ; 1.5], ORWomen=1.9 [1.3 ; 2.9]). There were no statistically significant differences in risk of death related to COVID-19 according to prescription of ULT or colchicine.InterpretationGout is a risk factor for death related to COVID-19 using the UK Biobank cohort with an increased risk in women with gout that was also driven by risk factors outside metabolic co-morbidities of gout.Research in contextEvidence before this studyThere are no studies investigating the risk of COVID-19 diagnosis and risk of death with COVID-19 in people with gout.Added value of this studyThe findings provide evidence that gout is a risk factor for diagnosis of COVID-19 and that gout is a risk factor for death with COVID-19, independent of included co-morbidities. Women with gout are at a higher risk of death with COVID-19 than men with gout.Implications of the available evidenceThe new evidence demonstrate that gout is a risk factor for death from COVID-19, particularly in women. This information will inform clinical decision-making in people with gout diagnosed with COVID-19. Future research should focus on replicating these findings, including a focus on understanding key factor(s) explaining the increased risk of death with COVID-19 in women with gout.

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 One-third of adults in the U.S. have metabolic syndrome, a combination of risk factors of chronic diseases such as heart disease, kidney disease, diabetes, and gout. These diseases are a burden for ethnic minorities, including Pacific Island peoples. Here, the metabolic conditions were described for a group of Pacific Island people, the CHamorus or natives of Guam, a U.S. Territory in the Mariana Islands in the Western Pacific. Methods A cross-sectional survey was conducted in Guam from August 2019 to January 2020. A non-random sample of 152 adults, ≥18 years old, with CHamoru ancestry were recruited and consented. Information collected included socio-demographics, metabolic history, lifestyle behaviors, height and weight, blood pressure, and non-fasting blood and urine. Statistical analyses included frequencies of metabolic conditions and Pearson’s Chi-square test for gender differences, alpha=0.05. Results Of the 152 CHamorus, 49.3% were male, 50% were female, and 0.7% was transgender. The mean age was 43±15.1 years. Mean education was 14.4±3.6 years and hyperuricemia he majority (69.7%) pursued postsecondary studies. Self-reported metabolic conditions included: diabetes (19.7%), gout (28.9%), hypertension (34.9%), dyslipidemia (17.8%), and heart conditions (9.9%). Compared to females, more males reported gout (40.5% versus 18.7%; P=.003) and measured to be hypertensive (48% versus 21.1%; P Conclusion Metabolic conditions were common among CHamorus, though gout, hypertension, hyperuricemia, and obesity were predominant in the men. Key messages Strategies to reduce the burden of metabolic conditions may be targeted to CHamoru men in this community.

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 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.

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The CREBRF missense variant (p.Arg457Gln) is paradoxically associated with lower risk of type 2 diabetes, yet higher body mass index (BMI). Here we sought to determine whether this CREBRF variant might be associated with adult height. Linear regression was used to analyse the association of the CREBRF minor (A) allele with height in 2286 Māori and Pacific adults living in Aotearoa/New Zealand. A potential type 2 diabetes index event was corrected to account for a bias that may be the cause of paradoxical association between the CREBRF diabetes-protective allele and higher BMI and height. The CREBRF protective allele was associated with increased adult height (s = 1.25 cm, P = 3.9 × 10−6), with the effect being more pronounced in males. The lower odds of diabetes remained similar when analyses were adjusted for height (OR = 0.67–0.65). We found no evidence of a diabetes index event bias to explain the paradoxical effect of CREBRF with either BMI or height and diabetes. The orthologous CREBRF p.Arg457Gln variant was created in knock-in mice to independently assess the effect of the variant, and length was found to be greater in male mice at 8 weeks of age. These data taken together indicate that CREBRF p.Arg457Gln is associated with taller stature in Māori and Pacific adults.

ObjectiveThe 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.MethodsWe 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).ResultsThis 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–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.ConclusionsThis 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.

The Great Lakes “Priority Watershed” effort targeted the Upper East River watershed, a 116.5-km2 tributary watershed to Wisconsin's Green Bay, to reduce its sediment and nutrients loads from agricultural sources. A Soil and Water Assessment Tool (SWAT) model was created to determine the effectiveness of agricultural Best Management Practices (BMPs) funded through the Great Lakes Restoration Initiative. The model was calibrated at the monthly time-step for flow, sediment, dissolved reactive phosphorus (DRP), total phosphorus (TP), nitrate, and total nitrogen (TN). Field- and watershed-scale sediment and nutrient reductions were calculated due to the implementation of 74 BMP combinations on dairy and cash grain rotations. Modeling results indicated that when multiple BMPs were placed on a field, especially those including filter strips and grassed waterways, sediment and nutrient loads generally were reduced more than single BMP implementation. The most effective in-field practice at reducing DRP and TP on dairy fields was a combination of 5 different BMPs: cover crops, crop rotation, nutrient management plan, reduced tillage, and a filter strip. Conservation cover was the single most effective practice at reducing sediment and nutrient yields. Sediment and nutrient loads decreased at the watershed scale as the quantity and coverage of BMPs increased. When all contracted BMPs were simulated at the watershed scale, sediment loads were reduced 2%, while TP, DRP, TN and nitrate loads were reduced 20%, 9%, 24%, and 17%, respectively. Modeling scenarios also indicated that over-winter manure storage was important to keep soluble nutrients out of waterways.

Hyperuricaemia (increased serum urate concentration) occurs mainly in higher primates, including in humans, because of inactivation of the gene encoding uricase during primate evolution. Individuals with hyperuricaemia might develop gout - a painful inflammatory arthritis caused by monosodium urate crystal deposition in articular structures. Hyperuricaemia is also associated with common chronic diseases, including hypertension, chronic kidney disease, type 2 diabetes and cardiovascular disease. Many mouse models have been developed to investigate the causal mechanisms for hyperuricaemia. These models are highly diverse and can be divided into two broad categories: mice with genetic modifications (genetically induced models) and mice exposed to certain environmental factors (environmentally induced models; for example, pharmaceutical or dietary induction). This Review provides an overview of the mouse models of hyperuricaemia and the relevance of these models to human hyperuricaemia, with an emphasis on those models generated through genetic modifications. The challenges in developing and comparing mouse models of hyperuricaemia and future research directions are also outlined.

Objective Intake of sugary drinks, especially soft drinks, carries increased risk for obesity and diabetes. This article reviews whether sugary drinks carry different risks for metabolic syndrome compared with foods that contain natural or added sugars. Methods A narrative review was performed to evaluate differences between liquid and solid sugars in their ability to induce metabolic syndrome and to discuss potential mechanisms to account for the differences. Results Epidemiological studies support liquid added sugars, such as soft drinks, as carrying greater risk for development of metabolic syndrome compared with solid sugar. Some studies suggest that fruit juice may also confer relatively higher risk for weight gain and insulin resistance compared with natural fruits. Experimental evidence suggests this may be due to differences in how fructose is metabolized. Fructose induces metabolic disease by reducing the energy levels in liver cells, mediated by the concentration of fructose to which the cells are exposed. The concentration relates to the quantity and speed at which fructose is ingested, absorbed, and metabolized. Conclusions Although reduced intake of added sugars (sucrose and high-fructose corn syrup) remains a general recommendation, there is evidence that sugary soft drinks may provide greater health risks relative to sugar-containing foods.

Hyperuricemia (HU) is a cause of gout. Clinical studies show a link between HU and cardiovascular disease. However, the role of soluble serum urate (SU) on atherosclerosis development remains elusive. We aimed to use a new HU mouse model [Uricase/Uox knockout (KO)] to further investigate the relationship between HU and atherosclerosis. A mouse model by perivascular collar placement of induced carotid atherosclerosis was established in male Uox‐ KO mice. The Uox‐ KO mice had elevated SU levels and enhanced levels of atherosclerosis inflammatory response proteins. In contrast, Uox‐ KO mice with carotid atherosclerosis showed severe neointimal changes in histology staining consistent with increases in intimal area and increases in proliferating cell nuclear antigen (PCNA)‐ and F4/80‐positive cells. Allopurinol reduced neointimal areas induced by the perivascular collar in hyperuricemic mice, accompanied by decreased expression of PCNA‐ and F4/80‐positive cells. Urate‐lowering treatment alleviated atherosclerosis inflammatory response factors and reactive oxygen species (ROS) intensities in both collar placement Uox‐ KO mice and urate‐stimulated human umbilical vein endothelial cells (HUVECs). In vitro results using HUVECs showed ROS was induced by urate and ROS induction was abrogated using antioxidants. These data demonstrate that urate per se does not trigger atherosclerosis intima lesions in male mice. Urate worsens carotid neointimal lesions induced by the perivascular collar and urate‐lowering therapy partially abrogates the effects. The current study warrants clinical studies on the possible benefits of urate‐lowering therapy in atherosclerosis patients with HU., Clinical studies show a link between hyperuricemia (HU) and cardiovascular disease. However, the role of soluble urate on atherosclerosis development remains unclear. A mouse model of induced carotid atherosclerosis was established in a spontaneous HU mouse with the uricase gene inactivated. This study demonstrates that urate worsens carotid neointimal lesions induced by the perivascular collar and that urate‐lowering therapy partially abrogates the effects.

BACKGROUND Fructose consumption has been linked with insulin resistance, obesity and diabetes, which are more prevalent in those of Māori or Pacific ethnicity compared to New Zealand European. AIM To determine whether the acute effects of fructose consumption on serum glucose, insulin, lipids and C-reactive protein differs according to body mass index (BMI) and/or ethnicity. METHODS Participants of Māori (n = 25), Pacific (n = 26) or New Zealand European (n = 25) ethnicity consumed a 64 g fructose/16 g glucose solution. Changes in lipids, glucose, insulin and C-reactive protein were analysed using mixed models for repeated measures. RESULTS After adjustment for age and gender, those with higher BMI had a higher glucose (P = 0.0064) and insulin (P = 0.0007) response than those with lower BMI. Those of Māori or Pacific ethnicity had similar glucose levels (P = 0.077) to those of New Zealand European ethnicity but higher insulin responses (P = 0.0005), which remained after additional adjustment for BMI (P = 0.001). Reported sugar-sweetened beverages (SSB) intake was higher among Māori and Pacific than New Zealand European (median 1.0 vs 0.0 SSB/day P = 0.002). CONCLUSION Even after adjustment for BMI, those of Māori and Pacific ethnicity have a significantly higher insulin response to fructose than New Zealand Europeans. Higher habitual SSB intake may be a contributing factor.

To examine the associations of changes in serum urate (SU) with health-related quality of life (HRQOL) in gout.We used the first 6-months of data from four interventional trials and one observational, open-label study of urate-lowering therapy (ULT) use. HRQOL were assessed at baseline and every 3-months, and SU was measured monthly. Primary outcome measures were Short-form 36 physical and mental component summary scores, Health Assessment Questionnaire Disability Index (HAQ-DI), Sheehan Disability Scale (SDS), Patient Global Assessment, and pain scores in the last week. Linear mixed models for each outcome were adjusted as appropriate for current SU, change in urate in the last month, number of flare-affected days in the last month, baseline BMI, age, comorbidities, sex, ethnicity, trial/study and treatment combination, and tophi status (fixed effects); subject, and the trial/study month were random effects.Higher current SU correlated with reduced physical and mental HRQOL, and increased SDS and pain but not with HAQ-DI score. In the first 6-months of new/escalating ULT use, absolute change in SU levels associated with poorer outcomes on the HAQ-DI scale (β (95% CI) = 0.013 (0.007-0.019)) and poorer outcomes on SDS, SF-36 MCS, patient global and pain scales. Reduction of SU associated with poorer outcomes in all six measures.High SU levels were associated with poorer HRQOL, pain and Sheehan disability score. Recent SU level fluctuations are associated with poorer outcomes, primarily driven by a reduction in SU. Clinical emphasis on slow rather than fast SU reduction and the routine use of effective, anti-inflammatory medications at ULT initiation/escalation may avoid short-term poor outcomes.

Emerging data suggest gout and hyperuricemia may now be more frequent among Black adults in the US than White adults, especially Black women. However, national-level, sex-specific general population data on racial differences in gout prevalence and potential socioclinical risk factors are lacking.To identify sex-specific factors driving disparities between Black and White adults in contemporary gout prevalence in the US general population.This cross-sectional analysis used nationally representative, decadal survey data from successive cycles of the National Health and Nutrition Examination Survey from 2007 to 2016. Data were analyzed from November 1, 2019, through May 31, 2021. Participants included US adults self-reporting Black or White race.Self-reported race, excess body mass index, chronic kidney disease (CKD; defined as estimated glomerular filtration rate60 mL/min/1.73 m2, according to latest equations without race coefficient), poverty, poor-quality diet, low educational level, alcohol consumption, and diuretic use.Race- and sex-specific prevalence of physician- or clinician-diagnosed gout and hyperuricemia and their differences before and after adjusting for potential socioclinical risk factors.A total of 18 693 participants were included in the analysis, consisting of 3304 Black women (mean [SD] age, 44.8 [0.4] years), 6195 White women (mean [SD] age, 49.8 [0.3] years), 3085 Black men (mean [SD] age, 43.6 [0.5] years]), and 6109 White men (mean [SD] age, 48.2 [0.3] years). Age-standardized prevalence of gout was 3.5% (95% CI, 2.7%-4.3%) in Black women and 2.0% (95% CI, 1.5%-2.5%) in White women (age-adjusted odds ratio [OR], 1.81 [95% CI, 1.29-2.53]); prevalence was 7.0% (95% CI, 6.2%-7.9%) in Black men and 5.4% (95% CI, 4.7%-6.2%) in White men (age-adjusted OR, 1.26 [95% CI, 1.02-1.55]). These associations attenuated after adjusting for poverty, diet, body mass index, and CKD among women and for diet and CKD among men but became null after adjusting for all risk factors (ORs, 1.05 [95% CI, 0.67-1.65] among women and 1.05 [95% CI, 0.80-1.35] among men). Hyperuricemia end point findings were similar.In this nationally representative race- and sex-specific cross-sectional study of US adults, gout was more prevalent in adults self-reporting Black race during a recent 10-year period compared with their White counterparts. These racial differences may be explained by sex-specific differences in diet and social determinants of health and clinical factors. Culturally informed efforts focusing on these factors could reduce current gout-related disparities.

Objectives The objective of this study was to develop and validate a prediction model for renal urate underexcretion (RUE) in male gout patients. Methods Men with gout enrolled from multicenter cohorts in China were analyzed as the development and validation data sets. The RUE phenotype was defined as fractional excretion of uric acid (FEUA) Results One thousand two hundred thirty-eight and two thousand twenty-three patients were enrolled as the development and validation cohorts, with 1220 and 754 randomly chosen patients genotyped, respectively. Rs3775948.GG of SLC2A9/GLUT9, rs504915.AA of NRXN2/URAT1, and 7 clinical features (age, hypertension, nephrolithiasis, blood glucose, serum urate, urea nitrogen, and creatinine) were generated by LASSO. Two additional SNP variants (rs2231142.GG of ABCG2 and rs11231463.GG of SLC22A9/OAT7) were selected based on their contributions to gout in the development cohort and their reported effects on renal urate handling. The optimized classifiers yielded AUCs of ~0.914 and PRCs of ~0.980 using these 11 variables. The SGD model was conducted in the validation cohort with an AUC of 0.899 and the PRC of 0.957. Conclusions A prediction model for RUE composed of four SNPs and readily accessible clinical features was established with acceptable accuracy for men with gout.

The minor allele (A) of the rs373863828 variant (p.Arg457Gln) in CREBRF is restricted to indigenous peoples of the Pacific islands (including New Zealand Māori and peoples of Polynesia), with a frequency of up to 25% in these populations. This allele associates with a large increase in body mass index (BMI) but with significantly lower risk of type-2 diabetes (T2D). It remains unclear whether the increased BMI is driven by increased adiposity or by increased lean mass.We undertook body composition analysis using DXA in 189 young men of Māori and Pacific descent living in Aotearoa New Zealand. Further investigation was carried out in two orthologous Arg458Gln knockin mouse models on FVB/NJ and C57BL/6j backgrounds.The rs373863828 A allele was associated with lower fat mass when adjusted for BMI (p0.05) and was associated with significantly lower circulating levels of the muscle inhibitory hormone myostatin (p0.05). Supporting the human data, significant reductions in adipose tissue mass were observed in the knockin mice. This was more significant in older mice in both backgrounds and appeared to be the result of reduced age-associated increases in fat mass. The older male knockin mice on C57BL/6j background also had increased grip strength (p0.01) and lower levels of myostatin (p0.05).Overall, these results prove that the rs373863828 A-allele is associated with a reduction of myostatin levels which likely contribute to an age-dependent lowering of fat mass, at least in males.

The minor allele (A) of the rs373863828 variant (p.Arg457Gln) in CREBRF is restricted to indigenous peoples of the Pacific islands (including New Zealand Māori and peoples of Polynesia), with a frequency up to 25% in these populations. This allele associates with a large increase in body mass index (BMI) but with significantly lower risk of type-2 diabetes (T2D). It is unclear whether the increased BMI is driven by increased adiposity or by increased lean mass. Hence, we undertook body composition analysis using DXA in 189 young men of Māori and Pacific descent living in Aotearoa New Zealand. The rs373863828 A allele was associated with a trend toward increased relative lean mass although this was not statistically significant (p=0.06). Notably though this allele was associated with significantly lower circulating levels of the muscle inhibitory hormone myostatin (p

Insulin and hyperinsulinemia reduce renal fractional excretion of urate (FeU) and play a key role in the genesis of hyperuricemia and gout, via uncharacterized mechanisms. To explore this association further we studied the effects of genetic variation in insulin-associated pathways on serum urate (SU) levels and the physiological effects of insulin on urate transporters. We found that urate-associated variants in the human insulin (INS), insulin receptor (INSR), and insulin receptor substrate-1 (IRS1) loci associate with the expression of the insulin-like growth factor 2, IRS1, INSR, and ZNF358 genes; additionally, we found genetic interaction between SLC2A9 and the three loci, most evident in women. We also found that insulin stimulates the expression of GLUT9 and increases [14C]-urate uptake in human proximal tubular cells (PTC-05) and HEK293T cells, transport activity that was effectively abrogated by uricosurics or inhibitors of protein tyrosine kinase (PTK), PI3 kinase, MEK/ERK, or p38 MAPK. Heterologous expression of individual urate transporters in Xenopus oocytes revealed that the [14C]-urate transport activities of GLUT9a, GLUT9b, OAT10, OAT3, OAT1, NPT1 and ABCG2 are directly activated by insulin signaling, through PI3 kinase (PI3K)/Akt, MEK/ERK and/or p38 MAPK. Given that the high-capacity urate transporter GLUT9a is the exclusive basolateral exit pathway for reabsorbed urate from the renal proximal tubule into the blood, that insulin stimulates both GLUT9 expression and urate transport activity more than other urate transporters, and that SLC2A9 shows genetic interaction with urate-associated insulin-signaling loci, we postulate that the anti-uricosuric effect of insulin is primarily due to the enhanced expression and activation of GLUT9.

Background Pain experienced at teeth during orthodontic treatment varies largely over time, with the reasons for its interindividual variability being largely unknown: age, sex, clinical activations, psychosocial factors and genetic polymorphisms of candidate genes are putative factors that may account to explain this variability. We aimed to investigate the effect of clinical, demographic, psychological and genetic factors on pain levels experienced during fixed orthodontic treatment. Methods A convenience sample of 183 patients undergoing full-fixed orthodontic treatment were recruited. Participant's pain levels were assessed seven times over a three-day period via a smartphone app. Clinical, demographic and psychological data were collected via questionnaires. This included the Pain Catastrophising Scale (Child version), the Corah Dental Anxiety Scale and the State and Trait Anxiety Inventory. Participants provided a DNA sample either in the form of blood or saliva, which were used for genotyping COMT gene rs6269, rs4680, rs4646310, NR3C1 gene rs2963155 and the HTR2A gene rs9316233. Results Bond ups had the greatest influence on perceived levels of pain experienced on teeth during orthodontic treatment, accounting for over 20% of total variance in pain response. High-pain responders had higher scores on pain catastrophising (magnification subscale). Self-reported pain during fixed orthodontic treatment was not influenced by sex, age, time into treatment, anxiety, nor by polymorphisms of COMT, HTR2A or NR3C1 genes. Conclusions Pain on teeth resulting from orthodontic fixed appliances is stronger during bonds-up and in patients with high catastrophising scores. Demographics, type of clinical activations and the genetic polymorphisms investigated in this research had little or no impact on perceived pain levels.

Introduction Elevated serum urate (SU) concentration is the central risk factor for the development of gout. The aim of this study was to examine the incidence of gout in people with low and normal SU levels ( Methods Longitudinal cohort data from the Atherosclerosis Risk in Communities Study (ARIC), Coronary Artery Risk Development in Young Adults Study (CARDIA), and both the Original and Offspring cohorts of the Framingham Heart Study (FHS) were used to determine incident gout by baseline SU over 3, 5, 10, 12 and 15 year periods. A Cox proportional hazards model with covariables of age, gender, ethnicity, and cohort was calculated to report the hazard ratios (HR) for incident gout. Results The incidence of gout at 15 years for a baseline SU 7.00 mg/dL was 12.2%. In an adjusted Cox proportional hazards model, compared to the referent baseline SU 7.00 mg/dL (HR 18.62). Conclusion A baseline SU of 5.50 mg/dL or more is a risk factor for development of gout over 15 years. However, incident gout does occur over time in a small proportion of people with lower baseline SU levels.

Hyperuricemia is associated with several cardiometabolic and renal diseases, such as gout and chronic kidney disease. Previous studies have examined the shared genetic basis of chronic kidney disease and hyperuricemia either using single-variant tests or estimating whole-genome genetic correlations between the traits. Individual variants typically explain a small fraction of the genetic correlation between traits, thus reducing the power to map pleiotropic loci. Alternatively, genome-wide estimates of genetic correlation, while useful, do not shed light on what regions may be implicated in the shared genetic basis of traits. Therefore, to fill the gap between these two approaches, we used local Bayesian regressions to estimate the genetic covariance between markers for chronic kidney disease and hyperuricemia in specific genomic regions. We identified 267 linkage disequilibrium segments with statistically significant covariance estimates, 17 of which had a positive directionality and 250 negative, the latter being consistent with the directionality of the overall genetic covariance. These 267 significant segments implicated 188 genetically distinct shared loci. Many of these loci validate previously identified shared loci with consistent directionality, including 22 loci previously identified as shared. Numerous novel shared loci were also identified, such asTHBS3/MTX1/GBAP1, LINC01101, SLC7A9/CEP89, CYP24A1, KCNS3, CHD9, ARL15, PAX8, andIGF1R. Finally, to examine potential biological mechanisms for these shared loci, we have implicated a subset of the genomic segments that are associated with gene expression using colocalization analyses. In particular, five genes (FGF5, ARL6IP5, TRIM6, BCL2L1, andNTRK1) expressed in the kidney are causal candidates potentially contributing to pleiotropic pathways between chronic kidney disease and hyperuricemia. The regions identified by our local Bayesian regression approach may help untangle and explain the association between chronic kidney disease and hyperuricemia.Author SummaryChronic kidney disease is of increased prevalence among people with hyperuricemia, suggesting a shared genetic etiology. Since markers for chronic kidney disease and hyperuricemia have an overall non-zero genetic correlation, there appears to be genetic basis to the shared etiology. However, genome-wide genetic correlation estimates do not elucidate the specific genomic regions contributing to both traits, particularly regions that contribute to the traits with opposite directionality to the overall directionality. We have implemented local Bayesian regressions to identify small genomic segments contributing to the overall genetic correlation. Our method is applicable to any pair of traits that have a shared genetic relationship. We have found numerous novel shared loci, validated previously reported loci, and identified new shared pathways simultaneously contributing to the markers between chronic kidney disease and hyperuricemia. These loci all merit detailed investigation as they may involve underlying biological mechanisms with the potential to explain the common pathogenesis of hyperuricemia and chronic kidney disease.

Increased urate levels and gout correlate with chronic kidney disease with consensus that the primary driver of this relationship is reduced kidney function. However, a comparison of results of genome-wide association studies in serum urate levels and kidney function indicate a more complex situation. Approximately 20% of loci are shared-comprised of those in which the urate-raising allele associates with reduced kidney function, the vice versa situation, and those in which the signals/alleles are different. Although there is very little known regarding the molecular basis of the shared genetic relationship, it is clear that there is no major role for urate transporters and associated transportasome machinery. Some loci, however, do provide clues. The ATXN2 locus, with a shared signal, is one of only a small number of master regulators of expression by chromatin interaction, regulating expression of genes relevant for cholesterol and blood pressure. This suggests a role for systemic metabolic alteration. At HNF4A there is genetic heterogeneity with different genetic variants conferring risk to hyperuricemia and chronic kidney disease, suggesting different pathways. Interestingly, the shared loci congregate in the olfactory receptor pathway. The genome-wide association studies have generated a range of experimentally testable hypotheses that should provide insights into the shared pathogenesis of hyperuricemia/gout and chronic kidney disease.

AimThe minor A allele of rs373863828 (CREBRF p.Arg457Gln) is associated with increased body mass index (BMI), but reduced risk of type 2 and gestational diabetes in Polynesian (Pacific peoples and Aotearoa New Zealand Māori) populations. This study investigates the effect of the A allele on insulin release and sensitivity in overweight/obese men without diabetes.MethodsA mixed meal tolerance test was completed by 172 men (56 with the A allele) of Māori or Pacific ancestry, and 44 (24 with the A allele) had a frequently sampled intravenous glucose tolerance test and hyperinsulinemic-euglycemic clamp. Mixed linear models with covariates age, ancestry and BMI were used to analyse the association between the A allele of rs373863828 and markers of insulin release and blood glucose regulation.ResultsThe A allele of rs373863828 is associated with a greater increase in plasma insulin 30 min following a meal challenge without affecting the elevation in plasma glucose or incretins GLP-1 or GIP. Consistent with this point, following an intravenous infusion of a glucose bolus, participants with an A allele had higher early (prs373863828 genotype was not associated with a significant difference (p>0.05) in insulin sensitivity index or glucose disposal during hyperinsulinemic-euglycemic clamp.Conclusion/interpretationrs373863828-A allele associates with increased glucose-stimulated insulin release without affecting insulin sensitivity, suggesting that CREBRF p.Arg457Gln may increase maximal ability for β-cells to release insulin to reduce the risk of type 2 diabetes.

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.

Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations (p –8) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes (CYP11B1, CYP17A1 HSD3B2 and STAR) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO, suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.

The minor A allele of rs373863828 (CREBRF p.Arg457Gln) is associated with increased BMI, but reduced risk of type 2 and gestational diabetes in Polynesian (Pacific peoples and Aotearoa New Zealand Māori) populations. This study investigates the effect of the A allele on insulin release and sensitivity in overweight/obese men without diabetes.A mixed meal tolerance test was completed by 172 men (56 with the A allele) of Māori or Pacific ancestry, and 44 (24 with the A allele) had a frequently sampled IVGTT and hyperinsulinaemic-euglycaemic clamp. Mixed linear models with covariates age, ancestry and BMI were used to analyse the association between the A allele of rs373863828 and markers of insulin release and blood glucose regulation.The A allele of rs373863828 is associated with a greater increase in plasma insulin 30 min following a meal challenge without affecting the elevation in plasma glucose or incretins glucagon-like polypeptide-1 or gastric inhibitory polypeptide. Consistent with this point, following an i.v. infusion of a glucose bolus, participants with an A allele had higher early (p 0.05 at 2 and 4 min) plasma insulin and C-peptide concentrations for a similar elevation in blood glucose as those homozygous for the major (G) allele. Despite increased plasma insulin, rs373863828 genotype was not associated with a significant difference (p 0.05) in insulin sensitivity index or glucose disposal during hyperinsulinaemic-euglycaemic clamp.rs373863828-A allele associates with increased glucose-stimulated insulin release without affecting insulin sensitivity, suggesting that CREBRF p.Arg457Gln may increase insulin release to reduce the risk of type 2 diabetes.

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.

Pleiotropy (i.e., genes with effects on multiple traits) leads to genetic correlations between traits and contributes to the development of many syndromes. Identifying variants with pleiotropic effects on multiple health-related traits can improve the biological understanding of gene action and disease etiology, and can help to advance disease-risk prediction. Sequential testing is a powerful approach for mapping genes with pleiotropic effects. However, the existing methods and the available software do not scale to analyses involving millions of SNPs and large datasets. This has limited the adoption of sequential testing for pleiotropy mapping at large scale. In this study, we present a sequential test and software that can be used to test pleiotropy in large systems of traits with biobank-sized data. Using simulations, we show that the methods implemented in the software are powerful and have adequate type-I error rate control. To demonstrate the use of the methods and software, we present a whole-genome scan in search of loci with pleiotropic effects on seven traits related to metabolic syndrome (MetS) using UK-Biobank data (n~300 K distantly related white European participants). We found abundant pleiotropy and report 170, 44, and 18 genomic regions harboring SNPs with pleiotropic effects in at least two, three, and four of the seven traits, respectively. We validate our results using previous studies documented in the GWAS-catalog and using data from GTEx. Our results confirm previously reported loci and lead to several novel discoveries that link MetS-related traits through plausible biological pathways.

OBJECTIVES: The objectives for this study were to assess whether gout and/or rheumatoid arthritis (RA) are risk factors for coronavirus disease 2019 (COVID-19) diagnosis and to assess whether gout and/or RA are risk factors for death from COVID-19. METHODS: We used data from the UK Biobank. Multivariable-adjusted logistic regression was employed in the following analyses: analysis A, to test for association between gout and/or RA and COVID-19 diagnosis (n = 473,139); analysis B, to test for association between gout and/or RA and death from COVID-19 in a case-control cohort of people who died of or survived COVID-19 (n = 2059); analysis C, to test for association between gout and/or RA and death from COVID-19 in the entire UK Biobank cohort (n = 473,139). RESULTS: RA, but not gout, was associated with COVID-19 diagnosis in analysis A. Neither RA nor gout was associated with risk of death in the group diagnosed with COVID-19 in analysis B. However, RA was associated with risk of death related to COVID-19 by using the UK Biobank cohort in analysis C, independent of comorbidities and other measured risk factors (odds ratio [OR] 1.9; 95% confidence interval CI 1.2-3.0). Gout was not associated with death related to COVID-19 in the same UK Biobank analysis (OR 1.2; 95% CI 0.8-1.7). CONCLUSION: RA is a risk factor for death from COVID-19 by using the UK Biobank cohort. These findings require replication in larger data sets that also allow for inclusion of a wider range of factors.

OBJECTIVE Observational studies have consistently demonstrated that serum urate level positively correlates with bone mineral density (BMD). We undertook this study to determine whether moderate hyperuricemia induced by inosine supplements influences bone turnover markers in postmenopausal women over a 6-month period. METHODS One hundred twenty postmenopausal women were recruited for a 6-month randomized, double-blind, placebo-controlled trial. Key exclusion criteria were osteoporosis, previous fragility fracture, bisphosphonate therapy, gout, kidney stones, and a urine pH level of ≤5.0. Participants were randomized in a 1:1 ratio to receive placebo or inosine. The coprimary end points were change in levels of N-propeptide of type I procollagen (PINP) and change in levels of β-C-telopeptide of type I collagen (β-CTX). Change in BMD, as measured by dual x-ray absorptiometry, was an exploratory end point. RESULTS Administration of inosine led to a significant increase in serum urate concentration over the study period (P < 0.0001 for all follow-up time points). At week 26, the mean change in serum urate concentration was +0.13 mmoles/liter (+2.2 mg/dl) in the inosine group and 0.00 mmoles/liter (0 mg/dl) in the placebo group. There was no difference in PINP or β-CTX levels between groups over the 6 months. There were no significant changes in bone density between groups over the 6 months. Adverse events and serious adverse events were similar between the 2 groups. CONCLUSION This clinical trial shows that although inosine supplementation leads to sustained increases in serum urate levels over a 6-month period, it does not alter markers of bone turnover in postmenopausal women. These findings do not support the concept that urate has direct biologic effects on bone turnover.

Background:Risk behaviors for young adults such as alcohol use are associated with increased risk of morbidity and mortality. Patterns of risk behavior may be genetically determined and vary between genders. Previous studies in both young adults and heavy drinking adult samples have demonstrated that some genotypes, such asOPRM1A118G,COMTVal158Met andDRD2Taq1A andDRD4C52IT, may predict addictive behaviors including alcohol consumption and impulsivity, although results have been mixed.Methods:This study aimed to investigate the predictive relationship of these four single nucleotide polymorphisms (SNPs) prospectively on student patterns of drinking using a micro-longitudinal daily diary design in a sample of 628 young adults ages 18–25 of predominantly of European ethnicity. Linear mixed models were used to examine the effect of SNPs on the number of drinks per drinking session with gender as a moderating variable.Results:There were no main effects for genotype on alcohol consumption, nor for gender × genotype for any of the SNPs. There was a trend for an effect of theDRD2Taq1A on the number of drinks per drinking day and for the interaction of gender andDRD2Taq1A on the number of drinks per drinking day.Conclusion:These findings suggest that theDRD2Taq1A, OPRM1A118G,DRD4C521T, orCOMTVal158Met polymorphisms, are not associated with alcohol consumption in young adults, although there may be a relationship betweenDRD2Taq1A and alcohol consumption in young adult males.

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.

Objective To systematically profile metabolic alterations and dysregulated metabolic pathways in hyperuricemia and gout, and to identify potential metabolite biomarkers to discriminate gout from asymptomatic hyperuricemia. Methods Serum samples from 330 participants, including 109 with gout, 102 with asymptomatic hyperuricemia, and 119 normouricemic controls, were analyzed by high-resolution mass spectrometry-based metabolomics. Multivariate principal components analysis and orthogonal partial least squares discriminant analysis were performed to explore differential metabolites and pathways. A multivariate methods with Unbiased Variable selection in R (MUVR) algorithm was performed to identify potential biomarkers and build multivariate diagnostic models using 3 machine learning algorithms: random forest, support vector machine, and logistic regression. Results Univariate analysis demonstrated that there was a greater difference between the metabolic profiles of patients with gout and normouricemic controls than between the metabolic profiles of individuals with hyperuricemia and normouricemic controls, while gout and hyperuricemia showed clear metabolomic differences. Pathway enrichment analysis found diverse significantly dysregulated pathways in individuals with hyperuricemia and patients with gout compared to normouricemic controls, among which arginine metabolism appeared to play a critical role. The multivariate diagnostic model using MUVR found 13 metabolites as potential biomarkers to differentiate hyperuricemia and gout from normouricemia. Two-thirds of the samples were randomly selected as a training set, and the remainder were used as a validation set. Receiver operating characteristic analysis of 7 metabolites yielded an area under the curve of 0.83-0.87 in the training set and 0.78-0.84 in the validation set for distinguishing gout from asymptomatic hyperuricemia by 3 machine learning algorithms. Conclusion Gout and hyperuricemia have distinct serum metabolomic signatures. This diagnostic model has the potential to improve current gout care through early detection or prediction of progression to gout from hyperuricemia.

ObjectivesTo assess whether gout and / or rheumatoid arthritis (RA) are risk factors for coronavirus disease 19 (COVID-19) diagnosis. To assess whether gout and / or RA are risk factors for death with COVID-19.MethodsWe used data from the UK Biobank. Multivariable-adjusted logistic regression was employed in the following analyses: Analysis A, to test for association between gout or RA and COVID-19 diagnosis (n=473,139); Analysis B, to test for association between gout or RA and death with COVID-19 in a case-control cohort of people who died or survived with COVID-19 (n=2,059); Analysis C, to test for association with gout or RA and death with COVID-19 in the entire UK Biobank cohort (n=473,139)ResultsRA, but not gout, associated with COVID-19 diagnosis in analysis A. Neither RA nor gout associated with risk of death in the COVID-19-diagnosed group in analysis B. However RA associated with risk of death related to COVID-19 using the UK Biobank cohort in analysis C independent of comorbidities and other measured risk factors (OR=1.9 [95% CI 1.2 ; 3.0]). Gout was not associated with death related to COVID-19 in the same UK Biobank analysis (OR=1.2 [95% CI 0.8 ; 1.7]).ConclusionRheumatoid arthritis is a risk factor for death with COVID-19 using the UK Biobank cohort. These findings require replication in larger data sets that also allow inclusion of a wider range of factors.Key messagesInformation on the risk of death from COVID-19 for people with gout and rheumatoid arthritis is scarce.In an analysis of the UK Biobank there is an increased risk of death related to COVID-19 for people with rheumatoid arthritis independent of included co-morbidities, but not gout.The findings need to be replicated in other datasets where the influence of therapies for rheumatoid arthritis can be tested.

Background High body mass index (BMI) is strongly associated with hyperuricaemia. It is unknown whether overweight and obesity influences serum urate primarily through increased urate production or reduced renal clearance of uric acid. The aim of this study was to determine the influence of BMI on the response to inosine, a purine nucleoside that functions as an intermediate in the purine salvage and degradation pathways. Methods Following an overnight fast, 100 healthy participants without gout attended a study visit. Blood and urine samples were taken prior to and over 180 min after 1.5 g oral inosine. Serum urate and fractional excretion of uric acid (FEUA) were analysed according to high BMI (≥ 25 kg/m2) and low/normal BMI (2) groups, and according to BMI as a continuous variable. Results Participants in the high BMI group (n = 52, mean BMI 30.8 kg/m2) had higher serum urate concentrations at baseline (P = 0.002) compared to those with low/normal BMI (mean BMI 21.8 kg/m2). However, the high BMI group had a smaller increase in serum urate following the inosine load (P = 0.0012). The two BMI groups had a similar FEUA at baseline (P = 0.995), but those in the high BMI group had a smaller increase in FEUA following the inosine (P = 0.0003). Similar findings were observed when analysing BMI as a continuous variable. Those with high BMI had a smaller increase in FEUA per increase in serum urate, compared to those with low BMI (P = 0.005). Conclusions In a fasting state, people with high BMI have elevated serum urate levels but similar FEUA values compared with those with low/normal BMI. Following a purine load, those with high BMI have an attenuated renal excretion of uric acid. These data, using an experimental method to dynamically assess human urate handling, suggest that people with high BMI have a higher renal capacity for uric acid reabsorption when fasted and following a dietary purine intake have reduced renal clearance. Trial registration Australia and New Zealand Clinical Trials Registry, ACTRN12615001302549, date of registration 30 November 2015.

Urate in the fingernails of gout patients and healthy volunteers was successfully detected by high-performance liquid chromatography (HPLC) with ultraviolet (UV) in our previous research. This study aimed to further investigate whether nail urate could be a proxy for the burden of monosodium urate (MSU) crystals deposits in gout. To this end, we conducted a study in two parts. Firstly, we successfully detected urate in the nail by HPLC–UV and evaluated nail urate concentrations in control subjects and patients with gout. As expected, we found that levels of nail urate were significantly higher in patients with gout than in healthy controls, and the nail urate level was significantly correlated with the volume of MSU crystals deposits measured by dual-energy CT (DECT). Secondly, we found that nail urate can reflect changes in urate levels in the body during urate lowering therapy through a 3-month follow-up study. Our results provide the possibility of quantification of urate in human fingernails as a non-invasive alternative for assessing MSU crystals deposits in gout.

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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.