Effects of sequential treatment with lixisenatide, insulin glargine, or their combination on meal-related glycaemic excursions, insulin and glucagon secretion, and gastric emptying in patients with type 2 diabetes.

AIM: To examine the glucose-lowering mechanisms of the glucagon-like peptide-1 receptor agonist lixisenatide after two subsequent meals and in combination with basal insulin. MATERIALS AND METHODS: Twenty-eight metformin-treated patients with type 2 diabetes were randomly assigned to treatment sequences with either lixisenatide or insulin glargine alone for 4 weeks, and a combination of both treatments for 4 weeks. Metabolic examinations were performed before and after each treatment period following breakfast and a late lunch 8 hours later. RESULTS: Lixisenatide mainly reduced postprandial glycaemia, while insulin glargine mainly reduced fasting glucose after breakfast (P < 0.05). This was partially preserved after a late lunch (P < 0.05). After breakfast, lixisenatide reduced insulin secretion and glucagon levels significantly. These effects were lost after a late lunch. Insulin glargine did not significantly reduce glucagon or insulin secretion. Gastric emptying was slowed by lixisenatide, but not by insulin glargine after breakfast. After the late lunch, lixisenatide slightly accelerated gastric emptying. CONCLUSIONS: Lixisenatide decelerates gastric emptying after breakfast, thereby reducing glycaemic excursions, insulin secretion and glucagon levels. The glycaemic reduction persists until after a late lunch, despite accelerated gastric emptying. The combination with insulin glargine enhances the glucose-lowering effect because of complementary modes of action.

Prospective External Validation of an Algorithm Predicting Hourly Basal Insulin Infusion Rates from Characteristics of Patients with Type 1 Diabetes Treated with Insulin Pumps.

BACKGROUND: We previously published an algorithm predicting 24 h basal insulin infusion profiles in insulin pump-treated subjects with type 1 diabetes profiles from six subject characteristics. This algorithm was to be externally validated in an independent environment and patient population. METHODS: Thirty-two patients with pump-treated type diabetes were switched to their individually algorithm-derived basal insulin infusion profile, and the appropriateness of fasting glycemic control was scrutinized by means of a supervised 24 h fast. Primary endpoint was appropriate fasting glycemic control according to pre-defined criteria in at least 80% of the cohort. RESULTS: In 24 out of 32 patients switching to the algorithm-derived basal insulin infusion rate and undergoing a 24-h fasting period, appropriate glycemic control was achieved (=75%, lower than the pre-defined threshold of 80%), two patients discontinued the fast due to hyperglycemia, and six finished the fasting period, however, with inappropriate fasting glycemic control (entirely due to hyperglycemic episodes). There were no obvious differences in baseline characteristics between those with appropriate vs. inappropriate fasting glycemic control on the basal insulin infusion rate provided by the algorithm. CONCLUSION: In conclusion, when testing fasting glycemic control with an algorithm-derived individual basal insulin infusion profile during a 24 h fasting period in a cohort unrelated in terms of the hospital environment and catchment area, the success rate was lower than a pre-defined threshold for concluding utility of this algorithm. Therefore, applying this algorithm in order to initiate or optimize basal insulin infusion profiles in type 1 diabetes cannot be generally recommended.

A Prospective, Randomized Trial Testing Different Regimens of Carbohydrate Administration to Prevent Major Reduction in Plasma Glucose Follwing a Standardized Bout of Moderate Physical Activity in Patients with Type 1 Diabetes.

AIM/HYPOTHESIS: It was the aim to prospectively study regimes of "preventive" carbohydrate administration to avoid major reduction in plasma glucose during physical activity. METHODS: 24 patients with type 1 diabetes (age 41±12 years; 11 women, 13 men; BMI 26.5±4.7 kg/m2; HbA1c 9.1±1.5%; insulin dose 0.64±0.22 IU/kg body weight and day) participated in one experiment without physical activity and in three experiments with a 4 km, 60 min hike starting at 2 p.m.. No "preventive" carbohydrates, 2×10 g or 2×20 g carbohydrates (muesli bars) were taken when starting and after 30 min (randomized order). Plasma glucose was determined. RESULTS: Within 30 min after starting physical activity, plasma glucose fell by approximately 70 mg/dl, making additional carbohydrate intake necessary in 70% of the subjects. This drop was not prevented by any regimens of "preventive" carbohydrate intake. After the nadir, plasma glucose rose faster after the 2×20 g carbohydrate regime (the largest amount tested; p=0.0036). With "preventive" administration of carbohydrates, significantly (p<0.05) less additional "therapeutic" carbohydrates needed to be administered in 6 h following the initiation of the hike. CONCLUSIONS/INTERPRETATION: In conclusion, in the setting of 2 h postprandial exercise in type 1 diabetes, preventive carbohydrate supplementation alone will not completely eliminate the risk of brisk falls in plasma glucose concentrations or hypoglycaemic episodes. Else, higher amounts or repeated administration of carbohydrates may be necessary.

Owning a Dog as a Determinant of Physical Activity and Metabolic Control in Patients With Type 1 and Type 2 Diabetes Mellitus.

BACKGROUND/AIMS: Physical activity is recommended for patients with type 1 (T1D) and type 2 diabetes (T2D). We wanted to assess whether owning a dog influences duration or intensity of physical activity and metabolic control of diabetes mellitus. PATIENTS AND METHODS: 143 patients with T1D (age 50±16 y.; BMI 25.7±4.5 kg/m2, HbA1c 8.6±1.6%) and 303 with T2D (age 63±11 y., BMI 33.7±7.3 kg/m2, HbA1c 9.0±1.6%, 232 [76.6%] insulin-treated, 89±61 IU/d), respectively, participated. A standardized questionnaire assessed diabetes history and treatment, details regarding time spent (per week) and intensity (MET, metabolic equivalent of task) of physical activity ("walking the dog" and other activities), anthropometric (BMI) and laboratory measures. RESULTS: 31.5% of T1D 23.1% of T2D patients were dog owners. Dog owners with T1D and T2D diabetes spent 19.0±3.3 and 19.8±2.6 MET.h per week walking the dog, which represented 61.3±5.7 and 62.9±4.9% of their total physical activity. Participants not owning a dog compensated by performing significantly more other activities. Taken together, total physical activity was similar in dog owners with T1D (p=0.80), but higher in dog owners with T2D (30.1±2.8 vs. 18.6±1.4 MET.h per week in those not owning a dog; p=0.0001). Body-mass-index or HbA1c were not significantly different in either patients with T1D or T2D either owning a dog or not. CONCLUSIONS: Owning a dog motivates to a significant amount of physical activity, but this was fully compensated for by other forms of physical activity in (younger) patients with T1D. Even the higher physical activity in dog owners with T2D did not result in improved glycaemic or body weight control.

Prediction of Individual Basal Rate Profiles From Patient Characteristics in Type 1 Diabetes on Insulin Pump Therapy.

BACKGROUND: Basal rate profiles in patients with type 1 diabetes on insulin pump therapy are subject to enormous inter-individual heterogeneity. Tools to predict basal rates based on clinical characteristics may facilitate insulin pump therapy. METHODS: Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy were collected. Basal rate tests were performed over 24 hours. A mathematical algorithm to predict individual basal rate profiles was generated by relating the individual insulin demand to selected clinical characteristics in an exploratory cohort of 170 patients. The predicted insulin pump profiles were validated in a confirmatory cohort of 169 patients. FINDINGS: Basal rates (0.27 ± 0.01 IU.d-1.kg-1) showed circadian variations with peaks corresponding to the "dawn" and "dusk" phenomena. Age, gender, duration of pump treatment, body-mass-index, HbA1c, and triacylglycerol concentrations largely predicted the individual basal insulin demand per day (IU/d; exploratory vs prospective cohorts: r2 = 0.518, P < .0001). Model-predicted and actual basal insulin rates were not different (exploratory cohort: Δ 0.1 (95% CI -0.9; 1.0 U/d; P = .95; prospective cohort: Δ -0.5 (95% CI -1.5; 0.6 IU/d; P = .46). Similarly, precise predictions were possible for each hour of the day. Actual and predicted "dawn" index correlated significantly in the exploratory but not in the confirmatory cohort. INTERPRETATION: Clinical characteristics predict 52% of the variation in individual basal rate profiles, including their diurnal fluctuations. The multivariate regression model can be used to initiate or optimize insulin pump treatment in patients with type 1 diabetes.

Irp2 regulates insulin production through iron-mediated Cdkal1-catalyzed tRNA modification.

Regulation of cellular iron homeostasis is crucial as both iron excess and deficiency cause hematological and neurodegenerative diseases. Here we show that mice lacking iron-regulatory protein 2 (Irp2), a regulator of cellular iron homeostasis, develop diabetes. Irp2 post-transcriptionally regulates the iron-uptake protein transferrin receptor 1 (TfR1) and the iron-storage protein ferritin, and dysregulation of these proteins due to Irp2 loss causes functional iron deficiency in ß cells. This impairs Fe-S cluster biosynthesis, reducing the function of Cdkal1, an Fe-S cluster enzyme that catalyzes methylthiolation of t6A37 in tRNALysUUU to ms2t6A37. As a consequence, lysine codons in proinsulin are misread and proinsulin processing is impaired, reducing insulin content and secretion. Iron normalizes ms2t6A37 and proinsulin lysine incorporation, restoring insulin content and secretion in Irp2-/- ß cells. These studies reveal a previously unidentified link between insulin processing and cellular iron deficiency that may have relevance to type 2 diabetes in humans.

Clinical Predictors of the Need for Further Treatment Escalation in Patients with Type 2 Diabetes on Basal Insulin Therapy - A Retrospective Observational Study.

BACKGROUND/AIMS: The aim of this study was to identify clinical characteristics that distinguish patients who achieve sufficient glycaemic control with basal insulin and oral glucose-lowering medications from those who need treatment intensification. PATIENTS/METHODS: 213 out of 1 042 consecutively hospitalized type 2-diabetic patients were treated with basal insulin/oral agents. After titration to fasting glucose target, in 156 patients (73.2%) continuation of basal insulin treatment was recommended, while in 57 (26.8%), intensification of treatment was necessary. We compared patients' characteristics and plasma glucose profiles between these groups. RESULTS: Patients needing intensified regimens (basal-bolus regimes, premixed insulin ;GLP-1 receptor agonists) had higher initial HbA1c values (87±17 mmol/mol [10.1±1.7%] vs. 80±19 mmol/mol [9.5±1.9%], p=0.028), were more likely to be female (49.1 vs. 25.0%, p=0.0014) and more obese, and required higher basal insulin doses (62±40 vs. 39±27 IU/d, p<0.0001). In both patient groups, basal insulin reduced fasting plasma glucose into the target range (6.6±1.3 vs. 5.7±0.8 mmol/l), however, in those needing treatment intensification, post-breakfast plasma glucose remained substantially higher after basal insulin titration (12.6±2.0 vs.9.4±1.6 mmol/l, p<0.0001). Before hospital discharge, similar plasma glucose profiles were reached in both groups. CONCLUSIONS: Basal insulin therapy can provide satisfactory glucose control in more than 70% of patients with type 2 diabetes. Long diabetes duration, obesity, insulin resistance and female sex indicate a need for further treatment intensification.