Fructose overconsumption causes dyslipidemia and ectopic lipid deposition in healthy subjects with and without a family history of type 2 diabetes

BACKGROUND: Both nutritional and genetic factors are involved in the pathogenesis of nonalcoholic fatty liver disease and insulin resistance. OBJECTIVE: The aim was to assess the effects of fructose, a potent stimulator of hepatic de novo lipogenesis, on intrahepatocellular lipids (IHCLs) and insulin sensitivity in healthy offspring of patients with type 2 diabetes (OffT2D)--a subgroup of individuals prone to metabolic disorders. DESIGN: Sixteen male OffT2D and 8 control subjects were studied in a crossover design after either a 7-d isocaloric diet or a hypercaloric high-fructose diet (3.5 g x kg FFM(-1) x d(-1), +35% energy intake). Hepatic and whole-body insulin sensitivity were assessed with a 2-step hyperinsulinemic euglycemic clamp (0.3 and 1.0 mU x kg(-1) x min(-1)), together with 6,6-[2H2]glucose. IHCLs and intramyocellular lipids (IMCLs) were measured by 1H-magnetic resonance spectroscopy. RESULTS: The OffT2D group had significantly (P < 0.05) higher IHCLs (+94%), total triacylglycerols (+35%), and lower whole-body insulin sensitivity (-27%) than did the control group. The high-fructose diet significantly increased IHCLs (control: +76%; OffT2D: +79%), IMCLs (control: +47%; OffT2D: +24%), VLDL-triacylglycerols (control: +51%; OffT2D: +110%), and fasting hepatic glucose output (control: +4%; OffT2D: +5%). Furthermore, the effects of fructose on VLDL-triacylglycerols were higher in the OffT2D group (group x diet interaction: P < 0.05). CONCLUSIONS: A 7-d high-fructose diet increased ectopic lipid deposition in liver and muscle and fasting VLDL-triacylglycerols and decreased hepatic insulin sensitivity. Fructose-induced alterations in VLDL-triacylglycerols appeared to be of greater magnitude in the OffT2D group, which suggests that these individuals may be more prone to developing dyslipidemia when challenged by high fructose intakes. This trial was registered at clinicaltrials.gov as NCT00523562.

[Insulin and type 2 diabetes mellitus]

Worldwide an increasing number of persons suffers from type 2 diabetes. Often treatment with oral hypoglycemic agents is not sufficient for adequate glycemic control and additional insulin treatment is necessary. Treatment with insulin is recommended if HbA1c levels below 7% cannot be achieved despite lifestyle measures and the proper use of oral hypoglycemic agents. In addition, pregnancy, periods pre and post major operations, treatment in intensive care units, glucocorticoid medication, severe peripheral neuropathy as well as contraindications of oral hypoglycaemic agents may be indications for insulin therapy irrespective of the actual glycemic control. The choice of the appropriate insulin regimen depends on the daily blood glucose profiles and patient needs.

A reduction in severe hypoglycaemia in type 1 diabetes in a randomized crossover study of continuous intraperitoneal compared with subcutaneous insulin infusion

Continuous intraperitoneal insulin infusion (CIPII) with the DiaPort system using regular insulin was compared to continuous subcutaneous insulin infusion (CSII) using insulin Lispro, to investigate the frequency of hypoglycemia, blood glucose control, quality of life, and safety.

[Type 2 diabetes among elderly people]

Type 2 Diabetes is frequent among elderly people. The appropriate target for HbA1c in elderly patients ( > 70 years or life expectancy < 10 years) should be around 7.0% (maximally 8%). In patients with multiple co-morbidities, the goal must be an improvement of symptoms and preservation of weight, especially muscle mass. In the setting of an uncontrolled symptomatic diabetes with concomitant catabolism, insulin is the most effective therapy and, therefore, the treatment of choice. The prevention of hypoglycemia must be a major aim. A balanced and regular food intake facilitates therapy and improves quality of life. The priorities of the management of cardiovascular risk factors should be based upon the individual's overall health condition.

Liraglutide once a day versus exenatide twice a day for type 2 diabetes: a 26-week randomised, parallel-group, multinational, open-label trial (LEAD-6)

BACKGROUND: Unlike most antihyperglycaemic drugs, glucagon-like peptide-1 (GLP-1) receptor agonists have a glucose-dependent action and promote weight loss. We compared the efficacy and safety of liraglutide, a human GLP-1 analogue, with exenatide, an exendin-based GLP-1 receptor agonist. METHODS: Adults with inadequately controlled type 2 diabetes on maximally tolerated doses of metformin, sulphonylurea, or both, were stratified by previous oral antidiabetic therapy and randomly assigned to receive additional liraglutide 1.8 mg once a day (n=233) or exenatide 10 microg twice a day (n=231) in a 26-week open-label, parallel-group, multinational (15 countries) study. The primary outcome was change in glycosylated haemoglobin (HbA(1c)). Efficacy analyses were by intention to treat. The trial is registered with ClinicalTrials.gov, number NCT00518882. FINDINGS: Mean baseline HbA(1c) for the study population was 8.2%. Liraglutide reduced mean HbA(1c) significantly more than did exenatide (-1.12% [SE 0.08] vs -0.79% [0.08]; estimated treatment difference -0.33; 95% CI -0.47 to -0.18; p<0.0001) and more patients achieved a HbA(1c) value of less than 7% (54%vs 43%, respectively; odds ratio 2.02; 95% CI 1.31 to 3.11; p=0.0015). Liraglutide reduced mean fasting plasma glucose more than did exenatide (-1.61 mmol/L [SE 0.20] vs -0.60 mmol/L [0.20]; estimated treatment difference -1.01 mmol/L; 95% CI -1.37 to -0.65; p<0.0001) but postprandial glucose control was less effective after breakfast and dinner. Both drugs promoted similar weight losses (liraglutide -3.24 kg vs exenatide -2.87 kg). Both drugs were well tolerated, but nausea was less persistent (estimated treatment rate ratio 0.448, p<0.0001) and minor hypoglycaemia less frequent with liraglutide than with exenatide (1.93 vs 2.60 events per patient per year; rate ratio 0.55; 95% CI 0.34 to 0.88; p=0.0131; 25.5%vs 33.6% had minor hypoglycaemia). Two patients taking both exenatide and a sulphonylurea had a major hypoglycaemic episode. INTERPRETATION: Liraglutide once a day provided significantly greater improvements in glycaemic control than did exenatide twice a day, and was generally better tolerated. The results suggest that liraglutide might be a treatment option for type 2 diabetes, especially when weight loss and risk of hypoglycaemia are major considerations.

The effect of growth hormone (GH) replacement therapy in adult patients with type 1 diabetes mellitus and GH deficiency

Specific problems in patients with insulin-dependent diabetes mellitus (IDDM) and GH deficiency are hypoglycaemic attacks, increased insulin sensitivity and loss of energy. These problems may be related to GH deficiency.

Normal VLDL metabolism despite altered lipoprotein composition in type 1 diabetes mellitus

Patients with type 1 diabetes are at increased risk of cardiovascular disease, which may be related to abnormal lipid metabolism. Secretion and clearance of VLDL apolipoprotein B100 (apoB) are important determinants of plasma lipid concentrations and are known to be influenced by hormones, including insulin and growth hormone.

[Diabetes update: preventing type 2 diabetes. Individualized stepwise therapy (oral antidiabetic agents). Multifactorial intervention]

Preclinical disorders of glucose metabolism should be systematically included in the high-risk group for diabetes mellitus and affected individuals provided with preventive measures. Their underlying insulin resistance is determined with the help of a checklist and a method called homeostasis model assessment (HOMA). Patients with impaired fasting glucose (IFG) must change their lifestyles. If this does not lead to a response or the patient is unable to modify behavior, medication is required. In the case of manifest type 2 diabetes mellitus, a graded schedule is used for differential management, which should be based on nutritional and exercise therapy. Oral medication with metformin is probably the drug of choice in both obese and non-obese patients. It is crucial not to delay raising the level of treatment until HbA1c has fallen to within an unsatisfactory range (wait-and-see strategy). Rather, the level should be intensified when persistent exacerbation starts to become apparent (proactive therapy). In diabetes mellitus, the same guidelines for secondary prevention apply to the associated cardiovascular risk factors as with coronary heart disease. An intensified and, especially, early treatment is to be preferred over a conservative, wait-and-see approach, in this case as well.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

A Communication Platform for Tele-monitoring and Tele-management of Type 1 Diabetes

Type 1 diabetes mellitus is a chronic disease characterized by blood glucose levels out of normal range due to inability of insulin production. This dysfunction leads to many short- and long-term complications. In this paper, a system for tele-monitoring and tele-management of Type 1 diabetes patients is proposed, aiming at reducing the risk of diabetes complications and improving quality of life. The system integrates Wireless Personal Area Networks (WPAN), mobile infrastructure, and Internet technology along with commercially available and novel glucose measurement devices, advanced modeling techniques, and tools for the intelligent processing of the available diabetes patients information. The integration of the above technologies enables intensive monitoring of blood glucose levels, treatment optimisation, continuous medical care, and improvement of quality of life for Type 1 diabetes patients, without restrictions in everyday life activities.

A neural network approach for insulin regime and dose adjustment in type 1 diabetes

A decision support system based on a neural network approach is proposed to advise on insulin regime and dose adjustment for type 1 diabetes patients.