Body mass index is independently associated with xanthine oxidase activity in overweight/obese population.

PURPOSE: The pathophysiological mechanism of the relationship between xanthine oxidase (XO) activity and obesity has not been completely elucidated. Since inflammation and oxidative stress are regarded as key determinants of enlarged adipose tissue, we aimed to investigate the association between oxidative stress (as measured with XO activity), inflammation [as measured with high-sensitivity C-reactive protein (hsCRP)] and obesity [as measured with body mass index (BMI)]. In addition, we wanted to examine whether hsCRP itself plays an independent role in XO activity increase or it is only mediated through obesity. METHODS: A total of 118 overweight/obese volunteers (mean age 54.76 ± 15.13 years) were included in the current cross-sectional study. Anthropometric, biochemical parameters, and blood pressure were obtained. RESULTS: Significant differences between age, BMI, waist circumference, concentrations of uric acid and hsCRP, as well as xanthine dehydrogenase (XDH) activities were evident among XO tertile groups. Multiple linear regression analysis revealed that BMI (beta = 0.241, p = 0.012) and XDH (beta = - 0.489, p < 0.001) are the independent predictors of XO activity (R2-adjusted = 0.333), whereas hsCRP lost its independent role in XO activity prediction. CONCLUSION: Obesity (as determined with increased BMI) is an independent predictor of high XO activity in overweight/obese population. LEVEL OF EVIDENCE: Level V: cross-sectional descriptive study.

Cardiovascular Risk Assessed by Reynolds Risk Score in Relation to Waist Circumference in Apparently Healthy Middle-Aged Population in Montenegro.

Reynolds Risk Score (RRS) is regarded as a good screening tool for cardiovascular disease (CVD) risk. Since CVD is the leading cause of death in Montenegro, we aimed to assess the risk of CVD as assessed by RRS and to examine its association with cardiometabolic parameters in apparently healthy middle-aged population. In addition, we aimed to test whether obesity had an independent influence on RRS. A total of 132 participants (mean age 56.2±6.73 years, 69% females) were included. Body mass index (BMI), waist circumference (WC), blood pressure (BP) and biochemical parameters (fasting glucose, insulin, lipid parameters, creatinine and high sensitivity C-reactive protein) were determined. Insulin resistance (HOMA-IR) and glomerular filtration rate (eGFR) were calculated. Compared with females, a significantly higher number of males were in the high RRS subgroup (χ2=45.9, p<0.001). Furthermore, significantly higher fasting glucose (p=0.030), insulin, HOMA-IR, triglycerides (p<0.001 all), anthropometric parameters (e.g., BMI and WC; p=0.004 and p<0.001, respectively), and creatinine, but lower eGFR and HDL-c (p<0.001 both) were recorded in the high-risk subgroup compared with low and medium risk subgroups. In all participants, in addition to LDL-c, diastolic BP and creatinine, WC was independently positively associated with RRS (ß=0.194, p=0.006; ß=0.286, p=0.001; ß=0.267, p=0.001; and ß=0.305, p=0.019, respectively), and 40% of variation in RRS could be explained with this model. In conclusion, middle-aged population with higher WC should be screened for RRS in order to estimate CVD risk.

Relationship between Oxidative Stress, Inflammation and Dyslipidemia with Fatty Liver Index in Patients with Type 2 Diabetes Mellitus.

INTRODUCTION/AIM: Considering the high prevalence of non-alcoholic fatty liver disease (NAFLD) in individuals with type 2 diabetes mellitus (DM2), we aimed to investigate the potential benefit of determining markers of oxidative stress, inflammation and dyslipidemia for prediction of NAFLD, as estimated with fatty liver index (FLI) in individuals with DM2. METHODS: A total of 139 individuals with DM2 (of them 49.9% females) were enrolled in cross-sectional study. Anthropometric and biochemical parameters, as well as blood pressure were obtained. A FLI was calculated. RESULTS: Multivariate logistic regression analysis showed that high density lipoprotein cholesterol (HDL-c) and malondialdehyde (MDA) were independent predictors of higher FLI [Odds ratio (OR)=0.056, p=0.029; and OR=1.105, p=0.016, respectively]. In Receiver Operating Characteristic curve analysis, the addition of fatty liver risk factors (e. g., age, gender, body height, smoking status, diabetes duration and drugs metabolized in liver) to each analysed biochemical parameter [HDL-c, non-HDL-c, high sensitivity C-reactive protein (hsCRP), MDA and advanced oxidant protein products (AOPP)] in Model 1, increased the ability to discriminate patients with and without fatty liver [Area under the curve (AUC)=0.832, AUC=0.808, AUC=0.798, AUC=0.824 and AUC=0.743, respectively]. Model 2 (which included all five examined predictors, e. g., HDL-c, non-HDL-c, hsCRP, MDA, AOPP, and fatty liver risk factors) improved discriminative abilities for fatty liver status (AUC=0.909). Even more, Model 2 had the highest sensitivity and specificity (89.3% and 87.5%, respectively) together than each predictor in Model 1. CONCLUSION: Multimarker approach, including biomarkers of oxidative stress, dyslipidemia and inflammation, could be of benefit in identifying patients with diabetes being at high risk of fatty liver disease.

Xanthine oxidase and uric acid as independent predictors of albuminuria in patients with diabetes mellitus type 2.

Xanthine oxidase (XO) is an important enzyme responsible for conversion of purine bases to uric acid and represents the major source of reactive oxygen species (ROS) production in circulation. Since pathophysiological mechanism of the relationship between XO activity and urinary albumin excretion (UAE) rate is not well elucidated, we aimed to investigate this association in patients with diabetes mellitus type 2 (DM2). In addition, we wanted to examine whether uric acid itself plays an independent role in albuminuria onset and progression, or it is only mediated through XO activity. A total of 83 patients with DM2 (of them 56.6% females) were included in this cross-sectional study. Anthropometric, biochemical parameters and blood pressure were obtained. Multivariate logistic regression analysis showed that uric acid and XO were the independent predictors for albuminuria onset in patients with DM2 [odds ratio (OR) 1.015, 95% CI (1.008-1.028), p = 0.026 and OR 1.015, 95% CI (1.006-1.026), p = 0.040, respectively]. Rise in uric acid for 1 µmol/L enhanced the probability for albuminuria by 1.5%. Also, elevation in XO activity for 1 U/L increased the probability for albuminuria for 1.5%. A total of 66.7% of variation in UAE could be explained with this Model. Both XO and uric acid are independently associated with albuminuria in diabetes. Better understanding of pathophysiological relationship between oxidative stress and albuminuria could lead to discoveries of best pharmacological treatment of XO- and/or uric acid-induced ROS, in order to prevent albuminuria onset and progression.

Association between unfavorable lipid profile and glycemic control in patients with type 2 diabetes mellitus.

BACKGROUND: Recent studies hypothesize that dyslipidemia can predict glycated hemoglobin (HbA1c) and could be important contributing factor to the pathogenesis of type 2 diabetes mellitus (DM2). Therefore, we aimed to evaluate the influence of lipid parameters on long-term glycemic control in DM2. MATERIALS AND METHODS: A total of 275 sedentary DM2 (mean [±standard deviation] age 60.6 [±10.0] years) who volunteered to participate in this cross-sectional study were enrolled. Anthropometric (body weight, body hight, and waist circumference), biochemical parameters (fasting glucose, HbA1c, lipid parameters, creatinine), as well as blood pressure were obtained. RESULTS: Total cholesterol (odds ratio [OR] =1.30, 95% confidence interval [CI] [1.02-1.66], P = 0.032), triglycerides (OR = 1.34, 95% CI (1.07-1.67), P = 0.010), and low density lipoprotein cholesterol (OR = 1.42, 95% CI [1.10-1.83], P = 0.006) were the independent predictors of higher HBA1c, and as they increased by 1 mmol/L each, probabilities of higher HBA1c increased by 30%, 34%, and 42%, respectively. Low level of high-density lipoprotein cholesterol (HDL-c) was found to be the independent predictor of higher HBA1c (OR = 0.44, 95% CI [0.20-0.67], P = 0.039), and increase in HDL-c by 1 mmol/L, reduced the probability of higher HBA1c by 56%. CONCLUSION: Unfavorable lipid profile can predict HbA1c level in DM2 patients. Early diagnosis of dyslipidemia, as well as its monitoring and maintaining good lipids control can be used as a preventive measure for optimal long-term glycemic control.

Bioavailable testosterone is independently associated with Fatty Liver Index in postmenopausal women.

INTRODUCTION: Previous studies have examined the correlation between hyperandrogenemia and non-alcoholic fatty liver disease (NAFLD) in women and showed contradictory results. Therefore, we aimed to evaluate the relationship between testosterone level and Fatty Liver Index (FLI), as a surrogate marker for NAFLD, in a cohort of postmenopausal women. MATERIAL AND METHODS: A total of 150 postmenopausal women were included in this cross-sectional study. Anthropometric and biochemical parameters, as well as blood pressure, were obtained. Non-alcoholic fatty liver disease is assessed by FLI, an algorithm based on body mass index, waist circumference, triglycerides and γ-glutamyl transferase, as a simple and accurate predictor of hepatic steatosis. Women were divided into three groups (FLI < 30, n = 80; 30 ≤ FLI < 60, n = 44; FLI ≥ 60, n = 26). Homeostasis model assessment of insulin resistance (HOMA-IR) as a surrogate marker of insulin resistance was calculated. RESULTS: Multiple linear regression analysis revealed that the best model consisted of 4 parameters (e.g., bioavailable testosterone (ß = 0.288, p = 0.001), log HOMA-IR (ß = 0.227, p = 0.005), log high-sensitivity C-reactive protein (ß = 0.322, p < 0.001), and retinol-binding protein 4 (ß = 0.226, p < 0.001)). Adjusted R2 for the best model was 0.550, which means that as much as 55.0% of variation in FLI could be explained with this model. CONCLUSIONS: Bioavailable testosterone is independently associated with FLI in postmenopausal women.