Transferências lipídicas para HDL em diabéticos tipo 2: associações com microalbuminúria, estatina e insulina

Effect of carnosine supplementation on the plasma lipidome in overweight and obese adults: a pilot randomised controlled trial

Carnosine has been shown to reduce oxidation and glycation of low density lipoprotein hence improving dyslipidaemia in rodents. The effect of carnosine on human plasma lipidome has thus far not been investigated. We aimed to determine whether carnosine supplementation improves the plasma lipidome in overweight and obese individuals. Lipid analysis was performed by liquid chromatography mass spectrometry in 24 overweight and obese adults: 13 were randomly assigned to 2 g carnosine daily and 11 to placebo, and treated for 12 weeks. Carnosine supplementation maintained trihexosylceramide (0.01 ± 0.19 vs -0.28 ± 0.34 nmol/ml, p = 0.04), phosphatidylcholine (77 ± 167 vs -81 ± 196 nmol/ml, p = 0.01) and free cholesterol (20 ± 80 vs -69 ± 80 nmol/ml, p = 0.006) levels compared to placebo. Trihexosylceramide was inversely related with fasting insulin (r = -0.6, p = 0.002), insulin resistance (r = -0.6, p = 0.003), insulin secretion (r = -0.4, p = 0.05) and serum carnosinase 1 activity (r = -0.3, p = 0.05). Both phosphatidylcholine and free cholesterol did not correlate with any cardiometabolic parameters. Our data suggest that carnosine may have beneficial effects on the plasma lipidome. Future larger clinical trials are needed to confirm this.

Inconsistency in albuminuria predictors in type 2 diabetes: a comparison between neural network and conditional logistic regression

Albuminuria is a sensitive marker to predict future cardiovascular events in patients with type 2 diabetes mellitus. However, current studies only use conventional regression models to discover predictors of albuminuria. We have used 2 different statistical models to predict albuminuria in type 2 diabetes mellitus: a multilayer perception neural network and a conditional logistic regression. Neural network models were used to predict the level of albuminuria in patients with type 2 diabetes mellitus, which include a matched case-control study for the population. For each case, we randomly selected 1 control matched by age and body mass index (BMI). The input variables were sex, duration of diabetes, systolic and diastolic blood pressure, glomerular filtration rate, high-density lipoprotein, low-density lipoprotein, triglyceride, high-density lipoprotein/triglyceride ratio, cholesterol, fasting blood sugar, and glycated hemoglobin. Age and BMI were included only in the neural network model. This model included 4 hidden layers and 1 bias. Relative error of predictions was 0.38% in the training group, 0.52% in the testing group, and 1.20% in the holdout group. The most robust predictors of albuminuria were high-density lipoprotein (21%), cholesterol (14.4%), and systolic blood pressure (9.7%). Using the conditional logistic regression model, glomerular filtration rate, time of onset to diabetes, and sex were significant indicators in the onset of albuminuria. Using a neural network model, we show that high-density lipoprotein is the most important factor in predicting albuminuria in type 2 diabetes mellitus. Our neural network model complements the current risk factor models to improve the care of patients with diabetes.

Removal from the plasma of the free and esterified forms of cholesterol and transfer of lipids to HDL in type 2 diabetes mellitus patients

BACKGROUND

The aim was to investigate new markers for type 2 diabetes (T2DM) dyslipidemia related with LDL and HDL metabolism. Removal from plasma of free and esterified cholesterol transported in LDL and the transfer of lipids to HDL are important aspects of the lipoprotein intravascular metabolism. The plasma kinetics (fractional clearance rate, FCR) and transfers of lipids to HDL were explored in T2DM patients and controls, using as tool a nanoemulsion that mimics LDL lipid structure (LDE).

RESULTS

14C- cholesteryl ester FCR of the nanoemulsion was greater in T2DM than in controls (0.07 ± 0.02 vs. 0.05 ± 0.01 h-1, p = 0.02) indicating that LDE was removed faster, but FCR 3 H- cholesterol was equal in both groups. Esterification rates of LDE free-cholesterol were equal. Cholesteryl ester and triglyceride transfer from LDE to HDL was greater in T2DM (4.2 ± 0.8 vs. 3.5 ± 0.7%, p = 0.03 and 6.8 ± 1.6% vs. 5.0 ± 1.1, p = 0.03, respectively). Phospholipid and free cholesterol transfers were not different.

CONCLUSIONS

The kinetics of free and esterified cholesterol tended to be independent in T2DM patients and the lipid transfers to HDL were also disturbed. These novel findings may be related with pathophysiological mechanisms of diabetic macrovascular disease.