Changes Over Time in Uric Acid in Relation to Changes in Insulin Sensitivity, Beta-Cell Function, and Glycemia

Uric Acid Inhibits Mice Pancreatic Steatosis via the Glycerophospholipid Pathway

Background: despite evidence for mutually reinforcing effects of serum uric acid (SUA) and lipids, the effects of uric levels on pancreatic steatosis are not well-established. In this study, the relationship between low concentrations of uric acid and pancreatic steatosis was evaluated. Methods: forty C57BL/6J mice were fed a diet of high uric acid (HU), high fat (HF), high uric acid and high fat (HUHF), and normal control (NC) (10 mice in each group). Weight was measured weekly. Ultrasonography was performed to observe the pancreatic echo intensity of all mice before the end of feeding. Subsequently, peripheral blood was taken for biochemical examination. Intact pancreatic tissues were taken, part of which was used for pathological examination, part of which was used for PCR experiments and Western Blot experiments to obtain glycerophospholipid-associated mRNA data and protein levels. Results: body weight was significantly higher in the HF group than in the other three groups. Higher uric acid matched lower total cholesterol and triglyceride, matched higher low-density lipoprotein, and matched equal high-density lipoprotein. Ultrasound images and HE staining of pancreatic tissues of mice showed that higher uric acid matched lower fat content. The mRNA levels of phospholipase A2 group IB were highest in high uric acid group, while relative protein expression levels were lowest in high uric acid and control groups. Phospholipase A2 group IIA showed the opposite patterns. Conclusions: elevated serum uric acid at low concentrations can inhibit pancreatic steatosis, which is modulated via the glycerophospholipid metabolic pathway.

Design of Machine Learning Algorithms and Internal Validation of a Kidney Risk Prediction Model for Type 2 Diabetes Mellitus

Objective

This study aimed to explore specific biochemical indicators and construct a risk prediction model for diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D).

Methods

This study included 234 T2D patients, of whom 166 had DKD, at the First Hospital of Jilin University from January 2021 to July 2022. Clinical characteristics, such as age, gender, and typical hematological parameters, were collected and used for modeling. Five machine learning algorithms [Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF)] were used to identify critical clinical and pathological features and to build a risk prediction model for DKD. Additionally, clinical data from 70 patients (nT2D = 20, nDKD = 50) were collected for external validation from the Third Hospital of Jilin University.

Results

The RF algorithm demonstrated the best performance in predicting progression to DKD, identifying five major indicators: estimated glomerular filtration rate (eGFR), glycated albumin (GA), Uric acid, HbA1c, and Zinc (Zn). The prediction model showed sufficient predictive accuracy with area under the curve (AUC) values of 0.960 (95% CI: 0.936-0.984) and 0.9326 (95% CI: 0.8747-0.9885) in the internal validation set and external validation set, respectively. The diagnostic efficacy of the RF model (AUC = 0.960) was significantly higher than each of the five features screened with the highest feature importance in the RF model.

Conclusion

The online DKD risk prediction model constructed using the RF algorithm was selected based on its strong performance in the internal validation.

Serum cell division cycle 42 reflects the development and progression of diabetic nephropathy in patients with diabetes mellitus

Cell division cycle 42 (CDC42) regulates podocyte apoptosis to take part in the development and progression of diabetic nephropathy (DN), but currently the clinical evidence is limited. The aim of the present study was to investigate the capability of serum CDC42 expression level to estimate the development and progression of DN in patients with diabetes mellitus (DM). Patients with type 2 DM (n=306) were enrolled and divided into normoalbuminuria (n=185), microalbuminuria (n=72) and macroalbuminuria (n=49) groups based on the urinary albumin-to-creatinine ratio. Serum CDC42 was measured in all subjects using enzyme-linked immunosorbent assay. The median (interquartile range) CDC42 in patients with DM was 0.461 (0.314-0.690) ng/ml (range, 0.087-1.728 ng/ml). CDC42 was positively associated with the estimated glomerular filtration rate (P<0.001), but negatively correlated with body mass index, systolic blood pressure, hemoglobin A1c, serum creatine, serum uric acid and C reactive protein (all P<0.050). CDC42 levels were lowest in the macroalbuminuria group, followed by the microalbuminuria group, and were highest in the normoalbuminuria group (P<0.001). CDC42 indicated that it was a favorable estimator for the presence of albuminuria [area under the curve (AUC), 0.792; 95% confidence interval (CI), 0.736-0.848] and macroalbuminuria (AUC, 0.845; 95% CI, 0.775-0.915). By analyses in four different multivariate logistic regression models, increased CDC42 was independently associated with the presence of microalbuminuria (all P<0.001), macroalbuminuria (most P<0.001) and microalbuminuria + macroalbuminuria (all P<0.001). Serum CDC42 level negatively correlated with microalbuminuria and macroalbuminuria in patients with DM, suggesting its ability for estimating the development and progression of DN.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

The Management of Diabetes with Hyperuricemia: Can We Hit Two Birds with One Stone?

Serum urate (SU) is an independent predictor for the incidence of diabetes. In current diabetes treatment regimens, there is insufficient appreciation of the importance of hyperuricemia (HU) in disease control and prevention. To summarize the updated knowledge on the effects of SU on β-cell function, insulin resistance and chronic diabetic complications, as well as to evaluate the management of patients with both HU and diabetes, we searched the MEDLINE PubMed database, and included 285 journal articles. An inverted U-shaped relationship between fasting plasma glucose and SU levels was established in this review. Elevated SU levels may enhance the development of chronic diabetic complications, including macrovascular and microvascular dysfunction. Diet and exercise are essential parts of the lifestyle changes necessary for HU and diabetes management. Glucose- and urate-lowering drug selection and combination should be made with the principle of ameliorating, and at least not deteriorating, diabetes and HU. Medical artificial intelligence technology and monitoring systems can help to improve the effectiveness of long-term management of HU and diabetes through digital healthcare. This study comprehensively reviews and provides a scientific and reliable basis for and viewpoints on the clinical management of diabetes and HU.

Relationship between baseline and changed serum uric acid and the incidence of type 2 diabetes mellitus: a national cohort study

Objective

To explore the correlation between baseline serum uric acid (SUA) and SUA changes with the incidence of type 2 diabetes mellitus (T2DM) among middle-aged and older individuals.

Method

Binary logistic regression was used to calculate the odds ratio (ORs) and 95% confidence intervals (CIs) of the effects of baseline and changes in SUA on the incidence of T2DM. Stratified analysis was conducted based on sex, and the SUA levels were classified into four quartiles to assess the effect of baseline and relative changes in SUA on the incidence of T2DM. Furthermore, interaction analysis was performed between body mass index (BMI) and SUA, age and SUA, and sex and SUA.

Results

In the cohort study, the highest quartiles of SUA were significantly correlated with an increased incidence of T2DM among females in model 1 [OR = 2.231 (1.631, 3.050)], model 2 [OR = 2.090 (1.523, 2.867)], model 3 [OR = 2.075 (1.511, 2.849)], and model 4 [OR = 1.707 (1.234, 2.362)]. The highest quartiles of SUA had a statistically significant effect on the incidence of T2DM among all participants in model 1 [OR = 1.601 (1.277, 2.008)], model 2 [OR = 1.519 (1.204, 1.915)], model 3 [OR = 1.597 (1.257, 2.027)], and model 4 [OR = 1.380 (1.083, 1.760)]. Regarding the relative change of SUA, the highest quantiles of SUA were significantly correlated with an increased incidence of T2DM among females in model 1 [OR = 1.409 (1.050, 1.890)], model 2 [OR = 1.433 (1.067, 1.926)], and model 3 [OR = 1.420 (1.056, 1.910)], and there was a statistically significant correlation with incident T2DM among all participants in model 4 [OR = 1.346 (1.079, 1.680)] after adjusting for all covariates. However, there was no significant correlation between baseline, relative, and absolute changes in SUA and the incidence of T2DM among males. The interaction analysis demonstrated that sex, BMI, and the relative changes in SUA had a combined effect on the incidence of T2DM, while age and the changes in SUA had a joint effect on the incidence of T2DM only in females.

Conclusion

There was a positive association between SUA and the incidence of T2DM for all participants. However, significant sex differences in incidence were observed only in women, not men.

Therapeutic effects of icariin and icariside II on diabetes mellitus and its complications

Diabetes mellitus (DM) is a global health issue in the twenty-first century, and there are numerous challenges in preventing and alleviating its chronic complications. The herb Epimedium has beneficial therapeutic effects on various human diseases, including DM. Its major flavonoid component, icariin, has significant anti-DM activity and may help improve pancreatic β-cell dysfunction and insulin resistance. Furthermore, preclinical evidence has shown that icariin and its in vivo bioactive form, icariside II, have preventive and therapeutic effects on several diabetic complications, including diabetic cardiomyopathy, diabetic vascular endothelial disorder, diabetic nephropathy, and diabetic erectile dysfunction. In this review, we present the general and toxicological information concerning icariin and icariside II and review the anti-DM effects of icariin from a molecular perspective. Additionally, we discuss the potential benefits of icariin and icariside II on the important pathological mechanisms of various diabetic complications. Despite positive preclinical evidence, additional investigations are needed before relevant clinical studies can be conducted. Therefore, we conclude with suggestions for future research. Hopefully, this review will provide a comprehensive molecular perspective for future research and product development related to icariin and icariside II in treating DM and diabetic complications.

Time course of serum uric acid accumulation and the risk of diabetes mellitus

Background

The impact of long-term serum uric acid (SUA) exposure and time course of SUA accumulation on diabetes mellitus (DM) is unknown. This study aimed to evaluate the association of cumulative SUA (cumSUA) exposure and its accumulation time course with risk of DM.

Methods

This prospective study included 46,434 participants without DM and underwent three examinations at 2006, 2008, and 2010. CumSUA from 2006 to 2010 was calculated, multiplying mean values between consecutive examinations by time intervals between visits. Time course of SUA accumulation was categorized as the slope of SUA versus time from 2006 to 2010, or by splitting the overall accumulation into an early (cumSUA_06-08) and late accumulation (cumSUA_08-10).

Results

During 6.99 years of follow-up, we identified 2971 incident DM cases. In the fully adjusted model, a higher risk of DM was observed in participants with the highest quartile of cumSUA (hazard ratio [HR], 1.31; 95% confidence interval [CI], 1.17–1.46), cumulative burden >0 (HR, 1.23; 95% CI, 1.08–1.40), and with 6 year of hyperuricemia exposure duration (HR, 1.25; 95% CI, 1.01–1.55). When considering the time course of SUA accumulation, participants with a negative slope (HR, 1.05; 95% CI, 1.01–1.12), or combined with cumSUA ≥ median and a negative slope had elevated risk of DM (HR, 1.58; 95% CI, 1.18–2.11).

Conclusions

Incident DM risk depends on cumulative exposure of SUA and time course of SUA accumulation. Early SUA accumulation resulted in a greater risk increase compared with later accumulation, emphasizing the importance of optimal SUA control early in life.

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.

Decrease in Serum Urate Level Is Associated With Loss of Visceral Fat in Male Gout Patients

OBJECTIVE

To clarify the relationship between serum urate (SU) decrease and visceral fat area (VFA) reduction in patients with gout.

METHODS

We retrospectively analyzed 237 male gout patients who had two sets of body composition and metabolic measurements within 6 months. Subjects included had all been treated with urate-lowering therapy (ULT) (febuxostat 20-80 mg/day or benzbromarone 25-50 mg/day, validated by the medical record). All patients were from the specialty gout clinic of The Affiliated Hospital of Qingdao University. The multiple linear regression model evaluated the relationship between change in SU [ΔSU, (baseline SU) - (final visit SU)] and change in VFA [ΔVFA, (baseline VFA) - (final visit VFA)].

RESULTS

ULT resulted in a mean (standard deviation) decrease in SU level (464.22 ± 110.21 μmol/L at baseline, 360.93 ± 91.66 μmol/L at the final visit, p <0.001) accompanied by a decrease in median (interquartile range) VFA [97.30 (81.15-118.55) at baseline, 90.90 (75.85-110.05) at the final visit, p < 0.001]. By multiple regression model, ΔSU was identified to be a significant determinant variable of decrease in VFA (beta, 0.302; p = 0.001).

CONCLUSIONS

The decrease in SU level is positively associated with reduced VFA. This finding provides a rationale for clinical trials to affirm whether ULT promotes loss of visceral fat in patients with gout.

Asymptomatic Hyperuricemia Associates with Cardiometabolic Risk Indicators in Overweight/Obese but Not in Lean Adolescents

PURPOSE

In overweight/obese adolescents, asymptomatic hyperuricemia is associated with increased prevalence of metabolic syndrome, its components, and a higher cardiometabolic risk. Whether similar associations exist in lean hyperuricemic adolescents is unknown.

SUBJECTS AND METHODS

In 2424 adolescents (51.9% females) aged 16-19 years, anthropometric variables, blood pressure, uric acid, glucose, insulin, lipid profile, inflammatory markers, and renal function were determined. Continuous cardiometabolic score was calculated. Normouricemic vs hyperuricemic subjects were compared among lean and overweight/obese individuals of both sexes.

RESULTS

Females (5.4%) and males (13.3%) presented with hyperuricemia; among them 63% of females and 53% of males were lean. In both sexes, hyperuricemic lean and hyperuricemic overweight/obese adolescents displayed similar uric acid concentrations (eg, males: 455±30 vs 461±32 µmol/L, respectively, p=0.933). Lean normouricemic adolescents manifested significantly lower uric acid levels than their overweight/obese peers (eg, males: 333±46 vs 357±41 µmol/L, respectively, p<0.001). Lean normouricemic and hyperuricemic subjects presented similar cardiometabolic score (eg, males: 2.60±0.67 vs 2.64±0.60, respectively, p=0.998); among overweight/obese adolescents those with hyperuricemia displayed higher scores compared with their normouricemic counterparts (eg, males: 3.36±1.04 vs 4.21±1.65, respectively, p<0.001). A decision-tree model revealed phenotypes associated with higher uricemia, however, distribution of individuals with hyperuricemia among phenotypes was random.

CONCLUSION

In lean adolescents, hyperuricemia is not associated with cardiometabolic profile indicating an increased risk. Existence of this rather prevalent phenotype remains undetected unless lean and overweight/obese subjects are analyzed separately. Longitudinal studies are needed to elucidate the potential clinical consequences of asymptomatic hyperuricemia in lean subjects in later life.