Serum uric acid, serum glucose and diabetes: relationships in a population study

Association of weight-adjusted waist index with hyperuricemia and gout among middle-aged and older adults in America: a cross-sectional analysis of NHANES 2007-2014

OBJECTIVES

The weight-adjusted waist circumference index (WWI), a novel obesity indicator, gives better accuracy in assessing both muscle and fat mass. Our goal was to evaluate the relationship between WWI and the occurrence of hyperuricemia/gout among middle-aged and older adults in America.

METHODS

We analyzed the National Health and Nutrition Examination Survey (NHANES) data from the 2007-2014 cycles. Logistic regression analyses, subgroup analyses, and restricted cubic splines (RCS) were performed to evaluate the association between WWI and hyperuricemia/gout prevalence.

RESULTS

A total of 5332 adults aged 50 years and above were included in this study. The prevalence of hyperuricemia and gout was 23.20% and 6.70% respectively. The fourth quartile of WWI was associated with a 56% higher risk for hyperuricemia, compared with the first quartile (OR = 1.56, 95% CI 1.07-2.27, P trend < 0.001). A similar association was found between continuous WWI increase and OR of hyperuricemia in the fully adjusted model (OR = 1.35, 95% CI = 1.13-1.61, P < 0.05). However, WWI was not significantly associated with the prevalence of gout. The RCS model suggested a significant linear relationship between WWI and the risk of hyperuricemia/gout. Stratification analysis showed that the positive associations of WWI with the risk of hyperuricemia were more pronounced in participants who were women, aged 50-59, smokers, no physical activity, non-diabetes, hypertension, and hyperlipidemia.

CONCLUSIONS

Our findings suggest a positive correlation between WWI and hyperuricemia among middle-aged and older adults in America. Employing WWI as a tool for hyperuricemia prevention may be meaningful. Key Points • Weight-adjusted waist circumference index is a new obesity evaluation index. • Weight-adjusted waist circumference index is associated with hyperuricemia not gout. • The association is more pronounced in participants who were women, aged 50-59, smokers, no physical activity, non-diabetes, hypertension, and hyperlipidemia.

Correlation between time in range and serum uric acid in Chinese patients with type-2 diabetes: an observational cross-sectional study

BACKGROUND

At present, the relationship between serum uric acid and blood glucose is controversial, and even opposite conclusions have been reached. We aimed to investigate the relationship between time in range and serum uric acid and estimate the influence of serum uric acid on blood glucose fluctuations in Chinese patients with type-2 diabetes mellitus (T2DM).

METHODS

A total of 458 hospitalized patients with T2DM were selected. According to the SUA level, patients were divided into four groups by quartile: Q1 (≤ 254.5 µmol/L), Q2 (254.5-306.0 µmol/L), Q3 (306.0-385.5 µmol/L) and Q4 (> 385.5 µmol/L). The differences in general data, TIR and other clinical indicators between the four groups were assessed. Multifactor regression was used to analyze the relationship between subgroups of SUA and TIR, TBR, TAR, MAGE, SD, ADRR, MODD and M value. Curve fitting was used to analyze the association between TIR and SUA and to identify the inflection point.

RESULTS

TIR showed an overall increasing trend with increasing SUA, while HbA1c, TAR, MAGE, SD, ADRR, MODD and M value showed an overall decreasing trend with increasing SUA. Multivariate regression analysis showed that, compared with Q1, there was no correlation between SUA and TIR, TAR, ADRR, SD, or MODD in all models of Q2. In the Q3 and Q4 groups, SUA was correlated with SD, MODD, and MAGE in all models. In the Q4 group, SUA was correlated with TIR, TAR, ADRR, and the M value in all models. When SUA > 306 µmol/L (Q3 and Q4), TIR and SUA have a curve-like relationship, and the inflection point of the fitted curve was SUA = 460 mmol/L. Before the inflection point, β was 0.1, indicating that when SUA increases by 10 mmol/L, the corresponding TIR increases by 1%. After the inflection point, there was no significant difference in the correlation between TIR and SUA (P > 0.05).

CONCLUSIONS

There is a close relationship between TIR and SUA in T2DM patients, it is speculated that SUA in a certain range had a positive protective effect on blood glucose control.

Plasma and Urinary Metabolomic Analysis of Gout and Asymptomatic Hyperuricemia and Profiling of Potential Biomarkers: A Pilot Study

Gout results from monosodium urate deposition caused by hyperuricemia, but most individuals with hyperuricemia remain asymptomatic. The pathogenesis of gout remains uncertain. To identify potential biomarkers distinguishing gout from asymptomatic hyperuricemia, we conducted a genetic analysis of urate transporters and metabolomic analysis as a proof-of-concept study, including 33 patients with gout and 9 individuals with asymptomatic hyperuricemia. The variant allele frequencies of rs72552713, rs2231142, and rs3733591, which are related to serum urate levels (SUA) and gout, did not differ between the gout and asymptomatic hyperuricemia groups. In metabolomic analysis, the levels of citrate cycle intermediates, especially 2-ketoglutarate, were higher in patients with gout than in those with asymptomatic hyperuricemia (fold difference = 1.415, p = 0.039). The impact on the TCA cycle was further emphasized in high-risk gout (SUA ≥ 9.0 mg/dL). Of note, urinary nicotinate was the most prominent biomarker differentiating high-risk gout from asymptomatic hyperuricemia (fold difference = 6.515, p = 0.020). Although urate transporters play critical roles in SUA elevation and promote hyperuricemia, this study suggests that the progression from asymptomatic hyperuricemia to gout might be closely related to other genetic and/or environmental factors affecting carbohydrate metabolism and urinary urate excretion.

Uric acid and diabetes mellitus: an update

The relationship between diabetes mellitus (DM) and high serum uric acid is complex and controversial. Many epidemiological studies have reported a positive association, whereas others have reported an inverse association or none. In the pathogenesis of DM it is the intracellular urate that is more important than the extracellular and dissociation between the two is possible. Evidence suggests that high serum uric acid induces insulin resistance and beta cell failure in animal models. Reduction of intracellular uric acid can be achieved by dietary measures such as reducing fructose and salt intake, and uric acid-lowering drugs. We suggest that in the Western diet, these elements play a crucial role in pathogenesis of DM. To determine the precise and exact interrelationship between intracellular and extracellular uric acid, well-designed studies are required. Besides this, clinical trials are needed to determine whether intracellular and extracellular urate reduction will provide benefit in prevention and treatment of DM and complications associated with it.

Women with Metabolic Syndrome and Unhealthy Lifestyle Factors Are at a Higher Risk for Hyperuricemia

Hyperuricemia (HUA) has become a significant medical concern due to its complications and links to metabolic syndrome (MetS) and cardiovascular disease (CVD), which result in increased mortality. The pathogenic processes associated with unhealthy behaviors, MetS, and HUA can be cooperative and potentially synergistic in the activation of risk factors. Recent research has shown sex-based differences in the relationship between HUA and its associated risk factors. This study aimed to investigate these differences, particularly in the context of MetS and CVD risk factors and unhealthy lifestyles. We also aimed to evaluate the joint effects of these factors based on sex. We conducted a cross-sectional study using nationally representative survey data from the Korean National Health and Nutritional Examination Survey 2016-2018. We performed multivariable logistic regression analysis, calculating adjusted odds ratios (ORs) with their 95% confidence intervals (CIs). We also conducted subgroup analyses based on sex and the presence of MetS with or without unhealthy lifestyle factors (tobacco use, alcohol intake). We found sex-based differences in the relationships between HUA and MetS, CVD risk factors, and lifestyle behaviors. Our major finding was a significant association between MetS and HUA in both men and women, regardless of alcohol consumption and smoking status, and this association was stronger in women. We also observed a synergistic effect of MetS and lifestyle factors on the risk of HUA, particularly in women, in whom the risk of HUA increased up to four times compared to the reference group. A sex-based clinical strategy for HUA is necessary to reduce related complications and their socio-economic burden.

Body Mass Index and the Risk of Rheumatic Disease: Linear and Nonlinear Mendelian Randomization Analyses

OBJECTIVE

Although the association between obesity and risk of rheumatic disease is well established, the precise causal relation has not been conclusively proven. Here, we estimate the causal effect of body mass index (BMI) on the risk of developing 5 different rheumatic diseases.

METHODS

Linear and nonlinear mendelian randomization (MR) were used to estimate the effect of BMI on risk of rheumatic disease, and sex-specific effects were identified. Analyses were performed in 361,952 participants from the UK Biobank cohort for 5 rheumatic diseases: rheumatoid arthritis (n = 8,381 cases), osteoarthritis (n = 87,430), psoriatic arthropathy (n = 933), gout (n = 13,638), and inflammatory spondylitis (n = 4,328).

RESULTS

Using linear MR, we found that 1 SD increase in BMI increases the incidence rate for rheumatoid arthritis (incidence rate ratio [IRR] 1.52 [95% confidence interval (95% CI) 1.36-1.69]), osteoarthritis (IRR 1.49 [95% CI 1.43-1.55]), psoriatic arthropathy (IRR 1.80 [95% CI 1.31-2.48]), gout (IRR 1.73 [95% CI 1.56-1.92]), and inflammatory spondylitis (IRR 1.34 [95% CI 1.14-1.57]) in all individuals. BMI was found to be a stronger risk factor in women compared to men for psoriatic arthropathy (P for sex interaction = 3.3 × 10-4 ) and gout (P for sex interaction = 4.3 × 10-3 ), and the effect on osteoarthritis was stronger in premenopausal compared to postmenopausal women (P = 1.8 × 10-3 ). Nonlinear effects of BMI were identified for osteoarthritis and gout in men, and for gout in women. The nonlinearity for gout was also more extreme in men compared to women (P = 0.03).

CONCLUSION

Higher BMI causes an increased risk for rheumatic disease, an effect that is more pronounced in women for both gout and psoriatic arthropathy. The novel sex- and BMI-specific causal effects identified here provide further insight into rheumatic disease etiology and mark an important step toward personalized medicine.

Lifestyle factors, serum parameters, metabolic comorbidities, and the risk of kidney stones: a Mendelian randomization study

Background and objective

The early identification of modifiable risk factors is important for preventing kidney stones but determining causal associations can be difficult with epidemiological data. We aimed to genetically assess the causality between modifiable factors (lifestyle factors, serum parameters, and metabolic comorbidities) and the risk of kidney stones. Additionally, we aimed to explore the causal impact of education on kidney stones and its potential mediating pathways.

Methods

We conducted a two-sample Mendelian randomization (MR) study to explore the causal association between 44 modifiable risk factors and kidney stones. The FinnGen dataset initially explored the causal relationship of risk factors with kidney stones and the UK Biobank dataset was used as the validation set. Then, a meta-analysis was conducted by combining discovery and validation datasets. We used two-step MR to assess potential mediators and their mediation proportions between education and kidney stones.

Results

The combined results indicated that previous exposures may increase the risk of kidney stones, including sedentary behavior, urinary sodium, the urinary sodium/potassium ratio, the urinary sodium/creatinine ratio, serum calcium, 25-hydroxyvitamin D (25OHD), the estimated creatinine-based glomerular filtration rate (eGFRcrea), GFR estimated by serum cystatin C (eGFRcys), body mass index (BMI), waist circumference, type 2 diabetes mellitus (T2DM), fasting insulin, glycated hemoglobin, and hypertension. Coffee intake, plasma caffeine levels, educational attainment, and the urinary potassium/creatinine ratio may decrease the risk of kidney stones. Ranked by mediation proportion, the effect of education on the risk of kidney stones was mediated by five modifiable risk factors, including sedentary behavior (mediation proportion, 25.7%), smoking initiation (10.2%), BMI (8.2%), T2DM (5.8%), and waist circumference (3.2%).

Conclusion

This study provides MR evidence supporting causal associations of many modifiable risk factors with kidney stones. Sedentary lifestyles, obesity, smoking, and T2DM are mediating factors in the causal relationship between educational attainment and kidney stones. Our results suggest more attention should be paid to these modifiable factors to prevent kidney stones.

Associations between obesity parameters and hyperuricemia by sex, age, and diabetes mellitus: A nationwide study in Korea

OBJECTIVE

We investigated the associations between obesity parameters and the risk of hyperuricemia among Korean adults by sex, age, and diabetes mellitus status.

METHODS

This study analyzed data from 17,753 adults from the Korea National Health and Nutrition Examination Survey (KNHANES) 2016-2018. Multivariable logistic regression analyses were conducted to examine the associations of body mass index (BMI), waist circumference (WC), and general and abdominal obesity with the risk of hyperuricemia (serum uric acid ≥7.0 mg/dL in men and ≥6.0 mg/dL in women).

RESULTS

Of all the participants, 12.7% (n = 2256) had hyperuricemia. The age-adjusted mean serum uric acid levels increased significantly with increasing BMI and WC (P for trend <0.001). The adjusted odds ratios (ORs) of hyperuricemia increased as BMI and WC increased in both sexes (P for trend <0.001). General (OR 1.98, 95% confidence interval [CI]: 1.69-2.32) and abdominal (OR 2.21, 95% CI: 1.89-2.58) obesity in men and general (OR 3.26, 95% CI: 2.60-4.09) and abdominal (OR 3.43, 95% CI: 2.69-4.37) obesity in women were associated with higher risks of hyperuricemia. These associations were prominent in women. The association between abdominal obesity and hyperuricemia persisted after additional adjustments for BMI in both sexes. Significant interactions were observed in younger adults and individuals without diabetes mellitus.

CONCLUSION

Increased BMI and WC, and general and abdominal obesity, may be important risk factors for hyperuricemia in both sexes. Women, young adults, and individuals without diabetes mellitus require particular attention to prevent obesity and hyperuricemia.

Efficient representations of binarized health deficit data: the frailty index and beyond

We investigated efficient representations of binarized health deficit data using the 2001-2002 National Health and Nutrition Examination Survey (NHANES). We compared the abilities of features to compress health deficit data and to predict adverse outcomes. We used principal component analysis (PCA) and several other dimensionality reduction techniques, together with several varieties of the frailty index (FI). We observed that the FI approximates the first - primary - component obtained by PCA and other compression techniques. Most adverse outcomes were well predicted using only the FI. While the FI is therefore a useful technique for compressing binary deficits into a single variable, additional dimensions were needed for high-fidelity compression of health deficit data. Moreover, some outcomes - including inflammation and metabolic dysfunction - showed high-dimensional behaviour. We generally found that clinical data were easier to compress than lab data. Our results help to explain the success of the FI as a simple dimensionality reduction technique for binary health data. We demonstrate how PCA extends the FI, providing additional health information, and allows us to explore system dimensionality and complexity. PCA is a promising tool for determining and exploring collective health features from collections of binarized biomarkers.

Association between uric acid levels and incidence of type 2 diabetes: Population-based Panasonic cohort study 11

AIMS

This cohort study intended to assess the association between serum uric acid levels and incidence of type 2 diabetes in a Japanese population.

METHODS

Individuals who participated a medical health checkup program carried out by Panasonic Corporation from 2008 to 2018 were included in this study. A total of 122,123 participants (92,718 men and 29,405 women) were included. During the research period, 6,386 participants developed type 2 diabetes.

RESULTS

Multivariate analysis showed that, in men, serum uric acid levels were not significantly associated with incident type 2 diabetes after adjusting for diabetes risk factors. However, in women, the risk of type 2 diabetes incidence was higher in the group with uric acid levels 5.1-6.0 mg/dL (hazard ratio, 2.01 [95 % confidence interval: 1.26-3.42]) or > 6.1 mg/dL (hazard ratio, 1.85 [95 % confidence interval: 1.11-3.22]) than in the group with uric acid levels ≤ 3 mg/dL. Furthermore, in women, the area under the receiver operating characteristic curve and optimized cut-off values of uric acid for the incidence of type 2 diabetes at 10 years were 0.720 and 4.8 mg/dL, respectively.

CONCLUSIONS

Serum uric acid levels were associated with incident type 2 diabetes in Japanese women but not in Japanese men.

High Prevalence of Hyperuricemia and Associated Factors among Zhuang Adults: A Cross-Sectional Study Based on the Ethnic Minority Population Cohort in the Southwestern China

The highest prevalence of hyperuricemia was found in Zhuang minority adults in two national surveys in China, with only 1% Zhuang study subjects. However, the prevalence of hyperuricemia and the associated factors in Zhuang adults have not been well-addressed. A cross-sectional study was conducted to explore the prevalence of hyperuricemia and the common comorbidities, and the associated factors in Zhuang adults based on the Guangxi Ethnic Minority Population Cohort. Among 11,175 Zhuang adults aged 35-74 years, the age- and sex-standardized prevalence rate was 18.1% for hyperuricemia and 1.1% for gout. The standardized prevalence rate and awareness rate were 31.6% and 32.3%, respectively, for hypertension, and were 5.1% and 48.2%, respectively, for diabetes. High education level, history of coronary heart disease (CHD), hypertension, being a current drinker, high body mass index (BMI), central obesity, hyper-triglyceride (hyper-TG), hyper-total cholesterol (hyper-TC), hypo-high density lipoprotein cholesterol (hypo-HDL-C), and abnormal aspartate aminotransferase (AST) were risk factors, while smoking and diabetes were protective factors of hyperuricemia in males. Older age, being single/divorced, having a high education level, hypertension, drinking tea, high BMI, central obesity, hyper-TG, hyper-TC, hypo-HDL-C, and abnormal alanine aminotransferase (ALT) were risk factors in females. The high prevalence of hyperuricemia but low prevalence of gout and common comorbidities in Zhuang adults may be due to a lag effect of lifestyle changes. Health education and health management should be strengthened to prevent the progression of comorbidities, considering the lag effect and low awareness rate.

Synergistic Interaction between Hyperuricemia and Abdominal Obesity as a Risk Factor for Metabolic Syndrome Components in Korean Population

BACKGROUND

The present study investigated the role of synergistic interaction between hyperuricemia and abdominal obesity as a risk factor for the components of metabolic syndrome.

METHODS

We performed a cross-sectional study using the data of 16,094 individuals from the seventh Korean National Health and Nutrition Examination Survey (2016 to 2018). The adjusted odds ratios of metabolic syndrome and its components were analyzed by multivariate logistic regression analysis. The presence of synergistic interaction between hyperuricemia and abdominal obesity was evaluated by calculating the additive scales-the relative excess risk due to interaction, attributable proportion due to interaction, and synergy index (SI).

RESULTS

There was a synergistic interaction between hyperuricemia and abdominal obesity in hypertriglyceridemia (men: SI, 1.39; 95% confidence interval [CI], 1.01 to 1.98; women: SI, 1.61; 95% CI, 1.02 to 2.69), and low high-density lipoprotein cholesterol (HDL-C) (men: SI, 2.03; 95% CI, 1.41 to 2.91; women: SI, 1.70; 95% CI, 1.05 to 2.95). There was no significant synergistic interaction between hyperuricemia and abdominal obesity for the risk of high blood pressure (men: SI, 1.22; 95% CI, 0.85 to 1.77; women: SI, 1.53; 95% CI, 0.79 to 2.97), and hyperglycemia (men: SI, 1.03; 95% CI, 0.72 to 1.47; women: SI, 1.39; 95% CI, 0.75 to 2.57).

CONCLUSION

Hyperuricemia and abdominal obesity synergistically increased the risk of hypertriglyceridemia and low HDL-C in both sexes.

Utility of Serum Uric Acid to High-Density Lipoprotein Ratio in Prediction of Glycemic Control

Introduction India has witnessed diabetes as a growing problem and is on the verge of a diabetes mellitus (DM) epidemic. Glycemic control is the way to prevent the morbidity associated with diabetes. This study aimed to find out the utility of uric acid to the high-density lipoprotein (HDL) ratio (UHR) as a marker of diabetic control.

Methodology A hospital-based cross-sectional study was conducted among type-2 diabetic individuals who attended outpatient clinics and individuals who admitted to the inpatient wards of our hospital were enlisted. HDL cholesterol, serum uric acid, glycated hemoglobin were performed. Hemoglobin A1c (HbA1c) lower than 7% was classified as a good-controlled type-2 (DM) group and those with HbA1c between 7 and 10% were classified as uncontrolled type-2 DM group and those with HbA1c greater than 10% were classified as poorly controlled type-2 DM group. HbA1c was correlated with HDL, serum uric acid, and UHR.

Results Our study demonstrates that uric acid is inversely related to HbA1c and uric acid decreases following elevated HbA1c, and this relationship was statistically significant, whereas there was a nonsignificant inverse relationship between HDL and HbA1c and UHR with HbA1c.

Conclusion Established diabetics will have a lowering of uric acid as the diabetic control worsens and UHR could not be used as a marker of diabetic control.

Association between serum uric acid with diabetes and other biochemical markers

Objective

This study aimed to decipher the association between serum uric acid (UA) and glycated hemoglobin (HbA1c) in the population from the southern region of Saudi Arabia.

Method

In this retrospective cross-sectional investigation, clinical data obtained from the different commercial laboratories in the Asir region of Saudi Arabia were screened over 2 years. Data were analyzed using standard statistical methods.

Results

A total of 1984 laboratory investigations with 1215 females (61.2%) and 769 males (38.6%) were included in the data analysis. In our investigation, the prevalence of hyperuricemia in the study population was 53.5% (41.2% females and 12.3% males) and in the diabetic population was 12.7% (9.47% females and 3.23% males), in prediabetics was 12.65% (9.8% females and 2.85% males), respectively. Prediabetic subjects had higher UA levels than people with diabetes or healthy people. Higher UA quartiles were associated with a high level of urea, blood urea nitrogen (BUN) creatinine, HbA1c, fasting blood sugar (FBS), and total cholesterol (TC) (P < 0.05). High UA (OR = 1.33 for diabetes; OR = 2.676 for prediabetes), high BUN (OR = 3.05 for diabetes; OR = 2.293 for prediabetes), high TC (OR = 3.75 for diabetes; OR = 1.098 for prediabetes), and high TG (OR = 2.67 for diabetes; OR = 1.943 for prediabetes) parameters are the most influential risk factor in diabetic and prediabetic patients than the people who have normal UA, BUN, TC, and TG value.

Conclusion

High UA levels are significantly associated with prediabetes as defined by HbA1c criteria, indicating that UA has a significant role in the disturbance of glucose metabolism. A significant positive association was observed between dyslipidemia and serum UA in the study population.

The prognostic impact of uric acid in acute heart failure according to coexistence of diabetes mellitus

BACKGROUND AND AIMS

Increased uric acid levels predict higher mortality in heart failure (HF) patients. Patients with diabetes mellitus (DM) appear to have increased xanthine oxidase activity. We aimed to study if the association between uric acid and mortality in acute HF was different according to the coexistence of DM.

METHODS AND RESULTS

We studied a cohort of patients hospitalized due to acute HF in 2009-2010. Patients with no uric acid measurement upon admission were excluded from the analysis.

FOLLOW-UP

2 years; endpoint: all-cause mortality. Patients with elevated uric acid (>80.0 mg/L) were compared with those with lower values. We used a multivariate Cox-regression analysis to assess the prognostic impact of uric acid (both continuous and categorical variable: cut-off 80.0 mg/L). The analysis was stratified according to coexistence of DM. We studied 569 acute HF patients, 44.6%male, mean age 76 years, 290 were diabetic. Median admission uric acid: 81.2 mg/L and 52.2%had uric acid >80.0 mg/L. Elevated uric acid predicted all-cause mortality in acute HF only in patients with DM. The multivariate-adjusted HR of 2-year mortality was 1.68 (95 % CI: 1.15-2.46) for diabetic HF patients with uric acid>80.0 mg/L compared to those with lower levels (p = 0.008) and 1.10 (95 % CI: 1.03-1.18) per each 10 mg/L increase in uric acid (p = 0.007). In non-diabetic HF patients, uric acid was not associated with mortality.

CONCLUSIONS

Increased uric acid predicts ominous outcome in acute HF patients with diabetes, however, it is not prognostic associated in non-diabetics. Uric acid may play a different role in acute HF depending on DM status.

Metabolic Syndrome Increases the Risk of Kidney Stone Disease: A Cross-Sectional and Longitudinal Cohort Study

We aimed to examine the association between metabolic syndrome and the risk of kidney stone development in a large-scale community-based cohort. A total of 121,579 participants enrolled in the Taiwan Biobank were analyzed. They were divided into two groups on the basis of presence of metabolic syndrome. The presence of kidney stone disease was defined by self-reported history of kidney stones. The mean age of participants was 50 years old, and self-reported kidney stones were observed in 3446 (10%) and 4292 (5%) participants with metabolic syndrome and without metabolic syndrome, respectively. Higher prevalence of kidney stone disease was found in participants with metabolic syndrome compared to those without metabolic syndrome (odds ratio (OR), 1.32; 95% confidence interval (95% CI), 1.25 to 1.39). In addition, the risk of incident kidney stone development was analyzed in a longitudinal cohort of 25,263 participants without kidney stones at baseline during a mean follow-up of 47 months. Multivariable Cox regression analysis revealed that the risk for incident kidney stone disease was higher in participants with metabolic syndrome than those without metabolic syndrome (hazard ratio, 1.24; 95% CI, 1.04 to 1.49). Our study suggests that metabolic syndrome does increase the risk of kidney stones.

Studies on effect of Tongfengxiaofang in HUM model mice using a UPLC-ESI-Q-TOF/MS metabolomic approach

Hyperuricemia (HUM) is a major risk factor for the development of gout. The traditional Chinese medicine (TCM) complex prescription Tongfengxiaofang (TFXF) is composed of a variety of TCMs. To study the therapeutic effect of TFXF on HUM mice and the mechanisms by which it exerts a therapeutic effect, the biochemical indices were measured and qPCR technique was used. In addition, plasma metabolomics analysis was carried out based on UPLC-Q-TOF/MS to evaluate the characteristics of the metabolic spectrum changes. TFXF significantly downregulated the contents of uric acid, urea nitrogen and creatinine in serum and the concentration of xanthine oxidase in liver of HUM mice. In addition, TFXF significantly inhibited the overexpression of uric acid transporter 1 and glucose transporter 9 and upregulated the expression of organic anion transporter 1 in the kidney. A total of 152 metabolites were identified and 11 key biomarkers were further selected from these pathways to understand the mechanism of TFXF on the arginine biosynthesis, galactose metabolism, pyrimidine metabolism, glycerophospholipid metabolism, tryptophan metabolism and the citrate cycle (TCA cycle). The results of this confirmed the effect of TFXF on HUM and revealed the metabolic activity mechanism.

Comparison of Equations Estimating Resting Metabolic Rate in Older Adults with Type 2 Diabetes

Measuring resting metabolic rate (RMR) is time-consuming and expensive, and thus various equations for estimating RMR have been developed. This study's objective was to compare five equations in elderly people with type 2 diabetes (T2DM). RMR was measured in 90 older adults (≥65 years) with T2DM (mean body mass index (BMI) of 31.5 kg/m2), using indirect calorimetry. Results were compared to four frequently used equations (those of Cunningham, Harris and Benedict, and Gougeon developed for young adults with T2DM, and that of Lührmann, which was developed for the elderly), in addition to a new equation developed recently at the Academic College at Wingate (Nachmani) for overweight individuals. Estimation accuracy was defined as the percentage of subjects with calculated RMR within ±10% of measured RMR. Measured RMR was significantly underestimated by all equations. The equations of Nachmani and Lührmann had the best estimation accuracy: 71.4% in males and 50.9% in females. Skeletal muscle mass, fat mass, hemoglobin A1c (HbA1c), and the use of insulin explained 70.6% of the variability in measured RMR. RMR in elderly participants with T2DM was higher than that calculated using existing equations. The most accurate equations for this specific population were those developed for obesity or the elderly. Unbalanced T2DM may increase caloric demands in the elderly. It is recommended to adjust the RMR equations used for the target population.

Uric acid-induced pancreatic β-cell dysfunction

Hyperuricemia is associated with insulin resistance, pancreatic β-cell dysfunction and consequently with development of type 2 diabetes. Although a direct relationship between high levels of uric acid (UA) and the development of diabetes is still a controversial issue, there is some evidence that strongly points to pancreatic β-cells damage as a result of high serum UA levels. Here, the mechanisms underlying UA-induced β-cell damage are discussed. Available literature indicates that UA can decrease glucose-stimulated insulin secretion and cause β-cell death. The mechanisms underlying these effects are UA-induced oxidative stress and inflammation within the β-cells. UA also stimulates inducible nitric oxide (NO) synthase (iNOS) gene expression leading to NO-induced β-cell dysfunction. Thus hyperuricemia may potentially cause β-cell dysfunction, leading to diabetes. It may be hypothesized that in hyperuricemic subjects, UA-lowering drugs may be beneficial in preventing diabetes.

Effects of Hyperuricemia on Beta-Cell Function, Renal Function, and Lipid Panels of Patients with Diabetic Kidney Disease: A Gender-Based Retrospective Study

<b><i>Objective:</i></b> Serum uric acid (SUA) has been linked with development and progression of diabetic kidney disease (DKD). In this study, we intend to compare the effects of hyperuricemia (HUA) on beta-cell function, renal function, and lipid panels of patients with DKD. <b><i>Methods:</i></b> A total of 492 patients with DKD were included for data collection and analysis. Males and females have different standard SUA levels; thus, we analyzed these 2 groups separately. Normouricemia (NUA) for men (<i>n</i> = 253) was ≤428 μmol/L and for women (<i>n</i> = 83) was ≤357 μmol/L, whereas HUA for men (<i>n</i> = 94) was &#x3e;428 μmol/L and for women (<i>n</i> = 62) was &#x3e;357 μmol/L. Clinical characteristics of patients were analyzed based on gender-specific NUA and HUA. The Spearman rank correlation test was used to evaluate the correlation between SUA and other clinical variables. Finally, stepwise multinomial logistic regression test was performed to identify the factors that are independently associated with HUA. <b><i>Results:</i></b> A total of 492 patients were included in this study. The regression analysis showed that there was a significant association between HUA and decreased estimated glomerular filtration rate (eGFR) in both male and female patients (odds ratio (OR) [95% confidence interval (CI)] = 4.73 [2.19–10.24], <i>p</i> value ≤0.01 in male patients and OR [95% CI] = 3.07 [], <i>p</i> value = 0.04 in female patients). FBG, 2hPBG, and HbA1c were negatively correlated with SUA in male patients (<i>r =</i> −0.182, <i>p</i> value ≤0.01; <i>r =</i> −0.168, <i>p</i> value ≤0.01; and <i>r</i> = −0.187, <i>p</i> value ≤0.01, respectively), whereas fasting insulin was positively correlated in male patients (<i>r =</i> 0.131, <i>p</i> value = 0.023) and female patients (<i>r =</i> 0.192, <i>p</i> value = 0.041). The atherogenic index of plasma was significantly high in patients with HUA (OR [95% CI] = 5.75 [2.32–14.23], <i>p</i> value ≤0.01 in male patients and OR [95% CI] = 8.37 [1.96–35.78], <i>p</i> value ≤0.01 in female patients). Other indices of lipid profile such as lipoprotein combine index, atherosclerosis index, and triglyceride/high-density lipoprotein ratio were also independently associated with HUA in both male and female patients. <b><i>Conclusion:</i></b> SUA can affect various clinical parameters in patients with DKD. There is a significant association between HUA and decline in eGFR in both male and female patients. HUA is also associated with dyslipidemia in DKD, increasing the risk of cardiac complications and mortality.

Hypouricemia and Mortality Risk in the US General Population

OBJECTIVE

The most recent European Alliance of Associations for Rheumatology (EULAR) recommendations for gout advise against maintaining a serum urate (SU) level of <3 mg/dl for prolonged periods of time. While several Asian cohort studies have shown higher rates of mortality in individuals with extremely low SU levels, data from non-Asian cohort studies are scarce, and the relationship between hypouricemia, cardiovascular risk, and mortality remains unclear.

METHODS

Using data collected from the 1988-1994 and 1999-2008 National Health and Nutrition Examination Survey (NHANES), we examined the relationship between SU level and overall and cause-specific mortality in 41,807 adults in the US. We calculated multivariable hazard ratios (HRs) that were compared to a referent SU level of 5-6 mg/dl for SU categories <4, 4-5, 6-7, 7-8, and >8 mg/dl in men and SU categories <3, 3-4, 4-5, 6-7, and >7 mg/dl in women.

RESULTS

A higher mortality risk was not observed in women who had an SU level of <3 mg/dl (HR 1.09 [95% confidence interval (95% CI) 0.92-1.28]). A 28% higher mortality risk was observed in men who had an SU level of <4 mg/dl (HR 1.28 [95% CI 1.13-1.45]), with a nearly three-times higher mortality risk from diabetes mellitus also noted (HR 2.89 [95% CI 1.59-5.23]), but no increase in mortality from any other specific cause.

CONCLUSION

We found no long-term excess mortality risk among American women with SU levels as low as <3 mg/dl, a finding which is incompatible with the notion of a causal relationship between hypouricemia and premature mortality in women. We found excess all-cause mortality and diabetes mellitus-related mortality among hypouricemic American men, which may in part be attributable to the uricosuric effect of hyperglycemia in fatal uncontrolled diabetes mellitus (analogous to reverse causality).

Association of serum uric acid concentration with components of pediatric metabolic syndrome: A systematic review and meta-analysis

Background:

Hyperuricemia is implicated in the pathogenesis of inflammatory diseases and metabolic disorders. Metabolic syndrome (MetS) in childhood is one of the most important causes of different noncommunicable diseases in adulthood. This study aimed to systematically review the association between serum uric acid (UA) concentration and components of pediatric MetS.

Materials and Methods:

In this meta-analysis and systematic review, related articles were gathered by searching English databases including PubMed, Web of Science, Scopus, and Google Scholar. We used the following keywords: uric acid, metabolic syndrome, hypertension, fasting blood sugar (FBS), hyperglycemia; the search was limited to English language and included observational and cohort studies performed among children or adolescents. Pooled relative risks (odds ratio [OR]) and corresponding 95% confidence interval (95% CI) were extracted. A random-effect model was used.

Results:

On the basis of 34 eligible studies, the pooled correlation between UA with metabolic components including FBS (r = 0.24, 95% CI = 0.09–0.40), fasting insulin (r = 0.26, 95% CI = 0.15–0.37), and hyperglycemia (r for triglyceride and UA = 0.23, 95% CI = 0.19–0.38) (r for high-density lipoprotein and UA = −0.28, 95% CI = −0.37 to −0.20) was statistically significant. The association of both diastolic blood pressure (DBP) and systolic blood pressure (SBP) was statistically significant with UA (r for SBP and UA = 0.34, 95% CI = 0.24–0.43; r for DBP and UA = 0.18, 95% CI = 0.11–0.25). The OR between risk of abdominal obesity with UA was statistically significant (OR = 2.62, 95% CI = 1.41–3.84).

Conclusion:

Serum UA concentration is associated with major components of the pediatric MetS. Its measurement and control should be underscored in at-risk children and adolescents.

Contribution of Rare Variants of the SLC22A12 Gene to the Missing Heritability of Serum Urate Levels

Gout is a common arthritis caused by monosodium urate crystals. The heritability of serum urate levels is estimated to be 30-70%; however, common genetic variants account for only 7.9% of the variance in serum urate levels. This discrepancy is an example of "missing heritability." The "missing heritability" suggests that variants associated with uric acid levels are yet to be found. By using genomic sequences of the ToMMo cohort, we identified rare variants of the SLC22A12 gene that affect the urate transport activity of URAT1. URAT1 is a transporter protein encoded by the SLC22A12 gene. We grouped the participants with variants affecting urate uptake by URAT1 and analyzed the variance of serum urate levels. The results showed that the heritability explained by the SLC22A12 variants of men and women exceeds 10%, suggesting that rare variants underlie a substantial portion of the "missing heritability" of serum urate levels.

Does chronic hyperglycaemia increase the risk of kidney stone disease? results from a systematic review and meta-analysis

DESIGN

Systematic review and meta-analysis of observational studies was performed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for studies reporting on diabetes mellitus (DM) or metabolic syndrome (MetS) and kidney stone disease (KSD).

OBJECTIVE

To examine the association between chronic hyperglycaemia, in the form of DM and impaired glucose tolerance (IGT) in the context of MetS and KSD.

SETTING

Population-based observational studies. Databases searched: Ovid MEDLINE without revisions (1996 to June 2018), Cochrane Library (2018), CINAHL (1990 to June 2018), ClinicalTrials.gov, Google Scholar and individual journals including the Journal of Urology, European Urology and Kidney International.

PARTICIPANTS

Patients with and without chronic hyperglycaemic states (DM and MetS).

MAIN OUTCOME MEASURES

English language articles from January 2001 to June 2018 reporting on observational studies.

EXCLUSIONS

No comparator group or fewer than 100 patients. Unadjusted values were used for meta-analysis, with further meta-regression presented as adjusted values. Bias was assessed using Newcastle-Ottawa scale.

RESULTS

2340 articles were screened with 13 studies included for meta-analysis, 7 DM (three cohort) and 6 MetS. Five of the MetS studies provided data on IGT alone. These included: DM, n=28 329; MetS, n=31 767; IGT, n=12 770.

CONTROLS

DM, n=5 89 791; MetS, n=1 78 050; IGT, n=2 93 852 patients. Adjusted risk for DM cohort studies, RR=1.23 (0.94 to 1.51) (p<0.001). Adjusted ORs for: DM cross-sectional/case-control studies, OR=1.32 (1.21 to 1.43) (p<0.001); IGT, OR=1.26 (0.92 to 1.58) (p<0.0001) and MetS, OR=1.35 (1.16 to 1.54) (p<0.0001). There was no significant difference between IGT and DM (cross-sectional/case-control), nor IGT and MetS. There was a moderate risk of publication bias. Statistical heterogeneity remained significant in adjusted DM cohort values and adjusted IGT (cross-sectional/case-control), but non-signficant for adjusted DM (cross-sectional/case-control).

CONCLUSION

Chronic hyperglycaemia increases the risk of developing kidney stone disease. In the context of the diabetes pandemic, this will increase the burden of stone related morbidity and mortality.

PROSPERO REGISTRATION NUMBER

CRD42018093382.

Diabetes Mellitus Is Associated with a Lower Risk of Gout: A Meta-Analysis of Observational Studies

AIMS

Although several epidemiological studies have investigated the relationship between diabetes mellitus (DM) and the risk of gout, the results are inconsistent. Therefore, we systematically retrospected available observational studies to clarify the impact of DM on the risk of gout.

METHODS

Embase, PubMed, Cochrane Library, Scopus, Web of Science, and China National Knowledge Infrastructure were searched for relevant articles from inception to 2 March 2020. The quality of the included studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. The multivariate adjusted relative risks (aRR) and corresponding 95% confidence intervals (CI) were pooled based on a random-effect model. Cochran's Q test and I ² were used to evaluate heterogeneity.

RESULTS

Five studies involving 863,755 participants were included in our meta-analysis. DM was associated with a lower risk of gout (aRR: 0.66; 95% CI: 0.59 to 0.73) but had a high heterogeneity (I ² = 89.2%). Metaregression analysis revealed that the types of DM were the source of heterogeneity. Subgroup analysis by types of DM showed that the risk of gout was significantly lower in type 1 DM (T1DM) (aRR: 0.42; 95% CI: 0.28 to 0.63) than in type 2 DM (T2DM) (aRR: 0.72; 95% CI: 0.70 to 0.74). Furthermore, when stratified according to gender in DM, sex-specific association was found. The inverse association was observed in males only (aRR: 0.57; 95% CI: 0.43 to 0.77) and not in females (aRR: 0.96; 95% CI: 0.87 to 1.05). Further stratified based on glycated hemoglobin (HbA1c) levels in DM, raised A1C levels were associated with a reduced risk of gout in patients with DM.

CONCLUSIONS

This meta-analysis indicated that DM was related to a lower risk of gout, and the protective effect of DM on the risk of gout was stronger in males, T1DM, or DM with high HbA1c levels. However, more prospective cohort studies are required to confirm these results.

Plasma Metabolic Profiling Analysis of Gout Party on Acute Gout Arthritis Rats Based on UHPLC-Q-TOF/MS Combined with Multivariate Statistical Analysis

Gout Party is a Chinese medicine prescription composed of Aconiti Lateralis Radix Praeparaia, Aconiti Radix Cocta, Cremastrae Pseudobulbus Pleiones Pseudobulbus, Smilacis Glabrae Rhizoma, Rehmanniae Radix, and Glycyrrhizae Radix et Rhizoma, which can relieve joint pain caused by gouty arthritis (GA) and rheumatoid, and has a therapeutic effect on acute gouty arthritis (AGA). However, little information is available on the molecular biological basis and therapeutic mechanism of Gout Party for the treatment of AGA. AGA model was established by injecting sodium urate, and colchicine served as a positive control drug. We established a metabolomic method based on ultra-high-performance liquid chromatography–tandem quadrupole/time-of-flight mass spectrometry (UHPLC–Q–TOF/MS) to analyze the plasma samples of model group rats and blank group rats. Multiple statistical analyses, including principal component analysis (PCA) and partial least square discrimination analysis (PLS-DA), were used to examine metabolite profile changes in plasma samples. Finally, we identified 2–ketobutyric acid, 3–hexenedioic acid, but–2–enoic acid, and so on; 22 endogenous metabolites associated with AGA. After successful molding, we found that 2–ketobutyric acid, 3–hexenedioic acid, but–2–enoic acid, argininic acid, galactonic acid, lactic acid, equol 4′–O–glucuronide, deoxycholic acid glycine conjugate, glycocholic acid, sphinganine 1–phosphate, LPE (0:0/20:3), LPE (0:0/16:0), LPC (15:0) decreased significantly (p < 0.05 or p < 0.01), alanine, erythrulose, 3–dehydrocarnitine, m–methylhippuric acid, 3–hydroxyoctanoic acid, p–cresol sulfate, estriol 3–sulfate 16–glucuronide, 10–hydroxy–9–(phosphonooxy)octadecenoate, docosahexaenoic acid increased significantly (p < 0.05 or p < 0.01). After Gout Party treatment, 14 biomarkers had a tendency to normal conditions. These above biomarkers were mainly involved in fatty acid metabolism, bile acid metabolism, amino acid metabolism, and energy metabolism pathways. These results suggested that Gout Party exerted therapeutic effects of treating AGA by improving energy metabolism disorder and amino acid metabolism dysfunction, and attenuating fatty acid metabolism abnormal and inflammation. The results of this experiment provided a reference for revealing the metabolic mechanism produced by Gout Party in the treatment of AGA, but the subsequent studies need to be further improved and supported by relevant cell experiments and clinical experiments.

Postprandial metabolic effects of fructose and glucose in type 1 diabetes patients: a pilot randomized crossover clinical trial

OBJECTIVE

To test the influence of oral fructose and glucose dose-response solutions in blood glucose (BG), glucagon, triglycerides, uricaemia, and malondialdehyde in postprandial states in type 1 diabetes mellitus (T1DM) patients.

SUBJECTS AND METHODS

The study had a simple-blind, randomized, two-way crossover design in which T1DM patients were selected to receive fructose and glucose solutions (75g of sugars dissolved in 200 mL of mineral-water) in two separate study days, with 2-7 weeks washout period. In each day, blood samples were drawn after 8h fasting and at 180 min postprandial to obtain glucose, glucagon, triglycerides, uric acid, lactate, and malondialdehyde levels.

RESULTS

Sixteen T1DM patients (seven men) were evaluated, with a mean age of 25.19 ± 8.8 years, a mean duration of disease of 14.88 ± 4.73 years, and glycated hemoglobin of 8.13 ± 1.84%. Fructose resulted in lower postprandial BG levels than glucose (4.4 ± 5.5 mmol/L; and 12.9 ± 4.1 mmol/L, respectively; p < 0.01). Uric acid levels increased after fructose (26.1 ± 49.9 µmol/L; p < 0.01) and reduced after glucose (-13.6 ± 9.5 µmol/L; p < 0.01). The malondialdehyde increased after fructose (1.4 ± 1.6 µmol/L; p < 0.01) and did not change after glucose solution (-0.2 ± 1.6 µmol/L; p = 0.40). Other variables did not change.

CONCLUSIONS

Fructose and glucose had similar sweetness, flavor and aftertaste characteristics and did not change triglycerides, lactate or glucagon levels. Although fructose resulted in lower postprandial BG than glucose, it increased uric acid and malondialdehyde levels in T1DM patients. Therefore it should be used with caution. ClinicalTrials.gov registration: NCT01713023.

Effect of sodium-glucose cotransporter 2 inhibitor on proximal tubular function and injury in patients with type 2 diabetes: a randomized controlled trial

Background

Intensive glucose control reduces the risk for microvascular complications in type 2 diabetes (T2DM). Recently, sodium-glucose cotransporter 2 (SGLT2) inhibitors have been shown to exert renoprotection beyond glycemic control, although their effects on the organs are not well known. There are limited data on SGLT2 inhibitors for the biomarkers of kidney injury in type 2 diabetes mellitus (T2DM) patients.

Objective

Our objective was to demonstrate the effect of SGLT2 inhibitors on proximal tubular injury and function in patients with T2DM.

Methods

T2DM patients with persistent glycated hemoglobin (HbA1c) levels >7% were randomly assigned to either dapagliflozin 10 mg/day (n = 28) or standard treatment (n = 29) for 12 weeks. Proximal tubular injury biomarkers, including urine kidney injury molecule-1:creatinine ratio (UKIM1CR), urine cystatin C:creatinine ratio (UCCR), urine albumin:creatinine ratio (UACR), fractional excretion of phosphate (FEPO₄) and fractional excretion of uric acid (FEUA) were measured at baseline and study end.

Results

Baseline characteristics were comparable between treatment groups. After 12 weeks, dapagliflozin-treated versus standard-treated patients showed reductions in HbA1c (–0.75 ± 0.21 versus –0.70 ± 0.25%; P = 0.882). There were significant between-group differences in the reduction in UACR {–23.3 [95% confidence interval (CI) –44.4 to –2.2] versus +19.9 (–4.0–43.8) mg/g Cr; P = 0.010} and UKIM1CR [–26.7 (95% CI –232.9–179.5) versus +422.2 (46.7–797.7) ng/g Cr; P = 0.047], but no significant difference in changes in UCCR between the two groups. There was no significant change in glomerular filtration rate, serum phosphate level, FEUA and FEPO₄ in the dapagliflozin group. No serious renal-related adverse events were observed in either group.

Conclusions

This study indicates that dapagliflozin in T2DM patients can decrease the levels of urinary proximal tubular injury biomarkers, thus highlighting its renoprotective effect. SGLT2 inhibitors could prove useful in treating T2DM by protecting against renal tubular injury and may lead to reduced long-term renal outcomes.

Antioxidant properties of citric acid interfere with the uricase-based measurement of circulating uric acid

BACKGROUND

Circulating uric acid (UA) is an important biomarker, not only in the detection and management of gout, but also in assessing the risk of related comorbidity. The impact of collection methods on clinical UA measurements has been the subject of limited study. After observing significant differences between UA concentrations of blood samples obtained by different collection tubes, we began examining the effects of exogenous tube components on measured UA concentrations. We aimed to: (1) demonstrate the variability in uricase-based UA measurements attributable to different collection methods and (2) identify factors influencing this variability.

METHODS

Blood samples from human subjects were collected using Serum Separator Tubes (SST tubes), Acid Citrate Dextrose (ACD) tubes, and Sodium Citrate (SC) tubes. Circulating UA concentrations were measured by chemistry analyzers utilizing the uricase method. Absorbance assays were run in order to determine the effects of citric acid, sodium citrate, and dextrose on measured absorbance in the presence of leuco crystal violet dye, hydrogen peroxide, and peroxidase. Statistical analyses-including Student's T tests and ANOVA-were used to compare results.

RESULTS

UA concentrations of blood samples collected in ACD tubes were significantly lower than those collected in SST tubes (P < 0.01). Samples collected in SC tubes trended towards lower UA measurements than samples collected in SST tubes, although this difference did not reach statistical significance (P = 0.06). Blood samples spiked with separate concentrations of sodium citrate (3.2 and 22.0 g/L), citric acid (8.0 g/L), and dextrose (24.5 g/L) demonstrated significantly lower UA measurements compared to controls (P < 0.01). Absorbance assays demonstrated that increasing concentrations of citric acid and sodium citrate-in the presence of leuco crystal violet, hydrogen peroxide, and peroxidase-decreased the amount of oxidized dye in the uricase method of UA measurement in a dose-dependent manner (P < 0.01). In contrast, dextrose did not significantly alter the amount of oxidized dye available.

DISCUSSION

Our results indicate that citric acid obstructs accurate uricase-based UA measurement, providing falsely low values. Citric acid, a known antioxidant, scavenges hydrogen peroxide, a key intermediate using the uricase method. By scavenging hydrogen peroxide, citric acid decreases the amount of oxidized leuco dye leading to falsely low UA measurements. Therefore, collection tubes, like ACD and SC tubes, which contain concentrations of citric acid or its conjugate base sodium citrate should not be used to measure circulating UA levels when utilizing uricase-based measurement methods.

Effects of Body Mass Index, Glycemic Control, and Hypoglycemic Drugs on Serum Uric Acid Levels in Type 2 Diabetic Patients

Background

Plasma uric acid has been shown to be associated with an increased risk of hypertension, cardiovascular disease, chronic kidney disease, insulin resistance, and metabolic syndrome. Conflicting data regarding plasma uric acid levels in type 2 diabetes mellitus and their role in the development and progression of diabetic complications have been observed by many studies. The present study aimed to evaluate plasma uric acid levels in type 2 diabetic patients and to determine the effects of hypoglycemic drugs and pharmacologic insulin on plasma uric acid concentration.

Subjects and methods

The study included 162 type 2 diabetic patients divided into three groups (insulin taking group (N=58), glibenclamide taking group (N=40), and metformin taking group (N=64), and 47 normal healthy controls. A questionnaire that included variables such as age, sex, duration of disease, and body mass index (BMI) were answered by all the participants. Blood samples were collected and estimated for serum uric acid (SUA), fasting blood sugar (FBS), and glycated hemoglobin (HbA1c) using standard methods and the data were statistically analyzed.

Results

Diabetic patients showed a significant increase in serum uric acid, fasting blood sugar, glycated hemoglobin, and body mass index when compared to control subjects. The serum uric acid levels of metformin and glibenclamide taking groups were significantly higher than the control group. The difference of serum uric concentration between the insulin taking group and both the control and metformin groups was statistically non-significant. On the other hand, obese diabetics showed a significantly higher serum uric acid than overweight and lean diabetics. Furthermore, serum uric acid had a significant strong positive correlation with body mass index.

Conclusion

Type 2 diabetes mellitus (T2DM) is associated with high serum uric acid levels. Hypoglycemic drugs and pharmacologic insulin do not have a large impact on SUA concentration, but obesity seems to be the primary determinant of SUA levels in T2DM patients. The condition of diabetes may have a direct effect on the oxidation of the purine nucleotides resulting in the increased uric acid (UA) levels. In addition, hyperinsulinemia could lead to hyperuricemia by increasing the rate of xanthine oxidase synthesis. There is a strong relationship between T2DM and obesity with high uric acid levels.

Metabolomics approach by 1H NMR spectroscopy of serum reveals progression axes for asymptomatic hyperuricemia and gout

BACKGROUND

Gout is a metabolic disease and is the most common form of inflammatory arthritis affecting men. However, the pathogenesis of gout is still uncertain, and novel biomarkers are needed for early prediction and diagnosis of gout. The aim of this study was to develop a systemic metabolic profile of patients with asymptomatic hyperuricemia (HUA) and gout by using a metabolomics approach, and find potential pathophysiological mechanisms of and markers of predisposition to gout.

METHODS

Serum samples were collected from 149 subjects, including 50 patients with HUA, 49 patients with gout and 50 healthy controls. 1H nuclear magnetic resonance (NMR) spectroscopy combined with principal components analysis and orthogonal partial least squares-discriminant analysis were used to distinguish between samples from patients and healthy controls. Clinical measurements and pathway analysis were also performed to contribute to understanding of the metabolic change.

RESULTS

By serum metabolic profiling, 21 metabolites including lipids and amino acids were significantly altered in patients with HUA or gout. The levels of identified biomarkers together with clinical data showed apparent alteration trends in patients with HUA or gout compared to healthy individuals. According to pathway analysis, three and five metabolic pathways were remarkably perturbed in patients with HUA or gout, respectively. These enriched pathways involve in lipid metabolism, carbohydrate metabolism, amino acids metabolism and energy metabolism.

CONCLUSIONS

Taken together, we identified the biomarker signature for HUA and gout, which provides biochemical insights into the metabolic alteration, and identified a continuous progressive axis of development from HUA to gout.

Metabolic syndrome and uric acid nephrolithiasis: insulin resistance in focus

Uric acid nephrolithiasis (UAN) is an increasingly common disease in ethnically diverse populations and constitutes about 10% of all kidney stones. Metabolic syndrome and diabetes mellitus are accounted among the major risk factors for UAN, together with environmental exposure, individual lifestyle habits and genetic predisposition. The development and overt manifestation of UAN appears to stem on the background of insulin resistance, which acts at the kidney level by reducing urinary pH, thus hampering the ability of the kidney to generate renal ammonium in response to an acid load. Unduly acidic urinary pH and overt UAN are both considered renal manifestations of insulin resistance. The mechanisms underlying increased endogenous acid production and/or defective ammonium excretion are yet to be completely understood. Although the development of UAN and, more in general, of kidney stones largely recognizes modifiable individual determining factors, the rising prevalence of diabetes, obesity and accompanying metabolic disorders calls for the identification of novel therapeutic approaches and intervention targets. This review aims at providing an updated picture of existing evidence on the relationship between insulin resistance and UAN in the context of metabolic syndrome and in light of the most recent advancements in our understanding of its genetic signature.

Uric acid lowering in relation to HbA1c reductions with the SGLT2 inhibitor tofogliflozin

An integrated analysis was performed with data from 4 phase 2 and phase 3 studies of tofogliflozin in which patients with type 2 diabetes mellitus received the sodium-glucose cotransporter 2 inhibitor tofogliflozin for up to 24 weeks. Sex differences, baseline haemoglobin A1c (HbA1c) and serum uric acid (UA) levels, and log₁₀ -transformed urinary N-acetyl-β-D-glucosaminidase ratio were significantly correlated with the reduction in serum UA levels at both 4 and 24 weeks in multivariate analysis (respectively, P < .0001). The decrease in HbA1c levels was greatest in the group with the highest baseline HbA1c level (quartile 4; HbA1c > 8.6%) and lowest in the group with the lowest baseline HbA1c level (quartile 1; HbA1c ≤ 7.4%). The decrease in serum UA levels was greatest in the quartile 1 group and lowest in the quartile 4 group. In most groups, the maximum decrease in serum UA levels was seen in the first 4 weeks, while the maximum decrease in HbA1c was seen at week 24. Thus, serum UA levels were significantly decreased in patients with moderate HbA1c levels.

Uric acid and diabetes risk among Chinese women with a history of gestational diabetes mellitus

AIMS

To assess the association of uric acid (UA) with the risks of postpartum type 2 diabetes and prediabetes among women with prior gestational diabetes mellitus (GDM).

METHODS

We performed a cross-sectional study of 1262 GDM women at 1-5 years after delivery using the baseline data from the Tianjin Gestational Diabetes Mellitus Prevention Program. Logistic regression models were used to estimate the association of different levels of serum UA with the risks of type 2 diabetes and prediabetes.

RESULTS

The multivariable-adjusted odds ratios (ORs) across quartiles of serum UA were 1.00, 1.23 (95% confidence interval [CI] 0.55-2.78), 2.05 (95% CI 0.96-4.39), and 3.17 (95% CI 1.54-6.55) (P_trend < 0.001) for type 2 diabetes, and 1.00, 1.50 (95% CI 1.03-2.19), 2.28 (95% CI 1.58-3.30), and 2.88 (95% CI 1.99-4.17) (P_trend < 0.001) for prediabetes, respectively. Restricted cubic splines models showed positive linear associations of serum UA as a continuous variable with the risks of type 2 diabetes and prediabetes. This positive association was significant when stratified by healthy weight and overweight participants.

CONCLUSIONS

Serum UA levels have a graded positive association with the risks of type 2 diabetes and prediabetes among Chinese with a history of GDM.

Fasting plasma glucose and serum uric acid levels in a general Chinese population with normal glucose tolerance: A U-shaped curve

Objective

Although several epidemiological studies assessed the relationship between fasting plasma glucose (FPG) and serum uric acid (SUA) levels, the results were inconsistent. A cross-sectional study was conducted to investigate this relationship in Chinese individuals with normal glucose tolerance.

Research design and methods

A total of 5,726 women and 5,457 men with normal glucose tolerance were enrolled in the study. All subjects underwent a 75-g oral glucose tolerance test. Generalized additive models and two-piecewise linear regression models were applied to assess the relationship.

Results

A U-shaped relationship between FPG and SUA was observed. After adjusting for potential confounders, the inflection points of FPG levels in the curves were 4.6 mmol/L in women and 4.7 mmol/L in men respectively. SUA levels decreased with increasing fasting plasma glucose concentrations before the inflection points (regression coefficient [β] = -36.4, P < 0.001 for women; β = -33.5, P < 0.001 for men), then SUA levels increased (β = 17.8, P < 0.001 for women; β = 13.9, P < 0.001 for men). Additionally, serum insulin levels were positively associated with FPG and SUA (P < 0.05).

Conclusions

A U-shaped relationship between FPG and SUA levels existed in Chinese individuals with normal glucose tolerance. The association is partly mediated through serum insulin levels.

Asymptomatic hyperuricemia is independently associated with coronary artery calcification in the absence of overt coronary artery disease: A single-center cross-sectional study

Recently, the pathogenic role of uric acid (UA) in both systemic metabolic and atherosclerotic diseases has been investigated. We sought to determine the independent correlation between serum UA levels and coronary artery calcification, as a marker of subclinical atherosclerosis. A total of 4188 individuals without prior coronary artery disease or urate-deposition disease were included. All of the participants underwent multidetector computed tomography (MDCT) for the evaluation of coronary artery calcification (CAC) during their health check-ups. The subjects were divided into thre groups according to CAC scores (group 1: 0; group 2: 1-299; group 3: ≥300). After controlling for other confounders, serum UA levels were found to be positively associated with increasing CAC scores (P = 0.001). Adjusted mean serum UA levels in each CAC group were estimated to be 5.2 ± 0.1 mg/dL, 5.3 ± 0.1 mg/dL, and 5.6 ± 0.2 mg/dL from groups 1, 2, and 3, respectively. Subsequent subgroup analyses revealed that this positive association was only significant in participants who were male, relatively older, less overweight, and did not have diabetes mellitus (DM), hypertension, smoking history, or renal dysfunction. In conclusion, serum uric acid levels were independently associated with CAC score severity and this finding is particularly relevant to the subjects who were male, relatively older, less overweight (body mass index < 25 kg/m), and without a history of DM, hypertension, smoking, or renal dysfunction.

Diabetes and kidney disease: the role of sodium-glucose cotransporter-2 (SGLT-2) and SGLT-2 inhibitors in modifying disease outcomes

Patients with type 2 diabetes (T2D) often have coexisting chronic kidney disease (CKD). However, healthy renal function is crucial in maintaining glucose homeostasis, assuring that almost all of the filtered glucose is reabsorbed by the sodium glucose cotransporters (SGLTs) SGLT-1 and SGLT-2. In diabetes, an increased amount of glucose is filtered by the kidneys and SGLT-2 is upregulated, leading to increased glucose absorption and worsening hyperglycemia. Prolonged hyperglycemia contributes to the development of CKD by inducing metabolic and hemodynamic changes in the kidneys. Due to the importance of SGLT-2 in regulating glucose levels, investigation into SGLT-2 inhibitors was initiated as a glucose-dependent mechanism to control hyperglycemia, and there are three agents currently approved for use in the United States: dapagliflozin, canagliflozin, and empagliflozin. SGLT-2 inhibitors have been shown to reduce glycated hemoglobin (A1C), weight, and blood pressure, which not only affects glycemic control, but may also help slow the progression of renal disease by impacting the underlying mechanisms of kidney injury. In addition, SGLT-2 inhibitors have shown reductions in albuminuria, uric acid, and an increase in magnesium. Caution is advised when prescribing SGLT-2 inhibitors to patients with moderately impaired renal function and those at risk for volume depletion and hypotension. Published data on slowing of the development, as well as progression of CKD, is a hopeful indicator for the possible renal protection potential of this drug class. This narrative review provides an in-depth discussion of the interplay between diabetes, SGLT-2 inhibitors, and factors that affect kidney function.

Elevation of serum uric acid and incidence of type 2 diabetes: A systematic review and meta-analysis

Objective

Recently, several cohort studies suggested a positive relationship between serum uric acid (SUA) and type 2 diabetes mellitus (T2DM), which is inconsistent with the results of functional research. Our aim was to further evaluate this correlation by conducting a systematic review.

Methods

Computerized literature searches of the Medline database, EMBASE database, and PubMed were used to evaluate the relationship between SUA and T2DM in cohort studies. Cochran's Q and I² statistics were used to evaluate heterogeneity among studies, and pooled relative risk (RR) and odds ratio (OR) with 95% confidence intervals (CIs) were calculated using random-effects and fixed-effects models. The summary RR and OR of per 1 mg/ml-SUA increase were calculated separately because of their different epidemiological implications and calculation methods. Additionally, sensitivity analysis, stratified analysis, meta-regression, and multiple meta-regression were applied to investigate the heterogeneity among studies.

Results

A total of 970 articles were retrieved from the searches. Sixteen publications of cohort studies containing 61,714 participants were included. The pooled RR was 1.131 (95% CI: 1.084–1.179) with significant heterogeneity among studies (I² = 51.9%, P = 0.018). Adjusted RR to evaluate the stability of the relationship between SUA and T2DM in the sensitivity analysis was similar (RR = 1.140, 95% CI: 1.087–1.197), with statistically significant heterogeneity (I² = 54.5%, P = 0.015). Stratified analysis and meta-regression showed that the positive relationship remained irrespective of age, sex, region, and adjustment for confounding factors including body mass index, fasting blood glucose, systolic blood pressure, diastolic blood pressure, alcohol consumption, smoking, blood cholesterol, waist circumference, fatty liver, and drugs affecting SUA.

Conclusion

Although SUA is independently associated with development of T2DM, insulin resistance increased as the baseline SUA concentration increased; thus, the correlation between SUA and T2DM requires further evaluation and the baseline insulin resistance status should also be considered.

Bidirectional Association between Diabetes and Gout: the Singapore Chinese Health Study

We aimed to prospectively investigate the bidirectional association between type 2 diabetes (T2D) and gout. We analyzed follow-up data from the Singapore Chinese Health Study, when self-reports of diagnosed diabetes and gout were enquired at follow-ups I and II. Individuals who participated in both follow-ups and were free of cardiovascular disease or cancer at follow-up I were included. For T2D to gout (analysis I), prevalent gout were further excluded (final n = 31,137). For gout to T2D (analysis II), prevalent diabetes were excluded (final n = 28,668). Cox regression models were used to estimate relative risks (RRs). In the analysis I, the RR of diabetes to incident gout (682 cases) was 0.77 (95% CI 0.60–0.97). In the analysis II, the RR of gout to incident diabetes (2223 cases) was 1.36 (1.12–1.63), but became insignificant after adjustment for hypertension and BMI (1.00; 0.83–1.21). The gout to diabetes association was modified by BMI (P_interaction = 0.04) and hypertension (P_interaction = 0.007), and it was marginally significant in adults with BMI<24 while significant among non-hypertensive participants, but not in their counterparts. In conclusion, our results suggest that diabetes is associated with a lower risk of incident gout, while gout is positively related to diabetes among normal weight and non-hypertensive adults.

An Invert U-Shaped Curve: Relationship Between Fasting Plasma Glucose and Serum Uric Acid Concentration in a Large Health Check-Up Population in China

There are some published studies focus on the invert U-shaped relationship between fasting plasma glucose (FPG) and serum uric acid (UA), while the threshold value and gender differences of this relationship were still obscure. We aimed to explore the dose-response relation between FPG level and serum UA concentration by conducted this epidemiological research in a large health check-up population in China. A total of 237,703 people were collected from January 2011 to July 2014 in our cross-sectional study; 100,348 subjects age 18 to 89 years and without known diabetes were included for the current analysis. One-way analysis of variance, generalized additive models, and 2-piecewise linear regression model were used. The mean concentration of UA with FPG of <6.1, 6.1 to 6.9, and ≥7.0 mmol/L was 240.9, 260.2, and 259.6 μmol/L in women and 349.0, 360.8, and 331.0 μmol/L in men. An invert U-shape with a threshold FPG of 7.5 (women)/6.5 (men) mmol/L was observed in the regression curve of FPG and UA, even after adjusting for potential confounders. The adjusted regression coefficients were 2.4 (95% confidence interval [CI]: 1.5 to 3.4, P < 0.001) for FPG < 7.5 mmol/L, -3.2 (95% CI: -5.0 to -1.3, P < 0.001) for FPG ≥ 7.5 mmol/L in women; while 0.8 (95% CI: -0.4 to 2.0, P = 0.19) for FPG < 6.5 mmol/L, -7.1 (95% CI: -8.0 to -6.1, P < 0.001) for FPG ≥ 6.5 mmol/L in men. Furthermore, the interaction between different FPG level and sex was significant (P < 0.05). An invert U-shape with a threshold of FPG was existed for serum UA level in Chinese adults age 18 to 89 years without known diabetes, and significant gender differences were found. Future researches should pay more attention to this relationship.

The Effect of Glycemic Status on Kidney Stone Disease in Patients with Prediabetes

BACKGROUND

While the evidence supporting a positive association between diabetes mellitus and kidney stone disease (KSD) is solid, studies examining the association between impaired fasting glucose (IFG) and KSD show inconsistent results. Currently, there are no studies examining the relationship between impaired glucose tolerance (IGT) and KSD. The objective of this study is to investigate the effects of different glycemic statuses on KSD. The results may help to motivate patients with diabetes to conform to treatment regimens.

METHODS

We conducted a cross sectional study of a population that underwent health check-ups between January 2000 and August 2009 at the Health Evaluation Center of National Cheng Kung University Hospital. A total of 14,186 subjects were enrolled. The following categories of glycemic status were used according to the criteria of the 2009 American Diabetes Association: normal glucose tolerance, isolated IGT, isolated IFG, combined IFG/IGT, and diabetes. The existence of KSD was evaluated using renal ultrasonography, and the presence of any hyperechoic structures causing acoustic shadowing was considered to be indicative of KSD.

RESULTS

The prevalence of KSD was 7.4% (712/9,621), 9.3% (163/1,755), 10.8% (78/719), 12.0% (66/548), and 11.3% (174/1,543) in subjects with NGT, isolated IGT, isolated IFG, combined IFG/IGT, and diabetes, respectively. Isolated IFG, combined IFG/IGT, and diabetes were associated with KSD after adjusting for other clinical variables, but isolated IGT was not. Age (41 to 64 years vs. ≤40 years, ≥65 years vs. ≤40 years), male gender, hypertension, and hyperuricemia were also independently associated with KSD.

CONCLUSION

Isolated IFG, combined IFG/IGT, and diabetes, but not isolated IGT, were associated with a higher risk of KSD.

The Relation between Serum Uric Acid and HbA1c Is Dependent upon Hyperinsulinemia in Patients with Newly Diagnosed Type 2 Diabetes Mellitus

Objective. The aim of our study was to explore the dependent condition of the relationship between uric acid and blood glucose in type 2 diabetes. Research Design and Methods. We measured the HbA1c, serum uric acid, creatinine, lipids profiles, and so forth of 605 newly diagnosed type 2 diabetes patients, and oral glucose tolerance tests (OGTTs) were performed on each patient. The population was divided into high and low insulin groups. Multiple linear regression analyses were conducted to assess the relationship between uric acid and HbA1c. Results. Serum uric acid and HbA1c levels were low in newly diagnosed type 2 diabetes patients. However, we found no significant relationship between uric acid and HbA1c by regression analysis after adjusting total insulin. The concentration of uric acid was inversely correlated with HbA1c in the high insulin group, regardless of patient sex. However, no associations were found in low insulin group. Conclusions. The negative correlation between uric acid and HbA1c is conditional in newly diagnosed type 2 diabetes patients and is related to hyperinsulinemia. Therefore, uric acid is likely only useful as a biomarker of blood glucose in patients exhibiting hyperinsulinemia.

Epidemiological associations between hyperuricemia and cardiometabolic risk factors: a comprehensive study from Chinese community

Background

This study aimed to assess the associations of serum uric acid (SUA) levels and hyperuricemia with cardiometabolic risk factors in a Chinese community-dwelling population.

Methods

A large cohort of 4706 residents was enrolled in this study. Physical examinations and laboratory tests were performed following a standardized protocol. Multiple linear and logistic regression analyses were conducted with adjustment of cardiometabolic risk factors including age, sex, body mass index (BMI), blood pressure (BP), triglyceride (TG), high-density lipoprotein-cholesterol (HDL-c), low-density lipoprotein-cholesterol (LDL-c) and fasting blood glucose (FBG) levels using SPSS version 17 software.

Results

The prevalence of hyperuricemia was 7.6 %. There were significant differences in age, BMI, BP, TG, HDL-c, LDL-c and FBG levels and the proportion of men between participants with and without hyperuricemia. Multiple linear regression analysis showed that SUA levels were positively associated with age, sex, BMI, BP, TG and LDL-c levels, but negatively associated with HDL-c and FBG levels. Multiple logistic regression analysis showed that per unit increase in age was associated with a 1.014 times higher odds of the presence of hyperuricemia. Men had a 1.858 times higher odds of the presence of hyperuricemia compared with women. Per unit increases in BMI, BP, TG and LDL-c levels were associated with 1.103, 1.016, 1.173 and 1.200 times higher odds of the presence of hyperuricemia, respectively. Per unit increases in HDL-c and FBG levels were associated with 0.616 and 0.900 times lower odds of the presence of hyperuricemia, respectively.

Conclusions

In a Chinese community-dwelling population, age, sex, BMI, BP, TG, HDL-c, LDL-c and FBG levels are cardiometabolic risk factors that are significantly associated with SUA levels, as well as the presence of hyperuricemia.

Fructose and uric acid in diabetic nephropathy

Clinical studies have reported associations between serum uric acid levels and the development of diabetic nephropathy, but the underlying mechanisms remain elusive. There is evidence from animal studies that blocking uric acid production protects the kidney from tubulointerstitial injury, which may suggest a causal role for uric acid in the development of diabetic tubular injury. In turn, when fructose, which is endogenously produced in diabetes via the polyol pathway, is metabolised, uric acid is generated from a side-chain reaction driven by ATP depletion and purine nucleotide turnover. For this reason, uric acid derived from endogenous fructose could cause tubulointerstitial injury in diabetes. Accordingly, our research group recently demonstrated that blocking fructose metabolism in a diabetic mouse model mitigated the development of tubulointerstitial injury by lowering tubular uric acid production. In this review we discuss the relationship between uric acid and fructose as a novel mechanism for the development of diabetic tubular injury.

Individuals With Type 2 Diabetes Mellitus Are at an Increased Risk of Gout But This Is Not Due to Diabetes: A Population-Based Cohort Study

The relationship between type 2 diabetes and gout is complex. The objective of this study was to understand the role of diabetes itself and its comorbidities within the association between type 2 diabetes and gout.We conducted a retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD) GOLD. Persons with type 2 diabetes were identified as persons on a noninsulin antidiabetic drug (NIAD) between 2004 and 2012, and were matched to 1 control based on age, sex, and general practice. We estimated gout risk in NIAD users using Cox regression analysis. All analyses were stratified for sex.In total, 221,117 NIAD users were identified. NIAD users had an increased risk of gout (hazard ratio (HR) 1.48; 95% CI 1.41-1.54). This association was stronger in women (HR 2.23; 95% CI 2.07-2.41) compared with men (HR 1.19; 95% CI 1.13-1.26). After adjustments for BMI, eGFR, hypertension, renal transplantation, diuretics, statins, low-dose aspirin, ciclosporin, and tacrolimus, the risk disappeared in women (HR 1.01; 95% CI 0.92-1.11) and reversed in men (HR 0.61; 95% CI 0.58-0.66) (P for interaction <0.001). When stratifying gout risk according to HbA1c in male and female NIAD users, we found an inverse association between raising HbA1c and incident gout in men only. Further adjustment gave similar results.Individuals with type 2 diabetes are at increased risk of gout. This is not due to diabetes itself, but to the comorbid conditions. Diabetes itself is apparently associated with a decreased risk of gout, especially in men.

A systems view of type 2 diabetes-associated metabolic perturbations in saliva, blood and urine at different timescales of glycaemic control

AIMS/HYPOTHESIS

Metabolomics has opened new avenues for studying metabolic alterations in type 2 diabetes. While many urine and blood metabolites have been associated individually with diabetes, a complete systems view analysis of metabolic dysregulations across multiple biofluids and over varying timescales of glycaemic control is still lacking.

METHODS

Here we report a broad metabolomics study in a clinical setting, covering 2,178 metabolite measures in saliva, blood plasma and urine from 188 individuals with diabetes and 181 controls of Arab and Asian descent. Using multivariate linear regression we identified metabolites associated with diabetes and markers of acute, short-term and long-term glycaemic control.

RESULTS

Ninety-four metabolite associations with diabetes were identified at a Bonferroni level of significance (p < 2.3 × 10(-5)), 16 of which have never been reported. Sixty-five of these diabetes-associated metabolites were associated with at least one marker of glycaemic control in the diabetes group. Using Gaussian graphical modelling, we constructed a metabolic network that links diabetes-associated metabolites from three biofluids across three different timescales of glycaemic control.

CONCLUSIONS/INTERPRETATION

Our study reveals a complex network of biochemical dysregulation involving metabolites from different pathways of diabetes pathology, and provides a reference framework for future diabetes studies with metabolic endpoints.

The association between serum uric acid levels, metabolic syndrome and cardiovascular disease in middle aged and elderly Chinese: results from the DYSlipidemia International Study

Background

To explore the association between serum uric acid (SUA) levels, metabolic syndrome (MetS) and cardiovascular disease (CVD) in patients treated with lipid-lowering agents from multiple centers in China.

Method

We investigated 15,478 participants who had been documented with recorded SUA in the DYSlipidemia International Study which included 25,697 patients, aged 45 years old or older, who were treated with lipid-lowering agents from 122 centers between April 2012 and October 2012. Logistic regression analysis was performed to examine the association between SUA levels, MetS and CVD.

Result

After adjusting for multi-variables, hyperuricemia (the highest category of SUA level) showed a significantly higher risk of MetS compared to the lowest category[according to NCEP-ATPIII criteria, odds ratio (OR) 1.51, 95 % confidence interval (CI) (1.30,1.74) in men, OR 2.35 95 % CI (2.00,2.75) in women; and according to IDF criteria, OR 1.40 95 % CI (1.20,1.63) in men, OR 1.65 95 % CI (1.41,1.94) in women]. In addition, elevated SUA concentration was shown to be associated with coronary heart disease (CHD) (OR 1.26 95 % CI (1.09, 1.45) in men, and OR 1.27, 95 % CI (1.07, 1.50) in women) and heart failure (HF) (OR 1.61 95 % CI (1.15, 2.24) in men, and OR 1.91, 95 % CI (1.29, 2.82) in women).

Conclusion

Our research suggested a positive association between SUA levels and MetS in Chinese patients receiving lipid-lowering therapy. Elevated SU levels were positively associated independently of measured confounders to CHD and HF.