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.

Effect of IGF-I therapy on VLDL apolipoprotein B100 metabolism in type 1 diabetes mellitus

Abnormal lipid metabolism may be related to the increased cardiovascular risk in type 1 diabetes. Secretion and clearance rates of very low density lipoprotein (VLDL) apolipoprotein B100 (apoB) determine plasma lipid concentrations. Type 1 diabetes is characterized by increased growth hormone (GH) secretion and decreased insulin-like growth factor (IGF) I concentrations. High-dose IGF-I therapy improves the lipid profile in type 1 diabetes. This study examined the effect of low-dose (40 microg.kg(-1).day(-1)) IGF-I therapy on VLDL apoB metabolism, VLDL composition, and the GH-IGF-I axis during euglycemia in type 1 diabetes. Using a stable isotope technique, VLDL apoB kinetics were estimated before and after 1 wk of IGF-I therapy in 12 patients with type 1 diabetes in a double-blind, placebo-controlled trial. Fasting plasma triglyceride (P < 0.03), VLDL-triglyceride concentrations (P < 0.05), and the VLDL-triglyceride-to-VLDL apoB ratio (P < 0.002) significantly decreased after IGF-I therapy, whereas VLDL apoB kinetics were not significantly affected by IGF-I therapy. IGF-I therapy resulted in a significant increase in IGF-I and a significant reduction in GH concentrations. The mean overnight insulin concentrations during euglycemia decreased by 25% after IGF-I therapy. These results indicate that low-dose IGF-I therapy restores the GH-IGF-I axis in type 1 diabetes. IGF-I therapy changes fasting triglyceride concentrations and VLDL composition probably because of an increase in insulin sensitivity.

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.

IGF-I treatment in adults with type 1 diabetes: effects on glucose and protein metabolism in the fasting state and during a hyperinsulinemic-euglycemic amino acid clamp

Type 1 diabetes is associated with abnormalities of the growth hormone (GH)-IGF-I axis. Such abnormalities include decreased circulating levels of IGF-I. We studied the effects of IGF-I therapy (40 microg x kg(-1) x day(-1)) on protein and glucose metabolism in adults with type 1 diabetes in a randomized placebo-controlled trial. A total of 12 subjects participated, and each subject was studied at baseline and after 7 days of treatment, both in the fasting state and during a hyperinsulinemic-euglycemic amino acid clamp. Protein and glucose metabolism were assessed using infusions of [1-13C]leucine and [6-6-2H2]glucose. IGF-I administration resulted in a 51% rise in circulating IGF-I levels (P < 0.005) and a 56% decrease in the mean overnight GH concentration (P < 0.05). After IGF-I treatment, a decrease in the overnight insulin requirement (0.26+/-0.07 vs. 0.17+/-0.06 U/kg, P < 0.05) and an increase in the glucose infusion requirement were observed during the hyperinsulinemic clamp (approximately 67%, P < 0.05). Basal glucose kinetics were unchanged, but an increase in insulin-stimulated peripheral glucose disposal was observed after IGF-I therapy (37+/-6 vs. 52+/-10 micromol x kg(-1) x min(-1), P < 0.05). IGF-I administration increased the basal metabolic clearance rate for leucine (approximately 28%, P < 0.05) and resulted in a net increase in leucine balance, both in the basal state and during the hyperinsulinemic amino acid clamp (-0.17+/-0.03 vs. -0.10+/-0.02, P < 0.01, and 0.25+/-0.08 vs. 0.40+/-0.06, P < 0.05, respectively). No changes in these variables were recorded in the subjects after administration of placebo. These findings demonstrated that IGF-I replacement resulted in significant alterations in glucose and protein metabolism in the basal and insulin-stimulated states. These effects were associated with increased insulin sensitivity, and they underline the major role of IGF-I in protein and glucose metabolism in type 1 diabetes.

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 real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

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.

Circadian blood pressure during the early course of type 1 diabetes. Analysis of 1,011 ambulatory blood pressure recordings in 354 adolescents and young adults

OBJECTIVE Little information is available on the early course of hypertension in type 1 diabetes. The aim of our study, therefore, was to document circadian blood pressure profiles in patients with a diabetes duration of up to 20 years and relate daytime and nighttime blood pressure to duration of diabetes, BMI, insulin therapy, and HbA1c. RESEARCH DESIGN AND METHODS Ambulatory profiles of 24-h blood pressure were recorded in 354 pediatric patients with type 1 diabetes (age 14.6 +/- 4.2 years, duration of diabetes 5.6 +/- 5.0 years, follow-up for up to 9 years). A total of 1,011 profiles were available for analysis from patients not receiving antihypertensive medication. RESULTS Although daytime mean systolic pressure was significantly elevated in diabetic subjects (+3.1 mmHg; P < 0.0001), daytime diastolic pressure was not different from from the height- and sex-adjusted normal range (+0.1 mmHg, NS). In contrast, both systolic and diastolic nighttime values were clearly elevated (+7.2 and +4.2 mmHg; P < 0.0001), and nocturnal dipping was reduced (P < 0.0001). Systolic blood pressure was related to overweight in all patients, while diastolic blood pressure was related to metabolic control in young adults. Blood pressure variability was significantly lower in girls compared with boys (P < 0.01). During follow-up, no increase of blood pressure was noted; however, diastolic nocturnal dipping decreased significantly (P < 0.03). Mean daytime blood pressure was significantly related to office blood pressure (r = +0.54 for systolic and r = +0.40 for diastolic pressure); however, hypertension was confirmed by ambulatory blood pressure measurement in only 32% of patients with elevated office blood pressure. CONCLUSIONS During the early course of type 1 diabetes, daytime blood pressure is higher compared with that of healthy control subjects. The elevation of nocturnal values is even more pronounced and nocturnal dipping is reduced. The frequency of white-coat hypertension is high among adolescents with diabetes, and ambulatory blood pressure monitoring avoids unnecessary antihypertensive treatment.

Identification of a SIRT1 mutation in a family with type 1 diabetes.

Type 1 diabetes is caused by autoimmune-mediated β cell destruction leading to insulin deficiency. The histone deacetylase SIRT1 plays an essential role in modulating several age-related diseases. Here we describe a family carrying a mutation in the SIRT1 gene, in which all five affected members developed an autoimmune disorder: four developed type 1 diabetes, and one developed ulcerative colitis. Initially, a 26-year-old man was diagnosed with the typical features of type 1 diabetes, including lean body mass, autoantibodies, T cell reactivity to β cell antigens, and a rapid dependence on insulin. Direct and exome sequencing identified the presence of a T-to-C exchange in exon 1 of SIRT1, corresponding to a leucine-to-proline mutation at residue 107. Expression of SIRT1-L107P in insulin-producing cells resulted in overproduction of nitric oxide, cytokines, and chemokines. These observations identify a role for SIRT1 in human autoimmunity and unveil a monogenic form of type 1 diabetes.

Plasma Levels of MASP-1 and MASP-2 are Elevated in Type 1 Diabetes and Correlate with Glycaemic Control

There is increasing evidence that the complement system plays an important role in diabetes and the development of diabetic vascular complications. In particular, mannan-binding lectin (MBL) levels are elevated in diabetes patients, and diabetes patients with diabetic nephropathy have higher MBL levels than diabetes patients with normal renal function. The MBL-associated serine proteases (MASPs) MASP-1, MASP-2, and MASP-3, and MBL-associated protein MAp44 have not yet been studied in diabetes patients. We therefore measured plasma levels of MASP-1, MASP-2, MASP-3, and MAp44 in 30 children with type 1 diabetes mellitus (T1DM) and 17 matched control subjects, and in 45 adults with T1DM and 31 matched control subjects. MASP-1 and MASP-2 levels were significantly higher in children and adults with T1DM than in their respective control groups, whereas MASP-3 and MAp44 levels did not differ between patients and controls. MASP-1 and MASP-2 levels correlated with HbA1c, and MASP levels decreased when glycaemic control improved. Since MASP-1 and MASP-2 have been shown to directly interact with blood coagulation, elevated levels of these proteins may play a role in the enhanced thrombotic environment and consequent vascular complications in diabetes.

Prevalence of vascular disease in systemic lupus erythematosus compared with type-1 diabetes mellitus: a cross-sectional study of two cohorts.

OBJECTIVES Systemic lupus erythematosus (SLE) is associated with considerable cardiovascular morbidity that has not yet been directly compared with other diseases with known cardiovascular risk. METHODS Two hundred and forty-one patients of the multicentre Swiss SLE cohort study (SSCS) were cross-sectionally assessed for coronary heart disease (CHD), cerebrovascular disease (CVD) and peripheral artery disease (PAD). SLE patients were compared with a cohort of 193 patients with type-1 diabetes mellitus being followed at the University Hospital Basel. A subgroup analysis of 50 age- and sex-matched patients from the University Hospital Basel was performed. RESULTS Of patients within the SSCS 13.3% had one or more vascular events: 8.3% CHD, 5% CVD and 1.2% PAD. In type-1 diabetes mellitus patients, 15% had vascular events: 9.3% CHD, 3.1% CVD and 5.6% PAD. In the matched subgroup, 26% of SLE patients had vascular events (14% CHD) compared with 12% in type-1 DM patients (2% CHD). Cardiovascular risk factors were similar in both groups. Vascular events in SLE patients were associated with age, longer disease duration, dyslipidaemia, and hypertension. CONCLUSION Cardiovascular morbidity in SLE is at least as frequent as in age- and sex-matched type-1 diabetes mellitus patients. Therefore, aggressive screening and management of cardiovascular risk factors should be performed.