Mendelian randomization reveals the causal association between gout and hearing impairment in older adults.

With the global aging trend escalating, the holistic well-being of the elderly has become a paramount concern within public health. Traditional observational studies often struggle with confounding factors and establishing causality, leaving the relationship between age-related hearing loss (ARHL) and gout largely unexplored. Employing bidirectional two-sample Mendelian randomization (MR) analysis, this investigation elucidated the genetic underpinnings associated with age-related hearing impairment, gout, and urate levels within the IEU Open-GWAS database, thereby uncovering potential causal connections that underlie the intricate interplay between gout, serum urate concentrations, and auditory decline in the geriatric demographic. In the forward MR phase, a cohort of 30 single nucleotide polymorphisms was leveraged to dissect the causal dynamics between ARHL and both gout and urate concentrations. Conversely, in the reverse MR phase, gout and urate levels were posited as the exposome to delineate their impact on hearing acuity, employing an array of models for rigorous validation and sensitivity scrutiny. In the forward MR analysis, a statistically significant correlation was discerned between ARHL and gout (P = .003, odds ratio = 1.01, 95% confidence interval: 1.00-1.02), alongside a notable association with serum urate levels (P = .031, odds ratio = 1.39, 95% confidence interval: 1.03-1.88), intimating that ARHL could potentially influence the incidence of gout and urate concentrations. Conversely, the reverse MR investigation revealed that neither gout nor serum urate levels exerted significant impact on auditory degradation (P > .05), insinuating that these factors might not predominantly contribute to hearing loss. Sensitivity analyses concurred with this inference. This study enriches the comprehension of geriatric health intricacies and unveils that ARHL potentially influences gout and serum urate concentrations. This suggests that monitoring ARHL may play a crucial role in the early identification and management of gout and hyperuricemia, potentially contributing to a comprehensive approach to improving geriatric health outcomes.

Dietary Carbohydrates, Genetic Susceptibility, and Gout Risk: A Prospective Cohort Study in the UK.

This study aimed to investigate the associations between carbohydrate intake and gout risk, along with interactions between genetic susceptibility and carbohydrates, and the mediating roles of biomarkers. We included 187,387 participants who were free of gout at baseline and completed at least one dietary assessment in the UK Biobank. Cox proportional hazard models were used to estimate the associations between carbohydrate intake and gout risk. Over a median follow-up of 11.69 years, 2548 incident cases of gout were recorded. Total carbohydrate intake was associated with a reduced gout risk (Q4 vs. Q1: HR 0.67, 95% CI 0.60-0.74), as were total sugars (0.89, 0.80-0.99), non-free sugars (0.70, 0.63-0.78), total starch (0.70, 0.63-0.78), refined grain starch (0.85, 0.76-0.95), wholegrain starch (0.73, 0.65-0.82), and fiber (0.72, 0.64-0.80), whereas free sugars (1.15, 1.04-1.28) were associated with an increased risk. Significant additive interactions were found between total carbohydrates and genetic risk, as well as between total starch and genetic risk. Serum urate was identified as a significant mediator in all associations between carbohydrate intake (total, different types, and sources) and gout risk. In conclusion, total carbohydrate and different types and sources of carbohydrate (excluding free sugars) intake were associated with a reduced risk of gout.

Hyperuricemia and its related diseases: mechanisms and advances in therapy.

Hyperuricemia, characterized by elevated levels of serum uric acid (SUA), is linked to a spectrum of commodities such as gout, cardiovascular diseases, renal disorders, metabolic syndrome, and diabetes, etc. Significantly impairing the quality of life for those affected, the prevalence of hyperuricemia is an upward trend globally, especially in most developed countries. UA possesses a multifaceted role, such as antioxidant, pro-oxidative, pro-inflammatory, nitric oxide modulating, anti-aging, and immune effects, which are significant in both physiological and pathological contexts. The equilibrium of circulating urate levels hinges on the interplay between production and excretion, a delicate balance orchestrated by urate transporter functions across various epithelial tissues and cell types. While existing research has identified hyperuricemia involvement in numerous biological processes and signaling pathways, the precise mechanisms connecting elevated UA levels to disease etiology remain to be fully elucidated. In addition, the influence of genetic susceptibilities and environmental determinants on hyperuricemia calls for a detailed and nuanced examination. This review compiles data from global epidemiological studies and clinical practices, exploring the physiological processes and the genetic foundations of urate transporters in depth. Furthermore, we uncover the complex mechanisms by which the UA induced inflammation influences metabolic processes in individuals with hyperuricemia and the association with its relative disease, offering a foundation for innovative therapeutic approaches and advanced pharmacological strategies.

Familial juvenile hyperuricemic nephropathy: Revisiting the SLC8A1 gene, in a family with a novel terminal gross deletion in the UMOD gene.

Autosomal dominant tubulointerstitial kidney disease (ADTKD) comprises a heterogeneous group of rare hereditary kidney diseases characterized by family history of progressive chronic kidney disease (CKD) with bland urine sediment, absence of significant proteinuria and normal or small-sized kidneys. Current diagnostic criteria require identification of a pathogenic variant in one of five genes - UMOD, MUC1, REN, HNF1ß, SEC61A1. The most prevalent form of ADTKD is uromodulin-associated kidney disease (ADTKD-UMOD). Genetic study of a Portuguese family diagnosed with familial juvenile hyperuricemic nephropathy (FJHN), one of the nosological entities in the spectrum of ADTKD, revealed a previously unreported large deletion in UMOD encompassing the entire terminal exon, which strictly cosegregated with CKD and hyperuricemia/gout, establishing the primary diagnosis of ADTKD-UMOD; as well as an ultra-rare nonsense SLC8A1 variant cosegregating with the UMOD deletion in patients that consistently exhibited an earlier onset of clinical manifestations. Since the terminal exon of UMOD does not encode for any of the critical structural domains or amino acid residues of mature uromodulin, the molecular mechanisms underlying the pathogenicity of its deletion are unclear and require further research. The association of the SLC8A1 locus with FJHN was first indicated by the results of a genome-wide linkage analysis in several multiplex families, but those data have not been subsequently confirmed. Our findings in this family revive that hypothesis.

Associations of Circulating Biomarkers with Disease Risks: A Two-Sample Mendelian Randomization Study.

Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here, we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR-Egger. We use the MR-base resource (v0.5.6) from Hemani et al. 2018 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). We report novel causal relationships found by four or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in four or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.

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.

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.

Lower plasma linoleic acids as a risk factor for gout: an integrated analysis of population-based cohort and genetic data.

Background: Gout is a nutrition-related, highly prevalent inflammatory arthritis with undesirable effects on the quality of life. The relationships between circulating fatty acids (FAs) and gout remain poorly understood. Method: We included 268 174 participants with plasma FAs measured using nuclear magnetic resonance at the baseline (2006-2010) from the UK Biobank, of which 15 194 participants had repeated measures of FAs between 2012 and 2013. Cox proportional hazards models were used to assess the association of the baseline and longitudinal changes in relative levels of plasma FAs (% total FAs) with incident gout. Mendelian randomization (MR) analyses were conducted to assess the potential causality of the examined association. Results: Over a median follow-up of 12.8 years, 5160 incident cases of gout occurred. Baseline polyunsaturated fatty acids (PUFAs), n-6 PUFAs, and linoleic acids (LAs) were inversely associated with incident gout (all P-trend values < 0.0001). Baseline monounsaturated fatty acids (MUFAs), n-3 PUFAs, and docosahexaenoic acids (DHAs) were positively associated with incident gout (all P-trend values < 0.0001). Longitudinal increments of n-6 PUFAs and LAs were associated with a lower risk of subsequent gout, whereas an increment of n-3 PUFAs was associated with a higher risk. In two-sample MR analyses, genetically determined higher levels of PUFAs, n-6 PUFAs, and LAs were associated with a decreased risk of gout (all P values < 0.05). Conclusions: Our findings consistently indicate a causal relationship of elevated levels of n-6 PUFAs, especially LAs, with a reduced risk of gout.

Depression and risk of arthritis: A Mendelian randomization study.

INTRODUCTION: Observational studies have found that most patients with arthritis have depression. We aimed to determine the causal relationship between various types of arthritis and depression. METHODS: We conducted a two-sample bidirectional Mendelian randomized (MR) analysis to determine whether there was a significant causal relationship between depression and multiple types of arthritis. The data of our study were derived from the publicly released genome-wide association studies (GWASs) and the largest GWAS meta-analysis. MR analysis mainly used inverse-variance weighted method; supplementary methods included weighted median, weighted mode, and MR-Egger using MR pleiotropy residual sum and outlier to detect and correct for the presence of pleiotropy. RESULTS: After adjusting for heterogeneity and horizontal pleiotropy, we found that depression was associated with an increased risk of osteoarthritis (OA) (OR = 1.02, 95%CI: 1.01-1.02, p = 2.96 × E - 5). In the reverse analysis, OA was also found to increase the risk of depression (OR = 1.10, 95%CI: 1.04-1.15, p = .0002). Depression only increased the risk of knee OA (KOA) (OR = 1.25, 95%CI: 1.10-1.42, p = 6.46 × E - 4). Depression could potentially increase the risk of spondyloarthritis (OR = 1.52, 95%CI: 1.19-1.94, p ≤ 8.94 × E - 4). CONCLUSION: There is a bidirectional causal relationship of depression with OA. However, depression only augments the risk of developing KOA. Depression may increase the risk of spondyloarthritis and gout.

Single-cell and genome-wide Mendelian randomization identifies causative genes for gout.

BACKGROUND: Gout is a prevalent manifestation of metabolic osteoarthritis induced by elevated blood uric acid levels. The purpose of this study was to investigate the mechanisms of gene expression regulation in gout disease and elucidate its pathogenesis. METHODS: The study integrated gout genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and methylation quantitative trait loci (mQTL) data for analysis, and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and gout. RESULTS: We identified 17 association signals for gout at unique genetic loci, including four genes related by protein-protein interaction network (PPI) analysis: TRIM46, THBS3, MTX1, and KRTCAP2. Additionally, we discerned 22 methylation sites in relation to gout. The study also found that genes such as TRIM46, MAP3K11, KRTCAP2, and TM7SF2 could potentially elevate the risk of gout. Through a Mendelian randomization (MR) analysis, we identified three proteins causally associated with gout: ADH1B, BMP1, and HIST1H3A. CONCLUSION: According to our findings, gout is linked with the expression and function of particular genes and proteins. These genes and proteins have the potential to function as novel diagnostic and therapeutic targets for gout. These discoveries shed new light on the pathological mechanisms of gout and clear the way for future research on this condition.

Diastolic and systolic blood pressure and gout: a Mendelian randomization study.

Background: Although there is solid epidemiological evidence supporting the connection between hypertension and gout, little has been said about the relationship between diastolic and systolic blood pressure and gout, the causal relationship and direction associated are uncertain, so we aim to research the causal relationship between diastolic and systolic blood pressure and gout. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effect between 2 blood pressure phenotypes (including diastolic blood pressure and systolic blood pressure) and 5 gout phenotypes (including gout, drug-induced gout, idiopathic gout, unspecified gout, and strictly defined gout) using genome-wide association study statistics. The inverse variance weighting method was used to generate the main results, while sensitivity analyses using MR-Egger, weighted median, Cochran's Q test, Egger intercept test, and leave-one-out analysis, were performed to assess the stability and reliability of the results. Results: After the screening, we found a causal relationship between diastolic blood pressure and gout, idiopathic gout, unspecified gout, and strictly defined gout, and a causal relationship between systolic blood pressure and gout, idiopathic gout, unspecified gout, and strictly defined gout. Conclusion: From a genetic predisposition, controlling blood pressure may reduce the risk of gout.

Association between combined exposure to ambient air pollutants, genetic risk, and incident gout risk: A prospective cohort study in the UK Biobank.

BACKGROUND: Limited research has been conducted on the association between long-term exposure to air pollutants and the incidence of gout. OBJECTIVES: This study aims to assess the individual and combined effects of prolonged exposure to five air pollutants (NO2, NOx, PM10, PMcoarse and PM2.52) on the incidence of gout among 458,884 initially gout-free participants enrolled in the UK Biobank. METHODS: Employing a land use regression model, we utilized an estimation method to ascertain the annual concentrations of the five air pollutants. Subsequently, we devised a weighted air pollution score to facilitate a comprehensive evaluation of exposure. The Cox proportional hazards model was utilized to investigate the association between ambient air pollution and gout risk. Interaction and stratification analyses were conducted to evaluate age, sex, BMI, and genetic predisposition as potential effect modifiers in the air pollution-gout relationship. Furthermore, mediation analyses were conducted to explore the potential involvement of biomarkers in mediating the association between air pollution and gout. RESULTS: Over a median follow-up time of 12.0 years, 7,927 cases of gout were diagnosed. Significant associations were observed between the risk of gout and a per IQR increase in NO2 (HR3: 1.05, 95 % CI4: 1.02-1.08, p = 0.003), NOx (HR: 1.04, 95 % CI: 1.01-1.06, p = 0.003), and PM2.5 (HR: 1.03, 95 % CI: 1.00-1.06, p = 0.030). Per IQR increase in the air pollution score was associated with an elevated risk of gout (p = 0.005). Stratified analysis revealed a significant correlation between the air pollution score and gout risk in participants ≥60 years (HR: 1.05, 95 % CI: 1.02-1.09, p = 0.005), but not in those <60 years (p = 0.793), indicating a significant interaction effect with age (p-interaction=0.009). Mediation analyses identified five serum biomarkers (SUA:15.87 %, VITD: 5.04 %, LDLD: 3.34 %, GGT: 1.90 %, AST: 1.56 %5) with potential mediation effects on this association. CONCLUSIONS: Long-term exposure to air pollutants, particularly among the elderly population, is associated with an increased risk of gout. The underlying mechanisms of these associations may involve the participation of five serum biomarkers.

Large-scale cross-ancestry genome-wide meta-analysis of serum urate.

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.

Identification of potential biomarkers of gout through weighted gene correlation network analysis.

Background: Although hyperuricemia is not always associated with acute gouty arthritis, uric acid is a significant risk factor for gout. Therefore, we investigated the specific mechanism of uric acid activity. Methods: Using the gout-associated transcriptome dataset GSE160170, we conducted differential expression analysis to identify differentially expressed genes (DEGs). Moreover, we discovered highly linked gene modules using weighted gene coexpression network analysis (WGCNA) and evaluated their intersection. Subsequently, we screened for relevant biomarkers using the cytoHubba and Mcode algorithms in the STRING database, investigated their connection to immune cells and constructed a competitive endogenous RNA (ceRNA) network to identify upstream miRNAs and lncRNAs. We also collected PBMCs from acute gouty arthritis patients and healthy individuals and constructed a THP-1 cell gout inflammatory model, RT-qPCR and western blotting (WB) were used to detect the expression of C-X-C motif ligand 8 (CXCL8), C-X-C motif ligand 2 (CXCL2), and C-X-C motif ligand 1 (CXCL1). Finally, we predicted relevant drug targets through hub genes, hoping to find better treatments. Results: According to differential expression analysis, there were 76 upregulated and 28 downregulated mRNAs in GSE160170. Additionally, WGCNA showed that the turquoise module was most strongly correlated with primary gout; 86 hub genes were eventually obtained upon intersection. IL1ß, IL6, CXCL8, CXCL1, and CXCL2 are the principal hub genes of the protein-protein interaction (PPI) network. Using RT-qPCR and WB, we found that there were significant differences in the expression levels of CXCL8, CXCL1, and CXCL2 between the gouty group and the healthy group, and we also predicted 10 chemicals related to these proteins. Conclusion: In this study, we screened and validated essential genes using a variety of bioinformatics tools to generate novel ideas for the diagnosis and treatment of gout.

CAUSAL ROLES OF SERUM URIC ACID LEVELS AND GOUT IN SEPSIS: A MENDELIAN RANDOMIZATION STUDY.

ABSTRACT: Objective: Several epidemiological studies have identified a potential link between serum uric acid (UA), gout, and sepsis. The primary objective of this study is to delve deeper into this connection, investigating the causal effect of UA and gout on sepsis by applying Mendelian randomization (MR). Methods: The causal relationship was analyzed using data from Genome-Wide Association Study (GWAS). Inverse variance weighting (IVW) was used as the main analysis method. Three complementary methods were used for our MR analysis, which included the MR-Egger regression method, the weighted median method, the simple median method. Horizontal pleiotropy was identified by MR-Egger intercept test. Cochran's Q statistics were employed to assess the existence of instrument heterogeneity. The leave-one-out method was used as a sensitivity analysis. Results: The IVW results indicated that there was a positive causal relationship between UA and sepsis (critical care) (odds ratio [OR] = 0.24, 95% confidence interval [CI]: 0.04 to 0.43, P = 0.018, F = 4,291.20). There was no significant association between UA and sepsis (28-day death in critical care) (OR = 0.10, 95% CI = -0.29 to 0.50, P = 0.604). There was no significant association between gout and sepsis (critical care) (OR = 0.85, 95% CI = -4.87 to 6.57, P = 0.771), and sepsis (28-day death in critical care) (OR = -6.30, 95% CI = -17.41 to 4.81, P = 0.267). Horizontal pleiotropy was absent in this study. The results were robust under all sensitivity analyses. Conclusion: The study revealed that elevated UA levels were causally linked with sepsis (critical care). No causal relationship had been found between UA and sepsis (28-day death in critical care), as well as between gout and sepsis.

The gout epidemic in French Polynesia: a modelling study of data from the Ma'i u'u epidemiological survey.

BACKGROUND: Gout is the most common cause of inflammatory arthritis worldwide, particularly in Pacific regions. We aimed to establish the prevalence of gout and hyperuricaemia in French Polynesia, their associations with dietary habits, their comorbidities, the prevalence of the HLA-B*58:01 allele, and current management of the disease. METHODS: The Ma'i u'u survey was epidemiological, prospective, cross-sectional, and gout-focused and included a random sample of adults from the general adult population of French Polynesia. It was conducted and data were collected between April 13 and Aug 16, 2021. Participants were randomly selected to represent the general adult population of French Polynesia on the basis of housing data collected during the 2017 territorial census. Each selected household was visited by a research nurse from the Ma'i u'u survey who collected data via guided, 1-h interviews with participants. In each household, the participant was the individual older than 18 years with the closest upcoming birthday. To estimate the frequency of HLA-B*58:01, we estimated HLA-B haplotypes on individuals who had whole-genome sequencing to approximately 5× average coverage (mid-pass sequencing). A subset of individuals who self-reported Polynesian ancestry and not European, Chinese, or other ancestry were used to estimate Polynesian-ancestry specific allele frequencies. Bivariate associations were reported for weighted participants; effect sizes were estimated through the odds ratio (OR) of the association calculated on the basis of a logistic model fitted with weighted observations. FINDINGS: Among the random sample of 2000 households, 896 participants were included, 140 individuals declined, and 964 households could not be contacted. 22 participants could not be weighted due to missing data, so the final weighted analysis included 874 participants (449 [51·4%] were female and 425 [48·6%] were male) representing the 196 630 adults living in French Polynesia. The estimated prevalence of gout was 14·5% (95% CI 9·9-19·2), representing 28 561 French Polynesian adults, that is 25·5% (18·2-32·8) of male individuals and 3·5% (1·0-6·0) of female individuals. The prevalence of hyperuricaemia was estimated at 71·6% (66·7-76·6), representing 128 687 French Polynesian adults. In multivariable analysis, age (OR 1·5, 95% CI 1·2-1·8 per year), male sex (10·3, 1·8-60·7), serum urate (1·6, 1·3-2·0 per 1 mg/dL), uraturia (0·8, 0·8-0·8 per 100 mg/L), type 2 diabetes (2·1, 1·4-3·1), BMI more than 30 kg/m2 (1·1, 1·0-1·2 per unit), and percentage of visceral fat (1·7, 1·1-2·7 per 1% increase) were associated with gout. There were seven heterozygous HLA-B*58:01 carriers in the full cohort of 833 individuals (seven [0·4%] of 1666 total alleles) and two heterozygous carriers in a subset of 696 individuals of Polynesian ancestry (two [0·1%]). INTERPRETATION: French Polynesia has an estimated high prevalence of gout and hyperuricaemia, with gout affecting almost 15% of adults. Territorial measures that focus on increasing access to effective urate-lowering therapies are warranted to control this major public health problem. FUNDING: Variant Bio, the French Polynesian Health Administration, Lille Catholic University Hospitals, French Society of Rheumatology, and Novartis.

Exploring the causal associations of micronutrients on urate levels and the risk of gout: A Mendelian randomization study.

BACKGROUND & AIMS: Growing evidence has indicated a potential association between micronutrient levels, urate levels, and the risk of gout. However, the causal association underlying these associations still remains uncertain. Previous observational studies and randomized controlled trials investigating the association between micronutrients, urate levels, and the risk of gout have been limited in their scope and depth. The aim of this study was to utilize Mendelian randomization (MR) to investigate the causal associations between genetically predicted micronutrient levels, urate levels, and the risk of gout. METHODS: In this study, we conducted a comprehensive examination of 10 specific micronutrients (vitamin B6, vitamin B12, vitamin C, vitamin D, folate, calcium, iron, copper, zinc, and selenium) as potential exposures. Two-sample MR analyses were performed to explore their causal associations with urate levels and the risk of gout. In these analyses, gout data were collected from the Global Biobank Meta-Analysis Initiative (N = 1,069,839, N cases = 30,549) and urate levels data from CKDGen Consortium (N = 288,649) by utilizing publicly available summary statistics from independent cohorts of European ancestry. We performed inverse-variance weighted MR analyses as main analyses, along with a range of sensitivity analyses, such as MR-Egger, weighted median, simple mode, weighted mode, Steiger filtering, MR-PRESSO, and Radial MR analysis, to ensure the robustness of our findings. RESULTS: The results of our study indicate that there were negative associations between serum vitamin B12 and urate levels, as well as serum folate and the risk of gout. Specifically, we found a negative association between vitamin B12 levels and urate levels, with a ß coefficient of -0.324 (95% CI -0.0581 to -0.0066, P = 0.0137) per one standard deviation (SD) increase. Similarly, a negative association was observed between folate levels and gout risk, with an odds ratio of 0.8044 (95% CI 0.6637 to 0.9750, P = 0.0265) per one SD increase. On the other hand, we identified positive associations between serum calcium levels and both urate levels and the risk of gout. Specifically, there was a positive association between serum calcium levels and urate levels (ß coefficient: 0.0994, 95% CI 0.0519 to 0.1468, P = 4.11E-05) per one SD increase. Furthermore, a positive association was found between serum calcium levels and the risk of gout, with an odds ratio of 1.1479 (95% CI 1.0460 to 1.2598, P = 0.0036) per one SD increase. These findings were robust in extensive sensitivity analyses. By employing MR-PRESSO and Radial MR to eliminate outliers, the observed associations have been reinforced. No clear associations were found between the other micronutrients and the urate levels, as well as the risk of gout. CONCLUSION: Our findings provided evidence that there were negative associations between serum vitamin B12 and urate levels, as well as serum folate and the risk of gout, while positive associations existed between the serum calcium levels and urate levels, as well as the risk of gout.

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.