The objective of this study is to comprehensively to identify the core pharmacological components and their respective targets of three medicinal fungi Sanghuangs including Sanghuangporus vaninii (SV), Sanghuangporus lonicericola (SL), and Inonotus hispidus (IH). Metabolomics analysis indicated that a total of 495 and 660 differential metabolites were obtained in mycelium and fermentation broth samples among three Sanghuangs, respectively. The network pharmacology analysis showed that 6-[1]-ladderane hexanol, R-nostrenol, candidone, ellagic acid, and quercetin were the overlapping active ingredients of three Sanghuang species for diabetes mellitus, immune system disease, and neoplasm. Certonardosterol A, dalamid, and ethylene brassylate are unique active ingredients in SV, and certonardosterol K, kaempferide, and esculetin are unique active ingredients in SL. Asbestinine, neoandrographolide, isosakuranetin, and daucosterin are unique active ingredients in IH. Accordingly, the common core targets of active ingredients of the three Sanghuangs were ESR1, PIK3CA, and LYN. PRKCA, EGFR, and STAT3 were the unique targets of SV, SL, and IH, respectively. The primary active components and their respective targets, in addition to the component-target interaction of Sanghuangs that have been identified in the present study, provide a foundation for future research on the prevention and treatment of disease using Sanghuangs.

The relationship between HyperUricemia (HU) and Metabolic Sindrome (MS) and if Uric Acid (UA) should be inserted into MS definitions is a matter of debate. Aim of our study was to evaluate the correlation between UA and HU with Insulin Resistance (IR) and MS in a population of hypertensive patients. HU was defined with two cut-offs (the classic one of ≥6 mg/dL for women and ≥ 7 for men; the newly proposed URRAH one with ≥5.6 mg/dL for both sexes).

We enrolled 473 Hypertensive patients followed by the Hypertension Unit of San Gerardo Hospital (Monza, Italy). IR was defined through TG/HDL ratio and NCEP-ATP-III criteria were used for MS diagnosis.

MS was found in 33.6 % while HU affected 14.8 % of subjects according to the traditional cut-off and 35.9 % with the URRAH cut-off. 9.7 % (traditional cut-off) and 17.3 % (URRAH's threshold) of the subjects had both HU and MS. UA level was significantly higher in MS group (5.7 vs 4.9 mg/dL, p < 0.0001) as well as for HU (29.0 vs 7.6 % and 51.6 vs 28.0 %, for classic and URRAH cut-off respectively, p < 0.0001 for both comparison). Logistic multivariable regression models showed that UA is related to MS diagnosis (OR = 1.608 for each 1 mg/dL), as well as HU with both cut-off (OR = 5.532 and OR = 3.379, p < 0.0001 for all comparison, for the classic cut-off and the URRAH one respectively).

The main finding of our study is that UA and HU significantly relate to IR and MS. The higher the values of UA and the higher the cut-off used, the higher the strength of the relationship.

Nonalcoholic fatty liver disease (NAFLD) is characterized by over 5% hepatic fat accumulation without secondary causes. The prevalence of NAFLD has escalated in recent years due to shifts in dietary patterns and socioeconomic status, making it the most prevalent chronic liver disease and a significant public health concern globally. Serum uric acid (SUA) serves as the end product of purine metabolism in the body and is intricately linked to metabolic syndrome. Elevated SUA levels have been identified as an independent risk factor for the incidence and progression of NAFLD. This paper reviews the relationship between SUA and NAFLD, the underlying mechanisms of SUA involved in NAFLD, and the potential benefits of SUA-lowering therapy in treating NAFLD. The aim is to raise awareness of SUA management in patients with NAFLD, and to encourage further investigation into pharmacological interventions in this area.

Is there a relationship between serum uric acid and fructose levels in polycystic ovary syndrome (PCOS)?

Elevated serum uric acid levels in women with PCOS positively correlate with serum fructose levels, and elevated serum fructose levels are an independent risk factor for hyperuricemia in women with PCOS.

Our previous study suggested a link between elevated serum fructose levels and PCOS. Fructose is unique as it generates uric acid during metabolism, and high uric acid levels are associated with metabolic disorders and an increased risk of anovulation. However, the relationship between serum uric acid and fructose levels in women with PCOS remains unclear.

In a case-control study of 774 women (482 controls and 292 patients with PCOS) between May and October 2020 at the Shengjing Hospital of China Medical University, the relationship between uric acid and fructose levels in women with PCOS was examined. Participants were divided into subgroups based on various factors, including BMI, insulin resistance, dyslipidemia, metabolic syndrome, and hyperuricemia.

Serum uric acid concentrations were measured using enzymatic assays, and serum fructose levels were determined using a fluorescent enzyme immunoassay. Dietary fructose data were collected through a validated food-frequency questionnaire of 81 food items. We applied restricted cubic splines to a flexibly model and visualized the linear/nonlinear relationships between serum uric acid and fructose levels in PCOS. Multivariate logistic analysis was executed to assess the association between serum fructose levels and hyperuricemia in PCOS. Human granulosa cell and oocyte mRNA profile sequencing data were downloaded for mapping uric acid and fructose metabolism genes in PCOS. Further downstream analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and protein-protein interactions were then carried out on the differentially expressed genes (DEGs). The correlation between uric acid and fructose metabolism genes was calculated using the Pearson correlation coefficient. The GeneCards database was used to identify DEGs related to uric acid and fructose metabolism in PCOS, and then several DEGs were confirmed by quantitative real-time PCR.

Both serum fructose and uric acid levels were significantly increased in women with PCOS compared with the control women (P  <  0.001), and there was no statistically significant difference in dietary fructose intake between PCOS and controls, regardless of metabolic status. There was a positive linear correlation between serum uric acid and fructose levels in women with PCOS (Poverall < 0.001, Pnon-linear = 0.30). In contrast, no correlation was found in control women (Poverall = 0.712, Pnon-linear = 0.43). Additionally, a non-linear association was observed in the obese subgroup of patients with PCOS (Poverall < 0.001, Pnon-linear = 0.02). Serum uric acid levels were linearly and positively associated with serum fructose levels in patients with PCOS with insulin resistance, dyslipidemia, and metabolic syndrome. Furthermore, even after adjusting for confounding factors, elevated serum fructose levels were an independent risk factor for hyperuricemia in patients with PCOS (P  =  0.001; OR, 1.380; 95% CI, 1.207-1.577). There were 28 uric acid and 25 fructose metabolism genes which showed a significant correlation in PCOS. Seven upregulated genes (CAT, CRP, CCL2, TNF, MMP9, GCG, and APOB) related to uric acid and fructose metabolism in PCOS ovarian granulosa cells were ultimately successfully validated using quantitative real-time PCR.

Due to limited conditions, more possible covariates (such as smoking and ethnicity) were not included, and the underlying molecular mechanism between fructose and uric acid levels in women with PCOS remains to be further investigated.

The results of this study and our previous research indicate that the high uric acid status of PCOS may be mediated by fructose metabolism disorders, highlighting the importance of analyzing fructose metabolism, and especially its metabolic byproduct uric acid, during the clinical diagnosis of PCOS. These results suggest the adverse effects of high uric acid in PCOS, and the importance of taking early interventions regarding uric acid levels to reduce the occurrence and development of further clinical signs, such as metabolic disorders in women with PCOS.

This work was supported by: the National Natural Science Foundation of China (No. 82371647, No. 82071607, and No. 32100691); LiaoNing Revitalization Talents Program (No. XLYC1907071); Fok Ying Tung Education Foundation (No. 151039); and Outstanding Scientific Fund of Shengjing Hospital (No. 202003). No competing interests were declared.

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Acute physiological responses to psychosocial stressors are a potential pathway underlying racial disparities in stress-related illnesses. Uric acid (UA) is a potent antioxidant that has been linked to disparities in stress-related illnesses, and recent research has shown that UA is responsive to acute social stress. However, an examination of the relationships between the purinergic system and other commonly measured stress systems is lacking. Here, we measure and characterize associations of salivary uric acid (sUA) with markers of hypothalamic-pituitary-adrenal (HPA) axis activation, sympathetic-adreno-medullar (SAM) axis activation, and acute inflammation. A community sample of 103 African Americans (33 male, 70 female) completed the Trier Social Stress Test to induce social-evaluative threat. Passive drool collected before, during, and after the stressor task provided salivary reactivity measures of UA (sUA), cortisol, dehydroepiandrosterone sulfate (DHEAS), salivary alpha amylase (sAA - a surrogate marker of SAM activity) and C-reactive protein (sCRP). Multiple regressions revealed that total activation of cortisol, DHEAS, and sCRP were each positively associated with higher total activation of sUA. Additionally, DHEAS reactivity was positively associated with sUA reactivity. Relationships between HPA-axis markers and sUA were especially observed among younger and male participants. Overall, findings suggest potential coordination of stress systems with sUA in response to acute stress, which may further the contributions of biological stress processes to racial health disparities.

Molybdenum (Mo) is an essential element for human life, acting as a cofactor in various enzymes crucial for metabolic homeostasis. This review provides a comprehensive insight into the latest advances in research on molybdenum-containing enzymes and their clinical significance. One of these enzymes is xanthine oxidase (XO), which plays a pivotal role in purine catabolism, generating reactive oxygen species (ROS) capable of inducing oxidative stress and subsequent organ dysfunction. Elevated XO activity is associated with liver pathologies such as non-alcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC). Aldehyde oxidases (AOs) are also molybdenum-containing enzymes that, similar to XO, participate in drug metabolism, with notable roles in the oxidation of various substrates. However, beneath its apparent efficacy, AOs' inhibition may impact drug effectiveness and contribute to liver damage induced by hepatotoxins. Another notable molybdenum-enzyme is sulfite oxidase (SOX), which catalyzes the conversion of sulfite to sulfate, crucial for the degradation of sulfur-containing amino acids. Recent research highlights SOX's potential as a diagnostic marker for HCC, offering promising sensitivity and specificity in distinguishing cancerous lesions. The newest member of molybdenum-containing enzymes is mitochondrial amidoxime-reducing component (mARC), involved in drug metabolism and detoxification reactions. Emerging evidence suggests its involvement in liver pathologies such as HCC and NAFLD, indicating its potential as a therapeutic target. Overall, understanding the roles of molybdenum-containing enzymes in human physiology and disease pathology is essential for advancing diagnostic and therapeutic strategies for various health conditions, particularly those related to liver dysfunction. Further research into the molecular mechanisms underlying these enzymes' functions could lead to novel treatments and improved patient outcomes.

High-saturated fat (HF) or high-fructose (HFr) consumption in children predispose them to metabolic syndrome (MetS). In rodent models of MetS, diets containing individually HF or HFr lead to a variable degree of MetS. Nevertheless, simultaneous intake of HF plus HFr have synergistic effects, worsening MetS outcomes. In children, the effects of HF or HFr intake usually have been addressed individually. Therefore, we have reviewed the outcomes of HF or HFr diets in children, and we compare them with the effects reported in rodents. In humans, HFr intake causes increased lipogenesis, hypertriglyceridemia, obesity and insulin resistance. On the other hand, HF diets promote low grade-inflammation, obesity, insulin resistance. Despite the deleterious effects of simultaneous HF plus HFr intake on MetS development in rodents, there is little information about the combined effects of HF plus HFr intake in children. The aim of this review is to warn about this issue, as individually addressing the effects produced by HF or HFr may underestimate the severity of the outcomes of Western diet intake in the pediatric population. We consider that this is an alarming issue that needs to be assessed, as the simultaneous intake of HF plus HFr is common on fast food menus.

Plasmatic uric acid (UA) has been inconsistently associated with diabetic retinopathy (DR). Specific sight-threatening stages of DR have not been studied for their association with UA. Cross-sectional, comparative study. Between 2014 and 2018 we recruited 210 Mexican individuals > 18 years-old with type 2 diabetes (T2D). Clinical, ophthalmological and biochemical assessment was performed with standardized funduscopic examination. Certified readers classified DR stages. The association between DR and UA was assessed by multiple logistic regression analysis, calculating odds ratios (OR) and 95% CI, after adjustment for covariates. Two hundred and ten patients were included, 41 (19.5%) had referable DR. Subjects with referable (severe or worse) DR had longer diabetes duration, 22 (15-28) vs 15 (8-20) years (P < 0.01); higher levels of UA, 6.5 (5.8-8.1) vs 5.4 (4.5-6.6) mg/dL (P < 0.01); higher systolic blood pressure, 130 (120-140) vs 120 (110-130) mmHg (P < 0.01); higher diastolic blood pressure, 78.4 ± 9.7 vs 75.4 ± 9.2 mmHg (P = 0.03); and lower glomerular filtration rate , 54.1 (41.5-69.6) vs 87.3 (66.8-108.3) mL/min/1.73m2 (P < 0.01) compared with those without referable DR. With multiple logistic regression, after adjustment, per each unit of change (mg/dL) in UA the probability of having referable DR increased 45% (OR = 1.45, 95% CI 1.12-1.87, P < 0.01). When UA was evaluated as dichotomous variable, those with levels ≥ 7.8 mg/dL had almost two times (OR = 2.81, 95% CI 1.00-7.9., P = 0.049) the probability of having referable DR compared with those with levels < 7.8 mg/dL. UA may contribute to the microvascular damage in retinal vessels and therefore hyperuricemia could be a therapeutic target to prevent DR progression.

Metabolism dysfunction-associated fatty liver disease (MAFLD), is the most common chronic liver disease. Few MAFLD predictions are simple and accurate. We examined the predictive performance of the albumin-to-glutamyl transpeptidase ratio (AGTR), plasma atherogenicity index (AIP), and serum uric acid to high-density lipoprotein cholesterol ratio (UHR) for MAFLD to design practical, inexpensive, and reliable models.

The National Health and Nutrition Examination Survey (NHANES) 2007-2016 cycle dataset, which contained 12,654 participants, was filtered and randomly separated into internal validation and training sets. This study examined the relationships of the AGTR and AIP with MAFLD using binary multifactor logistic regression. We then created a MAFLD predictive model using the training dataset and validated the predictive model performance with the 2017-2018 NHANES and internal datasets.

In the total population, the predictive ability (AUC) of the AIP, AGTR, UHR, and the combination of all three for MAFLD showed in the following order: 0.749, 0.773, 0.728 and 0.824. Further subgroup analysis showed that the AGTR (AUC1 = 0.796; AUC2 = 0.690) and the combination of the three measures (AUC1 = 0.863; AUC2 = 0.766) better predicted MAFLD in nondiabetic patients. Joint prediction outperformed the individual measures in predicting MAFLD in the subgroups. Additionally, the model better predicted female MAFLD. Adding waist circumference and or BMI to this model improves predictive performance.

Our study showed that the AGTR, AIP, and UHR had strong MAFLD predictive value, and their combination can increase MAFLD predictive performance. They also performed better in females.

The study findings investigated uric acid reference values and their association with a cluster of cardiometabolic risk factors among adolescents using the Korea National Health and Nutrition Examination Survey (KNHANES).

A retrospective cross-sectional study was conducted using the KNHANES database from 2016 to 2018, involving a total of 2,462 participants aged between 10 and 18 years. Based on age- and sex-specific percentile curves for serum uric acid (SUA) levels from the KNHANES, we examined the correlation between cardiometabolic risk factors and serum uric acid levels.

The percentile values of SUA varied with sex and age. In male subjects, SUA levels tended to increase from 10 to 14 years of age and plateaued after 14 years of age. Moreover, the overall uric acid level in females was found to be lower than that in males; the levels tended to increase at approximately 10 to 12 years old but were relatively consistent according to age. Mean uric acid levels increased according to obesity status in both males and females. However, correlation analysis revealed that SUA levels were associated with several metabolic risks even after adjusting for obesity. The detailed metabolic syndrome (MetS) components that were observed to be associated with an increase in uric acid levels were different between males and females, but overall, high uric acid levels increased MetS risk. Additionally, a significant increase in MetS-related odds ratio (OR) for components, including waist circumference (WC), triglyceride (TG) levels, and low high-density lipoprotein cholesterol (HDL-c), was observed. However, differences between sexes were apparent, with a more pronounced increase in OR based on SUA levels in girls.

SUA levels were closely associated with MetS and its components, even in nonobese subjects. Therefore, high SUA levels in children and young adolescents should be closely monitored to prevent MetS.

Phenotypic expression of hypertrophic cardiomyopathy (HCM) and disease course are associated with unfavorable metabolic health. We investigated if Western diet (WD) feeding is sufficient to trigger cardiac hypertrophy and dysfunction in heterozygous (HET) Mybpc3 c.772G>A knock-in mice.

Wild-type (WT) and HET mice (3-months-old) were fed a WD or normal chow (NC) for 8 weeks. Metabolomic analyses on serum revealed systemic metabolic derailment in WD-fed WT and HET mice. Strikingly, only WD-fed HET mice developed cardiac hypertrophy and dysfunction, which was not driven by aggravated cardiac myosin binding protein-C haploinsufficiency. WD reduced oxidative phosphorylation and increased toxic lipids in the heart irrespective of genotype. Cardiac proteomic analyses revealed higher abundance of proteins involved in fatty acid oxidation in WD-fed mice, however this increase was blunted in HET compared to WT mice. Accordingly, cardiac metabolomic and lipidomic analyses showed accumulation of acylcarnitines in WD-fed HET vs WT mice.

WD feeding triggered cardiac dysfunction and hypertrophy in otherwise phenotype-negative HET Mybpc3 c.772G>A mice. We propose that the presence of a HCM mutation predisposes the heart to metabolic inflexibility when subjected to systemic metabolic stress. Our study represents a novel approach to study the interplay between unfavorable metabolic health and mutation-induced defects in HCM disease development.

Sleep-disordered breathing (SDB) is often accompanied by noncommunicable diseases (NCDs), including gout. However, the association between serum uric acid (sUA) levels and NCDs is complicated in patients with SDB. We aimed to clarify this issue utilizing large-scale epidemiological data. This community-based study included 9850 inhabitants. SDB and its severity were assessed by a 3% oxygen desaturation index (3% ODI) corrected for sleep duration using wrist actigraphy. The associations between sUA and moderate to severe SDB (MS-SDB) and sUA and NCDs in patients with MS-SDB were analyzed. A total of 7895 subjects were eligible. In females, the prevalence of MS-SDB increased according to an elevation in sUA levels even after adjusting for confounders, and sUA ≥ 5 mg/dL was the threshold. These were not found in males. There was a positive interaction between sUA ≥ 5 mg/dL and female sex for MS-SDB. In females with MS-SDB, the prevalence of diabetes mellitus (DM) increased according to an elevation in sUA levels, and those with sUA ≥ 5 mg/dL showed a higher prevalence of DM than their counterparts. There is a clear correlation between sUA levels and the severity of SDB, and elevated sUA poses a risk for DM in females with MS-SDB.

Obesity and type 2 diabetes mellitus (T2DM) are risk factors for hyperuricemia. However, which anthropometric indices can better predict incident hyperuricemia in patients with T2DM remains inconsistent. This study aimed to examine the associations between hyperuricemia and different anthropometric indices in middle-aged and older male patients with T2DM.

In this retrospective study, a total of 1447 middle-aged (45-65 years, n = 791) and older (≥ 65 years, n = 656) male patients with T2DM were collected from December 2015 to January 2020 at Shanghai Xinhua Hospital. Hyperuricemia was defined as a serum uric acid level above 7.0 mg/dL. Weight, height, waist circumference (WC) and hip circumference (HC) were measured by trained nurses at visit.

The median uric acid level of subjects was 5.6 (interquartile ranges: 4.7-6.7) mg/dl, and 279 (19.3%) were hyperuricemia, with 146 (18.5%) in the middle-aged group, and 133 (20.3%) in the older group. After adjusting for age, duration of T2DM, fasting plasma glucose and insulin, homeostasis model assessment-β, aspartate aminotransferase, triglycerides, high-density lipoprotein cholesterol and estimated glomerular filtration rate, body mass index (BMI), WC, HC, and waist-to-height ratio (WHtR) were associated with a higher risk of hyperuricemia in both middle-aged and older group (P < 0.05). After further adjusting for BMI and WC, HC still showed a positive relationship with the risk of hyperuricemia (Odds Ratio = 1.51, 95% confidence intervals: 1.06-2.14) in the middle-aged group, but such relationship was not found in the older group. Moreover, according to receiver operating characteristic analysis, the optimal cutoff value was 101.3 cm of HC for hyperuricemia screening in the middle-aged male patients with T2DM.

In middle-aged male patients with T2DM, more attention should be paid to HC with the cutoff value of 101.3 cm in clinical practice for early recognition of individuals with a high risk of hyperuricemia for targeted guidance on disease prevention, such as community screening.

Hyperinsulinemia and hyperuricemia are known to increase the risk of mortality due to certain complications, such as Type 2 Diabetes and cardiovascular disease. However, despite their common comorbidities, their combined effect has not been evaluated. The study's aim was to evaluate the combine effect of hyperinsulinemia and hyperuricemia on all-cause mortality.

NHANES datasets (cycles 2003-2018) were examined. Differences between groups were evaluated using Rao-Scott Chi-square and General Linear Model for categorical and continuous data, respectively. Hazard Ratios (HR) were calculated using Cox regression with 95% confidence intervals (95%CI). There was significant difference (p < 0.05) in the mortality rate between the control group (2.3 ± 0.2%), the hyperinsulinemia only group (3.1 ± 0.3%), the hyperuricemia only group (4.0 ± 0.8%), and both conditions (5.1 ± 0.8%). Individually, when compared to the control group, there was a significant increase in mortality risk for hyperinsulinemia (HR: 1.50, 95%CI: 1.12-2.01, p = 0.007) and hyperuricemia (HR: 1.80, 95%CI:1.18-2.75, p = 0.006). However, when both conditions were present, there appeared an additive effect in the mortality risk (HR: 2.32, 95%CI: 1.66-3.25, p < 0.001). When stratified by BMI class, only normal weight participants presented with a significant risk (HR: 7.00, 95%CI: 2.50-20.30, p < 0.001). Also, when stratified by age, only participants older than 40 years presented a risk (HR: 2.22, 95%CI: 1.56-3.16, p < 0.001).

Alone, hyperuricemia and hyperinsulinemia significantly increased the mortality rate; however, the combined presence of both pathologies was associated with a significantly augmented mortality rate. Normal weight participant or that were >40 years old had a greater risk for mortality.

This study aimed to determine whether serum uric acid (SUA) levels are associated with various indices of liver damage in the adult Korean population.

We used the Seventh (VII) Korean National Health and Nutritional Examination Surveys. Our study population comprised 6,007 men and 8,488 women. Levels of SUA were divided into four groups (≤ 5.3, 5.3-6.0, 6.0-7.0, and > 7.0 mg/dL for men and ≤ 4.0, 4.0-4.8, 4.8-6.0, and > 6.0 mg/dL for women). Elevated liver enzyme levels were defined as > 35 (men) and > 31 (women) IU/L for aspartate aminotransferase (AST), > 45 (men) and > 34 (women) IU/L for alanine aminotransferase (ALT). Hepatic steatosis index and fibrosis (FIB)-4 index was used to determine nonalcoholic fatty liver disease (NAFLD) and liver FIB, respectively. Adjusted odds ratios (aORs) were calculated by logistic regression analysis for liver enzymes, NAFLD, and liver FIB, according to the SUA level.

Among women, the 4.8-6.0 and > 6.0 mg/dL SUA groups showed higher ORs of elevated AST (aOR, 1.78 and 2.03; 95% confidence interval [CI], 1.37-2.32 and 1.40-2.96, respectively; P < 0.001) and the 4.0-4.8, 4.8-6.0, and > 6.0 mg/dL SUA groups showed a higher ORs of ALT elevation (aOR, 1.35, 2.26, and 2.37; 95% CI, 1.02-1.79, 1.72-2.97, and 1.60-3.50, respectively; P < 0.001) compared to the lowest level SUA group. Among women with normal ALT, > 6.0 mg/dL SUA group showed higher OR of NAFLD status (aOR, 1.52; 95% CI, 1.06-2.19). Among men and women with NAFLD, hyperuricemia showed higher ORs of liver FIB (aOR, 2.25 and 1.89; 95% CI, 1.21-4.19 and 1.09-3.27, respectively) than the lowest level SUA group.

High SUA levels may be associated with elevated liver enzymes and NAFLD, mainly in women. Even in women with normal ALT levels, SUA levels may predict the NAFLD status. Hyperuricemia may predict advanced liver FIB in both men and women with NAFLD. Further studies investigating the causal effects of SUA on liver damage are required.

Although the association between uric acid levels and adverse pregnancy outcomes has been investigated, the effects of higher uric acid levels on the risk of gestational diabetes mellitus (GDM) have yet to be established. Therefore, this systematic review and meta-analysis aimed to investigate the relationship between uric acid levels during pregnancy and the risk of GDM.

PubMed/Medline, Scopus and Web of Science databases were searched up to April 2022 for relevant observational studies. A random effects model was used to estimate pooled odds ratios (OR) and 95% confidence intervals (95% CI). To assess the heterogeneity of included studies, the I2 index was used.

Among the initial 262 studies that were recognized from the databases search, 23 studies including 105,380 participants were eligible. Pooled analysis showed that higher uric acid levels significantly affected the risk of GDM (OR 2.58, 95% CI 1.89-3.52, I2  = 90.8%, P < 0.001). Subgroup analyses based on the gestational week showed that higher uric acid levels before the 20th week of gestation were significantly associated with the risk of GDM (OR 3.26, 95% CI 2.26-4.71, I2  = 89.3%, P < 0.001). Based on the meta-regression analysis, uric acid levels and odds of GDM were significantly correlated with the participants' age, and it was more significant in younger pregnant women.

This study showed a positive association between uric acid levels and the risk of GDM. Also, our results indicate that measuring uric acid levels before 20 weeks of gestation can potentially predict GDM, especially in younger women.

Diabetes is the most common metabolic disorder that leads to various complications, and among these complications, disruption in the lipid profile and serum uric acid (SUA) is one of the significant cases that can lead to the deterioration of the health status of patients with diabetes. So, we aimed to evaluate the level of SUA and lipid profiles in patients with diabetes. A total of 230 patients with diabetes who were admitted to Razi Hospital, Rasht, Iran, were enrolled in this study. Demographical data and clinical characteristics of the patients include gender, body mass index (BMI), duration of diabetes, history of smoking, FBS, HbA1c, SUA, Creatinine (Cr), Cholesterol (Chol), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), retinopathy, hypertension, ischemic heart disease (IHD), and microalbuminuria were recorded. All data were analyzed using the SPSS version 21 by a significant level < 0.05.

According to our results, 70 were male, and 160 were female, with a mean age of 57.36 ± 8.05 years and a mean BMI of 28.10 ± 4.62. The most frequent comorbidities were hypertension, 67%. The serum level of FBS, HBA1c, SUA, Cr, Chol, LDL, HDL, and TG were 191.47 ± 71.66 mg/dL, 7.94 ± 1.21 mg/dL, 5.65 ± 1.95 mg/dL, 0.94 ± 0.16 mg/dL, 167.28 ± 45.22 mg/dL, 95.91 ± 37.03 mg/dL, 39.78 ± 10.44 mg/dL, and 186.75 ± 76.65 mg/dL, respectively. Only UA had a significant relationship with TG level (P < 0.05).

To examine the association between elevated serum uric acid (SUA) levels and the rapid decline in kidney function by conducting a retrospective cohort study on a physically healthy population in Urumqi, China.

A cohort study of 2,802 physically healthy people with a normal estimated glomerular filtration rate (eGFR) was investigated from 2018 to 2021. The examination procedure included using questionnaires, taking physical measurements, and blood sampling. The rapid decline in kidney function was defined as eGFR > 5 mL·min^-1 ·(1.73 m² )^-1 year. The relationship between elevated SUA levels and the rapid decline in kidney function was assessed.

When performing the three-year retrospective analysis, 688 (28.55%) cases experienced a rapid decline in kidney function, and 52 (1.9%) cases developed chronic kidney disease (CKD). They were divided into the stable group and the rapidly declining kidney function group according to eGFR > 15 mL·min^-1·(1.73 m² )^-1. The comparison revealed a greater increase in uric acid in the rapidly declining kidney function group [0.30 (-0.29, 0.82) mg/dL vs. - 0.07(-0.54, 0.37) mg/dL, Z = - 8.822, P < 0.001]. The participants were further divided into four groups according to their uric acid levels in 2018 and 2021, which included the normal to normal (N-N) group, the normal to hyperuricemia (HUA) (N-H) group, the HUA to normal (H-N) group, and the persistently HUA (H-H) group. The decrease in eGFR was significantly higher in the N-H group than in the other three groups (χ² = 20.580, P < 0.001). The results of the multifactorial logistic regression analysis showed that elevated uric acid was a risk factor for the rapid decline in kidney function (OR = 1.640, P < 0.001).

Elevated SUA levels were a risk factor for the rapid decline in kidney function in the Chinese health examination population. Higher SUA levels might predict the occurrence of progressive kidney impairment.

The prevalence rate of hyperuricemia remains high in Taiwan, at 21.6% in men and 9.57% in women. Both metabolic syndrome (MetS) and hyperuricemia can cause many complications; however, few studies have evaluated the correlation between MetS and hyperuricemia. Therefore, in this observational cohort study, we explored associations between metabolic syndrome (MetS) and its components and new-onset hyperuricemia. Of 27,033 individuals in the Taiwan Biobank who had complete follow-up data, we excluded those with hyperuricemia at baseline (n = 4871), those with gout at baseline (n = 1043), those with no data on baseline uric acid (n = 18), and those with no data on follow-up uric acid (n = 71). The remaining 21,030 participants (mean age 50.8 ± 10.3 years) were enrolled. We found a significant association between new-onset hyperuricemia with MetS and the components of MetS (hypertriglyceridemia, abdominal obesity, low high-density lipoprotein cholesterol, hyperglycemia, and high blood pressure). Furthermore, compared to those without any MetS components, those with one MetS component (OR = 1.816), two MetS components (OR = 2.727), three MetS components (OR = 3.208), four MetS components (OR = 4.256), and five MetS components (OR = 5.282) were significantly associated with new-onset hyperuricemia (all p < 0.001). MetS and its five components were associated with new-onset hyperuricemia in the enrolled participants. Further, an increase in the number of MetS components was associated with an increase in the incidence rate of new-onset hyperuricemia.

Elevated serum uric acid (SUA) is associated with the incidence of hypertension, but whether relevant metabolic factors have mediating effects is not certain. Our study was based on a functional community cohort established in Beijing. In 2015, a total of 7482 individuals without hypertension were recruited and followed up until 2019. Multivariate logistic regression analysis was used to investigate the association between SUA and hypertension. Cross-lagged panel analysis and mediation analysis were used to explore the effects of metabolic factors on the association between SUA and incident hypertension. During the average 4-year follow-up, the cumulative incidence of hypertension was 10.9% (n = 580). SUA was an independent risk factor for hypertension, and the RRs (95% CI) for subjects with baseline SUA levels in quartile 2, quartile 3 and quartile 4 were 1.20 (0.88-1.63), 1.50 (1.10-2.05), and 1.57 (1.11-2.22) compared to those in quartile 1, respectively. The cross-lagged panel analysis showed that the increases in Cr, TG, LDL, ALT, AST and WBC occurred after SUA increased (P < 0.001). Among these factors, TG, WBC and ALT played an intermediary role in both men (TG: 14.76%; WBC: 11.61%; ALT: 15.93%) and women (TG: 14.55%; WBC: 8.55%; ALT: 6.89%). The elevated SUA concentration was an independent risk factor for hypertension in the Chinese population, and TG, WBC and ALT had important mediating effects on the association between SUA and hypertension.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has increasingly become a significant and highly prevalent cause of chronic liver disease, displaying a wide array of risk factors and pathophysiologic mechanisms of which only a few have so far been clearly elucidated. A bidirectional interaction between hormonal discrepancies and metabolic-related disorders, including obesity, type 2 diabetes mellitus (T2DM), and polycystic ovarian syndrome (PCOS) has been described. Since the change in nomenclature from non-alcoholic fatty liver disease (NAFLD) to MAFLD is based on the clear impact of metabolic elements on the disease, the reciprocal interactions of hormones such as insulin, adipokines (leptin and adiponectin), and estrogens have strongly pointed to the intrinsic links that lead to the heterogeneous epidemiology, clinical presentations, and risk factors involved in MAFLD in different populations. The objective of this work is twofold. Firstly, there is a brief discussion regarding the change in nomenclature as well as epidemiology, risk factors, and pathophysiologic mechanisms other than hormonal effects, which include nutrition and the gut microbiome, as well as genetic and epigenetic influences. Secondly, we review the basis of the most important hormonal factors involved in the development and progression of MAFLD that act both independently and in an interrelated manner.

Hyperuricemia is the result of increased production and/or underexcretion of uric acid. Hyperuricemia has been epidemiologically associated with multiple comorbidities, including metabolic syndrome, gout with long-term systemic inflammation, chronic kidney disease, urolithiasis, cardiovascular disease, hypertension, rheumatoid arthritis, dyslipidemia, diabetes/insulin resistance and increased oxidative stress. Dysregulation of xanthine oxidoreductase (XOD), the enzyme that catalyzes uric acid biosynthesis primarily in the liver, and urate transporters that reabsorb urate in the renal proximal tubules (URAT1, GLUT9, OAT4 and OAT10) and secrete urate (ABCG2, OAT1, OAT3, NPT1, and NPT4) in the renal tubules and intestine, is a major cause of hyperuricemia, along with variations in the genes encoding these proteins. The first-line therapeutic drugs used to lower serum uric acid levels include XOD inhibitors that limit uric acid biosynthesis and uricosurics that decrease urate reabsorption in the renal proximal tubules and increase urate excretion into the urine and intestine via urate transporters. However, long-term use of high doses of these drugs induces acute kidney disease, chronic kidney disease and liver toxicity. Therefore, there is an urgent need for new nephroprotective drugs with improved safety profiles and tolerance. The current systematic review summarizes the characteristics of major urate transporters, the mechanisms underlying the pathogenesis of hyperuricemia, and the regulation of uric acid biosynthesis and transport. Most importantly, this review highlights the potential mechanisms of action of some naturally occurring bioactive compounds with antihyperuricemic and nephroprotective potential isolated from various medicinal plants.

Aim: The aim of this study was to measure serum levels of methylarginine derivatives and related metabolites in patients with gout. Materials & methods: This study enrolled 100 patients with gout and 80 patients in the control group. Serum asymmetric dimethylarginine, symmetric dimethylarginine, L-N-monomethylarginine, arginine, homoarginine, citrulline and ornithine levels were measured with tandem mass spectrometry. Results: Serum ornithine, citrulline and total methylated arginine load levels were statistically significantly higher in patients with gout compared with the control group, while serum arginine and homoarginine levels and global arginine bioavailability ratio were statistically significantly lower. Conclusion: There may be an association between gout, methylarginine levels and hyperuricemia and increased risk of cardiovascular disease.

The atherogenic index of plasma (AIP) is a predictor for cardiovascular diseases (CVD), while hyperuricemia is an independent risk factor for a variety of CVD. Apolipoprotein AI has been found to be a protective factor for CVD. However, the role of APO AI in the association between plasma uric acid and AIP among healthy Chinese people needs to be further explored.

To evaluate the relationship between blood uric acid and AIP level in healthy Chinese people. To evaluate the relationship between blood uric acid and Apolipoprotein AI in healthy Chinese people.

A total of 3501 normal and healthy subjects who had physical examinations were divided into the hyperuricemia (HUA) group and the normouricemia (NUA) group.

The AIP of HUA group was significantly higher than that of NUA group [0.17±0.30 vs. -0.08±0.29]. Apo AI (1.33 ± 0.21 vs. 1.47 ± 0.26 g/l) and HDL-c (1.12 ± 0.27 vs. 1.36 ± 0.33 mmol/l) were significantly lower in the HUA group than in the NUA group. LDL-C (2.81 ± 0.77 vs. 2.69 ± 0.73 mmol/l), Apo B (0.96 ± 0.20 vs. 0.89 ± 0.20 g/l), FBG (5.48 ± 0.48 vs. 5.36 ± 0.48 mmol/l) and HOMA-IR [2.75 (1.92-3.91) vs. 2.18 (1.50-3.12)] was significantly higher in HAU group than the NUA group. Increases in plasma UA were associated with increases in AIP (β = 0.307, p < 0.01) and decreases in Apo AI (β =  - 0.236, p < 0.01).

Hyperuricemia is an independent risk factor for high AIP level. Inhibition of Apolipoprotein AI may be one of the mechanisms of UA which is involved in the progression of cardiovascular disease.

Many studies have demonstrated that elevated serum uric acid independently increases the risk of developing hypertension. However, the role of insulin resistance in the relationship between serum uric acid and hypertension is still unelucidated. Based on a prospective cohort study, we aimed to examine the longitudinal link between serum uric acid and hypertension and whether this relationship was mediated by insulin resistance. Overall, 21,999 participants without hypertension or gout at baseline with a mean age of 46 ± 13 years in the Jinchang Cohort were included in our study. Adjusted Cox-regression analyses and mediation analyses were performed to assess the risk of hypertension by serum uric acid quartile distribution and whether insulin resistance mediated the association between serum uric acid and hypertension. During the first follow-up period, 3080 participants developed hypertension. After controlling for covariates, compared with the lowest quartile of serum uric acid, the risk of hypertension in the highest quartile was 1.21 (1.06, 1.38) in the overall population. The risks for males and females were 1.14 (1.00-1.29) and 1.30 (1.08-1.56), respectively. The correlation between serum uric acid and hypertension was especially observed in younger people (<30 years). The mediating effects of insulin resistance were 0.058 (0.051, 0.065), 0.030 (0.025, 0.036) and 0.056 (0.047, 0.065), and the proportions mediated were 39.73, 36.59 and 38.62% in the overall, male and female populations, respectively. Elevated serum uric acid levels are associated with an increased risk of incident hypertension, and insulin resistance may play a mediating role in the relationship between serum uric acid and hypertension.

Arterial stiffness (AS), measured by arterial stiffness index (ASI), is a determinant in cardiovascular (CV) diseases. A high serum uric acid (SUA) level is a known risk factor for CV disease. The authors investigated the relationship between SUA and ASI in the middle-age UK Biobank population study. AS was defined as ASI > 10 m/s. A cross-sectional study was conducted from 126 663 participants. Participants were divided into four quartiles according to SUA levels and sex. Sex multivariate analyses were performed with adjustment for confounding factors. The average ASI for overall participants was 9.3 m/s (SD: 2.9); 9.9 m/s (SD: 2.8) for men and 8.7 m/s (SD: 2.9) for women (P < .001). Men presented higher SUA rate (351.3 mmol/L (SD:67.9)) than women (270.7 mmol/L (SD:64.4)), P < .001. In men multivariate analysis, SUA remained a determinant of AS, with an increase in the strength of the association between the quartiles, Q4 versus Q1, OR = 1.10 [1.05-1.16], P < .001, Q3 versus Q1, OR = 1.09 [1.04-1.14], P < .001 but not between Q2 and Q1 (P = .136). In women, SUA remained significant for AS, with an increase in the strength of the association between the quartiles, Q4 versus Q1, OR = 1.22 [1.15-1.30], P < .001, Q3 versus Q1, OR = 1.13 [1.07-1.19], P < .001 and no difference between Q2 and Q1 (P = .101). When applying continuous SUA values in the multivariate analysis, SUA remained significant (P < .001), with a Youden index value for men = 338.3 mmol/L and for women = 267.3 mmol/L. High SUA levels were associated with AS, suggesting that SUA could be used as a predictor of atherosclerosis.

Insulin resistance, hypertension, hyperuricemia, and hypercholesterolemia are hypothesized to be important intermediates in the relationship between excess body weight and CKD risk. However, the magnitude of the total effect of excess body weight on ESKD mediated through these four pathways remains to be quantified.

We applied a model for analysis of correlated mediators to population-based data from 100,269 Austrian individuals (mean age 46.4 years). Association of body mass index (BMI) was coalesced with ESKD risk into direct association. Indirect associations were mediated through the triglyceride-glucose (TyG) index (as an indicator of insulin resistance), mean arterial pressure (MAP), uric acid (UA), and total cholesterol (TC).

Mean follow-up was 23.1 years with 463 (0.5%) incident ESKD cases. An unhealthy metabolic profile (prevalence 32.4%) was associated with a markedly increased ESKD risk (multivariably adjusted hazard ratio (aHR), 3.57; 95% CI, 2.89 to 4.40), independent of BMI. A 5-kg/m2 higher BMI was associated with a 57% increased ESKD risk (aHRtotal association, 1.57; 1.38 to 1.77). Of this association, 99% (76% to 140%) arose from all mediators jointly; 33% (22% to 49%) through TyG index; 34% (24% to 50%) through MAP; 30% (21% to 45%) through UA; and 2% (-1% to 4%) through TC. The remaining direct association was nonsignificant (aHRdirect association, 1.01; 0.88 to 1.14).

TyG index, MAP, and UA, but not TC, mediate the association of BMI with ESKD in middle-aged adults. Our findings highlight that in addition to weight reduction, the control of metabolic risk factors might be essential in mitigating the adverse effects of BMI on kidney function.

Increased serum uric acid (SUA) level is considered a risk factor for kidney diseases in type 2 diabetes mellitus (T2DM) patients. Deranged lipid profile in T2DM is an overall risk factor for cardiovascular complications.

This study aimed to find the correlation between SUA and serum lipid profile in T2DM patients who had serum creatinine levels within normal limits.

This cross-sectional observational study was conducted in a tertiary care hospital in eastern India. Serum creatinine level was measured first. Then, patients with serum creatinine levels within normal limits were recruited as the final sample. Anthropometric measurements were conducted by an experienced clinician. A 12-h fasting venous blood sample was used to measure serum urea, lipids, sugar, and glycated hemoglobin.

A total of 176 (male = 104 [59.1%], female = 72 [40.9%]) T2DM patients with a median age of 46 (Q1-Q3 = 40-55) years participated in the study. There was no gender difference in fasting blood sugar (FBS) (P = 0.57), SUA (P = 0.42), and high-density lipoprotein-cholesterol (HDL-C) (P = 0.17). Females showed higher total cholesterol (TC) (P < 0.0001), triglyceride (TG) (P = 0.002), low-density lipoprotein-cholesterol (LDL-C) (P = 0.0002), and very-low-density lipoprotein-cholesterol (VLDL-C) (P = 0.01). SUA showed significant positive correlation with TG (rs = 0.65, P < 0.0001) and VLDL-C (rs = 0.63, P < 0.0001) and significant negative correlation with HDL-C (rs = -0.35, P < 0.0001) and FBS (rs = -0.45, P < 0.0001).

A higher level of SUA, an indicator for kidney disease in T2DM patients, may be associated with a higher TG and VLDL-C and lower FBS and HDL-C. Thus, SUA should be monitored along with lipid profile for early detection of the risk of kidney diseases.

Previous studies have presented inconsistent results on the relationship between serum uric acid and skeletal muscle mass (SMM). We aimed to explore whether a higher serum uric acid level was associated with low SMM in the Chinese population.

We performed a cross-sectional analysis of 6595 subjects aged 45 years or older. They were tested for fasting blood glucose, total cholesterol, triglycerides, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, uric acid, blood urea nitrogen, creatinine, and estimated glomerular filtration rate. SMM was accessed by dual-energy x-ray absorptiometry using two approaches: weight-adjusted appendicular skeletal muscle mass (ASM)% and ASM/BMI (body mass index (kg/m²)). Low SMM was defined as a cut-off point of ASM/BMI<0.789 for men and<0.512 for women.

Compared with their normal group, patients with hyperuricemia had lower ASM% (29.33±2.33 vs 30.03±2.34 for males and 24.71±1.99 vs 25.19±2.07 for females, P<0.01) and ASM/BMI (0.83±0.10 vs 0.85±0.10 for male and 0.60±0.07 vs 0.62±0.07 for female), with a higher prevalence of the associated low SMM in both sexes (35.2 vs 26.5% for male and 10.5 vs 5.9% for female, P<0.01). Pearson analysis showed that ASM% and ASM/BMI were negatively correlated with SUA (male: ASM/BMI, r=-0.097, ASM%, r=-0.146; female: ASM/BMI, r=-0.151, ASM%, r=-0.157; all P<0.001). Logistic regression analysis showed a positive association of hyperuricemia with adjusted risk of low SMM association.

In a middle-aged and elderly Chinese population, hyperuricemia is independently and positively associated with low SMM and can vary by age and gender.

Studies examining the association between levels of serum uric acid (SUA) and risk of prehypertension still remained controversial conclusions. Also, a quantitative assessment of the dose-response association between them has not been reported. We aimed to quantitatively evaluate risk of prehypertension with levels of SUA based on observational study.

We searched the PubMed, Embase, and Web of Science databases up to December 3, 2019 for relevant studies. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were calculated using random-effects models. The possible linear or non-linear SUA-prehypertension association was modelled by restricted cubic splines.

We included 17 articles (17 studies) with a total of 79,358 participants and 34,591 cases of prehypertension. Compared with lowest levels of SUA, risk of prehypertension increased 46% (RR 1.46, 95% CI 1.28-1.66) for highest levels of SUA. For per 1 mg/dL increment in levels of SUA, risk of prehypertension increased by 12% (RR 1.12, 95% CI 1.08-1.17). Also, we found evidence of a linear SUA-prehypertension association (P_{non-linearity}=.368).

Elevated levels of SUA may be associated with increased risk of prehypertension. Present findings provide the evidence that lowering levels of SUA should be suggested in order to reduce the risk of prehypertension. More longitudinal and intervention studies are needed to clarify the optimal protective levels and whether reducing levels of SUA could prevent or control prehypertension and the progression of prehypertension to hypertension.

Sodium-glucose cotransporter-2 (SGLT2) inhibitors have been found to reduce serum urate in patients with type 2 diabetes mellitus. To evaluate if this effect applies to both patients with and without diabetes, we conducted a systematic review and meta-analysis of SGLT2 inhibitors on serum urate levels in this population.

Four electronic databases (PubMed, Embase, Cochrane and SCOPUS) were searched on 25 September 2021 for articles published from 1 January 2000 up to 25 September 2021, for studies that examined the effect of SGLT2 inhibitors on serum urate in study subjects. Random-effects meta-analysis was performed, with subgroup analyses on the type of SGLT2 inhibitor agent administered, presence of type 2 diabetes mellitus, presence of chronic kidney disease and drug dose.

A total of 43 randomized controlled trials, with a combined cohort of 31,921 patients, were included. Both patients with [-31.48 μmol/L; 95% confidence interval (CI): -37.35 to -25.60] and without diabetes (-91.38 μmol/L; 95% CI: -126.53 to -56.24) on SGLT2 inhibitors had significantly lower urate levels when compared with placebo. This treatment effect was similarly observed across different types of SGLT2 inhibitors. However, in type 2 diabetes mellitus (T2DM) patients with chronic kidney disease, the reduction in serum urate with SGLT2 inhibitors became insignificant (95% CI: -22.17 to 5.94, p < 0.01).

This study demonstrated that SGLT2 inhibitors are beneficial in reducing serum urate in patients with and without diabetes. SGLT2 inhibitors could therefore contribute to the general treatment of hyperuricaemia.

The triglyceride-glucose index (TyG) is positively correlated with serum uric acid (SUA) in patients with type 2 diabetes mellitus (T2DM). However, whether this relationship exists in non-obese T2DM patients remains unknown. The study investigated the relationship between TyG and SUA in Chinese non-obese T2DM patients and examined the prognostic value of TyG in hyperuricemia (HUA).

In total, 719 T2DM patients who were not obese were enrolled from among those who visited the Hebei General Hospital. The patients were categorized into groups according to their SUA levels. The relationship between TyG and clinical parameters was examined through correlation analysis. To consider covariates and examine the independent impact of TyG on HUA, logistic regression was performed. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of TyG and homeostasis model assessment of insulin resistance (HOMA-IR) for HUA.

The HUA prevalence was 12.10%. TyG was statistically different among the four SUA groups, with lower TyG levels in the Q1, Q2, and Q3 groups than that in the Q4 group. TyG was positively correlated with SUA (r = 0.176, P < 0.001). Logistic regression exhibited that TyG and SUA were independently correlated (OR = 2.427, 95% CI = 1.134-5.195, P = 0.022) even after adjustment for confounding factors. The ROC curve showed that the predictive value of TyG for HUA was higher than that of HOMA-IR (AUROC = 0.613, P = 0.001).

TyG was positively correlated with SUA in non-obese T2DM patients. TyG may better predict HUA in non-obese T2DM patients than HOMA-IR.

Background: Cardiovascular disease (CVD) is associated with morbidity and mortality in patients with type 2 diabetes mellitus (T2D). However, the role of serum uric acid as a risk factor for developing cardiovascular disease is controversial. This study investigated whether uric acid variability was associated with new-onset symptomatic CVD in patients with T2D, requiring percutaneous coronary intervention. Methods: A total of 1,071 patients were enrolled in this retrospective cross-sectional study after propensity score matching. Patients with T2D and new-onset symptomatic CVD who received percutaneous coronary intervention for the first time, and with at least three consecutive 6-monthly measurements of serum uric acid were recruited from Severance Hospital between January 2015 and December 2019. Uric acid variability was measured by average successive variability (ASV) and analyzed to evaluate a possible correlation with the risk of developing CVD. Results: The patients were divided into quartiles based on the uric acid variability. Patients in the highest quartile were older and presented lower renal function and a higher mortality from CVD. There was a linear association between a high uric acid variability and the development of CVD. Compared to the lowest quartile, patients in the higher quartiles had a higher risk of CVD [quartile 3: adjusted odds ratio (aOR) = 1.76; 95% confidence interval (CI), 1.20-2.82; P = 0.019; quartile 4 aOR = 2.89; 95% CI, 1.74-4.80; P < 0.001]. Conclusion: High uric acid variability is independently associated with an increased risk of new-onset symptomatic CVD requiring percutaneous coronary intervention in patients with T2D. Thus, maintaining serum uric acid in a narrow range by prescribing effective medications is essential to prevent new-onset CVD in patients with T2D. Nonetheless, the potential use of uric acid variability as a predictive marker of CVD in patients with T2D needs further validation.

The data on the association between serum uric acid (sUA) concentration and outcomes in patients with an ACS are inconsistent and do not focus on patients with non-ST-segment elevation acute coronary syndromes (NSTE-ACS). The aim of this study was to analyze an association of sUA concentration on admission and outcomes in those patients.

Data from the prospective, single-center registry of patients hospitalized due to NSTE-ACS from January 2006 to December 2016 were analyzed retrospectively. The population was divided into quartiles according to the baseline sUA. The primary outcome was the incidence of all-cause death, non-fatal myocardial infarction, stroke and ACS-driven revascularization at 36 months.

Total of 2,824 patients with sUA measured on admission were included in this analysis with a median sUA of 352 µmol/L (5.92 mg/dL). Patients with higher sUA were older and more burdened with cardiovascular risk factors and history of coronary events. The prevalence of multivessel coronary artery disease and left main stenosis was significantly higher in patients with higher sUA. Elevated sUA concentration was associated with significantly worse short-, mid- and long-term outcomes. All-cause mortality was significantly higher in each analyzed period. In the multivariable analysis, sUA elevation was identified as an independent predictor of all-cause mortality at 12-month and 36-month follow-up.

Elevated baseline sUA concentration was independently associated with worse mid- and long-term outcomes in patients with NSTE-ACS. Baseline sUA concentration could identify patients with NSTE-ACS at higher risk of more dismal prognosis.

Excessive sugar consumption is increasingly considered as a contributor to the emerging epidemics of obesity and the associated cardiometabolic disease. Sugar is added to the diet in the form of sucrose or high-fructose corn syrup, both of which comprise nearly equal amounts of glucose and fructose. The unique aspects of fructose metabolism and properties of fructose-derived metabolites allow for fructose to serve as a physiological signal of normal dietary sugar consumption. However, when fructose is consumed in excess, these unique properties may contribute to the pathogenesis of cardiometabolic disease. Here, we review the biochemistry, genetics, and physiology of fructose metabolism and consider mechanisms by which excessive fructose consumption may contribute to metabolic disease. Lastly, we consider new therapeutic options for the treatment of metabolic disease based upon this knowledge.

. - Higher serum uric acid (UA) has been associated with increased risk of type 2 diabetes mellitus. This cohort study examined whether there are any associations between serum UA in early pregnancy and the subsequent risk of gestational diabetes mellitus (GDM).

. - This cohort study was conducted in Shanghai, China, and included 85,609 pregnant women. Generalised additive models were used to estimate the associations of serum UA with risk of GDM.

. - The prevalence of GDM was 14.0% (11,960/85,609). Non-linear associations between serum UA and GDM risk were observed and these associations varied by gestational ages. Only elevated serum UA levels at 13-18 weeks gestation was associated with substantially increased risk of GDM. Analysis by UA quintiles at 13-18 weeks gestation showed the odds ratios for GDM were 1.11 (95%CI, 1.03-1.20) for the second, 1.27 (95%CI, 1.17-1.37) for the third, 1.37 (95%CI, 1.27-1.48) for the fourth and 1.70 (95%CI, 1.58-1.84) for the fifth quintile of serum UA in comparison with the first quintile. Stratified analysis showed the associations of serum UA with GDM were stronger among pregnant women aged 35 years or older.

. - We found higher serum UA at 13-18 gestational weeks was a risk factor for GDM. Our findings provide new evidence for the role of serum UA in the prevention and early intervention of GDM, and highlighted the need for monitoring serum UA at 13-18 gestational weeks.

The role of serum uric acid (SUA) as an independent risk factor for coronary artery disease remains unclear. The aim of this study was to investigate whether the SUA levels could affect the incidence of major adverse cardiac events (MACE) after percutaneous coronary intervention (PCI).

We retrospectively examined the clinical records of 1,949 patients who underwent successful PCI. First, they were divided into two groups based on an SUA level of 7.0mg/dl. Among the two groups, the incidence of MACE was measured for a maximum of 5 years after PCI. Next, we divided them into 6 groups at SUA intervals of 1.0mg/dl and estimated the hazard ratios of each group. The Kaplan-Meier curve demonstrated that patients with SUA levels of >7.0mg/dl had a higher incidence of MACE than those with 7.0mg/dl or less. However, according to the multivariate analysis, the SUA level was not significantly correlated with the incidence of MACE because other factors could strongly affect it. Meanwhile, the group with SUA levels between 4.1-5.0mg/dl had a lower hazard ratio compared to groups with SUA levels of more than 5.1mg/dl. However, the hazard ratio of the group with SUA levels of 4.0mg or less was not lower than that of the group with SUA levels of 4.1-5.0mg/dl. Even after adjustment for several parameters, nearly the same results before adjustment were obtained for the hazard ratios of each group.

The present study demonstrated that the SUA level was one of the most valuable predictors of cardiovascular events after PCI, with elevated SUA levels adversely affecting secondary prevention.

Weight reduction may reduce serum uric acid (SUA). This study aimed to examine the changes of SUA before and after bariatric surgery in patients with obesity with or without hyperuricaemia and gout.

This is a retrospective analysis of 147 routinely collected data on hospital patients with obesity who underwent bariatric surgery. The body weight and SUA were measured at baseline and after surgery at 1-7 days, 1, 3, 6 and 12 months.

The mean (95% CI) weight reduction of 147 patients was 30.7 (28.7, 32.7) kg 1 year after surgery (P < 0.001). SUA decreased rapidly from 419.0 (400.1, 437.8) µmol/l at baseline to 308.4 (289.6, 327.2) µmol/l at 1-7 days, flared up to 444.8 (423.9, 465.6) µmol/l at 1 month, then decreased again to 383.8 (361.5, 406.1) µmol/l at 3 months, 348.9 (326.3, 371.5) µmol/l at 6 months and 327.9 (305.3, 350.5) µmol/l at 12 months (P < 0.001). Similar trends but more rapid reductions were observed in 55 hyperuricaemia patients and 25 gout patients. All 25 gout patients had an elevated SUA above the therapeutic target (≥360µmmol/l) at baseline, but in 10 patients it was reduced below this target at 12 months. The mean reduction (95% CI) of SUA in all patients and gout patients was 84.3 (63.1-105.4) and 163.6 (103.9, 223.3) µmmol/l, respectively.

Bariatric surgery significantly reduces body weight and SUA for obese patients with hyperuricaemia and gout. Gout may be considered as an indicator for this surgical treatment in people with severe obesity.

Insulin resistance (IR) predisposes to type 2 diabetes mellitus (T2DM). Although previous studies have associated serum uric acid concentration with IR in T2DM, its association with impaired insulin secretion and beta-cell dysfunction in subjects at risk for developing T2DM remains uncertain. Thus, we aimed to analyze the association of serum uric acid concentration with IR using surrogate insulin resistance/secretion and beta-cell function indices in subjects at risk for developing T2DM.

This is a cross-sectional study that included 354 subjects who underwent an oral glucose tolerance test who had at least two risk factors for T2DM without any chronic disease.

Participants were 51±8 years old, 72.2% were women, had a mean body mass index of 29.9±6.5kg/m2 and mean serum uric acid concentration of 5.7±1.3mg/dL. HOMA-IR, first-phase insulin secretion (S1PhOGTT), second-phase insulin secretion (S2PhOGTT), Matsuda and disposition indices were significantly correlated with serum uric acid concentrations (r=0.239, r=0.225, r=0.201, r=-0.287, r=-0.208; respectively). After multiple linear regression analysis, serum uric acid concentration was independently associated with HOMA-IR (β=0.283), HOMA-B (β=0.185), S1PhOGTT (β=0.203), S2PhOGTT (β=0.186), and Matsuda Index (β=-0.322). A serum uric acid concentration of 5.5mg/dL had the best sensitivity/sensibility to identify subjects with IR (HOMA-IR ≥2.5).

Serum uric acid concentration is significantly associated with IR and impaired insulin secretion, but not with beta-cell dysfunction, in subjects at risk for developing T2DM.

Available evidence substantiates a strong association between metabolic syndrome and elevated oxidative stress. This study was aimed to assess the effects of probiotic yogurt containing Lactobacillus acidophilus La5 and Bifidobacterium lactis Bb12 on the oxidative stress biomarkers in patients with metabolic syndrome. Furthermore, the association between uric acid levels and insulin resistance indexes was assessed.

An 8-week randomized, double-blind, placebo-controlled, parallel study was designed. Forty-four patients, 22 males and 22 females aged 20-65 years, were assigned into two groups. Treatment (n = 22) and control (n = 22) groups consumed 300 g/d of probiotic and regular yogurt, respectively. The serum concentration of uric acid, oxidized Low-Density Lipoprotein (oxLDL), Malondialdehyde (MDA) and Total Antioxidant Capacity (TAC) were measured at the beginning and the end of the trial. This study was recorded at http://www.irct.ir (code: IRCT201608213140N17).

Probiotic yogurt consumption resulted in a significant decrease in the level of serum uric acid and a significant increase in the level of TAC (p < 0.05). A positive significant association between uric acid with insulin concentration and the homeostasis model assessment of insulin resistance (HOMA-IR) and an inverse significant relationship with insulin sensitivity (Quicki) were also found (p < 0.05).

Probiotic yogurt consumption through improvement in insulin sensitivity may exert positive effects on the oxidative stress and uric acid levels. However, further studies are needed to make concise conclusions.

The association between hyperuricemia and urolithiasis has been previously reported. However, this association is based on observational data, which are prone to residual confounding. The aim of this work was to use Mendelian randomization (MR) to evaluate if this relationship represents a causal effect of hyperuricemia.

MR analysis using 2 approaches: 2-stage MR and 2-sample MR.

Participants aged 40-69 years from the UK Biobank Resource.

Serum urate.

Urolithiasis.

An observational analysis testing for an association between serum urate level and urolithiasis was performed using logistic regression. For MR analyses, serum urate-associated single-nucleotide polymorphisms, identified from genome-wide association data, were used as instrumental variables for serum urate. In the 2-stage MR analysis, a weighted genetic urate score was calculated from the instrumental variables, and a control function estimation model was fit. In the 2-sample MR analysis, multiple-instrument MR via the inverse-variance weighted method was performed.

Individual-level data were available for 359,827 participants, of whom 6,398 (1.8%) reported urolithiasis. In the observational analysis, serum urate was positively associated with urolithiasis in an unadjusted analysis (odds ratio [OR], 1.47 [95% CI, 1.42-1.51]); however, after adjustment for relevant confounders, no association was observed (OR, 1.03 [95% CI, 0.99-1.08]). In the 2-stage MR analysis, no significant causal effect of serum urate level on urolithiasis was observed in the unadjusted (OR, 0.93 [95% CI, 0.81-1.08]) or adjusted (OR, 0.94 [95% CI, 0.80-1.09]) models. In the 2-sample MR analysis, multiple-instrument MR did not indicate a causal effect of serum urate on urolithiasis.

Stone composition and urinalysis data, including urine pH, were not available for this study.

Our analyses do not support a causal effect of serum urate level on urolithiasis. The association between serum urate level and urolithiasis reported in observational studies is likely due to residual confounding.