Risk Of Gout Research Articles

Assessing the causal associations of atrial fibrillation with serum uric acid level and gout: insights from a bidirectional mendelian randomization study.

Numerous observational studies consistently highlight a strong association between serum uric acid (sUA) levels and atrial fibrillation (AF). However, the causal relationship and the direction of this association remain elusive, despite extensive research efforts. This study aimed to investigate the bidirectional causal relationships between sUA, gout, and the risk of AF using the two-sample Mendelian randomization (MR) approach. We conducted a comprehensive analysis utilizing publicly available genome-wide association studies (GWAS) summary statistics, employing stringent criteria to meticulously select genetic variants associated with sUA, gout, and AF. Our primary analytical approach was the inverse-variance weighted (IVW) method, complemented by some sensitivity analyses, including MR-Egger, weighted median, simple mode, and weighted mode, to estimate the causal effects. To identify potential violations, we conducted Egger regression and leave-one-SNP-out analyses. We assessed the strength of instrumental variables using F values to evaluate weak instruments. Additionally, we referenced the Phenoscanner database to exclude single nucleotide polymorphisms (SNPs) associated with confounding factors or outcomes. Our forward Mendelian randomization analysis suggests that there is no causal relationship between UA levels/gout from different populations and the risk of AF [IVW OR 1.03, 95% CI: 0.97-1.08; p = 0.335; IVW OR 0.99, 95% CI: 0.97-1.02; p = 0.583; and IVW OR 1.07, 95% CI: 0.84-1.37; p = 0.575], respectively. We did not detect significant heterogeneity or potential pleiotropy, and we also excluded the possibility of weak instrumental variables. Furthermore, we did not find any reverse causal effects of AF on sUA levels and gout risk. Our findings challenge the widely held belief that lowering urate levels is uniformly effective in reducing the risk of atrial fibrillation (AF). Our study fails to substantiate the existence of a causal link between uric acid (UA) levels or gout and the development of AF, regardless of direction.

Weight Loss After Receiving Anti‐Obesity Medications and Gout Among Individuals With Overweight and Obese: A Population‐Based Cohort Study

ObjectiveWeight loss is conditionally recommended for gout management; however, its impact on incident gout and recurrent gout flares among individuals who were overweight and obese remains unknown. We investigate the relationship between weight loss rate following treatment with anti‐obesity medications and the risk of incident gout and recurrent gout flares among individuals who were overweight or obese.MethodsUsing data from the Health Improvement Network, we selected individuals aged 18 and older who were overweight or obese and started anti‐obesity medication. We emulated a target trial to examine the association of different weight loss rates, slow (2%–5%), moderate (5%–10%), or fast (≥10%), within the first year of treatment with incident gout and recurrent gout flares during a 5 year follow‐up period.ResultsAmong 131,000 participants without gout being treated with orlistat, the 5‐year risk of incident gout was 1.6% for those with weight gain or stability, compared with 1.5%, 1.3%, and 1.2% for those with slow, moderate, and fast weight loss, respectively. Compared with the group with weight gain or stability, the hazard ratios were 0.91 (95% confidence interval [CI] 0.81–1.01), 0.82 (95% CI 0.72–0.92), and 0.73 (95% CI 0.62–0.86) for those with a slow, moderate, and fast rate of weight loss, respectively. Similar results were observed for the recurrent gout flares among 3,847 individuals with overweight or obese with gout treated with orlistat.ConclusionA higher rate of weight loss after receiving treatment with orlistat within 1 year was associated with lower risks of incident gout and lower rates of recurrent gout flares among overweight or obese people.image

Exploring the associations and potential mediators between lipid biomarkers and the risk of developing gout: NHANES 2007–2018

BackgroundGout stands as a prevailing manifestation of inflammatory arthritis. While it is linked to several well-established risk factors, the associations between lipid profiles and the risk of gout remain unclear.MethodsThis research involved National Health and Nutrition Examination Survey data (2007–2018). The cardiometabolic index, which incorporates the Triglycerides (TG)/High-density lipoprotein cholesterol (HDL) ratio and waist to height ratio (WHtR), was used to assess lipid profiles and metabolic health. Multivariate logistic regression analysis, propensity score matching, and mediation analyses were utilized to evaluate the associations of lipid profiles and the cardiometabolic index with the risk of developing gout.ResultsAmong 11,032 participants, each 1-unit increase in TG levels was associated with a 65% increase in the odds of developing gout before matching [1.65 (1.15–2.38), P = 0.007] and a 155% increase in the odds of developing gout after matching [2.55 (1.59–4.09), P = 0.007]. Each 1-unit increase in the cardiometabolic index was linked to an 81% increase in the odds of developing gout before matching [1.81 (1.22–2.70), P = 0.004] and a 215% increase in the odds of developing gout after matching [3.15 (1.84–5.40), P < 0.001]. The participants with HDL levels in the third quartile presented a 35% reduction in gout risk relative to those with HDL levels in the first quartile before matching [0.65 (0.46–0.92), P = 0.014] and a 51% reduction in gout risk after matching [0.49 (0.32–0.75), P < 0.001]. Mediation analyses revealed that BMI, WHtR, and homeostatic model assessment for insulin resistance (HOMA-IR) mediated the relationships between TG levels and the risk of developing gout at 18.75%, 24.28%, and 5.35%, respectively. For the association between HDL levels and the risk of developing gout, the mediating effects of BMI, WHtR, leukocytes, γ-glutamyltransferase (in those with HDL < 56 mmol/L), and HOMA-IR were 57.98%, 69.03%, 8.77%, 5.18%, and 11.14%, respectively.ConclusionThis study reveals the relationship between lipid profiles and the risk of developing gout. Regularly checking TG and HDL levels and actively managing obesity, insulin resistance, oxidative stress and inflammation are important for lowering the risk of developing gout.

Development of gout in people with asymptomatic hyperuricemia: study protocol for a 5-year prospective cohort

IntroductionThe central biochemical cause of gout is hyperuricemia (elevated serum urate levels). Ultrasound features of monosodium urate (MSU) crystal deposition are common in people with asymptomatic hyperuricemia. However, it is...

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Some diabetes drugs ‘linked to lower risk of kidney stones and gout’, study finds

Association between hearing loss and gout based on National Health and Nutrition Examination Survey and Mendelian randomization analysis

Hearing loss(HL) represents a significant public health concern. This study aimed to determine the association between hearing loss and gout and to elucidate the underlying causative mechanisms. Data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES) and Mendelian randomization (MR) basic databases. Initially, baseline characteristics of individuals with and without gout were compared. A nonlinear relationship between pure tone audiometry (PTA) values and gout prevalence was confirmed through restricted cubic spline (RCS) curve analysis. Subsequently, hearing loss was categorized into different levels based on PTA values, and multiple logistic regression analysis was employed to calculate the impact of varying degrees of hearing loss on the risk of gout. Finally, MR analysis was conducted to further elucidate the causal relationship between hearing loss and gout. A total of 3,258 individuals were included in this study, with a gout prevalence of 3.7%. Significant differences were observed between the gout group and the non-gout group in variables such as age, gender, blood uric acid level, BMI, hypertension, and diabetes. RCS curve analysis revealed a significant nonlinear relationship between PTA values and gout risk, particularly when PTA values exceed a specific threshold, where the curve flattens. Based on different levels of hearing loss derived from PTA values, multiple logistic regression analysis demonstrated that mild and moderate hearing loss significantly increased the risk of gout, remaining statistically significant after adjusting for covariates (odds ratio (OR) = 2.10–3.48, P < 0.05). MR analysis further confirmed the causal relationship between hearing loss and gout. Inverse variance weighting (IVW) was employed as the primary method, revealing that both individuals with hearing difficulties (OR = 0.98, 95% confidence interval (CI) 0.96–0.999, P = 0.012) and those without hearing impairment (OR = 1.02, 95% CI 1.01–1.04, P = 0.012) exhibited a significant causal relationship with gout. Goodness-of-fit tests and sensitivity analyses were used to verify the reliability of the results. Hearing loss has a significant causal relationship with an increased risk of gout, providing a new perspective for the prevention and management of gout. Focused attention and prompt treatment of hearing loss, particularly mild and moderate hearing loss, may significantly reduce the risk of developing gout.

Association between gout and cancers: A systematic review and meta-analysis.

This study aimed to investigate the association between gout and cancer risk. This study was registered with the Prospective Registry for International Systematic Reviews (ID: CRD42023465587). We searched PubMed, Embase, Scopus, Cochrane, and Web of Science databases for studies related to gout and cancer risk, with a timeframe from the date the database was created to September 2023. We assessed the methodological quality of the included studies using the Newcastle-Ottawa scale and assessed heterogeneity between studies using the I2 statistic. Depending on the heterogeneity, we calculated pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) using fixed-effects or random-effects models. In addition, we performed sensitivity analyses and publication bias tests. In this study, we conducted a meta-analysis of 6 studies encompassing a total of 1279,804 participants. Our analysis revealed that individuals with gout are at a heightened risk of developing cancer in general (HR = 1.18, 95% CI = 1.04-1.34, P < .001). Moreover, specific types of cancer displayed a significant correlation with gout, including gastric cancer (HR = 1.31, 95% CI = 1.07-1.62, P = .012), liver cancer (HR = 1.24, 95% CI = 1.01-1.52, P < .001), lung cancer (HR = 1.26, 95% CI = 1.03-1.53, P = .001), and bladder cancer (HR = 1.57, 95% CI = 1.02-2.41, P < .001). Furthermore, gout exhibited a marginally increased risk for other cancer types, such as head and neck cancer and esophageal cancer, although these associations did not attain statistical significance. Our study suggests that gout is a risk factor for cancer, especially for stomach, liver, lung, and bladder cancers. Patients with gout have an increased risk of developing overall cancers, lung cancer, liver cancer, stomach cancer, and bladder cancer. However, more high-quality epidemiologic studies are needed to explore the association between gout and individual cancers more accurately.

Lowering the risk of hyperuricemia and gout is associated with ideal cardiovascular health

BackgroundHyperuricemia (HUA) and gout have been demonstrated as independent risk factors for cardiovascular disease. The relationship between the recently updated Life’s Essentials 8 (LE8), which measures ideal cardiovascular health (CVH), and HUA and gout remains unclear. The aim of this study was to explore the relationship between CVH and the prevalence of HUA and gout among a nationally representative sample of US adults.MethodsThis study utilized cross-sectional analysis of data from the National Health and Nutrition Examination Survey (NHANES) for the years 2007 to 2018. The CVH scores and their corresponding components were defined according to the guidelines established by the American Heart Association. The association between the LE8 score and both HUA and gout was assessed using weighted multivariable logistic and restricted cubic spline (RCS) models.ResultsAmong the 21,155 participants aged 20 years and older, the prevalence of HUA was 17.20% (95% CI, 16.05–18.36%), and the prevalence of gout was 3.58% (95% CI, 3.13–4.02%). After adjusting for potential confounders, compared to participants exhibiting low CVH, the multivariable adjusted odds ratio (OR) for HUA was 0.65 (95% CI, 0.56–0.75) in those with moderate CVH, and 0.25 (95% CI, 0.20–0.31) in those with high CVH. Additionally, compared to participants with low CVH, the multivariable adjusted OR for gout was 0.66 (95% CI, 0.53–0.81) in those with moderate CVH and 0.32 (95% CI, 0.20–0.50) in those with high CVH. The LE8 score exhibited a significant nonlinear negative association with HUA and linear negative correlation with gout. In subgroup analyses focusing on HUA, significant interactions were observed between LE8 score and age, sex, and CKD (P for interaction < 0.05). For gout, only a significant interaction between LE8 score and sex was observed (P for interaction < 0.05).ConclusionsAmong adults, there was a significant negative correlation between LE8 score and the prevalence of HUA and gout. Maintaining an ideal CVH may be beneficial in reducing the burden of HUA and gout.

The causal association between immune cells and gout: A bidirectional two-sample Mendelian randomization study.

Gout, a metabolic disorder, is increasingly being linked to immune cells. However, the causal relationships between these factors remain unclear. Our study aimed to elucidate the causal relationship between immune cells and gout. Our study used 2-sample Mendelian randomization (MR) to explore the causal relationship between immune cells and gout. It is noteworthy that we utilized 5 methods MR-Egger, weighted median, inverse variance weighted, weighted mode, and simple mode to ensure the reliability of the results. Comprehensive sensitivity analyses were performed to verify the robustness, heterogeneity, and horizontal pleiotropy of the results. After false discovery rate correction (PFDR <0.20), 3 immunophenotypes were identified: one in the B cell panel, one in the regulatory T cells panel, and another in the T lymphocytes, B lymphocytes, Natural Killer cells panel. Among them, 2 immunophenotypes (CD4-CD8-T cell absolute count and CD25 on IgD + CD24 + B cell) increased the risk of developing gout, whereas the other one immunophenotype (CD45RA + CD28- CD8 + T cell %T cell) decreased the risk of gout. Subsequently, we did not observe heterogeneity and horizontal pleiotropy stable in these data through comprehensive sensitivity analyses. Furthermore, we identified some positive results in reverse MR analysis, but after false discovery rate correction (PFDR <0.20), no significant results were detected. Our study revealed causal relationships between immune cells and gout, providing novel insights into the prevention and treatment of gout.

Prediagnostic Amino Acid Metabolites and Risk of Gout, Accounting for Serum Urate: Prospective Cohort Study and Mendelian Randomization.

Our objective was to prospectively investigate prediagnostic population-based metabolome for risk of hospitalized gout (ie, most accurate, severe, and costly cases), accounting for serum urate. We conducted prediagnostic metabolome-wide analyses among 249,677 UK Biobank participants with nuclear magnetic resonance metabolomic profiling (N = 168 metabolites, including eight amino acids) from baseline blood samples (2006-2010) without a history of gout. We calculated multivariable hazard ratios (HRs) for hospitalized incident gout, before and after adjusting for serum urate levels; we included patients with nonhospitalized incident gout in a sensitivity analysis. Potential causal effects were evaluated with two-sample Mendelian randomization. Correcting for multiple testing, 107 metabolites were associated with incidence of hospitalized gout (n = 2,735) before urate adjustment, including glycine and glutamine (glutamine HR 0.64, 95% confidence interval [CI] 0.54-0.75, P = 8.3 × 10-8; glycine HR 0.69, 95% CI 0.61-0.78, P = 3.3 × 10-9 between extreme quintiles), and glycoprotein acetyls (HR 2.48, 95% CI 2.15-2.87, P = 1.96 × 10-34). Associations remained significant and directionally consistent following urate adjustment (HR 0.83, 95% CI 0.70-0.98; HR 0.86, 95% CI 0.76-0.98; HR 1.41, 95% CI 1.21-1.63 between extreme quintiles), respectively; corresponding HRs per SD were 0.91 (95% CI 0.86-0.97), 0.94 (95% CI 0.91-0.98), and 1.10 (95% CI 1.06-1.14). Findings persisted when including patients with nonhospitalized incident gout. Mendelian randomization corroborated their potential causal role on hyperuricemia or gout risk; with change in urate levels of -0.05 mg/dL (95% CI -0.08 to -0.01) and -0.12 mg/dL (95% CI -0.22 to -0.03) per SD of glycine and glutamine, respectively, and odds ratios of 0.94 (95% CI 0.88-1.00) and 0.81 (95% CI 0.67-0.97) for gout. These prospective findings with causal implications could lead to biomarker-based risk prediction and potential supplementation-based interventions with glycine or glutamine.

The association between triglyceride glucose index and gout: a cross-sectional analysis based on NHANES 2007–2018

BackgroundThe triglyceride glucose (TyG) index, defined as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2], provides insights into overall metabolic status. However, the association between the TyG index and gout has not been investigated. Therefore, this study explored the correlation between the TyG index and gout.MethodsUsing data from the National Health and Nutrition Examination Survey, which was conducted from 2007 to 2018, this study investigated the relationship between the TyG index and gout. Demographic data and potential risk factors were analyzed and compared using t tests for continuous data and chi-square tests for categorical data. Logistic regression and subgroup analysis were performed to examine the association between the TyG index and gout.ResultsA total of 14,924 participants were enrolled, among whom 726 (4.86%) were diagnosed with gout. Without controlling for any covariates, a significant positive correlation was observed between an elevated TyG index and increased risk of gout, with an odds ratio (OR) of 2.07 and a 95% confidence interval (CI) ranging from 1.76 to 2.43. After full adjustment, this association remained statistically significant, with an adjusted OR of 1.43 and a 95% CI from 1.14 to 1.80. Subgroup analyses revealed significant interactions, particularly for females (OR = 2.55; 95% CI: 2.00-3.26), individuals with no military service history (OR = 2.15; 95% CI: 1.66–2.43), and those without diabetes (OR = 2.00; 95% CI: 1.64–2.43).ConclusionA positive correlation was observed between the TyG index and gout. Consequently, further large-scale prospective studies are warranted for a comprehensive analysis of the role of the TyG index in gout.

Cardiovascular risk according to genetic predisposition to gout, lifestyle and metabolic health across prospective European and Korean cohorts

ObjectiveRecent studies have reported that gout is associated with a risk of cardiovascular disease (CVD) later in life. However, the predictive value of genetic predisposition to gout combined with lifestyle...

Gout risk in adults with pre-diabetes initiating metformin

ObjectiveDespite the strong association between gout and pre-diabetes, the role of metformin in gout among individuals with pre-diabetes remains uncertain. We compared the incidence rates of gout in adults with...

Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare.

There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches. The single-cell RNA sequencing (scRNA-seq), large-scale genome-wide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data. The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that NLRP3 was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, IER3 was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized. Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases.

The Effect of Tolvaptan on Metabolism and Electrolyte Homeostasis in Patients with Heart Failure: A Systematic Review and Meta-Analysis.

This study aimed to investigate the effect of tolvaptan on metabolism and electrolyte homeostasis in patients with heart failure (HF). Literature databases, such as PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure, VIP, and WanFang Data, were systematically searched for relevant trials from inception to November 4, 2023. We used the fixed effect model to combine the effect sizes and used I2 to test heterogeneity. Funnel plots were plotted to assess publication bias. 16 studies were eligible for further analysis. No significant differences were identified in the incidence of hyperuricemia between the tolvaptan group and the placebo group (odds ratio (OR) = 1.23, 95% confidence interval (CI) = 0.97 to 1.55, p = 0.09). Tolvaptan decreased the levels of blood uric acid compared to traditional diuretics (mean difference (MD) = -82.8, 95% CI = -96.48 to -69.13, p < 0.00001). There was no significant difference in hypernatremia (OR = 1.62, 95% CI = 0.66 to 3.96, p = 0.29) and hyperkalemia (OR = 1.17, 95% CI = 0.93 to 1.48, p = 0.18) between the tolvaptan and control groups. Tolvaptan reduced the level of blood uric acid compared to conventional diuretics, and could be used as a substitute for traditional diuretics for HF patients with a high risk of gout.

Bidirectional Mendelian randomization highlights causal relationships between circulating INHBC and multiple cardiometabolic diseases and traits.

Human genetic and transgenic mouse studies have highlighted a potential liver-adipose tissue endocrine axis, involving activin C (Act-C) and/or Act-E and ALK7, influencing fat distribution and systemic metabolism. We investigated the bidirectional effects between circulating INHBC, which homodimerizes into Act-C, and adiposity traits, insulin resistance, inflammation, and cardiometabolic disease risk. Additionally, we examined if Act-C is an ALK7 ligand in human adipocytes. We used Mendelian randomization and in vitro studies in immortalized human abdominal and gluteal adipocytes. Circulating INHBC was causally linked to reduced lower-body fat, dyslipidaemia, and increased risks of coronary artery disease (CAD) and non-alcoholic fatty liver disease (NAFLD). Conversely, upper-body fat distribution, obesity, hypertriglyceridemia, subclinical inflammation, and type 2 diabetes positively impacted plasma INHBC levels. Mechanistically, an atherogenic lipid profile may partly explain the INHBC-CAD link, while inflammation and hypertriglyceridemia may partly explain how adiposity traits affect circulating INHBC. Phenome-wide Mendelian randomization showed weak causal relationships between higher plasma INHBC and impaired kidney function and higher gout risk. In human adipocytes, recombinant Act-C activated SMAD2/3 signaling via ALK7 and suppressed lipolysis. In summary, INHBC influences systemic metabolism by activating ALK7 in adipose tissue and may serve as a drug target for atherogenic dyslipidemia, CAD, and NAFLD.

Role of HIF1A gene polymorphisms with serum uric acid and HIF-1α levels in monosodium urate crystal-induced arthritis.

Gouty arthritis is a metabolic disease characterized by the deposition of monosodium urate crystals in the joints, which triggers the release of interleukin-1β (IL-β) by activating the NLRP3 inflammasome. Hypoxia-inducible factor-1α (HIF-1α) is a transcription factor involved in IL-β production and as a regulator of NLRP3. The aims were to analyze the association of HIF1A rs11549465, rs11549467, and rs2057482 variants in patients with gouty arthritis, and to evaluate the correlation between urate and HIF-1α levels according to the associated genotypes. Cases and controls were genotyped using TaqMan probes, and urate and HIF-1α levels were quantified. Data were analyzed using SPSS v21 software and P-values < 0.05 were considered statistically significant. Urate and HIF-1α levels were higher in patients than in controls (P < 0.05). Under the three inheritance models (codominant, dominant, and recessive), the AA genotype of the rs11549467 variant was associated with gout risk (OR = 5.74, P = 0.009, OR = 3.33, P = 0.024, and OR = 9.09, P = 0.003, respectively). There were significant differences in the distribution of serum levels of both HIF-1α (P < 0.0001) and urate (P = 0.016) according to the genotypes of the rs11549467 variant. These results suggest that the HIF1A rs11549467 variant may play a key role in the pathogenesis of gouty arthritis. Key Points • The pathogenesis of gouty arthritis involves the HIF1A gene. • In patients with gout, the AA genotype of the rs11549467 (HIF1A) variant is associated with increased serum levels of urate and HIF-1α. • HIF-1α is involved in the regulation of IL-1β and NLRP3.

Risk factors for nephrolithiasis formation: an umbrella review.

Nephrolithiasis is prevalent and burdensome worldwide. At present, evidence on the risk factors for nephrolithiasis is unconsolidated and the associations remain uncertain. The authors systematically evaluate the robustness of the meta-analytic evidence and aid more reliable interpretations of the epidemiological relationships. The authors conducted a comprehensive review of the meta-analyses, screened the included studies with the aid of the AMSTAR 2 evaluation tool, and then used R (4.1.1) software to perform data analysis to evaluate the association between candidate risk factors and kidney stones, and evaluated the credibility of the evidence of the association between risk factors and kidney stones according to the GRADE classification, and finally obtained the strength and effectiveness of the association. The authors finally included 17 meta-analyses regarding 46 risk factors, 34 of which (73.9%) showed statistically significant association with nephrolithiasis. Among the significant associations, the authors found that waist circumference, BMI, dietary intake and fructose intake were positively correlated with the occurrence and development of nephrolithiasis. Caffeine, dietary fiber and DASH-diet showed a tendency to reduce kidney stones. Interestingly, calcium supplementation, dietary calcium, and vitamin D, which are widely believed to be responsible for stone formation, made no difference or even reduced the risk of nephrolithiasis. The authors' study demonstrates the suggestive causal (central obesity, type 2 diabetes, gout, dietary sodium, fructose intake and higher temperatures) risk factors of nephrolithiasis. The authors also demonstrate the suggestive causal (coffee/alcohol/beer intake, dietary calcium and DASH-diet) protective factors of nephrolithiasis. To provide epidemiological basis for the treatment and prevention of nephrolithiasis.

Specific blood metabolite associations with Gout: a Mendelian randomization study.

Gout, common metabolic disorders, have poorly understood links with blood metabolites. Exploring these relationships could enhance clinical prevention and treatment strategies. We applied bidirectional two-sample Mendelian randomization (MR) analysis, using data from a genome-wide association (GWAS) study of 486 blood metabolites. Gout data was obtained from FinnGen R8 (7461 gout and 221,323 control cases). We implemented the inverse variance-weighted (IVW) method for main analytical approach. Extensive heterogeneity, pleiotropy tests, leave-one-out analysis, and reverse MR were conducted to validate the robustness of our findings. Both Bonferroni and False Discovery Rate (FDR) corrections were used to adjust for multiple comparisons, ensuring stringent validation of our results. Initial MR identified 31 candidate metabolites with potential genetic associations to gout. Following rigorous sensitivity analysis, 23 metabolites as potential statistical significance after final confirmation. These included metabolites enhancing gout risk such as X-11529 (OR = 1.225, 95% CI 1.112-1.350, P < 0.001), as well as others like piperine and stachydrine, which appeared to confer protective effects. The analysis was strengthened by reverse MR analysis. Additionally, an enrichment analysis was conducted, suggesting that 1-methylxanthine may be involved in the metabolic process of gout through the caffeine metabolism pathway. Identifying causal metabolites offers new insights into the mechanisms influencing gout, suggesting pathways for future research and potential therapeutic targets.

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.