Serum uric acid potentially links metabolic health to measures of fuel use in lean and obese individuals

Higher serum uric acid is associated with body fat, retinol-binding protein 4, and antioxidative status in Brazilian children

OBJECTIVE

The aim of this study was to evaluate the association of serum uric acid (SUA) with adiposity, adipokines, and anti- and oxidative markers in Brazilian children.

METHODS

This was a cross-sectional investigation with 378 children ages 8 to 9 y in Viçosa, Minas Gerais, Brazil. Information on sociodemographic and lifestyle characteristics was obtained via questionnaires, and body fat was determined by dual energy x-ray absorptiometry. We compared the distributions of adiposity (total and central), adipokines (adiponectin, chemerin, leptin, and retinol-binding protein 4 [RBP4]), anti- and oxidative markers (plasma ferric reducing antioxidant power [FRAP], superoxide dismutase [SOD], and malondialdehyde [MDA]) by SUA categories using linear regression.

RESULTS

SUA was positively associated with total and central fat. Every standard deviation (SD) of SUA was related, respectively, to a 3.4 (95% confidence interval [CI], 2.4-4.4), 4 (95% CI, 2.8-5.1), 4.2 (95% CI, 2.9-5.5), and 3.5 (95% CI, 2.4-4.6) units higher of total, truncal, android, and gynoid fat. We found a positive association of SUA with RBP4 and FRAP, and a negative association with MDA. Every SD of SUA was related, respectively, to 0.1 (95% CI, 0.01-0.1) and 7.8 (95% CI, 5.5-10.1) units higher of RBP4 and FRAP; and to -0.3 (95% CI, -0.5 to -0.1) units lower of MDA.

CONCLUSIONS

SUA was positively associated with adiposity, RBP4, and antioxidative status in Brazilian children.

Association of Chinese Visceral Adiposity Index and Its Dynamic Change With Risk of Carotid Plaque in a Large Cohort in China

Background

We aimed to evaluate the association between the Chinese visceral adiposity index (CVAI) and its dynamic change and risk of carotid plaque based on a large Chinese cohort.

Methods and Results

This cohort included 23 522 participants aged 20 to 80 years without elevated carotid intima‐media thickness and carotid plaque at baseline and who received at least 2 health checkups. CVAI was calculated at baseline and at every checkup. The dynamic change in CVAI was calculated by subtracting CVAI at baseline from that at the last follow‐up. Cox proportional hazard regression model was used to estimate hazard ratios (HRs) and 95% CIs. The restricted cubic spline was applied to model the dose‐response association between CVAI and carotid plaque risk. During the 82 621 person‐years of follow‐up, 5987 cases of carotid plaque developed (7.25/100 person‐years). We observed a significant positive correlation between CVAI and carotid plaque risk (HR, 1.53; 95% CI, 1.48–1.59 [P<0.001]) in a nonlinear dose‐response pattern (P_nonlinearity<0.001). The sensitivity analyses further confirmed the robustness of the results. The association was significant in all subgroup analyses stratified by sex, hypertension, and fatty liver disease except for the diabetes subgroup. The association between CVAI and carotid plaque risk was much higher in men than in women. No significant association was identified between change in CVAI and carotid plaque risk.

Conclusions

CVAI was positively associated with carotid plaque risk in a nonlinear dose‐response pattern in this study. Individuals should keep their CVAI within a normal level to prevent the development of carotid plaque.

The Adipokine Component in the Molecular Regulation of Cancer Cell Survival, Proliferation and Metastasis

A hormonal imbalance may disrupt the rigorously monitored cellular microenvironment by hampering the natural homeostatic mechanisms. The most common example of such hormonal glitch could be seen in obesity where the uprise in adipokine levels is in virtue of the expanding bulk of adipose tissue. Such aberrant endocrine signaling disrupts the regulation of cellular fate, rendering the cells to live in a tumor supportive microenvironment. Previously, it was believed that the adipokines support cancer proliferation and metastasis with no direct involvement in neoplastic transformations and tumorigenesis. However, the recent studies have reported discrete mechanisms that establish the direct involvement of adipokine signaling in tumorigenesis. Moreover, the individual adipokine profile of the patients has never been considered in the prognosis and staging of the disease. Hence, the present manuscript has focused on the reported extensive mechanisms that culminate the basis of poor prognosis and diminished survival rate in obese cancer patients.

Purine metabolites and complex diseases: role of genes and nutrients

PURPOSE OF REVIEW

Purines have several important physiological functions as part of nucleic acids and as intracellular and extracellular signaling molecules. Purine metabolites, particularly uric acid, have been implicated in congenital and complex diseases. However, their role in complex diseases is not clear and they have both beneficial and detrimental effects on disease pathogenesis. In addition, the relationship between purines and complex diseases is affected by genetic and nutritional factors. This review presents latest findings about the relationship between purines and complex diseases and the effect of genes and nutrients on this relationship.

RECENT FINDINGS

Evidence from recent studies show strong role of purines in complex diseases. Although they are causal in only few diseases, our knowledge about their role in other diseases is still evolving. Of all the purines, uric acid is the most studied. Uric acid acts as an antioxidant as well as a prooxidant under different conditions, thus, its role in disease also varies. Other purines, adenosine and inosine have been less studied, but they have neuroprotective properties which are valuable in neurodegenerative diseases.

SUMMARY

Purines are molecules with great potential in disease pathogenesis as either metabolic markers or therapeutic targets. More studies need to be conducted to understand their relevance for complex diseases.

Higher Body Mass Index, Uric Acid Levels, and Lower Cholesterol Levels are Associated with Greater Weight Loss

Background:

Identifying predictive factors that contribute to changes in body weight may well be an interesting approach to the management of obesity.

Objective:

This study was firstly aimed at examining the effect of a one-year lifestyle program based on improvements in the habitual diet and increased levels of physical activity on weight loss. Secondly, it was focused on identifying anthropometric, and serum hormonal, metabolic and haematochemical factors which can be associated with the degree of weight loss in Kg.

Methods:

488 overweight or obese subjects, 383 women and 105 men, aged 18-67 years, were enrolled in the study. Body mass index, waist circumference, serum blood glucose, lipids, uric acid, creatinine, insulin, TSH, FT3, FT4, and 24-h urine catecholamines were measured.

Results:

Weight loss was positively associated with BMI (P < 0.01), waist circumference (P < 0.01), uric acid (P < 0.01), creatinine (P < 0.05), smoking (P < 0.01), and negatively correlated with age (P < 0.01), total cholesterol (P < 0.05), LDL-cholesterol (P < 0.01), HDL cholesterol (P < 0.05). In a multiple regression model considering weight loss as a dependent variable, and smoking, age, BMI, uric acid, creatinine, total cholesterol, LDL-cholesterol and HDL cholesterol as independent variables, weight loss maintained a direct independent relationship with BMI (P < 0.001), uric acid (P < 0.05), LDL-cholesterol (P < 0.05), and HDL-cholesterol (P < 0.05), and an inverse independent association with cholesterol (P < 0.01).

Conclusions:

This study suggests that higher BMI and uric acid levels, and lower total cholesterol concentrations are associated with a greater potential to lose weight.

Fat-Free Mass Is Better Related to Serum Uric Acid Than Metabolic Homeostasis in Prader-Willi Syndrome

Background: Prader-Willi syndrome (PWS) is conventionally regarded as a model of genetic obesity carrying a metabolically healthier profile and fat compartmentalization than subjects with non-syndromic obesity. Serum uric acid (sUA) is a recognized surrogate marker of metabolic derangement. As no information is currently available on sUA levels in adults with PWS, we aimed to analyze sUA in a large cohort of adult patients with PWS in comparison to a control counterpart; secondly, we aimed to investigate the metabolic and non-metabolic determinants of sUA in PWS. Methods: A cross-sectional study was conducted on 89 consecutive adult patients with genetically confirmed PWS spanning a wide BMI range (17.2–56.7 kg/m²). As controls, 180 age-, sex- and BMI-matched healthy controls were included. sUA levels were analyzed in relation to the PWS status, metabolic variables, hormone status, body composition, and resting energy expenditure (REE). Bivariate correlation and multivariable regression studies were used to test for predictors of sUA in PWS. Results: Despite having similar BMI values, patients with PWS presented with higher FM (p < 0.0001), lower FFM (p < 0.0001) and REE values than controls (p < 0.0001). In PWS, sUA levels were non-significantly different between subjects with and without obesity (5.4 ± 1.3 vs. 4.9 ± 1.1 mg/dL, p = 0.09), and did not vary significantly in relation to genotype, sex steroid or GH replacement, as well as psychiatric treatments. Rates of hyperuricaemia (19.1% vs. 33.7%, p < 0.01) and absolute sUA levels were lower in patients with PWS compared to controls owing to significant differences between subgroups with obesity (5.5 ± 1.4 vs. 6.6 ± 1.6 mg/dL, p < 0.0001). In merged populations, sUA increased in parallel with age, BMI, FM, FFM, REE, glucolipid homeostasis, and inflammatory markers. In a separate analysis in PWS, however, sUA correlations with BMI, FM, and inflammatory markers were null. Stepwise multivariable regression analysis in the PWS group adjusted for karyotype, age, sex, FM, FFM, obesity, triglycerides, and HDL cholesterol, showed that sUA levels were independently associated with FFM (β = 0.35, p < 0.0001) and, albeit less significantly, with triglycerides (β = 0.23, p < 0.05). The introduction of height-normalized FFM (FFM index) in the regression model, however, abrogated the predictive role of FFM on sUA. Conclusions: FFM mass is a strong predictor of sUA. PWS is associated to lower sUA levels than controls likely due to genetic predisposition to different body composition and healthier metabolic phenotype. Further studies are warranted to assess purine metabolism and the clinical significance of the FFM index in PWS.

Irisin levels in genetic and essential obesity: clues for a potential dual role

Irisin is conventionally regarded as a myokine involved in the browning of white adipose tissue, energy expenditure and glucose tolerance. Its potential link to fat accumulation and metabolic dysfunction is debated. We sought to explore the relationship between circulating irisin and components of body composition in two different phenotypes of severe obesity. For this purpose, 30 obese adults with Prader-Will syndrome (PWS) (age 35.7 ± 1.5 y, BMI 45.5 ± 1.5 kg/m²) and 30 adult controls with common obesity (age 34.9 ± 1.7 y, BMI 46.8 ± 1.4 kg/m²) underwent analysis of irisin levels, metabolic profile, body composition and resting energy expenditure (REE). Normal irisin levels were obtained from a group of 20 lean donors (age 32.4 ± 1.5 y, BMI 23.8 ± 0.8 kg/m²). Expected differences in body composition and metabolic profile existed between study groups. PWS exhibited lower muscle mass (p < 0.001), FFM (p < 0.001), REE (p < 0.001), as well as insulin (p < 0.05), HOMA-IR (p < 0.05) and triglycerides levels (p < 0.05) than controls with common obesity. In PWS, irisin levels were significantly lower and overall less dispersed than in controls with common obesity (p < 0.05), while being similar to values recorded in lean subjects. To explore the relation between irisin and body composition in obesity, univariate correlation analysis in the obese populations as a whole showed positive associations between irisin and muscle mass (p = 0.03) as well as REE (p = 0.01), which disappeared when controlled for the PWS status. Noticeably, a positive association became evident between irisin and %FM after controlling for the PWS status (p = 0.02). Also positive were associations between irisin and insulin (p = 0.02), HOMA-IR (p = 0.02) and triglycerides (p = 0.04). In stepwise multivariable regression analysis, irisin levels were independently predicted by the PWS status (p = 0.001), %FM (p = 0.004) and triglycerides (p = 0.008). Current results suggest that obese adults with PWS harbor lower irisin levels than individuals with common obesity. The divergent models of obesity herein studied suggest a potential link between circulating irisin and muscle mass and metabolic dysfunction relating to adiposity.

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

PURPOSE

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

SUBJECTS AND METHODS

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

RESULTS

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

CONCLUSION

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

Beyond adiponectin and leptin: adipose tissue-derived mediators of inter-organ communication

The breakthrough discoveries of leptin and adiponectin more than two decades ago led to a widespread recognition of adipose tissue as an endocrine organ. Many more adipose tissue-secreted signaling mediators (adipokines) have been identified since then, and much has been learned about how adipose tissue communicates with other organs of the body to maintain systemic homeostasis. Beyond proteins, additional factors, such as lipids, metabolites, noncoding RNAs, and extracellular vesicles (EVs), released by adipose tissue participate in this process. Here, we review the diverse signaling mediators and mechanisms adipose tissue utilizes to relay information to other organs. We discuss recently identified adipokines (proteins, lipids, and metabolites) and briefly outline the contributions of noncoding RNAs and EVs to the ever-increasing complexities of adipose tissue inter-organ communication. We conclude by reflecting on central aspects of adipokine biology, namely, the contribution of distinct adipose tissue depots and cell types to adipokine secretion, the phenomenon of adipokine resistance, and the capacity of adipose tissue to act both as a source and sink of signaling mediators.