Decreased levels of uric acid after oral glucose challenge is associated with triacylglycerol levels and degree of insulin resistance

Acute Antiplatelet Effects of an Oleocanthal-Rich Olive Oil in Type II Diabetic Patients: A Postprandial Study

Postprandial dysmetabolism is a common entity of type 2 diabetes mellitus (T2DM) and may act as a daily stressor of the already dysfunctional diabetic platelets. This study aims to investigate whether oleocanthal-rich olive oils (OO), incorporated into a carbohydrate-rich meal, can affect postprandial dysmetabolism and platelet aggregation. Oleocanthal is a cyclooxygenase inhibitor with putative antiplatelet properties. In this randomized, single-blinded, crossover study, ten T2DM patients consumed five isocaloric meals containing 120 g white bread combined with: (i) 39 g butter, (ii) 39 g butter and 400 mg ibuprofen, (iii) 40 mL OO (phenolic content < 10 mg/Kg), (iv) 40 mL OO with 250 mg/Kg oleocanthal and (v) 40 mL OO with 500 mg/Kg oleocanthal. Metabolic markers along with ex vivo ADP- and thrombin receptor-activating peptide (TRAP)-induced platelet aggregation were measured before and for 4 h after the meals. The glycemic and lipidemic response was similar between meals. However, a sustained (90-240 min) dose-dependent reduction in platelets' sensitivity to both ADP (50-100%) and TRAP (20-50%) was observed after the oleocanthal meals in comparison to OO or butter meals. The antiplatelet effect of the OO containing 500 mg/Kg oleocanthal was comparable to that of the ibuprofen meal. In conclusion, the consumption of meals containing oleocanthal-rich OO can reduce platelet activity during the postprandial period, irrespective of postprandial hyperglycemia and lipidemia.

Effects of Lowering Glycemic Index of Dietary Carbohydrate on Plasma Uric Acid Levels: The OmniCarb Randomized Clinical Trial

OBJECTIVE

The effects of carbohydrates on plasma uric acid levels are a subject of controversy. We determined the individual and combined effects of carbohydrate quality (the glycemic index) and quantity (the proportion of total daily energy [percentage of carbohydrates]) on uric acid levels.

METHODS

We conducted a randomized, crossover trial of 4 different diets in overweight or obese adults without cardiovascular disease (n = 163). Participants consumed each of 4 diets over a 5-week period, each of which was separated by a 2-week washout period. Body weight was kept constant. The 4 diets were high glycemic index (≥65) with high percentage of carbohydrates (58% kcal), low glycemic index (≤45) with low percentage of carbohydrates (40% kcal), low glycemic index with high percentage of carbohydrates, and high glycemic index with low percentage of carbohydrates. Plasma uric acid levels were measured at baseline and after completion of each 5-week period for comparison between the 4 diets.

RESULTS

Of the 163 study participants, 52% were women and 50% were non-Hispanic African American subjects; their mean age was 52.6 years, and their mean ± SD uric acid level was 4.7 ± 1.2 mg/dl. Reducing the glycemic index lowered uric acid levels when the percentage of carbohydrates was low (-0.24 mg/dl; P < 0.001) or high (-0.17 mg/dl; P < 0.001). Reducing the percentage of carbohydrates marginally increased the uric acid level only when the glycemic index was high (P = 0.05). The combined effect of lowering the glycemic index and increasing the percentage of carbohydrates was -0.27 mg/dl (P < 0.001). This effect was observed even after adjustment for concurrent changes in kidney function, insulin sensitivity, and products of glycolysis.

CONCLUSION

Reducing the glycemic index lowers uric acid levels. Future studies should examine whether reducing the glycemic index can prevent gout onset or flares.

Association between Uric Acid and Metabolic Syndrome in Qazvin Metabolic Diseases Study (QMDS), Iran

Background:

The prevalence of Metabolic Syndrome (MS) has been increasing worldwide. Although Uric Acid (UA) Levels are often increased in subjects with MS, it is still unclear whether uric acid plays a causal role for MS or is a marker. The purpose of this study was to examine the association between UA and the MS in Qazvin, Iran.

Methods:

529 men and 578 women aged 20 – 78 years attended in cross sectional study from September 2010 to April 2011 in Qazvin, Iran. The criteria proposed by new joint Interim societies (JIS) were applied for diagnosis of MS. Hyperuricemia was defined as UA ≥ 7 mg/dL in men and UA ≥ 6 mg/dL in women. Logistic regression analysis was performed to evaluate the relationship between UA quartiles and MS.

Results:

The prevalence of MS was found to be 39.3%. Prevalence of hyperuricemia was 8.4% in males and 4.1% in females (P=0.004). Mean UA level was higher in males than in females (P<0.001). UA levels increased significantly with an increasing number of MS components in both genders. Prevalence of MS increased across UA quartiles in females; however the increasing trend began from second quartile in males. Using the lowest quartile of UA level as a reference, there were no significant association between UA quartile groups and MS.

Conclusion:

This study showed that UA levels are not an appropriate predictor of MS in Iranian population. More longitudinal studies are necessary to confirm the role of UA in MS occurrence.

The relationship between uric acid and metabolic syndrome in normal glucose tolerance and normal fasting glucose subjects

Elevated serum uric acid (SUA) concentrations have been suggested to associate with metabolic syndrome (MetS) and its components. However, limited information is available regarding the relationship between SUA and MetS in subjects with normal glucose levels. A total of 501 subjects with normal fasting glucose and normal glucose tolerance were included in the study. Anthropometrical and biochemical parameters were examined using standard methods. The updated NECP criteria were used to define the MetS. Values of SUA above the sex-specific percentile 75 were used to define hyperuricemia. The prevalence of general and abdominal obesity, hypertension, hypertriglyceridemia, low-HDL, smokers, MetS and insulin resistance was significantly greater in the fourth SUA quartile. Multiple regression indicated that SUA was independently predicted by BMI, triglyceride and 2 h glucose in women, and BMI, triglyceride, 2 h glucose and cholesterol in men. Logistic regression analysis showed that the obesity, hypertriglyceridemia, MetS and insulin resistance were independent determinants of hyperuricemia in women. In men, hyperuricemia was associated with the obesity, hypertriglyceridemia and hypercholesterolemia. Factor analysis yielded three factors interpreted as weight/waist, blood pressure and lipid/glucose. Including SUA in the model did not affect total variance of factor analysis. Our results indicate that SUA is associated with MetS and its components even in subjects with normal glucose levels. General obesity was the major determinant of hyperuricemia in this population. The data from this study do not show the contribution of SUA as an additional component of the MetS.

[Uric acid predicts type 2 diabetes mellitus in the general population]

INTRODUCTION

Abnormal uric acid levels are considered by some to be a risk factor for metabolic disorders, whereas others consider it to be just a marker. We therefore examined the association between plasma uric acid concentrations and the risk of type 2 diabetes mellitus.

MATERIAL AND METHODS

We undertook a prospective, 8-year study of 411 persons from the general population with no carbohydrate metabolism disorder at the start of the study evaluated by oral glucose overload. The following variables were measured at the beginning and end of the study: uric acid, triglycerides, cholesterol, high-density lipoprotein cholesterol, glucose and insulin in plasma, body mass index and waist-to-hip ratio. The participants were classified according to their plasma uric acid concentration, with a cut-off at the 33rd percentile (men, 291.45 and women, 208.18 micromol/l).

RESULTS

Participants with plasma uric acid concentrations above the 33rd percentile at the start of the study had worse lipid and anthropometric profiles. These persons were at greater risk for carbohydrate disorder at the end of the 8- year follow-up study (relative risk, 1.73; 95% confidence interval, 1.04-2.8). No significant differences were found in age or in the remaining variables studied between these two groups.

CONCLUSIONS

Increased uric acid levels in response to a possible chronic increase in oxidative stress may predict future disorders or complications such as type 2 diabetes in otherwise healthy persons.