Mixed-meal tolerance test to assess residual beta-cell secretion: Beyond the area-under-curve of plasma C-peptide concentration

Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes affirms markers of disease

AIMS/HYPOTHESIS

While investigating markers for declining beta cell function in type 1 diabetes, we previously demonstrated 11 statistically significant protein associations with fasting C-peptide/glucose ratios in longitudinal serum samples from newly diagnosed (ND) individuals (n=86; 228 samples in total) participating in the INNODIA (Innovative approaches to understanding and arresting type 1 diabetes) study. Furthermore, comparison with protein measurements from age- and sex-matched autoantibody-negative unaffected family members (UFMs, n=194) revealed differences in the serum levels of 13 target proteins. To further evaluate these findings, we analysed longitudinal serum drawn during the first year after diagnosis from a new group of ND individuals subsequently enrolled in the study, together with samples from additional UFMs.

METHODS

To validate the previously reported statistically significant protein associations with type 1 diabetes progression, selected reaction monitoring (SRM) MS analyses were carried out. Sera from individuals diagnosed with type 1 diabetes under the age of 18 years (n=146) were collected within 6 weeks of diagnosis and at 3, 6 and 12 months after diagnosis (560 samples in total). The resulting SRM data were compared with fasting C-peptide/glucose measurements, which were used as a proxy for beta cell function. The protein data were further compared with cross-sectional SRM measurements from age- and sex-matched UFMs (n=272).

RESULTS

Our results confirmed the presence of significant (p<0.05) inverse associations between fasting C-peptide/glucose ratios and peptides from apolipoprotein B-100, apolipoprotein M and glutathione peroxidase 3 (GPX3) in ND individuals. Additionally, we observed consistent differences in the levels of ten of the 13 targeted proteins between individuals with type 1 diabetes and UFMs. These proteins included GPX3, transthyretin, prothrombin, apolipoprotein C1 and afamin.

CONCLUSIONS/INTERPRETATION

The validated results reflect the landscape of biological changes accompanying type 1 diabetes. For example, the association of the targeted apolipoproteins with fasting C-peptide/glucose ratios in the first year after diagnosis is likely to relate to lipid abnormalities observed in individuals with type 1 diabetes, and reiterates the connection of apolipoproteins with the underlying changes accompanying the disease. Further research is needed to explore the clinical value and relevance of these targets.

Plasma proteomics in children with new-onset type 1 diabetes identifies new potential biomarkers of partial remission

Partial remission (PR) occurs in only half of people with new-onset type 1 diabetes (T1D) and corresponds to a transient period characterized by low daily insulin needs, low glycemic fluctuations and increased endogenous insulin secretion. While identification of people with newly-onset T1D and significant residual beta-cell function may foster patient-specific interventions, reliable predictive biomarkers of PR occurrence currently lack. We analyzed the plasma of children with new-onset T1D to identify biomarkers present at diagnosis that predicted PR at 3 months post-diagnosis. We first performed an extensive shotgun proteomic analysis using Liquid Chromatography-Tandem-Mass-Spectrometry (LCMS/MS) on the plasma of 16 children with new-onset T1D and quantified 98 proteins significantly correlating with Insulin-Dose Adjusted glycated hemoglobin A1c score (IDAA1C). We next applied a series of both qualitative and statistical filters and selected protein candidates that were associated to pathophysiological mechanisms related to T1D. Finally, we translationally verified several of the candidates using single-shot targeted proteomic (PRM method) on raw plasma. Taken together, we identified plasma biomarkers present at diagnosis that may predict the occurrence of PR in a single mass-spectrometry run. We believe that the identification of new predictive biomarkers of PR and β-cell function is key to stratify people with new-onset T1D for β-cell preservation therapies.

Atypical Diabetes: What Have We Learned and What Does the Future Hold?

As our understanding of the pathophysiology of diabetes evolves, we increasingly recognize that many patients may have a form of diabetes that does not neatly fit with a diagnosis of either type 1 or type 2 diabetes. The discovery and description of these forms of "atypical diabetes" have led to major contributions to our collective understanding of the basic biology that drives insulin secretion, insulin resistance, and islet autoimmunity. These discoveries now pave the way to a better classification of diabetes based on distinct endotypes. In this review, we highlight the key biological and clinical insights that can be gained from studying known forms of atypical diabetes. Additionally, we provide a framework for identification of patients with atypical diabetes based on their clinical, metabolic, and molecular features. Helpful clinical and genetic resources for evaluating patients suspected of having atypical diabetes are provided. Therefore, appreciating the various endotypes associated with atypical diabetes will enhance diagnostic accuracy and facilitate targeted treatment decisions.

Approaches to Measuring Beta Cell Reserve and Defining Partial Clinical Remission in Paediatric Type 1 Diabetes

CONTEXT

Type 1 diabetes (T1D) results from the autoimmune T-cell mediated destruction of pancreatic beta cells leading to insufficient insulin secretion. At the time of diagnosis of T1D, there is residual beta cell function that declines over the subsequent months to years. Recent interventions have been approved to preserve beta cell function in evolving T1D.

OBJECTIVE

The aim of this review is to summarise the approaches used to assess residual beta cell function in evolving T1D, and to highlight potential future directions.

METHODS

Studies including subjects aged 0 to 18 years were included in this review. The following search terms were used; "(type 1 diabetes) and (partial remission)" and "(type 1 diabetes) and (honeymoon)". References of included studies were reviewed to determine if additional relevant studies were eligible.

RESULTS

There are numerous approaches to quantifying beta cell reserve in evolving T1D. These include c-peptide measurement after a mixed meal or glucagon stimuli, fasting c-peptide, the urinary c-peptide/creatinine ratio, insulin dose-adjusted haemoglobin A1c, and other clinical models to estimate beta cell function. Other biomarkers may have a role, including the proinsulin/c-peptide ratio, cytokines, and microRNA. Studies using thresholds to determine if residual beta cell function is present often differ in values used to define remission.

CONCLUSIONS

As interventions are approved to preserve beta cell function, it will become increasingly necessary to quantify residual beta cell function in research and clinical contexts. In this report, we have highlighted the strengths and limitations of the current approaches.

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

AIMS/HYPOTHESIS

There 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).

METHODS

Selected 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).

RESULTS

Eleven 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/INTERPRETATION

The 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.

Glucose variability in 6-12-month-old healthy infants

Background

Metabolic programming of glucose homeostasis in the first 1,000 days of life may impact lifelong metabolic and cardiovascular health. Continuous glucose monitoring (CGM) devices may help measure the impact of dietary intake on glucose rhythms and metabolism in infants during the complementary feeding period.

Objectives

Demonstrate the feasibility of CGM to measure and quantify glucose variability in response to infant feeding and to evaluate associations between macronutrient meal composition and glucose variability.

Methods

The "FreeStyle Libre Pro^®" device interstitial glucose meter was applied to the anterior thigh of 10 healthy 6-12-month-old infants. Parents recorded food intake, time of feeding, and used daily dairies to record sleep time and duration. Descriptive statistics were employed for food intake, sleep and key glycemic parameters over three full days. Mixed linear models were used to assess glycemic changes.

Results

Mid-day, afternoon, and evening feeds contained >30 g carbohydrate and induced higher 2-h iAUC (3.42, 3.41, and 3.50 mmol/L*h respectively) compared to early and mid-morning feedings with ≤25 g carbohydrates (iAUC 2.72 and 2.81 mmol/L*h, p < 0.05). Early morning and evening milk feedings contained approximately 9 g of fat and induced a longer time to reach maximal glucose value (Tmax; 75 and 68 min, respectively) compared to lower fat feedings (2.9-5.9 g; Tmax range: 34-60 min; p < 0.05). Incremental glucose value at time of food intake (C0) increased significantly from 0.24 ± 0.39 mM in early morning to 1.07 ± 0.57 mM in the evening (p < 0.05). Over the day, 70% of glucose values remained within the normal range (3.5-5.5 mmol/L), 10% were between 5.5-10 mmol/L, and 20% were < 3.5 mmol/L.

Conclusion

Our data support the feasibility of using CGM to measure glucose in 6-12-month-old infants. The observation of possible diurnal glucose variability and typical glucose values may have implications for future studies investigating metabolic adaptation to nutritional intake in early life.

Gene expression signature predicts rate of type 1 diabetes progression

BACKGROUND

Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes.

METHODS

Whole-blood samples were collected as part of the INNODIA study at baseline and 12 months after diagnosis of type 1 diabetes. We used linear mixed-effects modelling on RNA-seq data to identify genes associated with age, sex, or disease progression. Cell-type proportions were estimated from the RNA-seq data using computational deconvolution. Associations to clinical variables were estimated using Pearson's or point-biserial correlation for continuous and dichotomous variables, respectively, using only complete pairs of observations.

FINDINGS

We found that genes and pathways related to innate immunity were downregulated during the first year after diagnosis. Significant associations of the gene expression changes were found with ZnT8A autoantibody positivity. Rate of change in the expression of 16 genes between baseline and 12 months was found to predict the decline in C-peptide at 24 months. Interestingly and consistent with earlier reports, increased B cell levels and decreased neutrophil levels were associated with the rapid progression.

INTERPRETATION

There is considerable individual variation in the rate of progression from appearance of type 1 diabetes-specific autoantibodies to clinical disease. Patient stratification and prediction of disease progression can help in developing more personalised therapeutic strategies for different disease endotypes.

FUNDING

A full list of funding bodies can be found under Acknowledgments.

Glycemic Variability Patterns Strongly Correlate With Partial Remission Status in Children With Newly Diagnosed Type 1 Diabetes

OBJECTIVE

To evaluate whether indexes of glycemic variability may overcome residual β-cell secretion estimates in the longitudinal evaluation of partial remission in a cohort of pediatric patients with new-onset type 1 diabetes.

RESEARCH DESIGN AND METHODS

Values of residual β-cell secretion estimates, clinical parameters (e.g., HbA1c or insulin daily dose), and continuous glucose monitoring (CGM) from 78 pediatric patients with new-onset type 1 diabetes were longitudinally collected during 1 year and cross-sectionally compared. Circadian patterns of CGM metrics were characterized and correlated to remission status using an adjusted mixed-effects model. Patients were clustered based on 46 CGM metrics and clinical parameters and compared using nonparametric ANOVA.

RESULTS

Study participants had a mean (± SD) age of 10.4 (± 3.6) years at diabetes onset, and 65% underwent partial remission at 3 months. β-Cell residual secretion estimates demonstrated weak-to-moderate correlations with clinical parameters and CGM metrics (r2 = 0.05-0.25; P < 0.05). However, CGM metrics strongly correlated with clinical parameters (r2 >0.52; P < 0.05) and were sufficient to distinguish remitters from nonremitters. Also, CGM metrics from remitters displayed specific early morning circadian patterns characterized by increased glycemic stability across days (within 63-140 mg/dL range) and decreased rate of grade II hypoglycemia (P < 0.0001) compared with nonremitters. Thorough CGM analysis allowed the identification of four novel glucotypes (P < 0.001) that segregate patients into subgroups and mirror the evolution of remission after diabetes onset.

CONCLUSIONS

In our pediatric cohort, combination of CGM metrics and clinical parameters unraveled key clinical milestones of glucose homeostasis and remission status during the first year of type 1 diabetes.

An Exploratory Study of Itolizumab on the Preservation of Beta Cell Function in Adults with Recent-Onset Type 1 Diabetes

We conducted a phase I-IIa, randomized, monocentric, double-blind, placebo-controlled clinical trial to evaluate the safety and impact of the combination treatment of Itolizumab and insulin on preserving beta cell function in adults with recent-onset type 1 diabetes. Twelve patients were randomly assigned to three treatment groups, each receiving a different Itolizumab dose (0.4/0.8/1.6 mg/kg body weight, respectively) and a placebo group. All patients received concomitant intensive multiple-dose insulin therapy. Endogenous insulin secretion was assessed by the measurement of C-peptide during the mixed-meal tolerance test. No serious adverse events were reported. No changes in the total daily insulin doses, glycated hemoglobin levels, and stimulated C-peptide were observed between the Itolizumab and placebo groups at 52 weeks. A significant decrease in stimulated C-peptide was observed during the follow-up period (p = 0.012). One subject treated with 1.6 mg of Itolizumab showed a marked increase in the levels of stimulated C-peptide three years after completion of the trial. Taken together, this is the first study to demonstrate that combination treatment with Itolizumab and insulin is safe in humans and does not affect the residual function of beta cells up to 52 weeks. The findings from our study show preliminary evidence that high doses of Itolizumab could potentially arrest the loss of beta cell function in the long term. Further studies with a longer follow-up and larger numbers of patients are envisaged to assess the effect with high dose Itolizumab.

Serum metabolomic biomarkers of perceptual speed in cognitively normal and mildly impaired subjects with fasting state stratification

Cognitive decline is associated with both normal aging and early pathologies leading to dementia. Here we used quantitative profiling of metabolites involved in the regulation of inflammation, vascular function, neuronal function and energy metabolism, including oxylipins, endocannabinoids, bile acids, and steroid hormones to identify metabolic biomarkers of mild cognitive impairment (MCI). Serum samples (n = 212) were obtained from subjects with or without MCI opportunistically collected with incomplete fasting state information. To maximize power and stratify the analysis of metabolite associations with MCI by the fasting state, we developed an algorithm to predict subject fasting state when unknown (n = 73). In non-fasted subjects, linoleic acid and palmitoleoyl ethanolamide levels were positively associated with perceptual speed. In fasted subjects, soluble epoxide hydrolase activity and tauro-alpha-muricholic acid levels were negatively associated with perceptual speed. Other cognitive domains showed associations with bile acid metabolism, but only in the non-fasted state. Importantly, this study shows unique associations between serum metabolites and cognitive function in the fasted and non-fasted states and provides a fasting state prediction algorithm based on measurable metabolites.

Kinetics of C-peptide during mixed meal test and its value for treatment optimization in monogenic diabetes patients

AIM

The mixed meal tolerance test (MMTT) is a gold standard for evaluating beta-cell function. There is limited data on MMTT in monogenic diabetes (MD). Therefore, we aimed to analyze plasma C-peptide (CP) kinetics during MMTT in young MODY and neonatal diabetes patients as a biomarker for beta-cell function.

METHODS

We included 41 patients with MD diagnosis (22 GCK, 8 HNF1A, 3 HNF4A, 4 KCNJ11, 2 ABCC8, 1 INS, 1 KLF11). Standardized 3-hour MMTT with glycemia and plasma CP measurements were performed for all individuals. Pancreatic beta-cell response was assessed by the area under the curve CP (AUC_CP), the baseline CP (CP_Base) and the peak CP (CP_max). Threshold points of CP_Base, CP₉₀, CP_max and CP_AUC were determined from analysis of ROC curves.

RESULTS

GCK diabetes patients had significantly higher AUC_CP, CP_Base and CP_max compared to HNF4A and KCNJ11 patients. In HNF4A, KCNJ11 and ABCC8 patients with all CP levels < 200 pmol/L, the treatment change attempt to sulfonylurea agent was unsuccessful. The ROC analysis showed that CP baseline threshold equal or higher to 133.5 pmol/L could be used to predict successful switch to oral agents.

CONCLUSION

A pretreatment challenge with MMTT might be used to guide the optimal treatment after molecular diagnosis of MD.

Mixed-meal tolerance test to assess residual beta-cell secretion: Beyond the area-under-curve of plasma C-peptide concentration

AIMS

Residual beta-cell secretion in type 1 diabetes is commonly assessed by area-under-curve of plasma C-peptide concentration (AUCCpep ) following mixed-meal tolerance test (MMTT). We aimed to investigate alternative measures of beta-cell responsiveness.

METHODS

We analyzed data from 32 youth (age 7 to 17 years) undergoing MMTT within 6 months of type 1 diabetes diagnosis. We related AUCCpep with (a) validated mechanistic index of postprandial beta-cell responsiveness MI accounting for glucose level during MMTT, and (b) pragmatic marker calculated as baseline plasma C-peptide concentration corrected for baseline plasma glucose concentration.

RESULTS

Postprandial responsiveness MI was correlated with age and BMI SDS (Rs = 0.66 and 0.44, P < 0.01 and P < 0.05) and was more correlated with glycated hemoglobin than AUCCpep (Rs = 0.79, P = 0.04). The pragmatic marker was highly correlated with AUCCpep (Rs = 0.94, P < 0.01).

CONCLUSIONS

Postprandial responsiveness MI may be more relevant to glucose control than AUCCpep . Baseline C-peptide corrected for baseline glucose appears to be a suitable surrogate of AUCCpep if MMTT is not performed.