Insulin resistance acts as an independent risk factor exacerbating high-purine diet induced renal injury and knee joint gouty lesions

Anthropometry and blood biomarkers of diabetes and their possible association with obesity and metabolic syndrome

Background

Diabetes, a rapidly increasing heterogeneous disorder, is closely linked to the epidemic of obesity and metabolic syndrome (MetS). At present, we do not understand completely the blood biomarkers, molecular aetiology, and role of lifestyle modification and interventions to combat diabetes hand in hand with obesity and the MetS epidemic.

Methods

To measure different anthropometric and blood biomarkers in pre-diabetic and diabetic patients, we collected data and blood samples from patients in a hospital OPD. This was a cross-sectional study that included the identification of possible relationships between different parameters to predict early diagnostic markers of diabetes.

Results

We found increased body mass index (BMI), fasting blood glucose, neck, waist, and hip circumference, sagittal abdominal diameter, and skin fold thickness in the diabetic as compared to the pre-diabetic group. Also, serum uric acid and insulin resistance (HOMA-IR) values were significantly increased in diabetic individuals. We found a significant positive correlation between serum uric acid and BMI, fasting blood glucose, serum insulin, and HOMA-IR values.

Conclusions

Here, we found that pre-diabetic and diabetic patients have increased fasting glucose levels while we did not find any difference in insulin levels. Both pre-diabetic and diabetic patients show high serum uric acid, positively associated with a higher prevalence of diabetes and HOMA-IR. Uric acid may hence be an important parameter for early diagnostics. These findings may be used as a basis for future studies that aim to identify the mechanistic details of the association of uric acid with insulin signaling and hence better understanding of the phenomenon associated with diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01276-4.

Fractional Excretion of Urate is Positively Associated with Type 2 Diabetes in HUA Patients: A Cross-Sectional Study

Purpose

People with hyperuricemia (HUA) are often related to metabolic disorders such as diabetes, metabolic syndrome (MetS), and obesity. However, the correlation between excretion of uric acid and these diseases is unclear. Our study aimed to explore the relationship between uric acid excretion and type 2 diabetes (T2D).

Methods

A total of 228 HUA patients from Tianjin Medical University General Hospital from 2022 to 2023 were included in this study. We collected demographic, biochemical, and anthropometric data on each subject. Urine uric acid excretion (UUAE) was calculated enzymatically from a single urine collection that lasted 24 hours. And fractional excretion of uric acid (FEUA) was calculated from serum uric acid and creatinine and uric acid and creatinine. Binary logistic regression modeling assessed the association between uric acid excretion and T2D.

Results

Of the 228 subjects, 13.4% had T2D and 48.7% had obesity. The obesity group had a lower FEUA (p<0.05) and a higher UUAE compared to the control group (p<0.05). And FEUA had a stronger correlation with the risk of T2D (p<0.001). Also, there was a negative association between BMI and FEUA and a positive link between BMI and UUAE in the outpatients.

Conclusion

Increased FEUA levels were significantly associated with T2D in HUA patients. Therefore, routine calculating of FEUA is essential for proper diagnosis and appropriate treatment T2D of in HUA patients.

A Possible Therapeutic Application of the Selective Inhibitor of Urate Transporter 1, Dotinurad, for Metabolic Syndrome, Chronic Kidney Disease, and Cardiovascular Disease

The reabsorption of uric acid (UA) is mainly mediated by urate transporter 1 (URAT1) and glucose transporter 9 (GLUT9) in the kidneys. Dotinurad inhibits URAT1 but does not inhibit other UA transporters, such as GLUT9, ATP-binding cassette transporter G2 (ABCG2), and organic anion transporter 1/3 (OAT1/3). We found that dotinurad ameliorated the metabolic parameters and renal function in hyperuricemic patients. We consider the significance of the highly selective inhibition of URAT1 by dotinurad for metabolic syndrome, chronic kidney disease (CKD), and cardiovascular disease (CVD). The selective inhibition of URAT1 by dotinurad increases urinary UA in the proximal tubules, and this un-reabsorbed UA may compete with urinary glucose for GLUT9, reducing glucose reabsorption. The inhibition by dotinurad of UA entry via URAT1 into the liver and adipose tissues increased energy expenditure and decreased lipid synthesis and inflammation in rats. Such effects may improve metabolic parameters. CKD patients accumulate uremic toxins, including indoxyl sulfate (IS), in the body. ABCG2 regulates the renal and intestinal excretion of IS, which strongly affects CKD. OAT1/3 inhibitors suppress IS uptake into the kidneys, thereby increasing plasma IS, which produces oxidative stress and induces vascular endothelial dysfunction in CKD patients. The highly selective inhibition of URAT1 by dotinurad may be beneficial for metabolic syndrome, CKD, and CVD.

The synergistic effect of the triglyceride-glucose index and serum uric acid on the prediction of major adverse cardiovascular events after coronary artery bypass grafting: a multicenter retrospective cohort study

BACKGROUND

Elevated serum uric acid (SUA) is regarded as a risk factor for the development of cardiovascular diseases. Triglyceride-glucose (TyG) index, a novel surrogate for insulin resistance (IR), has been proven to be an independent predictor for adverse cardiac events. However, no study has specifically focused on the interaction between the two metabolic risk factors. Whether combining the TyG index and SUA could achieve more accurate prognostic prediction in patients undergoing coronary artery bypass grafting (CABG) remains unknown.

METHODS

This was a multicenter, retrospective cohort study. A total of 1225 patients who underwent CABG were included in the final analysis. The patients were grouped based on the cut-off value of the TyG index and the sex-specific criteria of hyperuricemia (HUA). Cox regression analysis was conducted. The interaction between the TyG index and SUA was estimated using relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). The improvement of model performance yielded by the inclusion of the TyG index and SUA was examined by C-statistics, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). The goodness-of-fit of models was evaluated using the Akaike information criterion (AIC), Bayesian information criterion (BIC) and χ² likelihood ratio test.

RESULTS

During follow-up, 263 patients developed major adverse cardiovascular events (MACE). The independent and joint associations of the TyG index and SUA with adverse events were significant. Patients with higher TyG index and HUA were at higher risk of MACE (Kaplan-Meier analysis: log-rank P < 0.001; Cox regression: HR = 4.10; 95% CI 2.80-6.00, P < 0.001). A significant synergistic interaction was found between the TyG index and SUA [RERI (95% CI): 1.83 (0.32-3.34), P = 0.017; AP (95% CI): 0.41 (0.17-0.66), P = 0.001; SI (95% CI): 2.13 (1.13-4.00), P = 0.019]. The addition of the TyG index and SUA yielded a significant improvement in prognostic prediction and model fit [change in C-statistic: 0.038, P < 0.001; continuous NRI (95% CI): 0.336 (0.201-0.471), P < 0.001; IDI (95% CI): 0.031 (0.019-0.044), P < 0.001; AIC: 3534.29; BIC: 3616.45; likelihood ratio test: P < 0.001).

CONCLUSIONS

The TyG index interacts synergistically with SUA to increase the risk of MACE in patients undergoing CABG, which emphasizes the need to use both measures concurrently when assessing cardiovascular risk.

Urate Transporter 1 Can Be a Therapeutic Target Molecule for Chronic Kidney Disease and Diabetic Kidney Disease: A Retrospective Longitudinal Study

Chronic kidney disease (CKD) is a major global health problem for which there are no curative drug treatments. Hyperuricemia is one of risk factors for CKD. The evidence on effects of uric acid (UA)-lowering treatments on the progression of CKD was very limited and previous meta-analyses used only trials which primarily used xanthin oxidase (XO) inhibitors because the reports on fulminant hepatitis due to benzbromarone kept us from using uricosuric agents for hyperuricemia patients. Dotinurad, a novel selective urate reabsorption inhibitor for the treatment of hyperuricemia, reduces serum UA levels by selectively inhibiting urate transporter 1 (URAT1). We retrospectively picked up patients who had taken dotinurad from June 2018 to August 2021 and compared metabolic parameters at baseline with the data at 3 and 6 months after the start of dotinurad. We found 84 patients, and approximately 74% of patients were complicated with CKD. After the start of dotinurad, improvements in serum lipids, systolic blood pressure, body weight, and albuminuria, in addition to reduction in serum UA, were observed. Dotinurad increased urinary UA excretion, and was effective to reduce serum UA in patients with both UA underexcretion type and renal UA overload type. Furthermore, urinary UA excretion was significantly and negatively correlated with serum creatine levels at baseline and at 6 months after the start of dotinurad, and the change in urinary UA excretion after 3 months was significantly and negatively correlated with change in serum creatine levels. The property of dotinurad, which selectively inhibits URAT1, but not other UA transporters, such as ATP-binding cassette, subfamily G, and 2 (ABCG2), which ABCG2 is a UA and uremic toxin exporter, may be beneficially associated with pathology of CKD. URAT1 can be a therapeutic target molecule for CKD and DKD.

The elevated visceral adiposity index increases the risk of hyperuricemia in Chinese hypertensive patients: A cross-sectional study

Background

Uncertainty still remained about the relationship between visceral adiposity index (VAI) and hyperuricemia. The aim of this study was to investigate whether VAI was an independent risk factor for hyperuricemia in hypertensive Chinese patients.

Methods

A cross-sectional study including 13176 hypertensive participants (6478 males) recruited from Wuyuan County, Jiangxi province, was conducted. All patients received anthropometric measurements, completed questionnaires and provided blood samples for biochemical testing. VAI was calculated by waist circumference, BMI, triglyceride and high-density lipoprotein cholesterol. Hyperuricemia was defined as serum uric acid ≥ 7 mg/dL in men and ≥ 6 mg/dL in women.

Results

Overall, the average level of uric acid was 7.8 ± 2.0 mg/dL in males and 6.34 ± 1.78 in females and prevalence of hyperuricemia was 61.4% and 51.30%, respectively. In multivariate logistic regression analysis, the risk of hyperuricemia increased 1.77 times and 1.88 times with the increase of ln VAI in males (OR:1.77, 95% CI: 1.62, 1.94) and females (OR:1.88, 95% CI: 1.73, 2.04). For males, compared to quartile 1, the risk of hyperuricemia in the second, third and the forth quartile of visceral adiposity index were 1.34 (95% CI: 1.14, 1.57),1.82(95% CI: 1.54, 2.14) and 2.97 (95% CI: 2.48, 3.57). For females, compared to quartile 1, the risk of hyperuricemia in the second, third and the forth quartile of visceral adiposity index were 1.48 (95% CI: 1.28, 1.72), 1.99 (95% CI: 1.71, 2.32) and 2.92 (95% CI: 2.50, 3.42).

Conclusions

This study found that VAI was an independent risk factor for hyperuricemia among hypertensive patients, which may provide some strategies for reducing the level of uric acid.

Assessing the Causal Effects of Adipokines on Uric Acid and Gout: A Two-Sample Mendelian Randomization Study

Previous observational studies have highlighted associations between adipokines and hyperuricemia, as well as gout, but the causality and direction of these associations are not clear. Therefore, we attempted to assess whether there are causal effects of specific adipokines (such as adiponectin (ADP) and soluble leptin receptors (sOB-R)) on uric acid (UA) or gout in a two-sample Mendelian randomization (MR) analysis, based on summary statistics from large genome-wide association studies. The inverse-variance weighted (IVW) method was performed as the primary analysis. Sensitivity analyses (including MR-Egger regression, weighted median, penalized weighted median, and MR pleiotropy residual sum and outlier methods) were also performed, to ensure reliable results. In the IVW models, no causal effect was found for sOB-R (odds ratios (OR), 1.002; 95% confidence intervals (CI), 0.999–1.004; p = 0.274) on UA, or ADP (OR, 1.198; 95% CI, 0.865–1.659; p = 0.277) or sOB-R (OR, 0.988; 95% CI, 0.940–1.037; p = 0.616) on gout. The results were confirmed in sensitivity analyses. There was no notable directional pleiotropy or heterogeneity. This study suggests that these specific adipokines may not play causal roles in UA or gout development.

Effects of a Novel Selective Peroxisome Proliferator-Activated Receptor α Modulator, Pemafibrate, on Metabolic Parameters: A Retrospective Longitudinal Study

The modulation of peroxisome proliferator-activated receptors (PPARs), the superfamily of steroid–thyroid–retinoid nuclear receptors, is expected to induce an amazing crosstalk between energy-demanding organs. Here, we aimed to study the effects of the novel selective PPARα modulator, pemafibrate, on metabolic parameters in patients with dyslipidemia. We retrospectively studied patients who had taken pemafibrate and compared metabolic parameters at baseline with the data at 3, 6 and 12 months after the start of pemafibrate. Serum triglyceride significantly decreased and high-density lipoprotein-cholesterol significantly increased at 3, 6 and 12 months after the start of pemafibrate. Serum aspartate aminotransferase levels significantly decreased at 3 and 6 after the start of pemafibrate as compared with baseline. Serum alanine aminotransferase and gamma-glutamyl transferase significantly decreased and albumin significantly increased after 3, 6 and 12 months. HbA1c levels significantly decreased after 3 months. Further, serum uric acid significantly decreased after 12 months. Such metabolic favorable changes due to pemafibrate were significantly correlated with changes in serum lipids. In conclusion, we observed a significant improvement of liver function, HbA1c and serum uric acid along with an amelioration of dyslipidemia after the start of pemafibrate.

The role of obesity, type 2 diabetes, and metabolic factors in gout: A Mendelian randomization study

BACKGROUND

Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity, dyslipidemia, and hypertension. However, it is unclear if this association is causal.

METHODS

We used Mendelian randomization (MR) to evaluate the causal relation between metabolic conditions and gout or serum urate concentration by inverse-variance-weighted (conventional) and weighted median methods. Furthermore, MR-Egger regression and MR-pleiotropy residual sum and outlier (PRESSO) method were used to explore pleiotropy. Genetic instruments for metabolic disorders and outcome (gout and serum urate) were obtained from several genome-wide association studies on individuals of mainly European ancestry.

RESULTS

Conventional MR analysis showed a robust causal association of increasing obesity measured by body mass index (BMI), high-density lipoprotein cholesterol (HDL), and systolic blood pressure (SBP) with risk of gout. A causal relationship between fasting insulin, BMI, HDL, triglycerides (TG), SBP, alanine aminotransferase (ALT), and serum urate was also observed. These results were consistent in weighted median method and MR-PRESSO after removing outliers identified. Our analysis also indicated that HDL and serum urate as well as gout have a bidirectional causal effect on each other.

CONCLUSIONS

Our study suggested causal effects between glycemic traits, obesity, dyslipidemia, blood pressure, liver function, and serum urate as well as gout, which implies that metabolic factors contribute to the development of gout via serum urate, as well as potential benefit of sound management of increased serum urate in patients with obesity, dyslipidemia, hypertension, and liver dysfunction.

Molecular Biological and Clinical Understanding of the Pathophysiology and Treatments of Hyperuricemia and Its Association with Metabolic Syndrome, Cardiovascular Diseases and Chronic Kidney Disease

Uric acid (UA) is synthesized mainly in the liver, intestines, and vascular endothelium as the end product of an exogenous purine from food and endogenously from damaged, dying, and dead cells. The kidney plays a dominant role in UA excretion, and the kidney excretes approximately 70% of daily produced UA; the remaining 30% of UA is excreted from the intestine. When UA production exceeds UA excretion, hyperuricemia occurs. Hyperuricemia is significantly associated with the development and severity of the metabolic syndrome. The increased urate transporter 1 (URAT1) and glucose transporter 9 (GLUT9) expression, and glycolytic disturbances due to insulin resistance may be associated with the development of hyperuricemia in metabolic syndrome. Hyperuricemia was previously thought to be simply the cause of gout and gouty arthritis. Further, the hyperuricemia observed in patients with renal diseases was considered to be caused by UA underexcretion due to renal failure, and was not considered as an aggressive treatment target. The evidences obtained by basic science suggests a pathogenic role of hyperuricemia in the development of chronic kidney disease (CKD) and cardiovascular diseases (CVD), by inducing inflammation, endothelial dysfunction, proliferation of vascular smooth muscle cells, and activation of the renin-angiotensin system. Further, clinical evidences suggest that hyperuricemia is associated with the development of CVD and CKD. Further, accumulated data suggested that the UA-lowering treatments slower the progression of such diseases.

27-Hydroxycholesterol regulates human SLC22A12 gene expression through estrogen receptor action

The excretion and reabsorption of uric acid both to and from urine are tightly regulated by uric acid transporters. Metabolic syndrome conditions, such as obesity, hypercholesterolemia, and insulin resistance, are believed to regulate the expression of uric acid transporters and decrease the excretion of uric acid. However, the mechanisms driving cholesterol impacts on uric acid transporters have been unknown. Here, we show that cholesterol metabolite 27‐hydroxycholesterol (27HC) upregulates the uric acid reabsorption transporter URAT1 encoded by SLC22A12 via estrogen receptors (ER). Transcriptional motif analysis showed that the SLC22A12 gene promoter has more estrogen response elements (EREs) than other uric acid reabsorption transporters such as SLC22A11 and SLC22A13, and 27HC‐activated SLC22A12 gene promoter via ER through EREs. Furthermore, 27HC increased SLC22A12 gene expression in human kidney organoids. Our results suggest that in hypercholesterolemic conditions, elevated levels of 27HC derived from cholesterol induce URAT1/SLC22A12 expression to increase uric acid reabsorption, and thereby, could increase serum uric acid levels.

Blood Uric Acid Prediction With Machine Learning: Model Development and Performance Comparison

Background

Uric acid is associated with noncommunicable diseases such as cardiovascular diseases, chronic kidney disease, coronary artery disease, stroke, diabetes, metabolic syndrome, vascular dementia, and hypertension. Therefore, uric acid is considered to be a risk factor for the development of noncommunicable diseases. Most studies on uric acid have been performed in developed countries, and the application of machine-learning approaches in uric acid prediction in developing countries is rare. Different machine-learning algorithms will work differently on different types of data in various diseases; therefore, a different investigation is needed for different types of data to identify the most accurate algorithms. Specifically, no study has yet focused on the urban corporate population in Bangladesh, despite the high risk of developing noncommunicable diseases for this population.

Objective

The aim of this study was to develop a model for predicting blood uric acid values based on basic health checkup test results, dietary information, and sociodemographic characteristics using machine-learning algorithms. The prediction of health checkup test measurements can be very helpful to reduce health management costs.

Methods

Various machine-learning approaches were used in this study because clinical input data are not completely independent and exhibit complex interactions. Conventional statistical models have limitations to consider these complex interactions, whereas machine learning can consider all possible interactions among input data. We used boosted decision tree regression, decision forest regression, Bayesian linear regression, and linear regression to predict personalized blood uric acid based on basic health checkup test results, dietary information, and sociodemographic characteristics. We evaluated the performance of these five widely used machine-learning models using data collected from 271 employees in the Grameen Bank complex of Dhaka, Bangladesh.

Results

The mean uric acid level was 6.63 mg/dL, indicating a borderline result for the majority of the sample (normal range <7.0 mg/dL). Therefore, these individuals should be monitoring their uric acid regularly. The boosted decision tree regression model showed the best performance among the models tested based on the root mean squared error of 0.03, which is also better than that of any previously reported model.

Conclusions

A uric acid prediction model was developed based on personal characteristics, dietary information, and some basic health checkup measurements. This model will be useful for improving awareness among high-risk individuals and populations, which can help to save medical costs. A future study could include additional features (eg, work stress, daily physical activity, alcohol intake, eating red meat) in improving prediction.

Impacts of Anthropometric, Biochemical, Socio-demographic, and Dietary Habits Factors on the Health Status of Urban Corporate People in a Developing Country

This study focused on urban corporate people and applied multinomial logistic regression (MLR) to identify the impact of anthropometric, biochemical, socio-demographic and dietary habit factors on health status. Health status is categorized into four levels: healthy, caution, affected, and emergent. A cross-sectional study, based on convenience sampling method, was conducted to select 271 employees from 18 institutions under the Grameen Bank Complex, Dhaka, Bangladesh. Biochemical measurements such as blood uric acid are highly significant variables in the MLR model. When holding other factors as constants, with a one-unit increase in blood uric acid, a person is 11.02 times more likely to be "emergent" compared to "caution". The odds are also higher, at 1.82, for the blood uric acid to be "affected" compared "caution". The results of this study can help to prevent a large proportion of non-communicable diseases (NCDs) by reducing the most significant risk factor: blood uric acid. This study can contribute to the establishment of combined actions to improve disease management.

Association between dairy product consumption and hyperuricemia in an elderly population with metabolic syndrome

BACKGROUND AND AIMS

The prevalence of hyperuricemia has increased substantially in recent decades. It has been suggested that it is an independent risk factor for weight gain, hypertension, hypertriglyceridemia, metabolic syndrome (MetS), and cardiovascular disease. Results from epidemiological studies conducted in different study populations have suggested that high consumption of dairy products is associated with a lower risk of developing hyperuricemia. However, this association is still unclear. The aim of the present study is to explore the association of the consumption of total dairy products and their subtypes with the risk of hyperuricemia in an elderly Mediterranean population with MetS.

METHODS AND RESULTS

Baseline cross-sectional analyses were conducted on 6329 men/women (mean age 65 years) with overweight/obesity and MetS from the PREDIMED-Plus cohort. Dairy consumption was assessed using a food frequency questionnaire. Multivariable-adjusted Cox regressions were fitted to analyze the association of quartiles of consumption of total dairy products and their subtypes with the prevalence of hyperuricemia. Participants in the upper quartile of the consumption of total dairy products (multiadjusted prevalence ratio (PR) = 0.84; 95% CI: 0.75-0.94; P-trend 0.02), low-fat dairy products (PR = 0.79; 95% CI: 0.70-0.89; P-trend <0.001), total milk (PR = 0.81; 95% CI: 0.73-0.90; P-trend<0.001), low-fat milk (PR = 0.80; 95% CI: 0.72-0.89; P-trend<0.001, respectively), low-fat yogurt (PR = 0.89; 95% CI: 0.80-0.98; P-trend 0.051), and cheese (PR = 0.86; 95% CI: 0.77-0.96; P-trend 0.003) presented a lower prevalence of hyperuricemia. Whole-fat dairy, fermented dairy, and yogurt consumption were not associated with hyperuricemia.

CONCLUSIONS

High consumption of total dairy products, total milk, low-fat dairy products, low-fat milk, low-fat yogurt, and cheese is associated with a lower risk of hyperuricemia.

Associations of Triglyceride-Glucose Index and Its Derivatives with Hyperuricemia Risk: A Cohort Study in Chinese General Population

BACKGROUND

Identification and intervention of insulin resistance may be beneficial to the prevention of hyperuricemia (HUA) and its related diseases. Thus, we conducted this longitudinal study to examine the relation of triglyceride-glucose index (TyG), a simple noninsulin-based IR assessment tool, and its derivatives with the risk of HUA.

METHODS

A total of 42,387 adults who received routine health screening and were free of HUA were included for the longitudinal analyses. TyG, body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WtHR) were calculated through anthropometric and biochemical indicators. Associations of TyG, TyG-BMI, TyG-WC, and TyG-WHtR with HUA risk were estimated using Cox regression analyses.

RESULTS

The incident cases of HUA occurred in 4,230 subjects during the 138,163 person-years of observation, and the crude incidence rate of HUA was 30.6 per 1000 person-years. After multivariate adjustment, we observed an increased risk for incident HUA for the upper TyG and its derivatives' tercile. The HRs of TyG were greater than that of its components in both sexes. Compared with TyG, TyG-related parameters only had higher HRs in women but not in men.

CONCLUSIONS

TyG and its integration with obesity indicators have the potential to help risk stratification and prevention of HUA, especially among women.

Cardiovascular Risk in Type 2 Diabetic Patients With Asymptomatic Hyperuricemia and Gout

Aim: To study the differences in cardiovascular risk between type 2 diabetic and non-diabetic patients with asymptomatic hyperuricemia and gout using the Framingham Risk Score (FRS) and complex multimodal ultrasonography.

Patients and methods: A total of 201 patients participated, divided into two groups: 1/ patients with asymptomatic hyperuricemia (n = 52), and 2/ patients with gout (n = 149). FRS was determined as well as ultrasound parameters, independent predictors of cardiovascular risk: left atrial size (LA), intima-media thickness (IMT) and common carotid artery resistive index (CCARI).

Results: The patients in the two groups were age-matched and conventional cardiovascular risk factors were equally distributed. In the asymptomatic hyperuricemia group, 12 patients (23.1%) had diabetes. In this group, there was no difference in FRS between diabetic and non-diabetic individuals. However, diabetic patients had larger LA, thicker intima-media and higher CCARI. In the gout group 18 subjects (12%) had diabetes, but the FRS, LA, IMT and CCARI values were similar among diabetic and non-diabetic patients. Furthermore, when gout subjects were subdivided according to the presence of tophi, we found that the subgroup having gouty tophi and diabetes had larger LA (p = 0.014) compared to those with gouty tophi without diabetes.

Conclusion: In diabetic patients with asymptomatic hyperuricemia and gouty tophi, a more complex approach for estimation of cardiovascular risk is needed. Our work suggests that diabetes and tophi might potentiate their action on the cardiovascular system.

Prevalence of hyperuricemia and the relationship between serum uric acid and obesity: A study on Bangladeshi adults

Background and objectives

Recent studies have shown that hyperuricemia is commonly associated with dyslipidemia, cardiovascular diseases, hypertension and metabolic syndrome. Elevated serum uric acid has been demonstrated to be associated with obesity in the adult population in many countries; however, there is still a lack of evidence for the Bangladeshi population. The aims of this study were to evaluate the prevalence of hyperuricemia and determine the relationship between serum uric acid (SUA) and obesity among the Bangladeshi adults.

Methods

In this cross-sectional study, blood samples were collected from 260 adults (142 males and 118 females) and analyzed for SUA and lipid profile. All participants were categorized as underweight (n = 11), normal (n = 66), overweight (n = 120) and obese (n = 63) according to the body mass index (BMI) scale for the Asian population. Based on SUA concentration the participants were stratified into four quartiles (Q1: < 232 μmol/L, Q2: 232–291 μmol/L, Q3: 292–345 μmol/L and Q4: > 345 μmol/L).

Results

The mean age and BMI of the participants were 32.5 ± 13.3 years and 24.9 ± 3.8 kg/m², respectively. The average level of SUA was 294 ± 90 μmol/L with a significant difference between males and females (p < 0.001). Overall, the estimated prevalence of hyperuricemia was 9.3% with 8.4% in male and 10.2% in female participants. There were significant increases in the prevalence of obesity (17.4%, 22.2%, 28.6% and 31.8%, respectively, p < 0.01 for trend) across the SUA quartiles. A multiple logistic regression analysis revealed that SUA quartiles were independently associated with the presence of obesity (p < 0.01).

Conclusion

Present study indicates a significant positive relationship between SUA and obesity among the Bangladeshi adults. Therefore, routine measurement of SUA is recommended in obese individuals to prevent hyperuricemia and its related complications.

Pink Urine Syndrome: A Combination of Insulin Resistance and Propofol

Pink urine syndrome is mostly seen in patients treated with propofol anesthesia. The pink color is attributed to the presence of large concentrations of uric acid (and pigment), which is excreted in large amounts when propofol is given. We describe a case of propofol-induced pink urine syndrome and perform a comprehensive, evidence-based review. We discuss prior case studies already published in the literature as we speculate on the pathophysiology and how it translates to a clinically relevant entity.

Cotton rat (Sigmodon hispidus) develops metabolic disorders associated with visceral adipose inflammation and fatty pancreas without obesity

Obesity induces metabolic disorders such as type 2 diabetes, hypertension, and cardiovascular diseases and has become a global health concern. Recent studies imply that fat accumulation in nonadipose tissue correlates with metabolic disorders. However, there are no suitable animal models to evaluate this phenomenon. This study investigated the characteristics of metabolic disorders found in cotton rat (Sigmodon hispidus). Blood biochemical examinations revealed that cotton rats, predominantly males, developed hyperinsulinemia, hyperglycemia, and dyslipidemia when fed a normal diet. The islets increased in size through β-cell hyperplasia, which was associated with serum insulin level in both sexes, strongly indicating insulin resistance. In male cotton rats, oxidative stress was observed in β cells, and macrophage infiltration into the visceral white adipose tissue was reported, both of which were associated with serum insulin level without visceral obesity. In contrast, female cotton rats developed hyperinsulinemia without histopathological changes that were reported in males. Adipocytes were found to be accumulated in the pancreas but not in the liver of both sexes during aging. Pancreatic fat accumulation was associated with the serum insulin level only in females. Taken together, cotton rats developed metabolic disorders associated with visceral fat inflammation in the absence of obesity. In addition, pancreatic ectopic fat may also be related to the early stages of these conditions. Thus, the cotton rat may serve as a novel and useful model for metabolic disorders characterized by visceral adipose inflammation and ectopic fat accumulation in the pancreas without obesity.

Renal clearance of uric acid is linked to insulin resistance and lower excretion of sodium in gout patients

Inefficient renal excretion of uric acid is the main pathophysiological mechanism for hyperuricemia in gout patients. Polymorphisms of renal tubular transporters linked with sodium and monosaccharide transport have yet to be demonstrated. We intended to evaluate the impact of insulin resistance, evaluated with the homeostasis model assessment (HOMA), through a transversal study of non-diabetic patients with gout, with normal renal function, not treated with any medication but colchicine as prophylaxis. One hundred and thirty-three patients were evaluated. Clearance of uric acid was inversely correlated with insulin resistance and directly correlated with fractional excretion of sodium. In multivariate analysis, hypertension and hyperlipidemia, in addition to insulin resistance and fractional excretion of sodium, were associated with renal clearance of uric acid. HOMA cutoff for efficient versus inefficient renal handling of uric acid was 2.72, close to that observed in studies of reference population. The impact of insulin resistance and renal handling of sodium on renal clearance of uric acid may help to explain why hyperuricemia is more commonly associated with diabetes and hypertension.

Comparing the effects of inorganic nitrate and allopurinol in renovascular complications of metabolic syndrome in rats: role of nitric oxide and uric acid

INTRODUCTION

The epidemic of metabolic syndrome is increasing worldwide and correlates with elevation in serum uric acid and marked increase in total fructose intake. Fructose raises uric acid and the latter inhibits nitric oxide bioavailability. We hypothesized that fructose-induced hyperuricemia may have a pathogenic role in metabolic syndrome and treatment of hyperuricemia or increased nitric oxide may improve it.

MATERIAL AND METHODS

Two experiments were performed. Male Sprague-Dawley rats were fed a control diet or a high-fructose diet to induce metabolic syndrome. The latter received either sodium nitrate or allopurinol for 10 weeks starting with the 1(st) day of fructose to evaluate the preventive role of the drugs or after 4 weeks to evaluate their therapeutic role.

RESULTS

A high-fructose diet was associated with significant (p < 0.05) hyperuricemia (5.9 ±0.5 mg/dl), hypertension (125.2 ±7.8 mm Hg), dyslipidemia and significant decrease in tissue nitrite (27.4 ±2.01 mmol/l). Insulin resistance, as manifested by HOMAIR (20.6 ±2.2) and QUICKI (0.23 ±0.01) indices, as well as adiposity index (12.9 ±1.1) was also significantly increased (p < 0.1). Sodium nitrate or allopurinol was able to reverse these features significantly (p < 0.05) in the preventive study better than the therapeutic study.

CONCLUSIONS

Fructose may have a major role in the epidemic of metabolic syndrome and obesity due to its ability to raise uric acid. Either sodium nitrate or allopurinol can prevent this pathological condition by different mechanisms of action.

Hyperuricemia: a reality in the Indian obese

Hyperuricemia is known to be associated with obesity and metabolic syndrome. The aims of this study were to evaluate the prevalence of hyperuricemia in the Indian obese population and to determine if a correlation exists between hyperuricemia, body mass index, waist circumference and components of metabolic syndrome. This was a retrospective observational study. Four hundred nine obese patients were included. Anthropometric parameters were recorded. Prevalence of type 2 diabetes mellitus (T2DM), hypertension and dyslipidemia were recorded. Uric acid levels were measured in all patients. Hyperuricemia was defined as serum uric acid levels greater than 6 mg/dl. The population studied had a median body mass index (BMI) of 44.14 kg/m(2) (range 28.1-88.2 kg/m(2)) and a median age of 41 years (range 18 to 75 years). Overall prevalence of hyperuricemia was 44.6 %. Thirty-four percent in the BMI range of 28-35 kg/m(2) and 47 % of patients with a BMI of >35 kg/m(2) had hyperuricemia. The incidence of hyperuricemia in males was 50 vs 21.7 % in females. Of patients in the hyperuricemia group, 47.3 % had hypertension as compared to 37 % in the normouricemic group. Dyslipidemia was seen in 7.3 % of hyperuricemic patients as compared to 5.8 % of the normouricemic subjects. The prevalence of T2DM was comparable in both the groups. The Indian obese population has a significant high prevalence of hyperuricemia; the incidence of hyperuricemia in male patients was greater than in female patients. Central obesity had no direct link to hyperuricemia. There was no significant correlation between the occurrence of T2DM and dyslipidemia and hyperuricemia. Hypertension was the only comorbidity seen to occur in conjunction with hyperuricemia.