Genomic dissection of 43 serum urate-associated loci provides multiple insights into molecular mechanisms of urate control

The pathogenesis of gout: molecular insights from genetic, epigenomic and transcriptomic studies

The pathogenesis of gout involves a series of steps beginning with hyperuricaemia, followed by the deposition of monosodium urate crystal in articular structures and culminating in an innate immune response, mediated by the NLRP3 inflammasome, to the deposited crystals. Large genome-wide association studies (GWAS) of serum urate levels initially identified the genetic variants with the strongest effects, mapping mainly to genes that encode urate transporters in the kidney and gut. Other GWAS highlighted the importance of uncommon genetic variants. More recently, genetic and epigenetic genome-wide studies have revealed new pathways in the inflammatory process of gout, including genetic associations with epigenomic modifiers. Epigenome-wide association studies are also implicating epigenomic remodelling in gout, which perhaps regulates the responsiveness of the innate immune system to monosodium urate crystals. Notably, genes implicated in gout GWAS do not include those encoding components of the NLRP3 inflammasome itself, but instead include genes encoding molecules involved in its regulation. Knowledge of the molecular mechanisms underlying gout has advanced through the translation of genetic associations into specific molecular mechanisms. Notable examples include ABCG2, HNF4A, PDZK1, MAF and IL37. Current genetic studies are dominated by participants of European ancestry; however, studies focusing on other population groups are discovering informative population-specific variants associated with gout.

Changes in alcohol intake and serum urate changes: longitudinal analyses of annual medical examination database

INTRODUCTION

Despite the established cross-sectional association between alcohol intake and serum urate (SU), its longitudinal association remains unknown. This study aimed to determine whether changes in alcohol intake have a clinically relevant association with SU change.

METHOD

We conducted retrospective analyses using systematically collected annual medical examination data from October 2012 to October 2022 in a Japanese preventive medicine centre. The exposure was changes in alcohol intake between two consecutive visits. The association of SU changes with alcohol intake changes was estimated by mixed-effect linear regression with adjustment for relevant covariates.

RESULTS

We analysed 63 486 participants (median age, 47.0 years; 55% women; 58.6% regular alcohol drinkers with a median of 1.4 drinks/day) with 370 572 visits. The median SU level was 5.3 mg/dL, and 506 (0.8%) participants had diagnoses of gout or hyperuricemia without medication use during the study period. Decreasing one daily alcohol intake had a clinically small association with SU changes (-0.019 (95% CI: -0.021 to -0.017) mg/dL). Beer had the largest association with SU (-0.036 (95% CI: -0.039 to -0.032) mg/dL for one beer decrease). Complete discontinuation of any alcohol from a mean of 0.8 drinks/day was associated with -0.056 mg/dL (95% CI: -0.068 to -0.043) decrease in SU; the association became larger in hyperuricemic participants (-0.110 mg/dL (95% CI: -0.154 to -0.066) for alcohol discontinuation from a mean of 1.0 drinks/day).

CONCLUSIONS

This study revealed changes in alcohol intake had small associations with SU change at the general Japanese population level. Complete discontinuation of alcohol in hyperuricemic participants had only modest improvement in SU.

A phenome-wide association and factorial Mendelian randomization study on the repurposing of uric acid-lowering drugs for cardiovascular outcomes

Uric acid has been linked to various disease outcomes. However, it remains unclear whether uric acid-lowering therapy could be repurposed as a treatment for conditions other than gout. We first performed both observational phenome-wide association study (Obs-PheWAS) and polygenic risk score PheWAS (PRS-PheWAS) to identify associations of uric acid levels with a wide range of disease outcomes. Then, trajectory analysis was conducted to explore temporal progression patterns of the observed disease outcomes. Finally, we investigated whether uric acid-lowering drugs could be repurposed using a factorial Mendelian randomization (MR) study design. A total of 41 overlapping phenotypes associated with uric acid levels were identified by both Obs- and PRS- PheWASs, primarily cardiometabolic diseases. The trajectory analysis illustrated how elevated uric acid levels contribute to cardiometabolic diseases, and finally death. Meanwhile, we found that uric acid-lowering drugs exerted a protective role in reducing the risk of coronary atherosclerosis (OR = 0.96, 95%CI: 0.93, 1.00, P = 0.049), congestive heart failure (OR = 0.64, 95%CI: 0.42, 0.99, P = 0.043), occlusion of cerebral arteries (OR = 0.93, 95%CI: 0.87, 1.00, P = 0.044) and peripheral vascular disease (OR = 0.60, 95%CI: 0.38, 0.94, P = 0.025). Furthermore, the combination of uric acid-lowering therapy (e.g. xanthine oxidase inhibitors) with antihypertensive treatment (e.g. calcium channel blockers) exerted additive effects and was associated with a 6%, 8%, 8%, 10% reduction in risk of coronary atherosclerosis, heart failure, occlusion of cerebral arteries and peripheral vascular disease, respectively. Our findings support a role of elevated uric acid levels in advancing cardiovascular dysfunction and identify potential repurposing opportunities for uric acid-lowering drugs in cardiovascular treatment.

Multimodal Machine Learning-Based Marker Enables Early Detection and Prognosis Prediction for Hyperuricemia

Hyperuricemia (HUA) has emerged as the second most prevalent metabolic disorder characterized by prolonged and asymptomatic period, triggering gout and metabolism-related outcomes. Early detection and prognosis prediction for HUA and gout are crucial for pre-emptive interventions. Integrating genetic and clinical data from 421287 UK Biobank and 8900 Nanfang Hospital participants, a stacked multimodal machine learning model is developed and validated to synthesize its probabilities as an in-silico quantitative marker for hyperuricemia (ISHUA). The model demonstrates satisfactory performance in detecting HUA, exhibiting area under the curves (AUCs) of 0.859, 0.836, and 0.779 within the train, internal, and external test sets, respectively. ISHUA is significantly associated with gout and metabolism-related outcomes, effectively classifying individuals into low- and high-risk groups for gout in the train (AUC, 0.815) and internal test (AUC, 0.814) sets. The high-risk group shows increased susceptibility to metabolism-related outcomes, and participants with intermediate or favorable lifestyle profiles have hazard ratios of 0.75 and 0.53 for gout compared with those with unfavorable lifestyles. Similar trends are observed for other metabolism-related outcomes. The multimodal machine learning-based ISHUA marker enables personalized risk stratification for gout and metabolism-related outcomes, and it is unveiled that lifestyle changes can ameliorate these outcomes within high-risk group, providing guidance for preventive interventions.

Causal impact of human blood metabolites and metabolic pathways on serum uric acid and gout: a mendelian randomization study

Objective

Hyperuricaemia and gout are common metabolic disorders. However, the causal relationships between blood metabolites and serum urate levels, as well as gout, remain unclear. A systematic evaluation of the causal connections between blood metabolites, hyperuricemia, and gout could enhance early screening and prevention of hyperuricemia and gout in clinical settings, providing novel insights and approaches for clinical treatment.

Methods

In this study, we employed a bidirectional two-sample Mendelian randomization analysis utilizing data from a genome-wide association study involving 7,286 participants, encompassing 486 blood metabolites. Serum urate and gout data were sourced from the Chronic Kidney Disease Genetics consortium, including 288,649 participants for serum urate and 9,819 African American and 753,994 European individuals for gout. Initially, LDSC methodology was applied to identify blood metabolites with a genetic relationship to serum urate and gout. Subsequently, inverse-variance weighting was employed as the primary analysis method, with a series of sensitivity and pleiotropy analyses conducted to assess the robustness of the results.

Results

Following LDSC, 133 blood metabolites exhibited a potential genetic relationship with serum urate and gout. In the primary Mendelian randomization analysis using inverse-variance weighting, 19 blood metabolites were recognized as potentially influencing serum urate levels and gout. Subsequently, the IVW p-values of potential metabolites were corrected using the false discovery rate method. We find leucine (IVW P FDR = 0.00004), N-acetylornithine (IVW P FDR = 0.0295), N1-methyl-3-pyridone-4-carboxamide (IVW P FDR = 0.0295), and succinyl carnitine (IVW P FDR = 0.00004) were identified as significant risk factors for elevated serum urate levels. Additionally, 1-oleoylglycerol (IVW P FDR = 0.0007) may lead to a substantial increase in the risk of gout. Succinyl carnitine exhibited acceptable weak heterogeneity, and the results for other blood metabolites remained robust after sensitivity, heterogeneity, and pleiotropy testing. We conducted an enrichment analysis on potential blood metabolites, followed by a metabolic pathway analysis revealing four pathways associated with serum urate levels.

Conclusion

The identified causal relationships between these metabolites and serum urate and gout offer a novel perspective, providing new mechanistic insights into serum urate levels and gout.

Hyperuricemia Subtypes Classified According to Renal Uric Acid Handling Manifesting Distinct Phenotypic and Genetic Profiles in People With Gout

OBJECTIVE

Hyperuricemia can be stratified into four subtypes according to renal uric acid handling. The aim of this study was to comprehensively describe the biologic characteristics (including genetic background) of clinically defined hyperuricemia subtypes in two large geographically independent gout cohorts.

METHODS

Hyperuricemia subtype was defined as renal uric acid overload (ROL), renal uric acid underexcretion (RUE), combined, or renal normal. Twenty single nucleotide polymorphisms (SNPs) previously identified as gout risk loci or associated with serum urate (SU) concentration in the East Asian population were genotyped. Weighted polygenic risk scores were calculated to assess the cumulative effect of genetic risks on the subtypes.

RESULTS

Of the 4,873 participants, 8.8% had an ROL subtype, 60.9% RUE subtype, 23.1% combined subtype, and 7.2% normal subtype. The ROL subtype was independently associated with older age at onset, lower SU, tophi, and diabetes mellitus; RUE was associated with lower body mass index (BMI) and non-diabetes mellitus; the combined subtype was associated with younger age at onset, higher BMI, SU, estimated glomerular filtration rate (eGFR), and smoking; and the normal subtype was independently associated with older age at onset, lower SU, and eGFR. Thirteen SNPs were associated with gout with 6 shared loci and subtype-dependent risk loci patterns. High polygenic risk scores were associated with ROL subtype (odds ratio [OR] = 9.63, 95% confidence interval [95% CI] 4.53-15.12), RUE subtype (OR = 2.18, 95% CI 1.57-3.03), and combined subtype (OR = 6.32, 95% CI 4.22-9.48) compared with low polygenic risk scores.

CONCLUSION

Hyperuricemia subtypes classified according to renal uric acid handling have subtype-specific clinical and genetic features, suggesting subtype-unique pathophysiologic mechanisms.

A Genome-Wide Association Study of Oxypurinol Concentrations in Patients Treated with Allopurinol

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented with multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p > 5 × 10-8). Our results are consistent with prior findings regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, as well as allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Transporter Genes and statin-induced Hepatotoxicity

PURPOSE

Hepatotoxicity has emerged as a major cause of statin treatment interruption. Although organic anion-transporting polypeptide 1B1 (SLCO1B1), multidrug resistance protein 1 (ABCB1), and breast cancer resistance protein (ABCG2) have been identified as transporters of statins, knowledge of their role in statin-associated hepatotoxicity remains limited. Therefore, we aimed to conduct a comprehensive analysis to elucidate the association between hepatotoxicity and SLCO1B1, ABCB1, and ABCG2 polymorphisms.

METHODS

This study retrospectively analyzed prospectively collected samples. We selected 10 single nucleotide polymorphisms (SNPs) of SLCO1B1, 9 SNPs of ABCB1, and 12 SNPs of ABCG2. We developed two models for multivariable analyses (Model I: clinical factors only; Model II: both clinical and genetic factors), and the attributable risk (%) of variables in Model II was determined.

RESULTS

Among 851 patients, 66 (7.8%) developed hepatotoxicity. In Model I, lipophilic statins, atrial fibrillation (Afib), and diabetes mellitus showed a significant association with hepatotoxicity. In Model II, lipophilic statins and Afib, SLCO1B1 rs11045818 A allele, SLCO1B1 rs4149035 T allele, and ABCG2 rs2622629 TT genotype were associated with higher hepatotoxicity risk. Among them, the SLCO1B1 rs11045818 A allele exhibited the highest attributable risk (93.2%). The area under the receiver operating characteristic curve in Model I was 0.62 (95% CI: 0.55-0.69), and it was increased to 0.71 in Model II (95% CI: 0.64-0.77).

CONCLUSION

This study investigated the correlation between hepatotoxicity and polymorphisms of transporter genes in patients taking statins. The findings could help improve personalized treatments for patients receiving statin therapy.

GWAS-identified hyperuricemia-associated IGF1R variant rs6598541 has a limited role in urate mediated inflammation in human mononuclear cells

Gout is a common autoinflammatory joint diseases characterized by deposition of monosodium urate (MSU) crystals which trigger an innate immune response mediated by inflammatory cytokines. IGF1R is one of the loci associated with both urate levels and gout susceptibility in GWAS to date, and IGF-1-IGF-1R signaling is implicated in urate control. We investigate the role of IGF-1/IGF1R signaling in the context of gouty inflammation. Also, we test the gout and urate-associated IGF1R rs6598541 polymorphism for association with the inflammatory capacity of mononuclear cells. For this, freshly isolated human peripheral blood mononuclear cells (PBMCs) were exposed to recombinant IGF-1 or anti-IGF1R neutralizing antibody in the presence or absence of solubilized urate, stimulated with LPS/MSU crystals. Also, the association of rs6598541 with IGF1R and protein expression and with ex vivo cytokine production levels after stimulation with gout specific stimuli was tested. Urate exposure was not associated with IGF1R expression in vitro or in vivo. Modulation of IGF1R did not alter urate-induced inflammation. Developing urate-induced trained immunity in vitro was not influenced in cells challenged with IGF-1 recombinant protein. Moreover, the IGF1R rs6598541 SNP was not associated with cytokine production. Our results indicate that urate-induced inflammatory priming is not regulated by IGF-1/IGF1R signaling in vitro. IGF1R rs6598541 status was not asociated with IGF1R expression or cytokine production in primary human PBMCs. This study suggests that the role of IGF1R in gout is tissue-specific and may be more relevant in the control of urate levels rather than in inflammatory signaling in gout.

Interaction of genetic variation at ADH1B and MLXIPL with alcohol consumption for elevated serum urate level and gout among people of European ethnicity

BACKGROUND

Alcohol consumption is a risk factor for hyperuricaemia and gout. Multiple single-nucleotide polymorphisms (SNPs) have been identified as associated with both alcohol consumption and serum urate or gout in separate genome-wide association studies (GWAS). This study aimed to identify and characterise interactions between these shared signals of genetic association and alcohol consumption for serum urate level, hyperuricaemia, and gout.

METHODS

This research was conducted using the UK Biobank resource. The association of alcohol consumption with serum urate and gout was tested among 458,405 European participants. Candidate SNPs were identified by comparing serum urate, gout, and alcohol consumption GWAS for shared signals of association. Multivariable-adjusted linear and logistic regression analyses were conducted with the inclusion of interaction terms to identify SNP-alcohol consumption interactions for association with serum urate level, hyperuricaemia, and gout. The nature of these interactions was characterised using genotype-stratified association analyses.

RESULTS

Alcohol consumption was associated with elevated serum urate and gout. For serum urate level, non-additive interactions were identified between alcohol consumption and rs1229984 at the ADH1B locus (P = 3.0 × 10-44) and rs6460047 at the MLXIPL locus (P = 1.4 × 10-4). ADH1B also demonstrated interaction with alcohol consumption for hyperuricaemia (P = 7.9 × 10-13) and gout (P = 8.2 × 10-9). Beer intake had the most significant interaction with ADH1B for association with serum urate and gout among men, while wine intake had the most significant interaction among women. In the genotype-stratified association analyses, ADH1B and MLXIPL were associated with serum urate level and ADH1B was associated with hyperuricaemia and gout among consumers of alcohol but not non-consumers.

CONCLUSIONS

In this large study of European participants, novel interactions with alcohol consumption were identified at ADH1B and MLXIPL for association with serum urate level and at ADH1B for association with hyperuricaemia and gout. The association of ADH1B with serum urate and gout may occur through the modulation of alcohol metabolism rate among consumers of alcohol.

Hyperuricemia and Gout Reduction by SGLT2 Inhibitors in Diabetes and Heart Failure: JACC Review Topic of the Week

Gout is characterized by increased production of purines (through the pentose phosphate pathway), which is coupled with reduced renal or intestinal excretion of urate. Concurrent upregulation of nutrient surplus signaling (mammalian target of rapamycin and hypoxia-inducible factor-1a) and downregulation of nutrient deprivation signaling (sirtuin-1 and adenosine monophosphate-activated protein kinase) redirects glucose toward anabolic pathways (rather than adenosine triphosphate production), thus promoting heightened oxidative stress and cardiomyocyte and proximal tubular dysfunction, leading to cardiomyopathy and kidney disease. Hyperuricemia is a marker (rather than a driver) of these cellular stresses. By inducing a state of starvation mimicry in a state of nutrient surplus, sodium-glucose cotransporter-2 inhibitors decrease flux through the pentose phosphate pathway (thereby attenuating purine and urate synthesis) while promoting renal urate excretion. These convergent actions exert a meaningful effect to lower serum uric acid by ≈0.6 to 1.5 mg/dL and to reduce the risk of gout by 30% to 50% in large-scale clinical trials.

Genome-Wide Association Study of CKD Progression

SIGNIFICANCE STATEMENT

Rapid progression of CKD is associated with poor clinical outcomes. Most previous studies looking for genetic factors associated with low eGFR have used cross-sectional data. The authors conducted a meta-analysis of genome-wide association studies of eGFR decline among 116,870 participants with CKD, focusing on longitudinal data. They identified three loci (two of them novel) associated with longitudinal eGFR decline. In addition to the known UMOD/PDILT locus, variants within BICC1 were associated with significant differences in longitudinal eGFR slope. Variants within HEATR4 also were associated with differences in eGFR decline, but only among Black/African American individuals without diabetes. These findings help characterize molecular mechanisms of eGFR decline in CKD and may inform new therapeutic approaches for progressive kidney disease.

BACKGROUND

Rapid progression of CKD is associated with poor clinical outcomes. Despite extensive study of the genetics of cross-sectional eGFR, only a few loci associated with eGFR decline over time have been identified.

METHODS

We performed a meta-analysis of genome-wide association studies of eGFR decline among 116,870 participants with CKD-defined by two outpatient eGFR measurements of <60 ml/min per 1.73 m 2 , obtained 90-365 days apart-from the Million Veteran Program and Vanderbilt University Medical Center's DNA biobank. The primary outcome was the annualized relative slope in outpatient eGFR. Analyses were stratified by ethnicity and diabetes status and meta-analyzed thereafter.

RESULTS

In cross-ancestry meta-analysis, the strongest association was rs77924615, near UMOD / PDILT ; each copy of the G allele was associated with a 0.30%/yr faster eGFR decline ( P = 4.9×10 -27 ). We also observed an association within BICC1 (rs11592748), where every additional minor allele was associated with a 0.13%/yr slower eGFR decline ( P = 5.6×10 -9 ). Among participants without diabetes, the strongest association was the UMOD/PDILT variant rs36060036, associated with a 0.27%/yr faster eGFR decline per copy of the C allele ( P = 1.9×10 -17 ). Among Black participants, a significantly faster eGFR decline was associated with variant rs16996674 near APOL1 (R 2 =0.29 with the G1 high-risk genotype); among Black participants with diabetes, lead variant rs11624911 near HEATR4 also was associated with a significantly faster eGFR decline. We also nominally replicated loci with known associations with eGFR decline, near PRKAG2, FGF5, and C15ORF54.

CONCLUSIONS

Three loci were significantly associated with longitudinal eGFR change at genome-wide significance. These findings help characterize molecular mechanisms of eGFR decline and may contribute to the development of new therapeutic approaches for progressive CKD.

A functional genomics approach reveals suggestive quantitative trait loci associated with combined TLR4 and BCP crystal-induced inflammation and osteoarthritis

OBJECTIVE

Basic calcium phosphate (BCP) crystals can activate the NLRP3 inflammasome and are potentially involved in the pathogenesis of osteoarthritis (OA). In order to elucidate relevant inflammatory mechanisms in OA, we used a functional genomics approach to assess genetic variation influencing BCP crystal-induced cytokine production.

METHOD

Peripheral blood mononuclear cells (PBMCs) were isolated from healthy volunteers who were previously genotyped and stimulated with BCP crystals and/or lipopolysaccharide (LPS) after which cytokines release was assessed. Cytokine quantitative trait locus (cQTL) mapping was performed. For in vitro validation of the cQTL located in anoctamin 3 (ANO3), PBMCs were incubated with Tamoxifen and Benzbromarone prior to stimulation. Additionally, we performed co-localisation analysis of our top cQTLs with the most recent OA meta-analysis of genome-wide association studies (GWAS).

RESULTS

We observed that BCP crystals and LPS synergistically induce IL-1β in human PBMCs. cQTL analysis revealed several suggestive loci influencing cytokine release upon stimulation, among which are quantitative trait locus annotated to ANO3 and GLIS3. As functional validation, anoctamin inhibitors reduced IL-1β release in PBMCs after stimulation. Co-localisation analysis showed that the GLIS3 locus was shared between LPS/BCP crystal-induced IL-1β and genetic association with Knee OA.

CONCLUSIONS

We identified and functionally validated a new locus, ANO3, associated with LPS/BCP crystal-induced inflammation in PBMCs. Moreover, the cQTL in the GLIS3 locus co-localises with the previously found locus associated with Knee OA, suggesting that this Knee OA locus might be explained through an inflammatory mechanism. These results form a basis for further exploration of inflammatory mechanisms in OA.

Immune and inflammatory mechanisms and therapeutic targets of gout: An update

Gout is an autoimmune disease characterized by acute or chronic inflammation and damage to bone joints induced due to the precipitation of monosodium urate (MSU) crystals. In recent years, with the continuous development of animal models and ongoing clinical investigations, more immune cells and inflammatory factors have been found to play roles in gouty inflammation. The inflammatory network involved in gout has been discovered, providing a new perspective from which to develop targeted therapy for gouty inflammation. Studies have shown that neutrophil macrophages and T lymphocytes play important roles in the pathogenesis and resolution of gout, and some inflammatory cytokines, such as those in the interleukin-1 (IL-1) family, have been shown to play anti-inflammatory or proinflammatory roles in gouty inflammation, but the mechanisms underlying their roles are unclear. In this review, we explore the roles of inflammatory cytokines, inflammasomes and immune cells in the course of gout development and the research status of therapeutic drugs used for inflammation to provide insights into future targeted therapy for gouty inflammation and the direction of gout pathogenesis research.

Uric acid en route to gout

Gout and hyperuricemia (HU) have generated immense attention due to increased prevalence. Gout is a multifactorial metabolic and inflammatory disease that occurs when increased uric acid (UA) induce HU resulting in monosodium urate (MSU) crystal deposition in joints. However, gout pathogenesis does not always involve these events and HU does not always cause a gout flare. Treatment with UA-lowering therapeutics may not prevent or reduce the incidence of gout flare or gout-associated comorbidities. UA exhibits both pro- and anti-inflammation functions in gout pathogenesis. HU and gout share mechanistic and metabolic connections at a systematic level, as shown by studies on associated comorbidities. Recent studies on the interplay between UA, HU, MSU and gout as well as the development of HU and gout in association with metabolic syndromes, non-alcoholic fatty liver disease (NAFLD), and cardiovascular, renal and cerebrovascular diseases are discussed. This review examines current and potential therapeutic regimens and illuminates the journey from disrupted UA to gout.

Relationship between rs4349859 and rs116488202 polymorphisms close to MHC-I region and serum urate levels in patients with gout

BACKGROUND

Gout is the most common inflammatory rheumatic disease and elevated levels of serum urate (SU) are the main cause for its development. Major histocompatibility complex class 1 (MHC-1) plays an important role in the development of multiple inflammatory diseases; however, there is little evidence of its involvement in gout. The present study focused on evaluating the association of the rs4349859 and rs116488202 single nucleotide polymorphisms (SNPs) close to the MHC-1 region in patients with gout.

METHODS AND RESULTS

One hundred and seventy-six individuals of Mexican origin were included, of which 81 were patients with primary gout and 95 were healthy controls. The rs4349859 and rs116488202 SNPs were genotyped using TaqMan probes by allelic discrimination by real-time PCR. Serum concentrations of biochemical parameters were measured with enzymatic methods. Descriptive statistics were applied and P-values < 0.05 were considered significant. It was observed that the rs4349859 and rs116488202 SNPs showed significant association with the risk of gout (OR = 146, 95%CI = 44.8-480.2, P < 0.01; OR = 2885, 95%CI = 265-31398, P < 0.01, respectively). Our results also showed significantly higher serum SU levels in gout patients with respect to controls (P < 0.01) in the carriers of the GA genotype compared with the GG genotype of the rs4349859 variant, and in the carriers of the CT genotype compared with the CC genotype of the rs116488202 variant.

CONCLUSION

The study revealed that rs4349859 and rs116488202 SNPs close to MHC-I region confers strong susceptibility to gout in Mexican population, and the heterozygous genotypes of both were associated with higher levels of SU.

Genetic and Physiological Effects of Insulin-Like Growth Factor-1 (IGF-1) on Human Urate Homeostasis

SIGNIFICANCE STATEMENT

Hyperinsulinemia induces hyperuricemia by activating net renal urate reabsorption in the renal proximal tubule. The basolateral reabsorptive urate transporter GLUT9a appears to be the dominant target for insulin. By contrast, IGF-1 infusion reduces serum urate (SU), through mechanisms unknown. Genetic variants of IGF1R associated with reduced SU have increased IGF-1R expression and interact with genes encoding the GLUT9 and ABCG2 urate transporters, in a sex-specific fashion, which controls the SU level. Activation of IGF-1/IGF-1R signaling in Xenopus oocytes modestly activates GLUT9a and inhibits insulin's stimulatory effect on the transporter, which also activates multiple secretory urate transporters-ABCG2, ABCC4, OAT1, and OAT3. The results collectively suggest that IGF-1 reduces SU by activating secretory urate transporters and inhibiting insulin's action on GLUT9a.

BACKGROUND

Metabolic syndrome and hyperinsulinemia are associated with hyperuricemia. Insulin infusion in healthy volunteers elevates serum urate (SU) by activating net urate reabsorption in the renal proximal tubule, whereas IGF-1 infusion reduces SU by mechanisms unknown. Variation within the IGF1R gene also affects SU levels.

METHODS

Colocalization analyses of a SU genome-wide association studies signal at IGF1R and expression quantitative trait loci signals in cis using COLOC2, RT-PCR, Western blotting, and urate transport assays in transfected HEK 293T cells and in Xenopus laevis oocytes.

RESULTS

Genetic association at IGF1R with SU is stronger in women and is mediated by control of IGF1R expression. Inheritance of the urate-lowering homozygous genotype at the SLC2A9 locus is associated with a differential effect of IGF1R genotype between men and women. IGF-1, through IGF-1R, stimulated urate uptake in human renal proximal tubule epithelial cells and transfected HEK 293T cells, through activation of IRS1, PI3/Akt, MEK/ERK, and p38 MAPK; urate uptake was inhibited in the presence of uricosuric drugs, specific inhibitors of protein tyrosine kinase, PI3 kinase (PI3K), ERK, and p38 MAPK. In X. laevis oocytes expressing ten individual urate transporters, IGF-1 through endogenous IGF-1R stimulated urate transport mediated by GLUT9, OAT1, OAT3, ABCG2, and ABCC4 and inhibited insulin's stimulatory action on GLUT9a and OAT3. IGF-1 significantly activated Akt and ERK. Specific inhibitors of PI3K, ERK, and PKC significantly affected IGF-1 stimulation of urate transport in oocytes.

CONCLUSIONS

The combined results of infusion, genetics, and transport experiments suggest that IGF-1 reduces SU by activating urate secretory transporters and inhibiting insulin's action.

Infection and innate immune mechanism of goose astrovirus

Goose astrovirus (GAstV, genus Avian Astrovirus, family Astrovirus) was first discovered in 2005, but was not considered as a pathogen of gosling gout until 2016. Since then, goose astrovirus has erupted in Chinese goslings, causing at most 50% of gosling deaths. By December 2022, the disease had become epidemic and prevailed in goose farms in Jiangsu, Shandong, Anhui, Henan, Guangdong, Liaoning, Sichuan and other places in China. The disease mainly affects goslings within 3 weeks old. The typical symptoms of goose astrovirus are large deposits of urate in the viscera, joint cavity and ureter surface of infected goslings. Goose astrovirus infection can trigger high levels of iNOS, limiting goose astrovirus replication. The ORF2 domain P2 of the goose astrovirus activates the OASL protein, limiting its replication. Goose astrovirus can also activate pattern recognition receptors (RIG-I, MDA-5, TLR-3), causing an increase in MHC-Ia, MHC-Ib and CD81 mRNA, activating humoral and cellular immunity, thereby hindering virus invasion. Goose astrovirus also regulates the activation of IFNs and other antiviral proteins (Mx1, IFITM3, and PKR) in the spleens and kidneys to inhibit viral replication. The innate immune response process in goslings also activates TGF-β, which may be closely related to the immune escape of goose astrovirus. Gaining insight into the infection and innate immune mechanism of goose astrovirus can help researchers study and prevent the severe disease in goslings better.

Novel Insights into the Effects of Genetic Variants on Serum Urate Response to an Acute Fructose Challenge: A Pilot Study

Studies have shown that genetic variations can influence metabolic response to nutrient intake, and that diets rich in fructose contribute to hyperuricemia. In this pilot study, our aim was to determine the variability of serum urate in response to an acute fructose challenge and to investigate if genetic variants would affect this response in young to middle-aged adults who self-reported as Black or White. Fifty-seven participants consumed a fructose-rich beverage after an overnight fast. Blood was drawn at five time points (baseline, 30, 60, 120, and 180 min after consumption). Thirty urate-related single nucleotide polymorphisms (SNPs) were analyzed for their associations with baseline serum urate and its percent changes, using a two-step modeling approach followed by meta-analysis. At baseline, serum urate (mg/dL, mean ± SD) was higher in Whites (5.60 ± 1.01 vs. 5.37 ± 0.96), men (6.17 ± 1.14 vs. 5.24 ± 0.79), and those with obesity (5.69 ± 1.08 vs. 5.42 ± 1.06 vs. 5.34 ± 0.80). Three SNPs were significantly associated with baseline serum urate or its percent changes, and six SNPs were nominally associated with percent changes in serum urate. In summary, our results showed that genetic variants could play a role in short-term urate metabolism.

Trends in the Contribution of Genetic Susceptibility Loci to Hyperuricemia and Gout and Associated Novel Mechanisms

Hyperuricemia and gout are complex diseases mediated by genetic, epigenetic, and environmental exposure interactions. The incidence and medical burden of gout, an inflammatory arthritis caused by hyperuricemia, increase every year, significantly increasing the disease burden. Genetic factors play an essential role in the development of hyperuricemia and gout. Currently, the search on disease-associated genetic variants through large-scale genome-wide scans has primarily improved our understanding of this disease. However, most genome-wide association studies (GWASs) still focus on the basic level, whereas the biological mechanisms underlying the association between genetic variants and the disease are still far from well understood. Therefore, we summarized the latest hyperuricemia- and gout-associated genetic loci identified in the Global Biobank Meta-analysis Initiative (GBMI) and elucidated the comprehensive potential molecular mechanisms underlying the effects of these gene variants in hyperuricemia and gout based on genetic perspectives, in terms of mechanisms affecting uric acid excretion and reabsorption, lipid metabolism, glucose metabolism, and nod-like receptor pyrin domain 3 (NLRP3) inflammasome and inflammatory pathways. Finally, we summarized the potential effect of genetic variants on disease prognosis and drug efficacy. In conclusion, we expect that this summary will increase our understanding of the pathogenesis of hyperuricemia and gout, provide a theoretical basis for the innovative development of new clinical treatment options, and enhance the capabilities of precision medicine for hyperuricemia and gout treatment.

A Polynesian-specific copy number variant encompassing the MHC Class I Polypeptide-related Sequence A (MICA) gene associates with gout

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.

Genome-wide meta-analysis revealed several genetic loci associated with serum uric acid levels in Korean population: an analysis of Korea Biobank data

The serum uric acid (SUA) level is an important determinant of gout, hypertension, metabolic syndrome, and cardiovascular disease. Although previous genome-wide studies have identified multiple genetic variants associated with SUA, most genetic analyses have focused on individuals with European ancestry; thus, understanding of the genetic architecture of SUA is currently limited for Asian populations. We conducted a genome-wide meta-analysis based on Korea Biobank data consistent with three cohorts; namely, the Korean Genome and Epidemiology Study (KoGES) Ansan and Ansung, KoGES Health Examinee, and KoGES Cardiovascular Disease Association studies. In total, 60,585 participants aged ≥40 years were included in the analysis of the three cohorts. We used logistic regression analyses to perform genome-wide association study (GWAS) adjustments for confounding variables. Subsequently, a meta-analysis was conducted by combining the analyses of the three GWASs. We identified 8,105 variants at 22 genetic loci with a P value < 5 × 10^-8. Among these, six novel genetic loci associated with SUA in the Korean population were identified (rs4715517 in HCRTR2, rs145099458 in 3.2 kb 3' of MLXIPL, rs1137642 in B4GALT1, rs659107 in LOC105378410, rs7919329 in LOC107984274, and rs2240751 in MFSD12). Our meta-analysis provides insights into the genetic architecture of SUA in the Korean population. Further studies are warranted to replicate the study results and elucidate the specific role of these variants in SUA homeostasis.

A machine learning-assisted model for renal urate underexcretion with genetic and clinical variables among Chinese men with gout

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 (FE_UA) <5.5%. Candidate genetic and clinical features were screened by the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation. Machine learning algorithms (stochastic gradient descent (SGD), logistic regression, support vector machine) were performed to construct a predictive classifier of RUE. Models were assessed by the area under the receiver operating characteristic curve (AUC) and the precision-recall curve (PRC).

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.

Urate transport in health and disease

Circulation of urate levels is determined by the balance between urate production and excretion, homeostasis regulated by the function of urate transporters in key epithelial tissues and cell types. Our understanding of these physiological processes and identification of the genes encoding the urate transporters has advanced significantly, leading to a greater ability to predict risk for urate-associated diseases and identify new therapeutics that directly target urate transport. Here, we review the identified urate transporters and their organization and function in the renal tubule, the intestinal enterocytes, and other important cell types to provide a fuller understanding of the complicated process of urate homeostasis and its role in human diseases. Furthermore, we review the genetic tools that provide an unbiased catalyst for transporter identification as well as discuss the role of transporters in determining the observed significant gender differences in urate-associated disease risk.

Increase of serum uric acid levels associated with APOE ε2 haplotype: a clinico-genetic investigation and in vivo approach

Elevated serum uric acid (SUA)-hyperuricemia-is caused by overproduction of urate or by its decreased renal and/or intestinal excretion. This disease, which is increasing in prevalence worldwide, is associated with both gout and metabolic diseases. Several studies have reported relationships between apolipoprotein E (APOE) haplotypes and SUA levels in humans; however, their results remain inconsistent. This prompted us to investigate the relationship between APOE polymorphisms and SUA levels. Our subjects were 5,272 Japanese men, premenopausal women, and postmenopausal women. Multiple linear regression analyses revealed the ε2 haplotype of APOE to be independently associated with higher SUA in men (N = 1,726) and postmenopausal women (N = 1,753), but not in premenopausal women (N = 1,793). In contrast, the ε4 haplotype was little related to SUA levels in each group. Moreover, to examine the effect of Apoe deficiency on SUA levels, we conducted animal experiments using Apoe knockout mice, which mimics ε2/ε2 carriers. We found that SUA levels in Apoe knockout mice were significantly higher than those in wild-type mice, which is consistent with the SUA-raising effect of the ε2 haplotype observed in our clinico-genetic analyses. Further analyses suggested that renal rather than intestinal underexcretion of urate could be involved in Apoe deficiency-related SUA increase. In conclusion, we successfully demonstrated that the ε2 haplotype, but not the ε4 haplotype, increases SUA levels. These findings will improve our understanding of genetic factors affecting SUA levels.

The genetic basis of urate control and gout: Insights into molecular pathogenesis from follow-up study of genome-wide association study loci

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.

Urate-induced epigenetic modifications in myeloid cells

OBJECTIVES

Hyperuricemia is a metabolic condition central to gout pathogenesis. Urate exposure primes human monocytes towards a higher capacity to produce and release IL-1β. In this study, we assessed the epigenetic processes associated to urate-mediated hyper-responsiveness.

METHODS

Freshly isolated human peripheral blood mononuclear cells or enriched monocytes were pre-treated with solubilized urate and stimulated with LPS with or without monosodium urate (MSU) crystals. Cytokine production was determined by ELISA. Histone epigenetic marks were assessed by sequencing immunoprecipitated chromatin. Mice were injected intraarticularly with MSU crystals and palmitate after inhibition of uricase and urate administration in the presence or absence of methylthioadenosine. DNA methylation was assessed by methylation array in whole blood of 76 participants with normouricemia or hyperuricemia.

RESULTS

High concentrations of urate enhanced the inflammatory response in vitro in human cells and in vivo in mice, and broad-spectrum methylation inhibitors reversed this effect. Assessment of histone 3 lysine 4 trimethylation (H3K4me3) and histone 3 lysine 27 acetylation (H3K27ac) revealed differences in urate-primed monocytes compared to controls. Differentially methylated regions (e.g. HLA-G, IFITM3, PRKAB2) were found in people with hyperuricemia compared to normouricemia in genes relevant for inflammatory cytokine signaling.

CONCLUSION

Urate alters the epigenetic landscape in selected human monocytes or whole blood of people with hyperuricemia compared to normouricemia. Both histone modifications and DNA methylation show differences depending on urate exposure. Subject to replication and validation, epigenetic changes in myeloid cells may be a therapeutic target in gout.

Aotearoa New Zealand Māori and Pacific Population-amplified Gout Risk Variants: CLNK Is a Separate Risk Gene at the SLC2A9 Locus

OBJECTIVE

The 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.

METHODS

A 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.

RESULTS

We 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], OR_meta = 1.28, P _meta = 0.03; rs16869924 [CLNK], OR_meta = 1.37, P _meta = 0.002; rs2070025 [fibrinogen A alpha chain (FGA)], OR_meta = 1.34, P _meta = 0.02). The CLNK variant, within the established SLC2A9 gout locus, was genetically independent of the association signal at SLC2A9.

CONCLUSION

We 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.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

BACKGROUND

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

RESULTS

Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

CONCLUSIONS

Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

Genome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. We describe UK Biobank GWAS results for three molecular traits-urate, IGF-1, and testosterone-with better-understood biology than most other complex traits. We find that many of the most significant hits are readily interpretable. We observe huge enrichment of associations near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of each trait, including differences in testosterone regulation between females and males. At the same time, even these molecular traits are highly polygenic, with many thousands of variants spread across the genome contributing to trait variance. In summary, for these three molecular traits we identify strong enrichment of signal in putative core gene sets, even while most of the SNP-based heritability is driven by a massively polygenic background.

Why Does Hyperuricemia Not Necessarily Induce Gout?

Hyperuricemia is a risk factor for gout. It has been well observed that a large proportion of individuals with hyperuricemia have never had a gout flare(s), while some patients with gout can have a normuricemia. This raises a puzzle of the real role of serum uric acid (SUA) in the occurrence of gout flares. As the molecule of uric acid has its dual effects in vivo with antioxidant properties as well as being an inflammatory promoter, it has been placed in a delicate position in balancing metabolisms. Gout seems to be a multifactorial metabolic disease and its pathogenesis should not rely solely on hyperuricemia or monosodium urate (MSU) crystals. This critical review aims to unfold the mechanisms of the SUA role participating in gout development. It also discusses some key elements which are prerequisites for the formation of gout in association with the current therapeutic regime. The compilation should be helpful in precisely fighting for a cure of gout clinically and pharmaceutically.

Both variants of A1CF and BAZ1B genes are associated with gout susceptibility: a replication study and meta-analysis in a Japanese population

Gout is a common type of acute arthritis that results from elevated serum uric acid (SUA) levels. Recent genome-wide association studies (GWASs) have revealed several novel single nucleotide polymorphism (SNPs) associated with SUA levels. Of these, rs10821905 of A1CF and rs1178977 of BAZ1B showed the greatest and the second greatest significant effect size for increasing SUA level in the Japanese population, but their association with gout is not clear. We examined their association with gout using 1411 clinically-defined Japanese gout patients and 1285 controls, and meta-analyzed our previous gout GWAS data to investigate any association with gout. Replication studies revealed both SNPs to be significantly associated with gout (P = 0.0366, odds ratio [OR] with 95% confidence interval [CI]: 1.30 [1.02-1.68] for rs10821905 of A1CF, P = 6.49 × 10^-3, OR with 95% CI: 1.29 [1.07-1.55] for rs1178977 of BAZ1B). Meta-analysis also revealed a significant association with gout in both SNPs (P_meta = 3.16 × 10^-4, OR with 95% CI: 1.39 [1.17-1.66] for rs10821905 of A1CF, P_meta = 7.28 × 10^-5, OR with 95% CI 1.32 [1.15-1.51] for rs1178977 of BAZ1B). This study shows the first known association between SNPs of A1CF, BAZ1B and clinically-defined gout cases in Japanese. Our results also suggest a shared physiological/pathophysiological background between several populations, including Japanese, for both SUA increase and gout susceptibility. Our findings will not only assist the elucidation of the pathophysiology of gout and hyperuricemia, but also suggest new molecular targets.

The comparative effect of exposure to various risk factors on the risk of hyperuricaemia: diet has a weak causal effect

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 (< 25 kg/m²), 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.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.

Molecular Pathophysiology of Uric Acid Homeostasis

Uric acid, the end product of purine metabolism, plays a key role in the pathogenesis of gout and other disease processes. The circulating serum uric acid concentration is governed by the relative balance of hepatic production, intestinal secretion, and renal tubular reabsorption and secretion. An elegant synergy between genome-wide association studies and transport physiology has led to the identification and characterization of the major transporters involved with urate reabsorption and secretion, in both kidney and intestine. This development, combined with continued analysis of population-level genetic data, has yielded an increasingly refined mechanistic understanding of uric acid homeostasis as well as greater understanding of the genetic and acquired influences on serum uric acid concentration. The continued delineation of novel and established regulatory pathways that regulate uric acid homeostasis promises to lead to a more complete understanding of uric acid-associated diseases and to identify new targets for treatment.

Advances in our understanding of gout as an auto-inflammatory disease

Gout, the most common inflammatory arthritis, is the result of hyperuricemia and inflammation induced by monosodium urate (MSU) crystal deposition. However, most people with hyperuricemia will never develop gout, implying a molecular-genetic contribution to the development of gout. Recent genomic studies reveal links between certain genetic variations and gout. We highlight recent advances in our understanding of gout as an auto-inflammatory disease. We review the auto-inflammatory aspects of gout, including the inflammasome and thirteen gout-associated inflammatory-pathway genes and associated comorbidities. This information provides important insights into emerging immune-modulating targets in the management of gout, and future novel therapeutic targets in gout treatment. Cumulatively, this has important implications for treating gout as an auto-inflammatory disease, as opposed to a purely metabolic disease.

Sex Differences in Urate Handling

Hyperuricemia, or elevated serum urate, causes urate kidney stones and gout and also increases the incidence of many other conditions including renal disease, cardiovascular disease, and metabolic syndrome. As we gain mechanistic insight into how urate contributes to human disease, a clear sex difference has emerged in the physiological regulation of urate homeostasis. This review summarizes our current understanding of urate as a disease risk factor and how being of the female sex appears protective. Further, we review the mechanisms of renal handling of urate and the significant contributions from powerful genome-wide association studies of serum urate. We also explore the role of sex in the regulation of specific renal urate transporters and the power of new animal models of hyperuricemia to inform on the role of sex and hyperuricemia in disease pathogenesis. Finally, we advocate the use of sex differences in urate handling as a potent tool in gaining a further understanding of physiological regulation of urate homeostasis and for presenting new avenues for treating the constellation of urate related pathologies.

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

Background

The ABCG2 Q141K (rs2231142) and rs10011796 variants associate with hyperuricaemia (HU). The effect size of ABCG2 rs2231142 on urate is ~ 60% that of SLC2A9, yet the effect size on gout is greater. We tested the hypothesis that ABCG2 plays a role in the progression from HU to gout by testing for association of ABCG2 rs2231142 and rs10011796 with gout using HU controls.

Methods

We analysed 1699 European gout cases and 14,350 normouricemic (NU) and HU controls, and 912 New Zealand (NZ) Polynesian (divided into Eastern and Western Polynesian) gout cases and 696 controls. Association testing was performed using logistic and linear regression with multivariate adjusting for confounding variables.

Results

In Europeans and Polynesians, the ABCG2 141K (T) allele was associated with gout using HU controls (OR = 1.85, P = 3.8E^− 21 and OR_meta = 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 (OR_meta = 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 (P_Het = 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 (P_meta = 2.5E^− 03).

Conclusion

These data are consistent with a role for ABCG2 141K in gout in the presence of established HU.