Assessing the Causal Relationships Between Insulin Resistance and Hyperuricemia and Gout Using Bidirectional Mendelian Randomization

The exploration of the relationship between hyperuricemia, gout and vitamin D deficiency

Our study aims to provide evidence concerning the relationship between hyperuricemia, gout and Vitamin D deficiency by analyzing data from Peking Union Medical College Hospital (PUMCH), the National Health and Nutrition Examination Survey (NHANES) database, and through Mendelian randomization (MR) analyses. Sample 1 involved patients from PUMCH (n = 13,532), and sample 2 involved participants from NHANES (Unweighted n = 22,860; weight n = 182,829,142). Logistic regression and restricted cubic spline analyses were applied to assess above relationship. A two-sample MR analysis was performed using the genome-wide association study summary statistics to identify the causal association between gout and 25-hydroxyvitamin D (25(OH)D). The results from both samples confirmed a positive correlation among hyperuricemia, gout and risk of Vitamin D deficiency. The restricted cubic spline showed positive dose-response relationship between uric acid and risk of Vitamin D deficiency and the minimal threshold of uric acid at 307.5 umol/L and 316.1 umol/L, respectively. Mediation analysis in the sample 2 found that about 29.4% of the total effect of gout on Vitamin D deficiency were mediated by serum uric acid, and 37.1% of which were mediated by body mass index.The results of our MR analysis supported a causal association between gout (IVW β(SE), -0.843 (0.337); P = .0123) and 25(OH)D. Sensitivity analysis and genetic risk scores approach confirmed the robustness and reliability of the above findings. Hyperuricemia and gout are both strong indicators of increased risk of Vitamin D deficiency. Findings highlight the causal effects of gout-associated genetic variants on 25(OH)D.

Uric acid in diabetic microvascular complications: Mechanisms and therapy

Uric acid (UA) is mainly synthesized in the liver, intestine, and vascular endothelium and excreted by the kidney (70 %) and intestine (30 %). Hyperuricemia (HUA) occurs when UA production exceeds excretion. Many studies have found that elevated UA is associated with diabetic microvascular complications (DMC), including diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN). In addition, too high or too low UA levels will promote the occurrence and development of chronic diseases, but the relationship between UA and diabetic microvascular complications (DMC) is not clear. Therefore, the rational treatment of UA in patients with diabetes is essential. In this review, we summarize and discuss the mechanism and treatment of UA and DMC and may provide potential advice for rational drug selection.

Excess Weight Loss at 6 Months Following Laparoscopic Sleeve Gastrectomy Correlates with the Remission of Hyperuricemia

BACKGROUND

Hyperuricemia is a metabolic disorder associated with obesity. Many studies have reported the effect of bariatric surgery on the decrease of serum uric acid level in patients with hyperuricemia. However, since the update of diagnostic criteria of hyperuricemia, the correlation between preoperative body mass index, postoperative weight changes, and the remission of hyperuricemia in patients with obesity after sleeve gastrectomy requires consensus.

METHODS

One hundred and ninety-three patients with obesity and hyperuricemia who underwent laparoscopic sleeve gastrectomy were enrolled. All patients were followed up for 6 months postoperatively. Subgroup analysis was performed using the tertiles of preoperative body mass index, total weight loss, and excess weight loss to investigate the correlation with the remission of hyperuricemia after sleeve gastrectomy.

RESULTS

A total of 193 patients were included in this study. Among them, 123 patients were female and 70 were male. And the mean age was 30.2 ± 7.8 years, preoperative body weight was 116.1 ± 23.3 kg, and the preoperative BMI was 40.5 ± 6.7 kg/m2. 59.1% (114/193) patients achieved remission of hyperuricemia 6 months after sleeve gastrectomy. The TWL% and EWL% were 25.6% ± 5.4% and 75.9% ± 28.2%, respectively. Female patients had a significantly higher remission rate than that of male patients (p < 0.05). Correlations were found between EWL%/preoperative BMI with the remission of hyperuricemia (p < 0.05).

CONCLUSION

Sleeve gastrectomy had a positive effect on the remission of hyperuricemia in patients with obesity. EWL% may play a significant role in the remission of hyperuricemia.

Association between serum uric acid and dyslipidaemia in type 2 diabetes: a cross-sectional study

BACKGROUND

The association between serum uric acid (SUA) and dyslipidaemia is still unclear in patients with type 2 diabetes mellitus (T2DM). This study aimed to examine the association between SUA and dyslipidaemia and to explore whether there is an optimal SUA level corresponding to the lower risk of suffering from dyslipidaemia.

RESEARCH DESIGN AND METHODS

This cross-sectional study included 1036 inpatients with T2DM and the clinical data were extracted from the hospital medical records. Multivariate logistic regression analysis was performed to assess the association between hyperuricaemia and dyslipidaemia. Restricted cubic splines (RCS) analysis was performed to determine the optimal SUA level for the lower risk of dyslipidaemia.

RESULTS

After adjustment for the potential confounders, hyperuricaemia was significantly associated with dyslipidaemia (OR=3.72, 95% CI: 2.28, 6.07) and hypertriglyceridaemia (OR=2.63, 95% CI: 1.68, 4.12). Notably, mediation analysis revealed a significant mediating effect of SUA in this relationship (indirect effect=0.08, p<0.001), elucidating 20.1% of the total relationship.

CONCLUSIONS

Hyperuricaemia was positively associated with dyslipidaemia and hypertriglyceridaemia. SUA mediated the effect of insulin resistance on triglyceride metabolism in patients with T2DM. A potential benefit of stricter control of SUA levels among patients with T2DM is possibly reducing the risk of dyslipidaemia.

Gout and Hyperuricemia: A Narrative Review of Their Comorbidities and Clinical Implications

Gout is the most common form of inflammatory arthritis, caused by the deposition of monosodium urate crystals in the joints due to elevated serum uric acid levels. Its prevalence and associated healthcare burden have been rising in recent decades, a trend expected to continue. It is crucial to recognize that gout and hyperuricemia are not merely causes of painful joint flares, but systemic metabolic disorders linked to a broad spectrum of comorbidities such as cardiovascular diseases, chronic kidney disease, diabetes, insulin resistance, steatotic liver disease, osteoarthritis, and respiratory and eye diseases. Numerous risk factors for gout and hyperuricemia have been identified, with recent research uncovering further associations with other conditions. To optimize patient outcomes, gout and hyperuricemia must be addressed through a holistic approach that accounts for these risk factors while providing comprehensive management of related comorbidities affecting various organ systems. This review summarizes the current knowledge on the risk factors, comorbidities, and clinical implications of gout and hyperuricemia. Future research should focus on improving patient outcomes by tailoring treatments individually and addressing the underlying metabolic comorbidities of gout with multimodal treatment.

Impact of diabetes on the association between serum urate levels and incident dementia: a cohort study in the UK biobank

OBJECTIVES

Diabetes was associated with increased serum urate levels and a higher risk of dementia. However, current evidence regarding the association between serum urate and dementia is controversial.The research gap on how to effectively control urate levels in the population with diabetes still remains. We aim to examine the association of diabetes status and serum urate with dementia incidence, and the differences in this association among participants with different diabetes statuses.

METHODS

A total of 321,896 participants was recruited from the UK Biobank and followed up until 2022. Diabetes status was classified into diabetes, prediabetes and normoglycaemia according to the American Diabetes Association 2023 guideline. Serum urate levels were stratified using gender-specific quartiles of concentrations. All-cause dementia, Alzheimer's disease and vascular dementia were ascertained using the International Classification of Diseases-10th revision (ICD-10). Cox proportional hazards regression models were used to examine the association between serum urate, diabetes status, and dementia incidence.

RESULTS

Of the 321,896 participants (mean age, 57 years old; 43.5% males), 7,087 (2.20%) individuals were diagnosed with dementia during the follow-up period. Diabetes was associated with a 70% 58%, and 134% increased risk for all-cause dementia, Alzheimer's disease, and vascular dementia respectively. Elevated serum urate levels were associated with a lower risk of all-cause and cause-specific dementia regardless of the status of diabetes. Each standard deviation increase in urate concentration was related to a 11% reduced risk for all-cause dementia (HR, 0.89; 95% CI, 0.86 to 0.91), 7% for Alzheimer's disease (HR, 0.93; 95% CI, 0.88 to 0.98), and 12% for vascular dementia (HR, 0.88; 95% CI, 0.81 to 0.95).

CONCLUSION

Appropriately higher urate levels within the threshold of hyperuricemia can reduce the adverse health effects of excessively high urate levels and better protect the cognitive health of people with varying diabetes status.

Triglyceride-glucose index and its additive interaction with ABCG2/SLC2A9 polygenic risk score on hyperuricemia in middle age and older adults: findings from the DLCC and BHMC study

OBJECTIVE

We aim to investigate the joint effect of triglyceride-glucose (TyG) index and polygenic risk scores (PRS) of urate transporter genes ABCG2 and SLC2A9 on hyperuricemia.

METHODS

Baseline data from two prospective population-based cohort studies, including 30,453 individuals aged 50 years or older, were used to analyze the association between TyG index and hyperuricemia. A case-control study was then designed from the cohorts to investigate the interaction between genetic predisposition and TyG index on hyperuricemia among 595 matched pairs. PRS was constructed using 14 single nucleotide polymorphisms located in the ABCG2 and SLCA29 genes.

RESULTS

In both sexes, higher TyG index levels were correlated with elevated serum urate (SUA) levels (p values in both sexes < 0.001). In men, per unit increase of TyG was associated with a 1.44-fold (95% confidence interval [CI]: 1.35-1.55) higher risk of hyperuricemia after adjusted for covariates. In women, this estimate was 1.69 (1.51-1.89). Demonstrated by the restrict cubic spline model, TyG index was both linearly and non-linearly associated with elevated SUA (both p values < 0.001). Association between TyG index and hyperuricemia was stronger among people with higher genetic risk, and vice versa. Compared to people with TyG < 9 and PRS < 2, the odds ratios (ORs) (95% CIs) for hyperuricemia in the TyG <9 but PRS ≥2, TyG ≥9 but PRS < 2, TyG ≥9 and PRS ≥2 groups were 3.30 (1.53-7.14), 3.16 (1.23-8.11) and 7.55 (2.76-20.65), respectively. Additive interaction was also significant, with 57.5% (30.5%-84.4%) of the excess risk attributable to the additive gene-TyG index interaction.

CONCLUSIONS

The impact of genetic predisposition on hyperuricemia was significantly greater among individuals with a higher TyG index. Over 50% of the increased risk can be attributed to the interaction, indicating a crucial synergy between genetic factors and TyG index when estimating hyperuricemia risk.

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

BACKGROUND

Hyperuricemia (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.

METHODS

This 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.

RESULTS

Among 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).

CONCLUSIONS

Among 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 associations of insulin resistance, obesity, and lifestyle with the risk of developing hyperuricaemia in adolescents

BACKGROUND

Hyperuricaemia is common among obese children and adolescents, and is closely related to insulin resistance. The aim of this study was to explore the relationships between youth insulin resistance and hyperuricaemia, as well as their relationships with lifestyle factors in youths, to provide early guidance on the risk factors for hyperuricaemia in adolescents.

METHODS

This study included 233 adolescents aged 10 to 20 years. Insulin resistance was evaluated via the homeostasis model assessment-insulin resistance (HOMA-IR) method. Binary logistic regression analysis was used to assess the associations of HOMA-IR with hyperuricaemia status and serum uric acid (UA) levels. The participants were subsequently divided into two groups, the noninsulin resistant group (HOMA-IR ≤ 3.2) and the insulin resistant group (HOMA-IR > 3.2), to further explore the factors that may affect the serum UA level. Finally, the predictive ability of different indicators of hyperuricaemia was evaluated via the ROC curve.

RESULTS

Binary logistic regression analysis revealed a significant increase in the risk of developing hyperuricaemia for individuals with elevated HOMA-IR (p < 0.001) and insulin resistance (p < 0.01). Spearman's correlation analysis revealed a significant positive linear correlation between HOMA-IR and serum UA levels (r = 0.4652, p < 0.001). Among insulin-resistant adolescents, UA levels were positively correlated with weight ratings, frequency of staying up late, and sugary beverages intake. Notably, individuals who engaged in 1-3 h of weekly exercise had the lowest UA levels. The area under the ROC curve for HOMA-IR was 0.847 (cut-off value = 2.165, p < 0.001), and the optimal prediction model included HOMA-IR, BMI z-score, and other lifestyle factors (AUC: 0.870, p < 0.001)).

CONCLUSION

HOMA-IR was identified as an independent risk factor for the development of hyperuricaemia and could be used as a sensitive indicator for the prediction its development in adolescents. In insulin-resistant adolescents with hyperuricaemia, maintaining normal weight, engaging in physical exercise for 1-3 h per week, avoiding staying up late and limiting sugary beverages intake are recommended to reduce the prevalence of hyperuricaemia among adolescents.

Exploring the Relationship Between Different Obesity Metabolism Indices and Hyperuricemia in Patients with Hypertension and Coronary Heart Disease

Background

Previous studies have established a strong association between obesity, high metabolism, and the development of hyperuricemia. However, the relationship between obesity metabolism indices and hyperuricemia in high-risk patients with hypertension and coronary heart disease (CHD) remains unclear. The purpose of this study was to investigate this relationship in patients with both hypertension and CHD, and to identify the obesity metabolism index with the best diagnostic value.

Methods

A two-center study encompassed 6344 participants with hypertension and CHD. Multiple logistic regression was utilized to examine the correlation between six obesity metabolism indices and hyperuricemia, with restricted cubic spline (RCS) analysis to identify non-linear relationships. Diagnostic value was assessed via receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

Results

Multivariable logistic regression revealed a significant correlation between increased obesity metabolism indices and hyperuricemia. Furthermore, RCS analysis revealed a nonlinear dose-response relationship (P for nonlinear < 0.001). Moreover, ROC and DCA results showed that METS-VF index, which combined visceral obesity and metabolic parameters, became the most reliable diagnostic tool.

Conclusion

The study underscores a strong association between elevated obesity metabolism indices and hyperuricemia in patients with hypertension and CHD. The METS-VF index, amalgamating visceral obesity and metabolic parameters, emerged as the most reliable diagnostic tool.

Transient paper-based electrochemical biosensor Fabricated by superadditive Cu-TCPP(Fe)/Mxene for Multipathway non-invasive, highly sensitive detection of Bodily metabolites

Current advances in non-invasive fluid diagnostics highlight unique benefits for monitoring metabolic diseases. However, the low concentrations and complex compositions of biomarkers in fluids such as sweat, urine, and saliva impose stringent demands on the sensitivity and stability of detection technologies. Here, we developed a high-sensitivity, low-cost instantaneous electrochemical sensor based on the superadditive effect mechanism of Cu-TCPP(Fe)/Mxene (MMs Paper-ECL Sensor), which has been successfully applied for the simultaneous real-time detection of glucose and uric acid. Strong interfacial interactions between Mxene and Cu-TCPP(Fe) were revealed through precise simulation calculations and multi-dimensional characterization analysis, significantly enhancing the sensor's electrocatalytic performance and reaction kinetics. Experimentally, this exceptional electrocatalytic activity was demonstrated in its unprecedented high sensitivity and wide linear detection range for glucose and uric acid, with a non-invasive linear range from 0.001 nM to 5 mM, 0.025 nM-5 mM, detection limits as low as 1.88 aM and 5.80 pM, and stability extending up to 100 days. This represents not only a breakthrough in sensitivity and stability but also provides an effective, low-cost solution that overcomes the limitations of existing electronic devices, enabling multi-channel simultaneous detection. The universality of this sensor holds vast potential for application in the field of non-invasive fluid diagnostics.

Dietary polyunsaturated fatty acids intake is negatively associated with hyperuricemia: The National Health and Nutrition Examination Survey 2003-2015

BACKGROUND AND AIMS

The objective of this research was to explore the associations between dietary PUFAs intake and hyperuricemia risk.

METHODS AND RESULTS

Based on the National Health and Nutrition Examination Survey (NHANES) 2003-2015, all eligible individuals were divided into hyperuricemia and non-hyperuricemia groups based on diagnostic criteria for hyperuricemia (serum uric acid >420 μmol/L for men and >360 μmol/L for women). Multivariate-adjusted logistic regression was employed to explore the relationship between dietary PUFAs intake and hyperuricemia risk. Total PUFAs and their subtypes were modeled to isocalorically replace saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs). Higher intake of n-3 PUFAs, n-6 PUFAs, linoleic acid (LA), alpha-linoleic acid (ALA), and non-marine PUFAs intake correlated with decreased hyperuricemia risk, with adjusted odds ratio (OR) and 95% confidence interval (95%CIs) were 0.77 (0.63, 0.93), 0.75 (0.61, 0.92), 0.75 (0.61, 0.91), 0.69 (0.55, 0.87), and 0.73 (0.59, 0.91), respectively. Replacing 5% of total energy intake from SFAs with isocaloric PUFAs was associated with decreased odds of hyperuricemia in men (0.69 (0.57, 0.84)) and in individuals (0.81 (0.71, 0.92)). Similar trends were observed in the substitution of SFAs with non-marine PUFAs in men (0.87 (0.80, 0.94)) and in all individuals (0.92 (0.88, 0.98)). Sensitivity analyses exhibited consistent results with primary analyses.

CONCLUSION

Higher dietary intake of n-3 PUFAs, n-6 PUFAs, LA, ALA, and non-marine PUFAs was associated with decreased hyperuricemia risk. These results support the recommendation to substitute SFAs with PUFAs in diet.

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.

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.

J-shaped relationship between Chinese visceral adiposity index and hyperuricemia: a cross-sectional study

BACKGROUND

Recent years have seen the emergence of numerous novel indicators for visceral obesity. This study investigates the potential correlation between the Chinese visceral adiposity index (CVAI) and hyperuricemia (HUA).

METHODS

This research, derived from a 2011 cross-sectional analysis in Dalian, China, employed restricted cubic spline (RCS) plots to identify inflection points. Subsequently, one-way and multifactorial logistic regression models were utilized, with HUA as the outcome variable. Additionally, subgroup analyses and interaction tests were conducted. Eventually, receiver operating characteristic (ROC) curves were calculated to assess the effectiveness of CVAI and other body composition indices in predicting HUA.

RESULTS

The study included 10,061 individuals, with a HUA prevalence of 14.25%. Significant relationships with HUA were observed for CVAI. RCS analysis revealed a J-shaped relationship between CVAI and HUA. Compared to those in the low CVAI category, HUA was notably associated with individuals in the high CVAI category in multifactorial logistic regression (OR = 2.661, 95% CI: 2.323, 3.047). Subgroup analyses demonstrated stronger relationships in women, participants without hypertension, and participants without diabetes. Additional modeling via ROC curves suggested that the CVAI may offer effective predictive value for HUA.

CONCLUSION

This study confirmed that an elevated CVAI elevates the risk of HUA in middle-aged and elderly populations in the Dalian community. The findings advance obesity prevention strategies that mitigate HUA risk and support healthcare initiatives for China's aging population.

Association between triglyceride glycemic index and gout in US adults

BACKGROUND

Insulin resistance (IR) has been linked to the development of gout. The triglyceride glycemic (TyG) index is a useful biomarker of IR, and the evidences between TyG and gout are limited. Therefore, this study aimed to examine the association between the TyG index and gout in the United States (U.S).

METHODS

The cross-sectional study was conducted among adults with complete TyG index and gout data in the 2007-2017 National Health and Nutrition Examination Survey (NHANES). The TyG index was calculated as fasting triglycerides (mg/dl) * fasting glucose (mg/dl)/2. Gout was assessed by self-report questionnaire (MCQ160n). Weighted chi-squared and weighted Student's t-test were used to assess group differences. Weighted multivariable logistic regression analysis, subgroup analysis, and interaction tests were used to examine the TyG index and gout association.

RESULTS

The final participants were 11,768; 5910 (50.32%) were female, 7784 (73.26%) were 18-60 years old, 5232 (69.63%) were white, and 573 (5.12%) had gout. After adjusting for all covariates, the TyG index was positively associated with gout; each unit increase in TyG index was associated with 40% higher odds of gout (odds ratio (OR), 1.40; 95% CI: 1.82-2.66; p < 0.0001). Participants in the highest TyG index tertile group were at high risk of gout (odds ratio (OR), 1.64; 95% CI: 1.06-2.54, p = 0.03) versus those in the lowest tertile group. Interaction tests showed no significant effect of age, race, marital status, PIR level, education, BMI, smoking status, drinking status, hypertension, and DM on this association between TyG index and gout (p for interaction > 0.05).

CONCLUSIONS

In this large cross-sectional study, our results suggested that a higher TyG index was associated with an increased likelihood of gout in U.S. adults. Our findings highlight that the TyG index is a reliable biomarker of IR; management of IR among adults may prevent or alleviate the development of gout; meanwhile, the TyG index may be a simple and cost-effective method to detect gout.

Managing Gout in Patients with Metabolic Syndrome

Gout is characterized by monosodium urate (MSU) crystal deposition secondary to hyperuricemia. Gout is associated with metabolic syndrome (MetS) and its related comorbid conditions such as cardiovascular disease (CVD). Major advances have been made in the comprehension of the link between MetS and gout. Despite observational studies suggesting an association between MetS-related conditions and hyperuricemia, there is no proof of causality. Most studies using Mendelian randomization did not find hyperuricemia as a causal factor for MetS-related conditions. In contrast, these conditions were found associated with hyperuricemia, which suggests a reverse causality. Among patients with gout, this high CVD risk profile implies the need for systematic screening for MetS-related conditions. Most international guidelines recommend systematic screening for and care of CVD and related risk factors in patients with gout. Some anti-hypertensive agents, such as losartan and calcium channel blockers, are able to decrease serum urate (SU) levels. However, there are potential interactions between gout management therapies and the treatment of metabolic diseases. Some data suggest that anti-inflammatory drugs used for gout flare treatment, such as colchicine or canakinumab, might have benefits for CVD. Regarding the impact of urate-lowering therapies on CVD risk, recent studies found a similar CVD safety profile for allopurinol and febuxostat. Finally, sodium-glucose cotransporter-2 inhibitors are promising for gout because of their ability to decrease SU levels and risk of recurrent flares. In this review, we focus on the clinical challenge of managing MetS in patients with gout, particularly older patients with co-medications.

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.

Effect of gout and diabetic kidney disease on renal cancer development in Korea

Background

Chronic kidney disease (CKD) and gout are risk factors for renal cancer. We analysed the effects of comorbid diabetic kidney disease and gout on renal cancer.

Methods

This retrospective cohort study enrolled 847 884 patients with type 2 diabetes mellitus (T2DM) who underwent health assessments provided by the Korean National Health Insurance Service in 2009. Based on CKD occurrence (glomerular filtration rate <60 ml/min/1.73 m2) and gout (two outpatient visits or one hospitalization within 5 years), patients were classified into four groups: CKD-Gout- (87.5%), CKD-Gout+ (2.5%), CKD+Gout- (9.3%) and CKD+Gout+ (0.7%). Patients with incident renal cancer (International Classification of Diseases code C64) were followed up until December 2018.

Results

Renal cancer was diagnosed in 2376 patients (0.3%). Renal cancer incidence increased in sequential order of CKD-Gout- [0.29/1000 person-years (PY), CKD+Gout- and CKD-Gout+ (0.44 and 0.48/1000 PY, respectively) and CKD+Gout+ (1.14/1000 PY). Comorbid gout increased renal cancer risk depending on CKD occurrence {hazard ratio [HR] 1.28 [95% confidence interval (CI) 1.04-1.58 among those without CKD; HR 1.95 [95% CI 1.45-2.63] among those with CKD; P-value for interaction = 0.024}. The interaction was significant, particularly in men and patients with a shorter diabetes duration (<5 years) and lesser medication use (no insulin or fewer than three classes of oral hypoglycaemic agents).

Conclusions

CKD and gout individually contributed to renal cancer incidence, and the risk is further increased when gout coexists with CKD. Screening for gout and appropriate management of CKD at an early T2DM stage may be beneficial.

Prevalence and Associations Between Metabolic Syndrome Components and Hyperuricemia by Race: Findings From US Population, 2011-2020

OBJECTIVE

We explored the trend in prevalence of hyperuricemia and metabolic syndrome in US populations and investigated associations between components of metabolic syndrome and hyperuricemia by race.

METHODS

We analyzed data from the four most recent National Health and Nutrition Examination Survey (NHANES) cycles (2011 to March 2020), comprising 10,175 participants. Hyperuricemia is defined as serum urate >7.0 mg/dL (men) or >5.7 mg/dL (women), following the NHANES-III guideline. The definition of metabolic syndrome follows the National Cholesterol Education Program's Adult Treatment Panel III guideline. We estimated the prevalence of metabolic syndrome and hyperuricemia in each cycle and performed subgroup analyses with logistic regression to investigate the patterns of associated components of metabolic syndrome with hyperuricemia.

RESULTS

In the most recent cycle (2017 to March 2020), the prevalence of metabolic syndrome was 45.9% and that of hyperuricemia was 20.7%. Over the 2011 to 2020 period, a significant rise in metabolic syndrome prevalence was observed among Hispanic and Asian populations, and the prevalence of hyperuricemia has increased significantly only in the Hispanic population. After adjustment for confounding factors, patients with metabolic syndrome exhibited a higher hyperuricemia in women than in men. Elevated blood pressure was the strongest factor with hyperuricemia. The association was the weakest in the Asian population. Waist circumference was the only significant factor associated with hyperuricemia in the Asian population.

CONCLUSION

The prevalence of metabolic syndrome has an increasing pattern, but there was no specific decadal trend in prevalence of hyperuricemia. There is an ethnicity-specific association of metabolic syndrome and hyperuricemia, especially among Asians.

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.

Association between triglyceride glucose index and hyperuricemia: a new evidence from China and the United States

Background

Hyperuricemia (HUA) is a glo\bal public health problem. The etiology of HUA is complex and efficient and accurate assessment metrics are still lacking when conducting large-scale epidemiologic screening. The aim of this study was to evaluate the association of the triglyceride glucose (TyG) index, TyG-body mass index (BMI), TyG-waist-to-height ratio (WHtR) with the risk of HUA.

Methods

Based on data collected from the National Health and Nutrition Examination Survey (NHANES) in the United States and the China Health and Aging Longitudinal Study (CHARLS) in China, a total of 14,286 U.S. adults and 4,620 Chinese adults were included in the analysis. The study examined the levels of TyG, TyG-BMI, TyG-WHtR, and TyG-WC. Multivariate logistic regression was utilized to investigate the relationships between these variables and hyperuricemia (HUA), separately. Additionally, the study used restricted cubic splines (RCS) to explore the linear associations of TyG, TyG-BMI, TyG-WHtR, TyG-WC, and HUA, separately.

Results

The NHANES results showed that TyG [Q2, 1.58(1.26, 1.98); Q3, 2.36 (1.94, 2.88); Q4, 3.21 (2.61, 3.94)], TyG-BMI [Q2, 2.14 (1.74, 2.65); Q3, 3.38 (2.74, 4.17); Q4, 6.70 (5.55, 8.02)], TyG-WHtR [Q2, 1.92 (1.56, 2.36); Q3, 3.14 (2.56, 3.85); Q4, 6.28 (5.12, 7.69)], TyG-WC [Q2, 2.32 (1.85, 2.90); Q3, 3.51 (2.84, 4.34); Q4, 7.32 (5.95, 9.02)] were identified as risk factors for hyperuricemia (HUA). Similarly, the CHARLS results, when fully adjusted for covariates, indicated that TyG [Q4, 2.36 (1.08, 5.15)], TyG-BMI [Q3, 2.60 (1.05, 6.41); Q4, 3.70 (1.64, 8.32)], TyG-WHtR (Q4, 2.84 (1.23, 6.55), TyG-WC [Q4, 2.85 (1.23, 6.5)] were also risk factors for HUA. The predictive ability of each indicator for the risk of developing HUA was stronger in women than in men. Furthermore, there was an observed nonlinear relationship between TyG, TyG-BMI, TyG-WHtR, TyG-WC, and HUA in both the NHANES and CHARLS datasets (P-nonlinearity < 0.05).

Conclusion

These findings suggest that TyG, TyG-BMI, TyG-WHtR and TyG-WC are associated with an increased risk of HUA. They are potential indicators for screening HUA status in the general population in China and the United States.

A national study exploring the association between triglyceride-glucose index and risk of hyperuricemia events in adults with hypertension

Background

The triglyceride-glucose (TyG) index has been recommended as a practical surrogate of insulin resistance (IR). However, the association between the TyG index and hyperuricemia among adults with hypertension remains to be elucidated.

Methods

We included and analyzed 3134 HTN patients and 4233 non-HTN participants from the cross-sectional 2013-2018 U.S. National Health and Nutrition Examination Surveys (NHANES). Multivariable logistic regression and restricted cubic splines (RCS) were used to explore the association between the TyG index and hyperuricemia. Stratifed analyses were performed to assess the association in populations with different subgroups of hypertension.

Results

The prevalence of hyperuricemia was higher in HTN patients (28.00 %) than in non-HTN participants (12.47 %). The multivariable logistic regression showed that the TyG index was significantly associated with hyperuricemia. After multivariable adjustment, higher TyG index levels were found to be associated with a higher prevalence of hyperuricemia in HTN patients (OR: 2.39, 95 % CI: 1.37-4.17, Ptrend < 0.001) and non-HTN participants (OR: 2.61, 95 % CI: 1.45-4.69, Ptrend < 0.001). Restricted cubic spline regression showed linearity of the associations between the TyG index and hyperuricemia (p-nonlinear > 0.05). In the subgroup analysis suggested that the positive association seemed to be strong among male, alcohol use, and diabetes group (P for interaction < 0.05).

Conclusions

TyG index, a practical surrogate of IR, was linearly and positively associated with hyperuricemia in HTN and non-HTN participants. Proactive measures are needed to prevent the comorbidity of IR-driven hyperuricemia in the future.

Narrative literature review of antidiabetic drugs' effect on hyperuricemia: elaborating actual data and mechanisms

To optimize the treatment plan for patients with type 2 diabetes mellitus (T2DM) and hyperuricemia, this narrative literature review summarizes the effect of antidiabetic drugs on serum uric acid (SUA) levels using data from observational studies, prospective clinical trials, post hoc analyses, and meta-analyses. SUA is an independent risk factor for T2DM, and evidence has shown that patients with both gout and T2DM exhibit a mutually interdependent effect on higher incidences. We find that insulin and dipeptidyl peptidase 4 inhibitor (DPP-4i) except linagliptin could increase the SUA and other drugs including metformin, thiazolidinediones (TZDs), glucagon-like peptide-1 receptor agonists (GLP-1 RAs), linagliptin, sodium-glucose cotransporter 2 inhibitors (SGLT2i), and α-glucosidase inhibitors have a reduction effect on SUA. We explain the mechanisms of different antidiabetic drugs above on SUA and analyze them compared with actual data. For sulfonylureas, meglitinides, and amylin analogs, the underlying mechanism remains unclear. We think the usage of linagliptin and SGLT2i is the most potentially effective treatment of patients with T2DM and hyperuricemia currently. Our review is a comprehensive summary of the effects of antidiabetic drugs on SUA, which includes actual data, the mechanisms of SUA regulation, and the usage rate of drugs.

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.

Nonlinear association of triglyceride-glucose index with hyperuricemia in US adults: a cross-sectional study

BACKGROUND

Despite abundant evidence on the epidemiological risk factors of metabolic diseases related to hyperuricemia, there is still insufficient evidence regarding the nonlinear relationship between triglyceride-glucose (TyG) index and hyperuricemia. Thus, the purpose of this research is to clarify the nonlinear connection between TyG and hyperuricemia.

METHODS

From 2011 to 2018, a cross-sectional study was carried out using data from the National Health and Nutrition Examination Survey (NHANES). This study had 8572 participants in all. TyG was computed as Ln [triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. The outcome variable was hyperuricemia. The association between TyG and hyperuricemia was examined using weighted multiple logistic regression, subgroup analysis, generalized additive models, smooth fitting curves, and two-piecewise linear regression models.

RESULTS

In the regression model adjusting for all confounding variables, the OR (95% CI) for the association between TyG and hyperuricemia was 2.34 (1.70, 3.21). There is a nonlinear and reverse U-shaped association between TyG and hyperuricemia, with a inflection point of 9.69. The OR (95% CI) before the inflection point was 2.64 (2.12, 3.28), and after the inflection point was 0.32 (0.11, 0.98). The interaction in gender, BMI, hypertension, and diabetes analysis was statistically significant.

CONCLUSION

Additional prospective studies are required to corroborate the current findings, which indicate a strong positive connection between TyG and hyperuricemia among adults in the United States.

The association between monocyte-to-high-density lipoprotein ratio and hyperuricemia: Results from 2009 to 2018

Previous research has suggested that the monocyte-to-high-density lipoprotein ratio (MHR), an emerging inflammatory biomarker, holds promise in predicting the prevalence of various cardiovascular and metabolic diseases. However, earlier investigations were constrained by the relatively modest sample sizes. This study endeavored to expand the sample size and conduct a more comprehensive exploration of the potential relationship between MHR and hyperuricemia. This cross-sectional study incorporated data from participants of the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) with complete and qualifying information. MHR was determined by calculating the ratio between monocyte count and high-density lipoprotein levels. Various statistical methodologies such as weighted multivariate logistic regression, subgroup analysis, smoothed curve fitting, and threshold analysis, have been used to explore the correlation between hyperuricemia and MHR. The study included a cohort of 17,694 participants, of whom 3512 were diagnosed with hyperuricemia. MHR levels were notably higher in the hyperuricemia group than in the normal group, aligning with an elevated body mass index (BMI). A comprehensive multivariate logistic analysis, accounting for all relevant adjustments, revealed a notable positive correlation between MHR and hyperuricemia (P < .001, OR = 1.98, 95% CI: 1.54-2.54). Subgroup analysis indicated that the MHR exhibited an enhanced predictive capacity for identifying hyperuricemia risk, particularly in females (P < .05). Curvilinear and threshold analyses revealed a nonlinear association between MHR and hyperuricemia prevalence, with a notable inflection point at 0.826. In the US population, a clear positive correlation was observed between the MHR and prevalence of hyperuricemia. Importantly, the MHR is a more robust predictor of hyperuricemia risk in females. Further investigations are required to confirm these findings.

The clinical benefits of sodium-glucose cotransporter type 2 inhibitors in people with gout

Gout is the most common form of inflammatory arthritis worldwide and is characterized by painful recurrent flares of inflammatory arthritis that are associated with a transiently increased risk of adverse cardiovascular events. Furthermore, gout is associated with multiple cardiometabolic-renal comorbidities such as type 2 diabetes, chronic kidney disease and cardiovascular disease. These comorbidities, potentially combined with gout flare-related inflammation, contribute to persistent premature mortality in gout, independently of serum urate concentrations and traditional cardiovascular risk factors. Although better implementation of standard gout care could improve gout outcomes, deliberate efforts to address the cardiovascular risk in patients with gout are likely to be required to reduce mortality. Sodium-glucose cotransporter type 2 (SGLT2) inhibitors are approved for multiple indications owing to their ability to lower the risk of all-cause and cardiovascular death, hospitalizations for heart failure and chronic kidney disease progression, making them an attractive treatment option for gout. These medications have also been shown to lower serum urate concentrations, the causal culprit in gout risk, and are associated with a reduced risk of incident and recurrent gout, potentially owing to their purported anti-inflammatory effects. Thus, SGLT2 inhibition could simultaneously address both the symptoms of gout and its comorbidities.

Associations between obesity and hyperuricemia combing mendelian randomization with network pharmacology

Objective

Obesity has become a global health issue and a risk factor for hyperuricemia. However, the associations between obesity and hyperuricemia are sometimes confounding. In the present study, we performed mendelian randomization (MR) analysis to study their relationship and investigate the underlying mechanism by network pharmacology.

Method

Body mass index (BMI) and uric acid related to single nucleotide polymorphism were selected as instrumental variables for MR analysis. Three robust analytical methods are used for bidirectional MR analysis such as inverse-variance weighting, weighted median and MR-Egger regression. Then, we further performed sensitivity analysis to evaluate the horizontal pleiotropy, heterogeneities, and stability. The targets related to obesity and hyperuricemia were collected, screened and further conducted for Kyoto Encyclopedia of Genes and Genomes pathway enrichment to explore the mechanism of obesity and hyperuricemia using network pharmacology.

Results

The positive causality was indicated between BMI and hyperuricemia based on inverse variance-weighted analysis [odds ratio:1.23, 95% confidence interval: 1.11 to 1.30 for each standard deviation increase in BMI (4.6 kg/m2)]. Conversely, hyperuricemia did not influence BMI. 235 intersected targets from obesity and hyperuricemia were collected. Insulin resistance were the top 1 key target. The mechanism between obesity and hyperuricemia are associated with important pathways including adipocytokine signaling pathway, insulin resistance and cholesterol metabolism et al.

Conclusions

Our MR analysis supported the causal association between obesity and hyperuricemia based on availablegenome-wide association analysis summary statistics. Obesity leads to hyperuricemia via insulin resistance, which is a key link in the huge network pathways using network pharmacology.

Increased risk of incident gout in patients with hyperthyroidism: a nationwide retrospective cohort study

Previous studies have reported that thyroid dysfunction is associated with increased serum uric acid levels; however, the relationship between hyperthyroidism and incidence of clinical manifestations of gout has not been fully investigated. Therefore, this study aimed to longitudinally investigate the risk of gout in patients with hyperthyroidism. This nationwide retrospective cohort study used data from the Korean National Health Claims Database. We included 76,494 patients with hyperthyroidism and 76,542 age- and sex-matched controls. A Cox proportional hazard regression model was used to adjust for potential confounders and estimate the risk of incident gout in patients with hyperthyroidism. During a mean follow-up of 9 years, incident gout developed in 3,655 (4.8%) patients with hyperthyroidism and 3251 (4.2%) controls. Hyperthyroidism was significantly associated with increased risk of incident gout [adjusted hazard ratio (HR), 1.12; 95% confidence interval (CI) 1.07-1.18], independent of baseline metabolic profiles. The median time from the diagnosis of hyperthyroidism to the development of gout was 6 years. When stratified by age and sex, the risk of gout was still significant in the < 50-year age group (HR: 1.2, 95% CI 1.12-1.29) and males (HR: 1.21, 95% CI 1.12-1.30), but not in the older age group (> 50 years) and females. Hyperthyroidism is an important risk factor for incident gout, particularly in younger age groups (< 50 years) and males. Our results highlight the importance of continuous screening for gout in patients with hyperthyroidism.

Association between anthropometric indices and hyperuricemia: a nationwide study in China

This article explored the relationship between anthropometric indices and hyperuricemia in Chinese adults. The ability of each anthropometric index to predict hyperuricemia was also compared in this article. This is a cross-sectional study containing 69,842 samples from 31 provinces and cities in China. Anthropometric indices included body mass index (BMI), waist circumference (WC), a body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), triglyceride-glucose index (TyG), waist circumference-triglyceride index (WTI), and weight-adjusted waist index (WWI). The survey data obtained were disaggregated and analyzed according to sex and age. BMI, WC, BRI, WHtR, LAP, VAI, TyG, WTI, and WWI were all significantly associated with hyperuricemia (P < 0.001). In the total population, WTI (AUC 0.7015, P < 0.001) had the highest predictive power, and WWI (AUC 0.5417, P < 0.001) had the lowest. In addition, after dividing the male and female populations, LAP (AUC 0.6571, P < 0.001 for men; AUC 0.7326, P < 0.001 for women) had the highest predictive power among both men and women. The ABSI (AUC 0.5189, P < 0.001 for men; AUC 0.5788, P < 0.001 for women) had the lowest predictive power among both men and women. BMI, WC, BRI, WHtR, LAP, VAI, TyG, and WTI were positively correlated with the risk of hyperuricemia and serum uric acid concentrations in both sexes. Among the general population, WTI had the highest predictive power. After dividing the population by sex, LAP had the highest predictive power in both men and women. Key Points • Anthropometric indices are highly correlated with hyperuricemia. Waist circumference-triglyceride index (WTI) is first found to be associated with hyperuricemia, and it has high predictive power. • The predictive power of anthropometric indices for hyperuricemia is more useful in women. • The restricted cubic splines visually shows the ratio of anthropometric indices to hyperuricemia ratio and the patient's serum uric acid concentration.

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.

Sex-specific differences in the associations between adiposity indices and incident hyperuricemia among middle-aged and older adults: a nationwide longitudinal study

Objective

Although obesity is a known risk for hyperuricemia (HUA), the associations between adiposity indices and incident HUA and whether sex-specific differences exist is still unknown. We aimed to investigate the associations between adiposity indices and incident HUA in a longitudinal study.

Methods

Data from the China Health and Retirement Longitudinal Study (CHARLS) in 2011-2012 and 2015-2016 were used to conduct a cohort study. Participants aged ≥45 years without HUA at baseline were included in this study. Adiposity indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio body roundness index (BRI), conicity index (CI), lipid accumulation product (LAP) index, waist-to-height ratio (WHtR), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI), were calculated. Logistic analysis was used to analyze the association between adiposity indices and incident HUA risk stratified by gender. Receiver operating characteristic curve analysis was performed to evaluate the power of predictions for incident HUA.

Results

Of 5,873 participants aged 59.0 ± 8.7 years enrolled in this study, 578 (9.8%) participants developed HUA during the 4-year follow-up period. After adjusting for confounding variables, LAP, VAI, and CVAI showed significant association with incident HUA. BMI, WC, WHtR, BRI, and CI were significantly associated with incident HUA in women but not in men. LAP had the highest area under the curve (AUC) (0.612) followed by CVAI (0.596) in men, while CVAI had the highest AUC (0.707) followed by LAP (0.691) in women. All indices showed better predictive ability in women than in men.

Conclusion

Our findings indicated that adiposity indices were effective predictors of incident HUA and showed better predictive power in women than men. In clinical practice, adiposity indices could be used to assess and prevent incident HUA among Chinese middle-aged and older adults.

The association between hyperuricemia and insulin resistance surrogates, dietary- and lifestyle insulin resistance indices in an Iranian population: MASHAD cohort study

BACKGROUND

Previous studies have reported insulin resistance (IR) to be associated with hyperuricemia. In this study, we aimed to assess the possible associations between the empirical dietary index for IR (EDIR), the empirical lifestyle index for IR (ELIR), and non-insulin-based surrogates (triglyceride-glucose (TyG) index, triglyceride-to-high-density-lipoprotein-cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR) and TyG with body mass index (TyG-BMI)) and hyperuricemia in an Iranian population.

METHODS

In this cross-sectional study, 6457 participants aged 35-65 years were recruited as part of the MASHAD cohort study. EDIR and ELIR were calculated using dietary intakes, body mass index, and physical activity information. Insulin resistance surrogates including TyG, TyG-BMI, TG/HDL-C, and METS-IR were calculated for all participants. Hyperuricemia was defined as serum uric acid ≥ 7 mg/dl in men or ≥ 6 mg/dl in women. Multivariable logistic regression models were applied to determine the association between indexes of IR and hyperuricemia.

RESULTS

The mean ELIR and IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) were significantly higher in subjects with hyperuricemia compared to non-hyperuricemic subjects (p < 0.001). After adjusting for confounding variables, the association between hyperuricemia and EDIR was not significant, but ELIR had a significant association in all models (p < 0.001). All four IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) showed a significant association with hyperuricemia (p < 0.001).

CONCLUSION

There was a significant association between indexes of insulin resistance: TyG, TyG-BMI, TG/HDL-c, METS-IR, and ELIR with hyperuricemia, in a population sample from northeastern Iran.

Insufficient compensatory pancreatic β-cells function might be closely associated with hyperuricemia in U.S. adults: evidence from the National Health and Nutrition Examination Survey

BACKGROUND

The prevalence of hyperuricemia (HUA) is gradually increasing worldwide. HUA is closely related to diabetes, but the relationship between HUA and pancreatic β-cells function in the population is unclear. The purpose of this article is to investigate the association between pancreatic β-cells and HUA.

METHODS

This cross-sectional study examined the association between pancreatic β-cells and HUA in 1999-2004 using data from the National Health and Nutrition Examination Survey (NHANES). Subjects were divided into two groups: HUA and non-HUA. Pancreatic β-cells function levels were assessed using homeostasis model assessment version 2-%S (HOMA2-%S), homeostasis model assessment version 2-%B (HOMA2-%B) and disposition index (DI). Multivariate logistic regression models and restricted cubic spline models were fitted to assess the association of pancreatic β-cells function with HUA.

RESULTS

The final analysis included 5496 subjects with a mean age of 46.3 years (standard error (SE), 0.4). The weighted means of HOMA2-%B, HOMA2-%S and DI were 118.1 (SE, 1.0), 69.9(SE, 1.1) and 73.9 (SE, 0.7), respectively. After adjustment for major confounders, participants in the highest quartile of HOMA2-%B had a higher risk of HUA (OR = 2.55, 95% CI: 1.89-3.43) compared to participants in the lowest quartile. In contrast, participants in the lowest quartile of HOMA2-%S were significantly more likely to have HUA than that in the highest quartile (OR = 3.87, 95% CI: 2.74-5.45), and similar results were observed in DI (OR = 1.98, 95% CI: 1.32-2.97). Multivariate adjusted restricted cubic spline analysis found evidence of non-linear associations between HOMA2-%B, HOAM2-%S, DI and the prevalence of HUA.

CONCLUSION

Our finding illustrated the indicators of inadequate β-cells compensation might be a new predictor for the presence of HUA in U.S. adults, highlighting a critical role of pancreatic β-cells function on HUA.

The effect of metformin on urate metabolism: Findings from observational and Mendelian randomization analyses

AIM

To evaluate the effect of metformin on urate metabolism.

MATERIALS AND METHODS

Using the UK Biobank, we first performed association analyses of metformin use with urate levels, risk of hyperuricaemia and incident gout in patients with diabetes. To explore the causal effect of metformin on urate and gout, we identified genetic variants proxying the glycated haemoglobin (HbA1c)-lowering effect of metformin targets and conducted a two-sample Mendelian randomization (MR) utilizing the urate and gout genetic summary-level data from the CKDGen (n = 288 649) and the FinnGen cohort. We conducted two-step MR to explore the mediation effect of body mass index and systolic blood pressure. We also performed non-linear MR in the UK Biobank (n = 414 055) to show the results across HbA1c levels.

RESULTS

In 18 776 patients with type 2 diabetes in UK Biobank, metformin use was associated with decreased urate [β = -4.3 μmol/L, 95% confidence interval (CI) -7.0, -1.7, p = .001] and reduced hyperuricaemia risk (odds ratio = 0.87, 95% CI 0.79, 0.96, p = .004), but not gout. Genetically proxied averaged HbA1c-lowering effects of metformin targets, equivalent to a 0.62% reduction in HbA1c, was associated with reduced urate (β = -12.5 μmol/L, 95% CI -21.4, -4.2, p = .004). Body mass index significantly mediated this association (proportion mediated = 33.0%, p = .002). Non-linear MR results suggest a linear trend of the effect of metformin on urate reduction across various HbA1c levels.

CONCLUSIONS

The effect of metformin may reduce urate levels but not incident gout in the general population.

Leukocyte telomere length independently predicts hyperuricemia risk in a longitudinal study of the Chinese population

BACKGROUND AND AIMS

Leukocyte telomere length (LTL) has been correlated with uric acid levels, although results are inconsistent, and prospective studies are lacking. In this longitudinal, prospective cohort study, we aimed to assess whether a shorter LTL predicts the risk of hyperuricemia.

METHODS AND RESULTS

We conducted a longitudinal study in a Chinese cohort of 599 participants. Of these, 266 participants completed a 5.9-year follow-up from June 2014 to December 2021. LTL was assessed at baseline using real-time polymerase chain reaction. Hyperuricemia was defined as serum uric acid ≥420 mmol/L according to Chinese guidelines for diagnosis and treatment of hyperuricemia and gout. Participants who had developed hyperuricemia during follow-up (n = 17) had shorter LTL at baseline. Baseline LTL was independently associated with the development of hyperuricemia at follow-up after adjusting for conventional hyperuricemia risk factors (odds ratio [OR] 2.347 [95% confidence interval [CI] 1.123, 4.906]; P = 0.023). After grouping according to LTL tertiles, the incidence of hyperuricemia was 18.334-fold higher for the first than for the third tertile (OR 18.334 [95%CI 1.786, 191.272]; P = 0.014, P for trend = 0.050).

CONCLUSION

Our findings in a prospective cohort suggest that LTL could predict hyperuricemia risk, which might inform the timely prevention and treatment of hyperuricemia.

What is the relationship between serum uric acid level and insulin resistance?: A case-control study

Diabetes, arises from either an absolute or relative insufficiency of insulin or insulin resistance of peripheral tissues. For assessing long-term blood glucose concentration and insulin resistance, the utilization of glycosylated hemoglobin (HbA1c) and the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) is widespread. Insulin resistance can lead to hyperuricemia by reducing the kidney ability to excrete urate, thus increasing sodium reabsorption. The aim of this study was to investigate the possible relationship between serum uric acid levels and insulin resistance. This was a retrospective case-control study. A total of 2530 applications in 2-year time were included in the study. Patient, known hypertension status, fasting plasma glucose, insulin, uric acid, HDL, low-density lipoprotein (LDL), triglyceride/Tg, HbA1c laboratory values and Tg/HDL ratio were examined. A statistically significant difference existed in the median uric acid values between the insulin-resistant and insulin-sensitive groups (P < .001). Additionally, a weak positive statistical correlation was identified between uric acid and HOMA-IR values (R = 0.299; P < .001) and uric acid and Tg/HDL values (R = 0.357; P < .001). This study concludes that there is a positive correlation between serum uric acid levels and insulin resistance.

Response to febuxostat according to clinical subtypes of hyperuricemia: a prospective cohort study in primary gout

BACKGROUND

While xanthine oxidase inhibitors target uric acid production, renal urate underexcretion is the predominant subtypes in gout. This study was to compare treatment response to the XOI febuxostat in a gout cohort according to clinical subtypes of hyperuricemia.

METHODS

A prospective cohort study was conducted to compare the efficacy and safety of febuxostat (initially 20 mg daily, escalating to 40 mg daily if not at target) in 644 gout patients with the three major clinical subtypes for 12 weeks. Hyperuricemia was defined as the renal overload subtype, the renal underexcretion subtype, or the combined subtype based on UUE > or ≤ 600 mg/d/1.73 m2 and FEUA < or ≥ 5.5%. The primary endpoint was the rate of achieving serum urate (SU) < 6 mg/dL at week 12.

RESULTS

Fewer participants with combined subtype achieved the SU target, 45.5% compared with 64.8% with overload subtype (P = 0.007), and 56.6% with underexcretion subtype (P = 0.022). More participants with combined subtype (82%) had febuxostat escalated to 40 mg than those with overload (62%, P = 0.001) or underexcretion subtype (68%, P = 0.001). In all participants, combined subtype hyperuricemia (OR = 0.64, 95%CI 0.41-0.99, P = 0.048) and baseline SU (OR = 0.74, 95%CI 0.62-0.89, P = 0.001) were independently associated with lower rates of achieving SU target.

CONCLUSIONS

People with combined subtype have a lower response to febuxostat, compared to those with either overload or underexcretion subtype. Assessment of hyperuricemia subtype may provide useful clinical data in predicting febuxostat response.

The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective

Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.

Distinctive biochemistry profiles associated with hyperuricemia between Tibetans and Hans in China

Purpose

We sought to identify distinct risk factors for hyperuricemia in native Tibetan and immigrant Han populations in Tibet, China.

Methods

Three cohorts of male participants aged between 20 and 40 years were enrolled in this study. Biochemical parameters including serum uric acid (UA), fasting plasma glucose, insulin, lactate dehydrogenase (LDH), thyroxin, blood cell count, aminotransferase, and lipid profiles were analyzed. The association of risk factors with UA levels was evaluated using a multivariable line regression model. The effect of UA level on the biochemical parameters between the Hans and Tibetans was evaluated by two-way ANOVA.

Results

The prevalence of hyperuricemia (≥420 μmol/L) was 24.8% (62/250) in the Hans, similar to 23.8% (29/136) in the Tibetans. In the regression analysis, the risk factors that were significantly associated with UA in Hans did not apply to Tibetans. Tibetans had higher fasting insulin (P<0.05) and LDH (P<0.01) levels, in contrast with lower levels of triglycerides (P<0.05), total cholesterol (P<0.01), and low-density lipoprotein-cholesterol (P<0.01) than Hans in normal UA populations. Biochemistry analysis revealed lower albumin levels (P<0.001) and higher levels of all aminotransaminase and especially alkaline phosphatase (P<0.01) in Tibetans than in Hans in both populations. Compared with Hans, Tibetans had lower serum levels of urea, creatinine, and electrolytes in the normal UA population, which were further exacerbated in the high UA population. Tibetans had comparable white blood cell counts as Hans in both normal and high UA populations. In contrast, the red blood cell count and hemoglobin concentration were much lower in Tibetans than in Hans under high UA conditions.

Conclusions

The distinctive biochemistry between Tibetans and Hans may underlie the different etiologies of hyperuricemia in Tibet, China.

Insulin use and gout risk among patients with type 2 diabetes mellitus: a real-world cohort study in Shanghai, China

OBJECTIVES

The effect of insulin use on gout risk remains unknown. This study aimed to investigate the association between insulin use and gout risk among patients with type 2 diabetes mellitus (T2DM).

METHODS

Based on the Shanghai Link Healthcare Database, patients with newly diagnosed T2DM, with or without insulin exposure, were identified from January 1, 2014 to December 31, 2020, and followed until December 31, 2021. Apart from the original cohort, we also established a 1:2 propensity score-matched cohort. A time-dependent Cox proportional hazards model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for gout incidence associated with insulin exposure.

RESULTS

A total of 414,258 patients with T2DM, including 142,505 insulin users and 271,753 insulin non-users, were enrolled in this study. After a median follow-up of 4.08 years (interquartile range, 2.46-5.90 years), the incidence of gout was significantly higher in insulin users than in insulin non-users (319.35 versus 302.20 cases per 100,000 person-years; HR 1.09, 95% CI 1.03-1.16). The results were robust in propensity score-matched cohort, sensitivity analyses, and stratified analysis of aspirin. In other stratified analyses, the association between insulin use and increased gout risk was found only in patients who were female, or aged 40-69 years, or without hypertension, dyslipidemia, ischemic heart disease, chronic lung disease, kidney disease, or not using diuretic.

CONCLUSIONS

Insulin use is associated with a significantly increased risk of gout among patients with T2DM. Key Points • The first real-world study to investigate the effect of insulin use on gout risk. • Insulin use is associated with a significantly increased risk of gout among patients with type 2 diabetes mellitus.

New animal model of chronic gout reproduces pathological features of the disease in humans

OBJECTIVES

Gout, as the most prevalent form of inflammatory arthritis, necessitates the use of animal models to investigate the molecular mechanisms involved in its development. Therefore, our objective was to develop a novel chronic mouse model of gout that more closely mimics the progression of gout in humans.

METHODS

A novel chronic mouse model of gout was established by a simple method, which does not require high technical proficiency, predominantly involves daily intraperitoneal injections of potassium oxonate for approximately 4 months, combined with a high fat-diet and injections of acetic acid into the hind paws to facilitate the formation of monosodium urate (MSU). Arthritis scores and paw oedema were assessed, behavioural tests were conducted, and histopathological and imaging evaluations of the arthritic paw joints were performed.

RESULTS

After 4 months of induction, mice in the model group exhibited noticeable increases in arthritis severity, joint and cartilage damage, as well as bone erosion. Gomori's methenamine silver stain revealed the presence of MSU crystal deposition or tophi in the paw joints or ankle joints of up to 37.9% of the model mice (11 out of 29 mice). Moreover, treatment with benzbromarone effectively prevented the further development of gout or tophi formation in model mice.

CONCLUSIONS

Our model more accurately replicates the pathological features of gouty arthritis compared with gout induced by MSU crystal injections. Therefore, it is particularly suitable for further investigations into the pathogenesis of gout and also serves as a valuable platform for screening potential antigout agents.

Uric acid levels correlate with disease activity in growth hormone-secreting pituitary adenoma patients

Objective

Few studies reported the effects of growth hormone-secreting pituitary adenoma (GHPA) on uric acid (UA) metabolism and the relationship between growth hormone (GH)/insulin-like growth factor-1 (IGF-1) levels and UA are controversial. This study aimed to evaluate the relationship between IGF-1 and UA in patients with GHPA and to further clarify whether UA levels are associated with GHPA disease activity by follow-up.

Methods

A longitudinal study of 424 GHPA patients presenting to Beijing Tiantan Hospital, Capital Medical University between January 2015 and January 2023 was conducted. Spearman's correlation tests were performed to examine the relationship between IGF-1 and UA at baseline. Univariate and multivariate linear regression analysis was conducted to investigate the independent association between UA and IGF-1. Changes in postoperative IGF-1 and UA levels were followed prospectively, and the differences in UA levels between the biochemical remission and nonremission groups were compared.

Results

At baseline, male patients, the lower the age, the higher the IGF-1 and body mass index (BMI), and the higher the UA levels. IGF-1 was significantly associated with UA after controlling for sex, age, and BMI (r = 0.122, P = 0.012). In adjusted multiple linear regression analysis, IGF-1 was independently associated with UA, and UA levels increased significantly with increasing IGF-1. During postoperative follow-up, UA decreased gradually as IGF-1 levels decreased. At 12 months postoperatively, UA levels were significantly lower in the biochemical remission group than in the nonremission group (P = 0.038).

Conclusions

In patients with GHPA, UA levels are associated with disease activity. Changes in UA levels should be taken into account in the comprehensive treatment of GHPA, patients presenting with HUA should be given lifestyle guidance and appropriate urate-lowering treatment according to their condition to better improve their prognosis.

Prediagnostic Glycoprotein Acetyl Levels and Incident and Recurrent Flare Risk Accounting for Serum Urate Levels: A Population-Based, Prospective Study and Mendelian Randomization Analysis

OBJECTIVE

To prospectively investigate population-based metabolomics for incident gout and reproduce the findings for recurrent flares, accounting for serum urate.

METHODS

We conducted a prediagnostic metabolome-wide analysis among 105,615 UK Biobank participants with nuclear magnetic resonance metabolomic profiling data (168 total metabolites) from baseline blood samples collected 2006-2010 in those without history of gout. We calculated hazard ratios (HRs) for incident gout, adjusted for gout risk factors, excluding and including serum urate levels, overall and according to fasting duration before sample collection. Potential causal effects were tested with 2-sample Mendelian randomization. Poisson regression was used to calculate rate ratios (RRs) for the association with recurrent flares among incident gout cases.

RESULTS

Correcting for multiple testing, 88 metabolites were associated with risk of incident gout (N = 1,303 cases) before serum urate adjustment, including glutamine and glycine (inversely), and lipids, branched-chain amino acids, and most prominently, glycoprotein acetyls (GlycA; P = 9.17 × 10-32 ). Only GlycA remained associated with incident gout following urate adjustment (HR 1.52 [95% confidence interval (95% CI) 1.22-1.88] between extreme quintiles); the HR increased progressively with fasting duration before sample collection, reaching 4.01 (95% CI 1.36-11.82) for ≥8 hours of fasting. Corresponding HRs per SD change in GlycA levels were 1.10 (95% CI 1.04-1.17) overall and 1.54 (95% CI 1.21-1.96) for ≥8 hours of fasting. GlycA levels were also associated with recurrent gout flares among incident gout cases (RR 1.90 [95% CI 1.27-2.85] between extreme quintiles) with larger associations with fasting. Mendelian randomization corroborated a potential causal role for GlycA on gout risk.

CONCLUSION

This prospective, population-based study implicates GlycA, a stable long-term biomarker reflecting neutrophil overactivity, in incident and recurrent gout flares (central manifestation from neutrophilic synovitis) beyond serum urate.

Insulin resistance surrogate markers and risk of hyperuricemia among patients with and without coronary artery disease: a cross-sectional study

Background

Although emerging evidence emphasizes the associations between both insulin resistance and hyperuricemia with coronary artery disease (CAD) risk, no definite relationship has yet been established. In this respect, time-efficient and affordable methods to estimate insulin resistance (IR) status, and to predict risk of hyperuricemia, are needed. Thus, the goal of this investigation was to examine the associations between IR, as assessed by novel surrogate markers [triglyceride-glucose (TyG) and TyG-body mass index (TyG-BMI)], and risk of hyperuricemia in patients with and without diagnosed CAD.

Methods

This cross-sectional study used data from the medical records of 1,170 patients who were referred to the cardiology outpatient clinic. Medical records, anthropometrics, and serum analytes were determined at the initial visit. Hyperuricemia was defined as serum uric acid ≥ 5.6 mg/dL. IR was estimated through surrogate markers (TyG and TyG-BMI). Multiple regression analysis was performed to assess the relationship between these indices and odds of hyperuricemia among patients with and without CAD.

Results

Overall, 814 angiographically-confirmed CAD cases (mean age (SD) = 52 (8)yrs) were compared with 356 patients without CAD (mean age (SD) = 48 (8)yr). There were positive associations between TyG and TyG-BMI indices and odds of hyperuricemia in CAD patients after controlling for confounders (adjusted odds ratio (aOR) = 1.60; 95%CI: 1.02-2.51; p-value = 0.036; and aOR = 1.83; 95%CI: 1.24-2.70; p-value = 0.002, third tertiles for TYG and TYG-BMI, respectively).

Conclusion

The present findings suggest that higher levels of the IR surrogate markers, TyG and TyG-BMI, are associated with higher odds of hyperuricemia in patients with CAD. However, given the cross-sectional design of this study, the sensitivity and specificity of these novel markers could not be determined for confirming the diagnosis of IR and hyperuricemia, further studies are needed to determine such outcomes and to confirm the current findings.

The Association of Surrogates of Insulin Resistance with Hyperuricemia among Middle-Aged and Older Individuals: A Population-Based Nationwide Cohort Study

The triglyceride-glucose (TyG) index, triglyceride-to-high-density-lipoprotein-cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR) and TyG with body mass index (TyG-BMI) have been proposed as indicators of insulin resistance (IR). This study aimed to explore the association between these IR surrogates and their longitudinal variation with the development of hyperuricemia in a middle-aged and older Chinese population. Data from the China Health and Retirement Longitudinal Study (CHARLS) was used to identify 5269 participants aged ≥45 years. Logistic regression was used to assess the effect of IR surrogates and their variations on the risk of hyperuricemia. After four years of follow-up, 517 (9.81%) participants developed incident hyperuricemia. Increased baseline values of TyG, TG/HDL, METS-IR, and TyG-BMI were all significantly associated with higher risks of hyperuricemia. Compared to individuals with maintained low levels of IR surrogates, those with low-to-high and maintained high variation patterns had a significantly higher risk of hyperuricemia. These four IR surrogates have comparable predictive ability for hyperuricemia. This study provides evidence of the associations between IR and hyperuricemia. Early intervention among middle-aged and elderly Chinese individuals with high IR levels may effectively reduce the burden of hyperuricemia.

Interactions Between Genetic Risk and Diet Influencing Risk of Incident Female Gout: Discovery and Replication Analysis of Four Prospective Cohorts

OBJECTIVE

To examine whether the cross-sectional gene-diet interaction for prevalent hyperuricemia among women translates prospectively to risk of incident female gout.

METHODS

We analyzed the interaction between genetic predisposition and adherence to a healthy dietary pattern (i.e., Dietary Approaches to Stop Hypertension [DASH] score) on risk of incident female gout in 18,244 women from Nurses' Health Study (NHS; discovery) and 136,786 women from 3 additional prospective female cohorts from the US and UK (replication). Genetic risk score (GRS) was calculated from 114 urate-associated loci.

RESULTS

In the NHS and replication cohorts, association between diet and gout risk was larger and stronger among women with higher genetic risk. In all cohorts combined, compared to women with an unhealthy DASH score (less than the mean score), multivariable relative risk (RR) for incident gout among women with a healthy DASH score (greater than/equal to the mean score) was 0.67 (95% confidence interval [95% CI] 0.60-0.76) among higher GRS (greater than/equal to the mean score) and 0.91 (0.78-1.05) among lower GRS (P for multiplicative interaction = 0.001); multivariable RR for higher versus lower GRS was 2.03 (95% CI 1.80-2.29) and 1.50 (95% CI 1.31-1.71) among unhealthy and healthy DASH score groups, respectively. Additive interaction was also significant, in both the discovery and replication cohorts (P < 0.001), with 51% of the excess risk attributable to the additive gene-diet interaction in all cohorts combined.

CONCLUSION

The deleterious effect of genetic predisposition on risk of incident female gout was more pronounced among women with unhealthy diets, with nearly half the excess risk attributable to this gene-diet interaction. These data elucidate the important synergy of genetics and diet for female gout development.

Mechanistic insights of soluble uric acid-induced insulin resistance: Insulin signaling and beyond

Hyperuricemia is a metabolic disease caused by purine nucleotide metabolism disorder. The prevalence of hyperuricemia is increasing worldwide, with a growing trend in the younger populations. Although numerous studies have indicated that hyperuricemia may be an independent risk factor for insulin resistance, the causal relationship between the two is controversial. There are few reviews, however, focusing on the relationship between uric acid (UA) and insulin resistance from experimental studies. In this review, we summarized the experimental models related to soluble UA-induced insulin resistance in pancreas and peripheral tissues, including skeletal muscles, adipose tissue, liver, heart/cardiomyocytes, vascular endothelial cells and macrophages. In addition, we summarized the research advances about the key mechanism of UA-induced insulin resistance. Moreover, we attempt to identify novel targets for the treatment of hyperuricemia-related insulin resistance. Lastly, we hope that the present review will encourage further researches to solve the chicken-and-egg dilemma between UA and insulin resistance, and provide strategies for the pathogenesis and treatment of hyperuricemia related metabolic diseases.

Causal effect of lower birthweight on non-alcoholic fatty liver disease and mediating roles of insulin resistance and metabolites

BACKGROUND & AIMS

The causal association of lower birthweight with non-alcoholic fatty liver disease (NAFLD) and the mediating pathways remain unclear. We aimed to investigate the causal, independent association of lower birthweight with NAFLD and identify potential metabolic mediators and their mediation effects in this association.

METHODS

We performed two-step, two-sample Mendelian randomization (MR) using genome-wide association study (GWAS) summary statistics for birthweight from the Early Growth Genetics Consortium of 298 142 Europeans, NAFLD from a GWAS meta-analysis of 8434 NAFLD cases and 770 180 controls of Europeans, and 25 candidate mediators from corresponding reliable GWASs.

RESULTS

Genetically determined each 1-SD lower birthweight was associated with a 45% (95% CI: 1.25-1.69) increased risk of NAFLD, and this causal association persisted after adjusting for childhood obesity or adult adiposity traits in multivariable MR. Two-step MR identified 6 of 25 candidate mediators partially mediate the effect of lower birthweight on NAFLD, including fasting insulin (proportion mediated: 22.05%), leucine (17.29%), isoleucine (13.55%), valine (11.37%), alanine (10.01%) and monounsaturated fatty acids (MUFA; 7.23%). Bidirectional MR suggested a unidirectional effect of insulin resistance on isoleucine, leucine and valine and a unidirectional effect of alanine on insulin resistance.

CONCLUSIONS

This MR study elucidated the causal impact of lower birthweight on subsequent risk of NAFLD, independently of later-life adiposity and identified mediators including insulin resistance, branched-chain amino acids, alanine and MUFA in this association pathway. Our findings shed light on the pathogenesis of NAFLD and imply additional targets for prevention and intervention of NAFLD attributed to low birthweight.