Higher Serum Uric Acid May Contribute to Cerebral Infarction in Patients with Type 2 Diabetes Mellitus: a Meta-Analysis

The role of high fat diet on serum uric acid level among healthy male first degree relatives of type 2 diabetes mellitus

First-degree relatives (FDR) of type 2 diabetes mellitus have increased risk of developing insulin resistance-related disorders including hyperuricemia. We investigated metabolic profile and serum uric acid (SUA) metabolism in response to high-fat diet among healthy male FDR in comparison to those without family history of diabetes. A total of 30 FDR and 30 non-FDR subjects completed a 5-days-hypercaloric diet with fat added to regular daily intake. Despite similar insulin response, FDR displayed different changes in SUA compared to non-FDR subjects (0.26 ± 0.83 mg/dL vs - 0.21 ± 0.78 mg/dL, p = 0.028). In subgroup analyses stratified by body mass index and waist circumference, significant different SUA changes between FDR and non-FDR subjects were only found in obese (0.48 ± 0.87 mg/dL vs - 0.70 ± 0.71 mg/dL, p = 0.001) and centrally obese (0.59 ± 0.83 mg/dL vs - 0.55 ± 0.82 mg/dL, p = 0.011) subgroups. In multivariate analysis, visceral adiposity seemed mediating the different response in SUA metabolism between FDR and non-FDR subjects induced by short-term obesogenic diet.

Identification of a plausible serum uric acid cut-off value as prognostic marker of stroke: the Uric Acid Right for Heart Health (URRAH) study

The Working Group on Uric Acid and Cardiovascular Risk of the Italian Society of Hypertension conceived and designed an ad hoc study aimed at searching for prognostic cut-off values of serum uric acid (SUA) in predicting combined (fatal and non-fatal) cerebrovascular (CBV) events in the whole database. The URic acid Right for heArt Health study is a nationwide, multicenter, observational cohort study involving data on subjects aged 18-95 years recruited on a regional community basis from all the territory of Italy under the patronage of the Italian Society of Hypertension with a mean follow-up period of 120.7 ± 61.8 months. A total of 14,588 subjects were included in the analysis. A prognostic cut-off value of SUA able to discriminate combined CBV events (>4.79 mg/dL or >284.91 µmol/L) was identified by means of receiver operating characteristic curve in the whole database. Multivariate Cox regression analysis adjusted for confounders (age, sex, arterial hypertension, diabetes, chronic kidney disease, smoking habit, ethanol intake, body mass index, low-density lipoprotein cholesterol, and use of diuretics) identified an independent association between SUA and combined CBV events in the whole database (HR 1.249, 95% confidence interval, 1.041-1.497, p = 0.016). The results of the present study confirm that SUA is an independent risk marker for CBV events after adjusting for potential confounding variables, including arterial hypertension, and demonstrate that >4.79 mg/dL is a valid prognostic cut-off value.

Depletion of mmu_circ_0001751 (circular RNA Carm1) protects against acute cerebral infarction injuries by binding with microRNA-3098-3p to regulate acyl-CoA synthetase long-chain family member 4

Circular RNAs (circRNAs) play a critical role in acute cerebral infarction (ACI). Our research discussed the effect of circ-Carm1 in ACI and its potential molecular mechanisms. Healthy controls and patients with ACI were included in this study. The establishment of an oxygen and glucose deprivation/reoxygenation (OGD/R) model of HT22 cells was conducted to mimic ACI in vitro. Quantitative reverse transcription polymerase chain reaction was conducted to determine mRNA levels extracted from serum and HT22 cell samples, and Western blotting was performed to determine protein levels. Terminal deoxynucleotidyl transferase dUTP nick end labeling and cell counting kit 8 assays were conducted to evaluate cellular functions. Concentrations of Fe²⁺ and malondialdehyde, and levels of transferrin receptor 1, glutathione peroxidase 4, and glutathione were evaluated to determine ferroptosis in OGD/R-induced HT22 cells. The binding relationships between mRNAs and miRNAs were verified. circ-Carm1 was highly expressed in OGD/R-treated HT22 cells. Deficiency of circ-Carm1 restored cell viability and suppressed ferroptosis in OGD/R-induced HT22 cells. miR-3098-3p was predicted to be a target of circ-Carm1. The miR-3098-3p inhibitor partly neutralized the functions of circ-Carm1 in OGD/R-induced HT22 cells. Furthermore, acyl-CoA synthetase long-chain family member 4 (ACSL4) was confirmed to be a downstream target of miR-3098-3p and was elevated in OGD/R-induced HT22 cells. Overexpression of ACSL4 mitigated the functions of miR-3098-3p and accelerated HT22 cell dysfunction. Hence, circ-Carm1 is upregulated in ACI. circ-Carm1 suppression protects HT22 cells from dysfunction by inhibiting ferroptosis. Therefore, inducing circ-Carm1 deficiency may be a promising therapeutic method for ACI.

Associaton of Retinol Binding Protein 4 (RBP4) Levels With Hyperuricemia: A Cross-Sectional Study in a Chinese Population

BACKGROUND

There are few studies on predictive biomarkers for hyperuricemia, and the predictive value of these biomarkers tends to be poor. Additionally, no reports have described the predictive value of retinol binding protein 4 (RBP4) for hyperuricemia.

PURPOSE

This study was performed to evaluate the value of RBP4 for predicting the risk of hyperuricemia in a general population, determine whether RBP4 could be used alone or in combination with other factors to predict the risk of hyperuricemia in the general population, and establish an optimum predictive model.

METHODS

We conducted a population-based cross-sectional survey in 2018, involving a questionnaire, physical examination, and laboratory testing. We enrolled 2303 individuals by stratified random sampling, and 2075 were included in the data analysis after applying the eligibility criteria.

RESULTS

Serum RBP4 level had a highly significant association with hyperuricemia (P<0.001). After adjusting for potential confounders, logistic regression indicated that the risk of hyperuricemia was highest in the highest RBP4 quartile (odds ratio: 7.9, 95% confidence interval [CI]: 4.18-14.84, compared to the lowest quartile). The area under the receiver operating characteristic (ROC) curve (AUC) for RBP4 was 0.749 (95% CI: 0.725-0.774, P<0.001), which was higher than that for all the other predictors assessed. The optimum model for predicting hyperuricemia in the general population consisted of RBP4, sex (male), body mass index, serum creatinine, high-sensitivity C-reactive protein, fasting blood glucose, insulin, and alcohol consumption. The AUC was 0.804 (95% CI: 0.782-0.826, P<0.001).

CONCLUSIONS

RBP4 is strongly associated with hyperuricemia, and its predictive value was higher than that of traditional predictors.

Hyperuricemia, Gout, and the Brain-an Update

PURPOSE OF REVIEW

This review aims to summarize recent evidence regarding the complex relationship between uric acid (UA), gout, and brain diseases.

RECENT FINDINGS

Observational studies have suggested that patients with hyperuricemia or gout might have a decreased risk of neurodegenerative diseases. Conversely, they may be at increased risk of cerebrovascular disease. Mendelian randomization (MR) studies use a genetic score as an instrumental variable to address the causality of the association between a risk factor (here, UA or gout) and an outcome. So far, MR analyses do not support a causal relationship of UA or gout with Alzheimer's disease and dementia, and of UA with Parkinson's disease or stroke. Observation studies indicate a U-shaped association between UA and brain diseases, but MR studies do not support that this association is causal. Further studies should address the causal role of gout as well as the impact of urate-lowering therapy on these outcomes.

Serum Uric Acid and Diabetes: From Pathophysiology to Cardiovascular Disease

Hyperuricemia, has been traditionally related to nephrolithiasis and gout. However, it has also been associated with the development of type 2 diabetes mellitus (T2DM) and cardiometabolic and cardiovascular diseases. Pathophysiologically, elevated serum uric acid (SUA) levels may be associated with abnormal lipid and glucose metabolism. In this narrative review, we consider the associations between hyperuricemia, hyperglycemia, atherosclerosis and thrombosis. Furthermore, we comment on the available evidence linking elevated SUA levels with the incidence and outcomes of coronary heart disease, stroke, peripheral artery disease and non-alcoholic fatty liver in subjects with T2DM. The effects of antidiabetic drugs (e.g. metformin, pioglitazone, sulfonylureas, dipeptidyl peptidase 4 inhibitors, glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter 2 inhibitors and insulin) on SUA concentrations are also reviewed.

Identification of two novel subgroups in patients with diabetes mellitus and their association with clinical outcomes: A two-step cluster analysis

Aims/Introduction

The aim of this study was to determine whether distinct subphenotypes of patients with type 2 diabetes in the European classification exist in Chinese populations, and to further establish novel subphenotypes more suitable for Chinese populations.

Material and Methods

The research retrospectively analyzed 5414 patients with type 2 diabetes from the National Clinical Research Center for Metabolic Diseases Diabetes Center in China, and a two‐step cluster analysis was carried out. First, we confirmed the European classification in Chinese populations by six parameters, including age at disease onset, body mass index, glycosylated hemoglobin, homeostatic model assessment 2 to estimate β‐cell function and insulin resistance, and glutamate decarboxylase antibodies. Furthermore, triglycerides and uric acid were added to refine the cluster analysis, and Cox regression was used to evaluate the risk of diabetic complications.

Results

Just three clusters were replicated in our cohort according to Emma Ahlqvist's European classification. When other variables were added to the cluster analysis, seven subgroups were identified, including five clusters of the European classification and two novel subgroups, namely, uric acid‐related diabetes and inheritance‐related diabetes. Compared with patients with inheritance‐related diabetes, patients with severe insulin‐resistant diabetes showed a higher risk of diabetic peripheral neuropathy, hypertension and chronic kidney disease, and the uric acid‐related diabetes subgroup showed a higher risk of coronary heart disease, cerebral vascular disease and end‐stage renal disease. Patients with severe insulin‐deficient diabetes showed a higher risk of diabetic retinopathy and diabetic foot than those with inheritance‐related diabetes. Furthermore, there were sex‐specific associations between subgroups and clinical outcomes. No significant difference was observed in the prevalence of cancer in each subgroup.

Conclusions

Seven subgroups of type 2 diabetes were identified in Chinese populations, with distinct characteristics and disparate clinical outcomes. This etiology‐based stratification might contribute to the diagnosis and management of type 2 diabetes.

Associations of Serum Uric Acid with Clustering of Cardiovascular Risk Factors and a 10-Year Atherosclerotic Cardiovascular Disease Risk Score in Jiangsu Adults, China

PURPOSE

The relationship between serum uric acid (SUA) and Chinese characteristic 10-year atherosclerotic cardiovascular disease (ASCVD) risk score has not been well evaluated in Chinese populations. Aims of this cross-sectional study were to describe the correlation between SUA level and clustering of prevalent cardiovascular risk factors (CRFs) including overweight, central obesity, hypertension, diabetes and dyslipidemia, as well as the Chinese 10-year ASCVD risk score in adults from Jiangsu Province located in Eastern China.

PATIENTS AND METHODS

A total of 7700 adults from 12 cities in Jiangsu Province were selected through multi-stage stratified cluster random sampling method in 2015. Face-to-face interviews, physical examinations and laboratory examinations were carried out to collect the information of the participants. Multivariate logistic analysis was used to analyze the relationship between SUA quartiles and various CVD risk factors. The nonlinear analysis was conducted to evaluate the relationship between SUA levels and the China-PAR 10-year ASCVD risk scores.

RESULTS

The prevalence of hyperuricemia was 13.3% in all of the participants. By adjusting potential confounders, significant correlations were found between the SUA level and the overweight, central obesity, hypertension and dyslipidemia in both males and females. The clustering of CRFs was different across SUA quantiles (χ ²=607.685, P<0.001). After Gamma trend test (P < 0.001) and ordered logistic regression analysis, it was found out that with the increase of SUA quantiles, prevalent CRFs gradually gathered in both males and females. Furthermore, sex-specific difference was identified between SUA and 10-year ASCVD risk scores.

CONCLUSION

The accumulation of CRFs increased with elevated SUA levels, whereas it was different between genders in the relationship between SUA and 10-year ASCVD risk scores. Tailored strategies should be taken when it came to males and females in managing SUA.

Establishment of Clinical Prediction Model Based on the Study of Risk Factors of Stroke in Patients With Type 2 Diabetes Mellitus

Purpose: Stroke has sparked global concern as it seriously threatens people's life, bringing about dramatic health burdens on patients, especially for type 2 diabetes mellitus (T2DM) patients. Therefore, a risk scoring model is urgently valuable for T2DM patients to predict the risk of stroke incidence and for positive health intervention. Methods: We randomly divided 4,335 T2DM patients into two groups, training set (n = 3,252) and validation set (n = 1,083), at the ratio of 3:1. Characteristic variables were then selected based on the data of training set through least absolute shrinkage and selection operator regression. Three models were established to verify predictive ability. Foundation model was composed of basic information and physical indicators. Biochemical model consisted of biochemical indexes. Integrated model combined the above two models. Data of three models were then put into logistic regression analysis to form nomogram prediction models. Tools including C index, calibration plot, and curve analysis were implemented to test discrimination, calibration, and clinical use. To select the best predicting model, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were put into effect. Results: Eleven risk factors were determined, including age, duration of T2DM, estimated glomerular filtration rate, systolic blood pressure, diastolic blood pressure, low-density lipoprotein, high-density lipoprotein, triglyceride, body mass index, uric acid, and glycosylated hemoglobin A_1c, all with significant P-values through logistic regression analysis. In the training set, areas under the curve of three models were 0.810, 0.819, and 0.884, whereas in the validation set, they were 0.836, 0.832, and 0.909. Through calibration plot, the S:P values in the training set were 0.836, 0.754, and 0.621 and were 0.918, 0.682, and 0.666 separately in the validation set. In terms of the decision curve analysis, the risk thresholds were, respectively, 8-73%, 8-98%, and 8%~ in the training set and 8-70%, 8-90%, and 8-95% in the validation set. With the aid of NRI and IDI, integrated model is proved to be the best model in training set and validation set. Besides, internal validation was conducted on all the subjects in this study, and the C index was 0.890 (0.873-0.907). Conclusion: This study established a model predicting risk of stroke for T2DM patients through a community-based survey.

Effects of Uric Acid on Diabetes Mellitus and Its Chronic Complications

With the deepening of the researches on uric acid, especially in the study of metabolic diseases, uric acid has been found to be closely related to obesity, metabolic syndrome, nonalcoholic fatty liver disease, diabetes, and other metabolic diseases. Uric acid causes a series of pathophysiological changes through inflammation, oxidative stress, vascular endothelial injury, and so on and thus subsequently promotes the occurrence and development of diseases. This review confirmed the positive correlation between uric acid and diabetes mellitus and its chronic complications through the pathogenesis and clinical studies aspects.

Serum uric acid as a risk factor of all-cause mortality and cardiovascular events among type 2 diabetes population: Meta-analysis of correlational evidence

AIMS

To explore the association between serum uric acid (SUA) level and the risk of cardiovascular complications and all-cause mortality rates among individuals with type 2 diabetes.

METHODS

Web of Science and PubMed database were searched for studies reported associations between SUA level and cardiovascular complications and all-cause mortality among individuals with type 2 diabetes. Hazard ratios (HRs) were independently extracted by two investigators and synthesized through meta-analysis across selected studies.

RESULTS

6 (n = 11,750 patients), 4 (n = 3044 patients) and 2 studies (n = 7792 patients) were identified reporting associations between SUA level and all-cause mortality, coronary heart disease (CHD) and stroke respectively. HR for all-cause mortality, CHD, and stroke per 59 μmol/l increase was 1.06 (95% CI: 1.03, 1.09), 1.09 (95% CI: 0.94, 1.26) and 1.19 (95% CI: 1.08, 1.31), respectively.

CONCLUSIONS

Overall, the SUA level was associated with a higher risk of all-cause mortality and stroke. We found no significant association between SUA level and CHD among type 2 diabetes population.

Effectiveness of Fuyuan Xingnao Decoction for patients with diabetes mellitus combined cerebral infarction

BACKGROUND

Previous study has reported that Fuyuan Xingnao Decoction (FYXND) can be utilized for the treatment of patients with diabetes mellitus (DM) combined cerebral infarction (CI) effectively.

METHODS

We will search from the following databases of MEDLINE, EMBASE, Cochrane Library, PsycINFO, Global Health, Web of Science, Allied and Complementary Medicine Database, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. All databases will be searched from the inception to the present without language limitation. Two independent authors will perform literature selection, information collection, and methodological quality assessment. Statistical analysis will be carried out using RevMan 5.3 software.

RESULTS

This study will provide accurate results on the effectiveness and safety of FYXND on DM and CI through primary and secondary outcomes. The primary outcome is neurological deficit. The secondary outcomes consist of fasting blood glucose, hemoglobin Alc, fasting insulin, quality of life, and adverse effects.

CONCLUSIONS

This well-designed study will establish high quality evidence of the effectiveness and safety of FYXND for DM and CI to facilitate the clinical practice and guideline development.

The Impact Of Hyperuricemia On Cardiometabolic Risk Factors In Patients With Diabetes Mellitus: A Cross-Sectional Study

PURPOSE

Hyperuricemia (HUA) is linked to a variety of non-communicable diseases such as atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD) and hypertension, with evidence showing its role in the development of diabetes mellitus (DM). Our study's main aim was to explore the associations of HUA with other traditional risk factors in Romanian patients with DM and to assess the impact of the increase of serum UA on DM complications and HbA1c.

PATIENTS AND METHODS

In this cross-sectional, non-interventional study, we enrolled, according to a population-based, consecutive-case principle, 133 patients previously diagnosed with DM. HbA1c, uric acid, lipid profile, urinary albumin/creatinine ratio, glomerular filtration rate, TSH and FT₄ measurements were performed, while the diagnosis of retinopathy and of diabetic neuropathy was established using standardized methods.

RESULTS

An increased uric acid level was associated with a significant increase in the risk for development of stroke (OR=1.526; p=0.004). A weak, positive and statistically significant correlation can also be observed between the BMI and the presence of hyperuricemia (r=0.131; p=0.034), and between the triglyceride levels and hyperuricemia (r= 0.173; p=0.004). Glomerular filtration rate was correlated to hyperuricemia in a strong and negative manner, having an important statistical significance (r=-0.818; p=0.003). In our study, UA levels and HbA1c were negatively correlated, without reaching statistical significance.

CONCLUSION

Serum UA is strongly correlated with the BMI, triglyceride level and GFR in Romanian patients with DM and HUA is significantly associated with a higher risk of stroke in these individuals.

Serum uric acid concentrations and risk of intracerebral hemorrhage: A systematic review and meta-analysis

BACKGROUND AND AIMS

The relationship between serum uric acid (UA) and the risk of intracerebral hemorrhage (ICH) remains controversial. The aim of our systematic review and meta-analysis was to ascertain the association between serum UA concentrations and the risk of ICH.

METHODS

We systematically searched databases of Embase, Pubmed, Web of Science and Cochrane Library up to December 30, 2017, and additional papers were identified through a manual search. Mean difference (MD) for serum UA levels with 95% confidence intervals (CI) was calculated. Six studies, including 345 ICH patients, 574 ischemic stroke patients and 535 healthy controls, were identified for meta-analysis.

RESULTS

Our results revealed no statistically significant differences in the comparison of UA between ICH and healthy controls (95% CI = -9.04-15.61); UA levels in patients with ischemic stroke were significantly higher than those in healthy controls (95% CI = 3.91-56.32); further subgroup analysis of age showed higher UA levels in ICH patients over 65 years than healthy controls (age≥65: 95% CI = 1.44-35.96). Subgroup of ethnicity (Asians: CI = -9.06-21.00; Caucasians: 95% CI = -68.43-8.43), gender (Men: 95% CI = -56.08-4.73; Women: 95% CI = -27.19-35.91) and sample size (large samples: 95% CI = -20.54-41.05; small samples: 95% CI = -25.41-13.78) with respect to UA levels between ICH and healthy controls did not change these results.

CONCLUSIONS

This meta-analysis showed that serum UA levels did not increase the risk of ICH probably because of the dual roles of UA, i.e. pro-oxidant and antioxidant, in the progression of atherosclerosis. However, serum UA may be a potential risk factor for ICH in the elderly. There were no race-specific differences in UA levels between Asians and Caucasians as well as gender-related differences between men and women in the risk of ICH.

Curcumin improves diabetes mellitus‑associated cerebral infarction by increasing the expression of GLUT1 and GLUT3

Curcumin is characterized by anti‑inflammatory, anti‑oxidative, antiviral, antifibrotic, anticoagulation and glucose regulatory functions. However, whether it is protective in diabetes mellitus‑associated cerebral infarction remains to be fully elucidated. In the present study, it was demonstrated for the first time, to the best of our knowledge, that curcumin markedly improved neurological deficits, cerebral infarct volume and brain edema rate following middle cerebral artery occlusion (MCAO) surgery. It was also shown that the expression levels of glucose transporter (GLUT)1 and GLUT3 were reduced in the MCAO group. However, following curcumin treatment, the levels of GLUT1 and GLUT3 were markedly increased. In addition, curcumin markedly decreased cell apoptosis, indicating an anti‑apoptotic role of curcumin in the brain. To further evaluate whether curcumin prevented cell apoptosis by modulating the expression of GLUT1 and GLUT3, small interfering RNAs targeting GLUT1 and GLUT3 were selected. It was found that the knockdown of GLUT1 and GLUT3 inhibited the abundance of GLUT1, GLUT3 and B‑cell lymphoma 2, even following incubation with curcumin. These data showed that curcumin protected brain cells from apoptosis and cerebral infarction, predominantly by upregulating GLUT1 and GLUT3.