Measures Of Beta-cell Function Research Articles

Development of a Diabetes Dietary Quality Index: Reproducibility and Associations with Measures of Insulin Resistance, Beta Cell Function, and Hyperglycemia

Aims: Various dietary risk factors for type 2 diabetes have been identified. A short assessment of dietary patterns related to the risk for type 2 diabetes mellitus may be relevant in clinical practice given the largely preventable nature of the disease. The aim of this study was to investigate the reproducibility of a short food frequency questionnaire based on available knowledge of diabetes-related healthy diets. In addition, we aimed to investigate whether a Diabetes Dietary Quality Index based on this questionnaire was related to metabolic risk factors, including measures of beta cell function and insulin sensitivity. Methods: A short food frequency questionnaire was composed by selecting fourteen questions (representing eight dietary factors) from existing food frequency questionnaires on the basis of their reported relationship with diabetes risk. Healthy participants (N = 176) from a Dutch family study completed the questionnaire and a subgroup (N = 123) completed the questionnaire twice. Reproducible items from the short questionnaire were combined into an index. The association between the Diabetes Dietary Quality index and metabolic risk factors was investigated using multiple linear regression analysis. Measures of beta cell function and insulin sensitivity were derived from a mixed meal test and an euglycemic–hyperinsulinemic and modified hyperglycemic clamp test. Results: Our results show that this new short food frequency questionnaire is reliable (Intraclass Correlations ranged between 0.5 and 0.9). A higher Diabetes Dietary Quality index score was associated with lower 2 h post-meal glucose (β −0.02, SE 0.006, p < 0.05), HbA1c (β −0.07, SE 0.02, p < 0.05), total cholesterol, (β −0.02, SE 0.07, p < 0.05), LDL cholesterol, (β −0.19, SE 0.07, p < 0.05), fasting (β −0.4, SE 0.16, p < 0.05) and post-load insulin, (β −3.9, SE 1.40, p < 0.05) concentrations and the incremental AUC of glucose during MMT (β −1.9, SE 0.97, p < 0.05). The scores obtained for the oral glucose insulin sensitivity-derived mixed meal test were higher in subjects who scored higher on the Diabetes Dietary Quality index (β 0.89, 0.39, p < 0.05). In contrast, we found no significant associations between the Diabetes Dietary Quality index and clamp measures of beta cell function. Conclusions: We identified a questionnaire-derived Diabetes Dietary Quality index that was reproducible and inversely associated with a number of type 2 diabetes mellitus and metabolic risk factors, like 2 h post-meal glucose, Hba1c and LDL, and total cholesterol. Once relative validity has been established, the Diabetes Dietary Quality index could be used by health care professionals to identify individuals with diets adversely related to development of type 2 diabetes.

Four weeks SGLT2 inhibition improves beta cell function and glucose tolerance without affecting muscle free fatty acid or glucose uptake in subjects with type 2 diabetes.

Sodium glucose co-transporter-2 (SGLT2) inhibition lowers glucose levels independently of insulin, leading to reduced insulin secretion and increased lipolysis, resulting in elevated circulating free fatty acids (FFAs). While SGLT2 inhibition improves tissue insulin sensitivity, the increase in circulating FFAs could reduce insulin sensitivity in skeletal muscle and the liver. We aimed to investigate the effects of SGLT2 inhibition on substrate utilization in skeletal muscle and the liver and to measure beta-cell function and glucose tolerance. Thirteen metformin-treated individuals with type 2 diabetes were randomized to once-daily empagliflozin 25 mg or placebo for 4 weeks in a crossover design. Skeletal muscle glucose and FFA uptake together with hepatic tissue FFA uptake were measured using [18F]FDG positron emission tomography/computed tomography (PET/CT) and [11C]palmitate PET/CT. Insulin secretion and action were estimated using the oral minimal model. Empagliflozin did not affect glucose (0.73 ± 0.30 vs. 1.16 ± 0.64, μmol/g/min p = 0.11) or FFA (0.60 ± 0.30 vs. 0.56 ± 0.3, μmol/g/min p = 0.54) uptake in skeletal muscle. FFA uptake in the liver (21.2 ± 10.1 vs. 19 ± 8.8, μmol/100 ml/min p = 0.32) was unaffected. Empagliflozin increased total beta-cell responsivity (20 ± 8 vs. 14 ± 9, 10-9min-1, p < 0.01) and glucose effectiveness (2.6 × 10-2 ± 0.3 × 10-2 vs. 2.4 × 10-2 ± 0.3 × 10-2, dL/kg/min, p = 0.02). Despite improved beta-cell function and glucose tolerance, empagliflozin does not appear to affect skeletal muscle FFA or glucose uptake.

Evidence for C-Peptide as a Validated Surrogate to Predict Clinical Benefits in Trials of Disease-Modifying Therapies for Type 1 Diabetes.

Type 1 diabetes is a chronic autoimmune disease in which destruction of pancreatic beta cells causes life-threatening metabolic dysregulation. Numerous approaches are envisioned for new therapies, but limitations of current clinical outcome measures are significant disincentives to development efforts. C-peptide, a direct byproduct of proinsulin processing, is a quantitative biomarker of beta cell function that is not cleared by the liver and can be measured in the peripheral blood. Studies of quantitative measures of beta cell function have established a predictive relationship between stimulated C-peptide as a measure of beta cell function and clinical benefits. C-peptide levels at diagnosis are often high enough to afford glycemic control benefits associated with protection from end-organ complications of diabetes, and even lower levels offer protection from severe hypoglycemia in type 1 diabetes, as observed in large prospective cohort studies and interventional trials of islet transplantation. These observations support consideration of C-peptide not just as a biomarker of beta cell function, but also as a specific, sensitive, feasible, and clinically meaningful outcome defining beta cell preservation or restoration for clinical trials of disease-modifying therapies. Regulatory acceptance of C-peptide as a validated surrogate for demonstration of efficacy would greatly facilitate development of disease-modifying therapies for type 1 diabetes.

Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes distinguishes markers of disease and C-peptide trajectory

Aims/hypothesisThere is a growing need for markers that could help indicate the decline in beta cell function and recognise the need and efficacy of intervention in type 1 diabetes. Measurements of suitably selected serum markers could potentially provide a non-invasive and easily applicable solution to this challenge. Accordingly, we evaluated a broad panel of proteins previously associated with type 1 diabetes in serum from newly diagnosed individuals during the first year from diagnosis. To uncover associations with beta cell function, comparisons were made between these targeted proteomics measurements and changes in fasting C-peptide levels. To further distinguish proteins linked with the disease status, comparisons were made with measurements of the protein targets in age- and sex-matched autoantibody-negative unaffected family members (UFMs).MethodsSelected reaction monitoring (SRM) mass spectrometry analyses of serum, targeting 85 type 1 diabetes-associated proteins, were made. Sera from individuals diagnosed under 18 years (n=86) were drawn within 6 weeks of diagnosis and at 3, 6 and 12 months afterwards (288 samples in total). The SRM data were compared with fasting C-peptide/glucose data, which was interpreted as a measure of beta cell function. The protein data were further compared with cross-sectional SRM measurements from UFMs (n=194).ResultsEleven proteins had statistically significant associations with fasting C-peptide/glucose. Of these, apolipoprotein L1 and glutathione peroxidase 3 (GPX3) displayed the strongest positive and inverse associations, respectively. Changes in GPX3 levels during the first year after diagnosis indicated future fasting C-peptide/glucose levels. In addition, differences in the levels of 13 proteins were observed between the individuals with type 1 diabetes and the matched UFMs. These included GPX3, transthyretin, prothrombin, apolipoprotein C1 and members of the IGF family.Conclusions/interpretationThe association of several targeted proteins with fasting C-peptide/glucose levels in the first year after diagnosis suggests their connection with the underlying changes accompanying alterations in beta cell function in type 1 diabetes. Moreover, the direction of change in GPX3 during the first year was indicative of subsequent fasting C-peptide/glucose levels, and supports further investigation of this and other serum protein measurements in future studies of beta cell function in type 1 diabetes.Graphical

1094-P: Longitudinal Trajectories of Fasting C-Peptide in Youth-Onset Type 2 Diabetes—The SEARCH for Diabetes in Youth Study

In youth-onset type 2 diabetes (YO-T2D; diabetes diagnosed &amp;lt;20 years-old) loss of glycemic control is more rapid than in adults, partly attributed to accelerated beta cell decline. However, no studies have investigated the potential heterogeneity in the longitudinal trajectories of beta cell function and whether genetic factors might contribute to heterogeneity. We derived longitudinal trajectories of fasting C-peptide (FCP) levels, a surrogate measure of beta cell function, via discrete mixture modeling of repeated measures collected over 15 years of follow-up in youth with YO-T2D (antibody negative and insulin resistant; n=266) from the SEARCH for Diabetes in Youth cohort study. We tested the association between the derived trajectories and T2D genetic risk score (GRS) using a multinomial logistic regression model with adjustment for relevant covariates. A four-trajectory model best fit the data, classifying youth with YO-T2D as having either “initial low FCP and stable over time” (32%), “initial high FCP and slow incline” (8%), “initial high FCP and slow decline” (53%), or “initial very high FCP and rapid decline” (7%) (Figure). T2D GRS was not associated with FCP trajectory membership. These data demonstrate substantial heterogeneity in trajectories of FCP in YO-T2D and suggest that genetic predisposition to T2D is not a significant determinant of this heterogeneity. Disclosure A.Shapiro: None. A.Bellatorre: None. J.M.Stafford: None. A.S.Shah: None. C.Pihoker: None. F.Malik: None. A.D.Liese: None. D.J.Pettitt: None. D.Dabelea: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK127208-01, 1UC4DK108173); Centers for Disease Control and Prevention (U18DP006131, U18DP006133, U18DP006134, U18DP006136, U18DP006138, U18DP006139)

The importance of biomarker development for monitoring type 1 diabetes progression rate and therapeutic responsiveness.

Type 1 diabetes (T1D) is an autoimmune condition of children and adults in which immune cells target insulin-producing pancreatic β-cells for destruction. This results in a chronic inability to regulate blood glucose levels. The natural history of T1D is well-characterized in childhood. Evidence of two or more autoantibodies to the islet antigens insulin, GAD, IA-2 or ZnT8 in early childhood is associated with high risk of developing T1D in the future. Prediction of risk is less clear in adults and, overall, the factors controlling the progression rate from multiple islet autoantibody positivity to onset of symptoms are not fully understood. An anti-CD3 antibody, teplizumab, was recently shown to delay clinical progression to T1D in high-risk individuals including adults and older children. This represents an important proof of concept for those at risk of future T1D. Given their role in risk assessment, islet autoantibodies might appear to be the most obvious biomarkers to monitor efficacy. However, monitoring islet autoantibodies in clinical trials has shown only limited effects, although antibodies to the most recently identified autoantigen, tetraspanin-7, have not yet been studied in this context. Measurements of beta cell function remain fundamental to assessing efficacy and different models have been proposed, but improved biomarkers are required for both progression studies before onset of diabetes and in therapeutic monitoring. In this mini-review, we consider some established and emerging predictive and prognostic biomarkers, including markers of pancreatic function that could be integrated with metabolic markers to generate improved strategies to measure outcomes of therapeutic intervention.

The effect of age on longitudinal measures of beta cell function and insulin sensitivity during the progression of early stage type 1 diabetes

Aim/hypothesisThe risk of progressing from autoantibody positivity to type 1 diabetes is inversely related to age. Separately, whether age influences patterns of C-peptide loss or changes in insulin sensitivity in autoantibody-positive individuals who progress to stage 3 type 1 diabetes is unclear.MethodsBeta cell function and insulin sensitivity were determined by modelling of OGTTs performed in 658 autoantibody-positive participants followed longitudinally in the Diabetes Prevention Trial–Type 1 (DPT-1). In this secondary analysis of DPT-1 data, time trajectories of beta cell function and insulin sensitivity were analysed in participants who progressed to type 1 diabetes (progressors) to address the impact of age on patterns of metabolic progression to diabetes.ResultsAmong the entire DPT-1 cohort, the highest discriminant age for type 1 diabetes risk was 14 years, with participants aged <14 years being twice as likely to progress to type 1 diabetes as those aged ≥14 years. At study entry, beta cell glucose sensitivity was impaired to a similar extent in progressors aged <14 years and progressors aged ≥14 years. From study entry to stage 3 type 1 diabetes onset, beta cell glucose sensitivity and insulin sensitivity declined in both progressor groups. However, there were no significant differences in the yearly rate of decline in either glucose sensitivity (−13.7 [21.2] vs −11.9 [21.5] pmol min−1 m−2 [mmol/l]−1, median [IQR], p=0.52) or insulin sensitivity (−22 [37] vs −14 [40] ml min−1 m−2, median [IQR], p=0.07) between progressors aged <14 years and progressors aged ≥14 years.Conclusions/interpretationOur data indicate that during progression to stage 3 type 1 diabetes, rates of change in declining glucose and insulin sensitivity are not significantly different between progressors aged <14 years and progressors aged ≥14 years. These data suggest there is a predictable course of declining metabolic function during the progression to type 1 diabetes that is not influenced by age.Graphical abstract

Effect of Dietary Supplementation with a Natural Extract of Sclerocarya birrea on Glycemic Metabolism in Subjects with Prediabetes: A Randomized Double-Blind Placebo-Controlled Study.

A randomized, double-blind, placebo-controlled study was conducted with the primary objective of assessing the effect of a natural extract of Sclerocarya birrea on glucose metabolism in subjects with prediabetes. The duration of the study was 90 days. Thirty-three subjects assigned to the experimental group (daily ingestion of 100 mg of the nutraceutical product) and 34 assigned to the placebo group completed the study. There were 36 men and 31 women with a mean age of 32.3 ± 14.1 years. In the area under the curve (AUC) of the oral glucose tolerance test (OGTT), statistically significant decreases in the experimental group at 40 and 90 days as compared with baseline were found, whereas significant changes in the placebo group were not observed. Within-group differences were statistically significant in favor of the experimental group for glucose peak at OGTT, serum insulin, insulin resistance markers, and flow-mediated dilation. Changes in lipid and anthropometric parameters were not observed, although there was a trend for lower cholesterol levels and a decrease in body weight in the experimental group. Decreases in systolic blood pressure were also higher among subjects in the experimental group. This exploratory study confirms the antidiabetic activity of Sclerocarya birrea in prediabetes. Further studies using better measurements of beta-cell function are needed to clarify the underlying mechanisms of the hypoglycemic effect of this natural compound.

Correction to: Validation in the general population of a C-peptide estimate equation to measure beta cell function in recent-onset type 1 diabetes

Authors would like to correct the first name of author Joanne Wang from Joanne to Joanna.

A Single Bout of Premeal Resistance Exercise Improves Postprandial Glucose Metabolism in Obese Men with Prediabetes.

Prediabetes is a major risk factor for type 2 diabetes and cardiovascular diseases. Although resistance exercise (RE) is recommended for individuals with prediabetes, the effects of RE on postprandial glucose metabolism in this population are poorly understood. Therefore, the purpose of this study was to elucidate how RE affects postprandial glucose kinetics, insulin sensitivity, beta cell function, and glucose oxidation during the subsequent meal in sedentary men with obesity and prediabetes. We studied 10 sedentary men with obesity (body mass index, 33 ± 3 kg·m-2) and prediabetes by using a randomized, cross-over study design. After an overnight fast, participants completed either a single bout of whole-body RE (seven exercises, 3 sets of 10-12 repetitions at 80% one-repetition maximum each) or an equivalent period of rest. Participants subsequently completed a mixed meal test in conjunction with an intravenous [6,6-2H2]glucose infusion to determine basal and postprandial glucose rate of appearance (Ra) and disappearance (Rd) from plasma, insulin sensitivity, and the insulinogenic index (a measure of beta cell function). Skeletal muscle biopsies were obtained 90 min postmeal to evaluate pyruvate-supported and maximal mitochondrial respiration. Whole-body carbohydrate oxidation was assessed using indirect calorimetry. RE significantly reduced the postprandial rise in glucose Ra and plasma glucose concentration. Postprandial insulin sensitivity was significantly greater after RE, whereas postprandial plasma insulin concentration was significantly reduced. RE had no effect on the insulinogenic index, postprandial pyruvate respiration, or carbohydrate oxidation. A single bout of RE has beneficial effects on postprandial glucose metabolism in men with obesity and prediabetes by increasing postprandial insulin sensitivity, reducing the postprandial rise in glucose Ra, and reducing postprandial plasma insulin concentration.

Validation in the general population of a C-peptide estimate equation to measure beta cell function in recent-onset type 1 diabetes.

Validation in the general population of a C-peptide estimate equation to measure beta cell function in recent-onset type 1 diabetes.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one. In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community. ClinicalTrials.gov NCT03814915.

362-OR: The Biological Variability of the BETA-2 Score in Islet Transplant Recipients

Background: The BETA-2 score is a validated composite measure of beta cell function in islet transplantation. It is calculated from a fasting sample and lends itself to regular monitoring of islet graft function. To determine whether changes in the BETA-2 score are significant, it is important to understand inherent variability of the score. The aim of this study was to characterize the biological variability (coefficient of variation (CV)) of the BETA-2 score and to define the critical difference (CD) for the score which is the percentage change in score that reflects a significant change in islet function. Methods: Islet transplant recipients with stable graft function were included in this retrospective study. BETA-2 score was calculated weekly over 8 consecutive weeks and the CV was calculated based on the root mean square method. The CD at the 95% confidence limit was calculated as follows: CD = 2.8 x CV. Results: 21 transplant recipients were included of whom 6 were insulin dependent and 15 were insulin independent. These patients also varied in terms of kidney function: 10 subjects with eGFR ≥ 60 (76 ± 14 ml/min/1.73 m2) and 11 subjects with eGFR &amp;lt; 60 (44 ± 10 ml/min/1.73 m2). The CV for all patients was 9.3%, 95% CI [8.7, 10.0]. The CV was similar between insulin independent and insulin dependent subjects (9.0%, 95% CI [8.1, 9.9] vs. 10.2, 95% CI [9.3, 11.1], p=0.5), as well as between subjects with eGFR &amp;gt; 60 vs. eGFR &amp;lt; 60 (8.9%, 95% [8.1,9.8] vs. 9.7%, 95% CI [8.7,10.7], p=0.6). The critical difference for the BETA-2 score was 26.2% for all subjects, 25.1% for insulin independent subjects, 28.5% for insulin dependent subjects, 24.9% for those with eGFR&amp;gt;60, and 27.9% for those with GFR &amp;lt;60. Conclusions: The biological variability of the BETA-2 score appears stable across various clinical scenarios and a minimum difference of 26% between scores appears to constitute a significant change in BETA-2 score. Further analysis including more subjects and a greater range of kidney function is warranted. Disclosure R. Millott: None. R.A. Oram: None. S. Forbes: None. A. Shapiro: Consultant; Self; Viacyte, Inc. P.A. Senior: None. A. Lam: None.

260-LB: Continuous Glucose Monitoring Metrics in Islet Transplant Recipients with Long-Term Insulin Independence

Continuous glucose monitoring (CGM) following islet transplantation (ITx) has shown improved time-in-range, reduced glycemic variability (GV) and hypoglycemia prevention despite subnormal beta-cell function. However, it is unclear if improvement by CGM persists long-term in insulin independent (Ifree) ITx recipients. We evaluated 5 ITx recipients who remained Ifree for &amp;gt;5 years. Subjects completed 7-day non-blinded CGM (Dexcom G4 Platinum). HbA1c, 90min C-peptide, Clarke score, and BETA-2 score (composite measure of beta-cell function after ITx) were obtained. Before ITx, mean age was 47.2±4.0 years, diabetes duration 34.6±9.4 years, HbA1c 7.0±1.2%, insulin/Kg/day 0.44±0.08 units and Clarke score 5 (range 4-7). Subjects received 1-2 islet infusions. Induction immunosuppression consisted of ATG or daclizumab and dual maintenance with sirolimus, tacrolimus or mycophenolate mofetil. At time of CGM, subjects were Ifree and 10.7±3.5 years post-ITx (range 7.7-16.0). Two subjects were on non-insulin adjunct therapies. CGM and metabolic data, BETA-2 and Clarke scores are shown in Table 1. In Ifree ITx recipients with very good long-term graft function (BETA-2 score&amp;gt;15) and restoration of hypoglycemia awareness, CGM shows near-normalization of time-in-range and GV with minimal time-in-hypoglycemia. ITx is a successful long-term cellular therapy for T1D in a selected group of patients. Disclosure D. Baidal: None. A.M. Alvarez Gil: None. N. Padilla: None. C. Ricordi: Advisory Panel; Self; Zone Labs. R. Alejandro: None. Funding National Institute of Allergy and Infectious Diseases/National Institute of Diabetes and Digestive and Kidney Diseases (U01-DK-070460); Immune Tolerance Network (NIS01); Diabetes Research Institute Foundation; State of Florida; University of Miami Clinical and Translational Science Institute (1UL1TR000460); JDRF International (4-2004-361)

Relationship between DXA measured metrics of adiposity and glucose homeostasis; An analysis of the NHANES data.

IntroductionObesity is associated with insulin resistance and type 2 diabetes. Dual-energy X-ray absorptiometry (DXA) is a means of determining body composition and body fat distribution at different sites including whole body and trunk–locations where there tends to be high correlation at an individual level.MethodsWe performed an analysis of DXA-derived metrics of adiposity (truncal fat %,subtotal fat % and total fat %) from the NHANES database and then correlated the findings with markers of insulin resistance. We analyzed the data from DXA scans in NHANES 1999–2004. Homeostatic model assessment-insulin resistance and HOMA-β (beta-cell function) were estimated. Spearman correlation coefficients were calculated (ρ) between HOMA-IR,HOMA-β and different measures of obesity (Waist circumference(in cm), Body Mass Index (kg/m2), truncal fat %, subtotal fat % as well as total fat %) to gauge the relationship between markers of glucose homeostasis and DXA derived metrics of obesity. We also performed logarithmic transformation of HOMA-IR as well as HOMA-β to ensure normality of distribution and to meet the criteria for regression analysis. A forward selection model (by outcome and gender) was performed to predict log transformed insulin resistance (log HOMA-IR) as well as log transformed HOMA-β (log HOMA-β,measure of beta cell function) from age, serum triglycerides, HDL, trunk fat % and the SBP (in both males and females separately), after reviewing the spearman correlation coefficients.ResultsThere were a total of 6147 men and 6369 women who were part of the study cohort. There was a positive correlation between markers of adiposity and log HOMA-IR and log HOMA-β in both males and females.Truncal fat % had the highest nonparametric correlation coefficent with log HOMA-IR among the DXA derived fat% (0.54 in males and 048 in females). In the multivariate analysis, truncal fat % was an independent predictor of logHOMA-IR as well as logHOMA-β. In males, the significant predictors of log HOMA-IR were; age, truncal fat % and HDL cholesterol (Adjusted R square of 0.325 (±0.66), F(3,207) = 34.63, p < .01). In females, the significant predictors of log HOMA-IR were; age, truncal fat %, SBP, Serum triglyceride and HDL cholesterol (Adjusted R square of 0.307 (±0.65),F(5,198) = 18.9, p < .01). In both males and females, the significant predictors of log HOMA-β were; age, and truncal fat % (Males; adjusted R square of 0.25 (±0.63), F (2,208) = 36.4, p < .01, Females; adjusted R square of 0.27 (±0.62), F (2,201) = 38.4, p < .01).ConclusionsBody fat % on DXA is an imaging biomarker for insulin resistance. Incorporating this important information into DXA acquisitions and reporting frameworks may allow for this information to be available to providers who refer patients for these imaging studies.

Predicting and understanding the response to short-term intensive insulin therapy in people with early type 2 diabetes

ObjectiveShort-term intensive insulin therapy (IIT) early in the course of type 2 diabetes acutely improves beta-cell function with long-lasting effects on glycemic control. However, conventional measures cannot determine which patients are better suited for IIT, and little is known about the molecular mechanisms determining response. Therefore, this study aimed to develop a model that could accurately predict the response to IIT and provide insight into molecular mechanisms driving such response in humans. MethodsTwenty-four patients with early type 2 diabetes were assessed at baseline and four weeks after IIT, consisting of basal detemir and premeal insulin aspart. Twelve individuals had a beneficial beta-cell response to IIT (responders) and 12 did not (nonresponders). Beta-cell function was assessed by multiple methods, including Insulin Secretion-Sensitivity Index-2. MicroRNAs (miRNAs) were profiled in plasma samples before and after IIT. The response to IIT was modeled using a machine learning algorithm and potential miRNA-mediated regulatory mechanisms assessed by differential expression, correlation, and functional network analyses (FNA). ResultsBaseline levels of circulating miR-145-5p, miR-29c-3p, and HbA1c accurately (91.7%) predicted the response to IIT (OR = 121 [95% CI: 6.7, 2188.3]). Mechanistically, a previously described regulatory loop between miR-145-5p and miR-483-3p/5p, which controls TP53-mediated apoptosis, appears to also occur in our study population of humans with early type 2 diabetes. In addition, significant (fold change > 2, P < 0.05) longitudinal changes due to IIT in the circulating levels of miR-138-5p, miR-192-5p, miR-195-5p, miR-320b, and let-7a-5p further characterized the responder group and significantly correlated (|r| > 0.4, P < 0.05) with the changes in measures of beta-cell function and insulin sensitivity. FNA identified a network of coordinately/cooperatively regulated miRNA-targeted genes that potentially drives the IIT response through negative regulation of apoptotic processes that underlie beta cell dysfunction and concomitant positive regulation of proliferation. ConclusionsResponses to IIT in people with early type 2 diabetes are associated with characteristic miRNA signatures. This study represents a first step to identify potential responders to IIT (a current limitation in the field) and provides important insight into the pathophysiologic determinants of the reversibility of beta-cell dysfunction.ClinicalTrial.gov identifier: NCT01270789.

Capturing residual beta cell function in type 1 diabetes.

Since the 1970s, C-peptide has been used as a surrogate marker for monitoring the progression of type 1 and type 2 diabetes and to determine the effects of interventions designed to preserve or improve residual beta cell function. C-peptide measurement is a well-established surrogate of residual beta cell activity and of clinical significance as it is associated with HbA1c, risk for microvascular complications and the incidence of hyperglycaemia in longitudinal studies. Measurement of C-peptide after a mixed meal tolerance test is considered the gold standard of measuring beta cell function in type 1 diabetes, but the method is laborious and inconvenient. In this issue of Diabetologia, Wentworth et al ( https://doi.org/10.1007/s00125-018-4722-z ) report an algorithm for estimating C-peptide (CPEST) based on six routine clinical measures. These do not include stimulated C-peptide measurement and outperform other prevailing algorithms for estimating residual beta cell function. Going forward it is very likely that this new algorithm will serve as a simple measure of beta cell function in routine practice and as a more acceptable primary outcome measure in future trials of disease-modifying therapies.

Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables.

Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes.

Glycemic Variability from CGM Correlates with Indices of Glucose Metabolism in Healthy Obesity but Not in Type 2 Diabetes

We evaluated the relationship between measurements of beta cell function and insulin resistance assessed from OGTT and 2-step glucose clamp data with indices of glucose variability (GV) obtained with a continuous glucose monitor (CGM) in obese subjects with and without type 2 diabetes (T2D). 17 healthy obese (OB) (FPG 91 ± 4.9mg/dl and A1c 5.2 ± 0.4%) and 8 age- and weight-matched participants with T2D treated with diet and/or metformin (FPG 131.5 ± 42.8 mg/dl and A1c 6.8 ± 0.8%) wore CGM (Dexcom®) for up to 5 days. EasyGV® software was used to calculate indices of GV: standard deviation (SD), mean amplitude of glycemic excursions (MAGE), J-Index, continuous overlapping net glycemic action (CONGA), and Glycemic Risk Assessment in Diabetes Equation (GRADE). Indices of glucose metabolism were determined with a 2 hour OGTT and a two-step hyperglycemic-euglycemic clamp. Insulin levels during the hyperglycemic-step of clamp (116 ± 126 vs. 40 ± 23 mU/mL) were equal in both groups, while glucose infusion rate (GIR) (7.7 ± 3.1 vs. 3.9 ± 2.4 mg/kg/minutes) during euglycemia was as expected significantly lower in the T2D subjects compared to OB subjects. GV indices (SD, CONGA, J-Index, GRADE) were statistically lower in OB vs. T2D (P&amp;lt;0.05). Insulin Sensitivity Index (ISI0-120) and the insulin secretion-sensitivity index-2 (ISSI-2) were also lower in obese than in T2D subjects (P&amp;lt;0.001). CGM indices (mean, CONGA, J-index, and GRADE) correlated with incremental AUC of insulin during the OGTT, but not for glucose; as well as insulin levels during the hyperglycemic-step (r=0.740, P&amp;lt;0.01), and GIR during the euglycemic step of the clamp (r= -0.733, P&amp;lt;0.01). CGM measures of GV (CONGA, J-Index, and GRADE) were lower in obese compared to T2D subjects. These results suggest that GV indices are surrogate measurements of beta cell function and insulin action in obese subjects, and may help determine progression to T2D. Disclosure A. Elshafie: None. W. Lam: None. L. Parikh: None. E. Sanchez Rangel: None. C.P. Schmidt: None. J. Hwang: None. C.W. Yeckel: None. R. Sherwin: Other Relationship; Self; QuintilesIMS, MannKind Corporation. Research Support; Self; Regeneron Pharmaceuticals, Inc.. Other Relationship; Self; ICON plc. R. Belfort-DeAguiar: Research Support; Self; GlaxoSmithKline plc..

Pulse-Chase Biosynthetic Radiolabeling of Pancreatic Islets to Measure Beta Cell Function.

Pulse-chase radiolabeling of cells with radioactive amino acids is a common method for studying the biosynthesis of proteins. The labeled proteins can then be immunoprecipitated and analyzed by electrophoresis and gel imaging techniques. This chapter presents a protocol for the biosynthetic labeling and immunoprecipitation of pancreatic islet proteins which are known to be affected in disorders such as diabetes, obesity, and metabolic syndrome.