Circulating C-Peptide Levels in Living Children and Young People and Pancreatic β-Cell Loss in Pancreas Donors Across Type 1 Diabetes Disease Duration

Integrated histopathology of the human pancreas throughout stages of type 1 diabetes progression

Type 1 diabetes (T1D) is a progressive autoimmune condition that culminates in the loss of insulin-producing beta cells. Pancreatic histopathology provides essential insights into disease initiation and progression yet an integrated perspective of in situ pathogenic processes is lacking due to limited sample availability, the dispersed nature of anatomical lesions, and often restricted analytical dimensionality. Here, we combined multiplexed immunostaining, high-magnification whole-slide imaging, digital pathology, and semi-automated image analysis strategies to interrogate pancreatic tail and head regions obtained from organ donors across T1D stages including at-risk and at-onset cases. Deconvolution of architectural features, endocrine cell composition, immune cell burden, and spatial relations of ∼25,000 islets revealed a series of novel histopathological correlates especially in the prodromal disease stage preceding clinical T1D. Altogether, our comprehensive "single-islet" analyses permit the reconstruction of a revised natural T1D history with implications for further histopathological investigations, considerations of pathogenetic modalities, and therapeutic interventions.

Are Trends in Economic Modeling of Pediatric Diabetes Mellitus up to Date with the Clinical Practice Guidelines and the Latest Scientific Findings?

Background: Modeling techniques in the field of pediatrics present unique challenges beyond traditional model limitations, and sometimes difficulties in faithfully simulating the condition's evolution over time. Objective: This study aimed to identify whether economic modeling approaches in diabetes in pediatric patients align with the recommendations of clinical practice guidelines and the latest scientific evidence. Methods: A literature review was performed in March 2023 to identify modeling-based economic evaluations in diabetes in pediatric patients. Data were extracted and synthesized from eligible studies. Clinical practice guidelines for diabetes were gathered to compare their alignment with modeling strategies. Two endocrinology specialists provided insights on the latest findings in diabetes that are not yet included in the guidelines. A multidisciplinary group of experts agreed on the relevant themes to conduct the comparative analysis: parameter informing on glycemic control, diabetic ketoacidosis/hypoglycemia, C-peptide as prognostic biomarker, metabolic memory, age at diagnosis, socioeconomic status, pediatric-specific sources of risk equations, and pediatric-specific sources of utilities/disutilities. Results: Nineteen modeling-based studies (7 de novo, 12 predesigned models) and 34 guidelines were selected. Hemoglobin A1c was the main parameter to model the glycemic control; however, guidelines recommend the usage of complementary measures (eg, time in range) which are not included in economic models. Eight models included diabetic ketoacidosis (42.1%), 16 included hypoglycemia (84.2%), 2 included C-peptide (1 of those as prognostic factor) (10.5%) and 1 included legacy effect (5.3%). Neither guidelines nor models included recent findings, such as age at diagnosis or socioeconomic status, as prognostic factors. The lack of pediatric-specific sources for risk equations and utility/disutility values were additional limitations. Discussion: Economic models designed for assessing interventions in diabetes in pediatric patients should be based on pediatric-specific data and include novel adjuvant glucose-monitoring metrics and latest evidence on prognostic factors (C-peptide, legacy effect, age at diagnosis, socioeconomic status) to provide a more faithful reflection of the disease. Conclusions: Economic models represent useful tools to inform decision making. However, further research assessing the gaps is needed to enhance evidence-based health economic modeling that best represents reality.

Relationship Between C-Peptide Levels, Clinical Features, and Serum Data in a Brazilian Type 1 Diabetes Population with Large Variations in Genomic Ancestry

Type 1 diabetes (T1D) is a chronic disease characterized by the immune-mediated destruction of the pancreatic beta cells responsible for insulin production. The secreted insulin and C-peptide are equimolar. Due to its longer half-life, C-peptide has become a safer means of assessing the pancreatic reserve. C-peptide levels were evaluated in a population of patients with T1D, focusing on the relationship between this variable and other factors. In addition, the influence of C-peptide on metabolic control and microvascular complications was investigated. This cross-sectional study included 95 patients who had been diagnosed with T1D at least five years earlier. These patients were evaluated using a clinical demographic survey, anthropometric data, laboratory tests, and fundoscopy. This study showed that 29.5% of patients had residual insulin secretion, which correlated directly with their age at diagnosis. No statistically significant differences in metabolic control or microvascular complications were observed between the C-peptide level groups. In addition, our results indicate that ancestry does not influence the persistence of residual C-peptide function in our highly mixed population. It is recommended that future research consider incorporating new variables, such as HLA and pancreatic autoimmunity, as factors that may influence residual β-cell function.

The Predictive Potential of C-Peptide in Differentiating Type 1 Diabetes From Type 2 Diabetes in an Outpatient Population in Abu Dhabi

PURPOSE

We aimed to investigate the predictive potential of plasma connecting peptide (C-peptide) in differentiating type 1 diabetes (T1D) from type 2 diabetes (T2D) and to inform evidence-based diabetes classification criteria.

METHODS

A retrospective review was performed of all the patients with diabetes visiting an outpatient diabetology, endocrinology, general practice and family medicine tertiary health care center between January 2016 and December 2021.

FINDINGS

Two hundred twelve individuals with diabetes were included, 85 (44.8%) with T1D and 127 (55.2%) with T2D. Mean (SD) age at diagnosis was 35.9 (15.1) years, and 112 (52.8%) men. Median (interquartile range [IQR]) duration of diabetes was 3.8 (3.0-4.5) years (T1D, 3.9 [3.5-4.6]; T2D, 3.4 [2.4-4.4]; P = 0.001). Body mass index was <18.5 kg/m2 in 5 (2.5%) individuals (T1D, 5; T2D, none), 18.5 to <25 kg/m2 in 57 (28.5%) (T1D, 32; T2D, 25), 25 to <30 kg/m2 in 58 (29%) (T1D, 28; T2D, 30), and >30 kg/m2 in 80 (40.0%) (T1D, 20; T2D, 60). Median (IQR) glycosylated hemoglobin was 7.4% (6.7%-8.5%) (T1D, 8.3% [7.2%-9.9%]; T2D, 7% [6.3%-7.6%]; P = 0.0001). Median (IQR) C-peptide concentration was 0.59 nmol/L (0.01-1.14 nmol/L) (T1D, 0.01 nmol/L [0.003-0.05 nmol/L]; T2D, 1.03 nmol/L [0.70-1.44 nmol/L]; P = 0.0001). C-peptide concentration of ≤0.16 nmol/L showed 92.9% sensitivity, 1-specificity of 2.4%, and AUC of 97.2% (CI, 94.7%-99.6%; P = 0.0001) in differentiating T1D from T2D.

IMPLICATIONS

To our knowledge, this is the first study in the Middle East and North Africa region highlighting the role of C-peptide in diabetes classification. The estimated cutoff point for C-peptide concentration (≤0.16 nmol/L) will certainly help in accurately classifying the T1D and will rule out the routine clinical judgmental approaches in the region, especially in those scenarios and periods where it is always difficult to diagnose the diabetes type. Quantifying the cutoff for C-peptide is among the vital strengths of this study that will provide a better treatment plan in diabetes care management. Also, we evaluated concomitant glucose levels to rule out the phenomenon of falsely low C-peptide values in the setting of hypoglycemia or severe glucose toxicity. Based on our findings, C-peptide testing could be included in postulating an evidence-based guideline that differentiates T1D from T2D. Despite this, our study has some limitations, including the selection bias due to the retrospective design and low C-peptide levels could be indicative of low pancreatic reserves due to other causes or long-standing T2D, and quantifying these reasons requires additional resources and time.

Early Conversion of Intensive Insulin Therapy to IDegLira Demonstrates Higher Efficacy and Safety in Reducing Fasting Blood Glucose and HbA1c in T2DM Patients

Background

A short-term insulin intensive therapy is an important method used in clinical practice to control blood glucose, and a scientific post-treatment plan is key to long-term blood glucose stability control. This study aimed to investigate efficacy and safety of early conversion of intensive insulin therapy to IDegLira in T2DM patients.

Methods

This study was a prospective study, involving 80 T2DM patients finally. Patients were firstly treated with insulin for intensified therapy (Pre-IDegLira group), then switched to insulin degludec and liraglutide (IDegLira) for 3 months (IDegLira-3 months group). Data including HbA1c, fasting blood glucose, fasting C-peptide, weight, insulin dosage, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were analyzed. Correlations between fasting blood glucose and other parameters were evaluated with Pearson correlation analysis.

Results

IDegLira early conversion significantly reduced fasting blood glucose (p<0.001), weight (p=0.015), and insulin dosage (p=0.001) of T2DM patients compared to those of Pre-IDegLira group. HbA1c level was remarkably lower in T2DM patients underwent IDegLira early conversion compared to that in Pre-IDegLira group (p<0.001), with HbA1c <7% proportion of 73.75% (59/80). IDegLira early conversion significantly downregulated levels of TC (p<0.001), TG (p<0.001), LDL-C (p<0.001), and upregulated HDL-C level (p=0.017) of T2DM patients, compared to those in Pre-IDegLira group. IDegLira early conversion markedly reduced ALT (p<0.001) and AST (p=0.002) levels of T2DM patients compared to those in Pre-IDegLira group. IDegLira early conversion demonstrated a positive correlation between fasting blood glucose and HbA1c (r=0.531, p<0.001) or TG level (r=0.336, p=0.002) in T2DM patients.

Conclusion

Early conversion of intensive insulin therapy to IDegLira effectively reduced fasting blood glucose and HbA1c in T2DM patients with higher safety.

The INNODIA Type 1 Diabetes Natural History Study: a European cohort of newly diagnosed children, adolescents and adults

AIMS/HYPOTHESIS

Type 1 diabetes is an heterogenous condition. Characterising factors explaining differences in an individual's clinical course and treatment response will have important clinical and research implications. Our aim was to explore type 1 diabetes heterogeneity, as assessed by clinical characteristics, autoantibodies, beta cell function and glycaemic outcomes, during the first 12 months from diagnosis, and how it relates to age at diagnosis.

METHODS

Data were collected from the large INNODIA cohort of individuals (aged 1.0-45.0 years) newly diagnosed with type 1 diabetes, followed 3 monthly, to assess clinical characteristics, C-peptide, HbA1c and diabetes-associated antibodies, and their changes, during the first 12 months from diagnosis, across three age groups: <10 years; 10-17 years; and ≥18 years.

RESULTS

The study population included 649 individuals (57.3% male; age 12.1±8.3 years), 96.9% of whom were positive for one or more diabetes-related antibodies. Baseline (IQR) fasting C-peptide was 242.0 (139.0-382.0) pmol/l (AUC 749.3 [466.2-1106.1] pmol/l × min), with levels increasing with age (p<0.001). Over time, C-peptide remained lower in participants aged <10 years but it declined in all age groups. In parallel, glucose levels progressively increased. Lower baseline fasting C-peptide, BMI SD score and presence of diabetic ketoacidosis at diagnosis were associated with lower stimulated C-peptide over time. HbA1c decreased during the first 3 months (p<0.001), whereas insulin requirement increased from 3 months post diagnosis (p<0.001).

CONCLUSIONS/INTERPRETATION

In this large cohort with newly diagnosed type 1 diabetes, we identified age-related differences in clinical and biochemical variables. Of note, C-peptide was lower in younger children but there were no main age differences in its rate of decline.

Insulitis in human type 1 diabetes: lessons from an enigmatic lesion

Type 1 diabetes is caused by a deficiency of insulin secretion which has been considered traditionally as the outcome of a precipitous decline in the viability of β-cells in the islets of Langerhans, brought about by autoimmune-mediated attack. Consistent with this, various classes of lymphocyte, as well as cells of the innate immune system have been found in association with islets during disease progression. However, analysis of human pancreas from subjects with type 1 diabetes has revealed that insulitis is often less intense than in equivalent animal models of the disease and can affect many fewer islets than expected, at disease onset. This is especially true in subjects developing type 1 diabetes in, or beyond, their teenage years. Such studies imply that both the phenotype and the number of immune cells present within insulitic lesions can vary among individuals in an age-dependent manner. Additionally, the influent lymphocytes are often mainly arrayed peripherally around islets rather than gaining direct access to the endocrine cell core. Thus, insulitis remains an enigmatic phenomenon in human pancreas and this review seeks to explore the current understanding of its likely role in the progression of type 1 diabetes.

Type 1 diabetes in the pancreas: A histological perspective

AIMS

This review aims to introduce research in the pancreas to a broader audience. The pancreas is a heterocrine gland residing deep within our abdominal cavity. It is the home to our islets, which play a pivotal role in regulating metabolic homeostasis. Due to its structure and location, it is an impossible organ to study, in molecular detail, in living humans, and yet, understanding the pancreas is critical if we aim to characterise the immunopathology of type 1 diabetes (T1D) and one day prevent the triggering of the autoimmune attack associated with ß-cell demise.

METHODS

Over a 100 years ago, we began studying pancreatic histology using cadaveric samples and clever adaptations to microscopes. As histologists, some may say nothing much has changed. Nevertheless, our microscopes can now interrogate multiple proteins at molecular resolution. Images of pancreas sections are no longer constrained to a single field of view and can capture a thousands and thousands of cells. AI-image-analysis packages can analyse these massive data sets offering breakthrough findings.

CONCLUSION

This narrative review will provide an overview of pancreatic anatomy, and the importance of research focused on the pancreas in T1D. It will range from histological breakthroughs to briefly discussing the challenges associated with characterising the organ. I shall briefly introduce a selection of the available global biobanks and touch on the distinct pancreatic endotypes that differ immunologically and in ß-cell behaviour. Finally, I will introduce the idea of developing a collaborative tool aimed at developing a cohesive framework for characterising heterogeneity and stratifying endotypes in T1D more readily.

Quantifying beta cell function in the preclinical stages of type 1 diabetes

Clinically symptomatic type 1 diabetes (stage 3 type 1 diabetes) is preceded by a pre-symptomatic phase, characterised by progressive loss of functional beta cell mass after the onset of islet autoimmunity, with (stage 2) or without (stage 1) measurable changes in glucose profile during an OGTT. Identifying metabolic tests that can longitudinally track changes in beta cell function is of pivotal importance to track disease progression and measure the effect of disease-modifying interventions. In this review we describe the metabolic changes that occur in the early pre-symptomatic stages of type 1 diabetes with respect to both insulin secretion and insulin sensitivity, as well as the measurable outcomes that can be derived from the available tests. We also discuss the use of metabolic modelling to identify insulin secretion and sensitivity, and the measurable changes during dynamic tests such as the OGTT. Finally, we review the role of risk indices and minimally invasive measures such as those derived from the use of continuous glucose monitoring.

Pediatric Type 1 Diabetes: Is Age at Onset a Determining Factor in Advanced Hybrid Closed-Loop Insulin Therapy?

BACKGROUND

The integration of continuous glucose monitoring systems with insulin infusion pumps has shown improved glycemic control, with improvements in hyperglycemia, hypoglycemia, Hb1Ac, and greater autonomy in daily life. These have been most studied in adults and there are currently not many articles published in the pediatric population that establish their correlation with age of debut.

METHODS

Prospective, single-study. A total of 28 patients (mean age 12 ± 2.43 years, 57% male, duration of diabetes 7.84 ± 2.46 years) were included and divided into two groups according to age at T1D onset (≤4 years and >4 years). Follow-up for 3 months, with glucometric variables extracted at different cut-off points after the start of the closed-loop (baseline, 1 month, 3 months).

RESULTS

Significant improvement was evidenced at 1 month and 3 months after closed-loop system implantation, with better glycemic control in the older age group at baseline at TIR (74.06% ± 6.37% vs. 80.33% ± 7.49% at 1 month, p < 0.003; 71.87% ± 6.58% vs. 78.75% ± 5.94% at 3 months, p < 0.009), TAR1 (18.25% ± 4.54% vs. 14.33% ± 5.74% at 1 month, p < 0.006; 19.87% ± 5.15% vs. 14.67% ± 4. 36% at 3 months, p < 0.009) and TAR2 (4.75% ± 2.67% vs. 2.75% ± 1.96% at 1 month, p = 0.0307; 5.40% ± 2.85% vs. 3% ± 2.45% at 3 months, p < 0.027).

CONCLUSIONS

the use of automated systems such as the MiniMedTM780G system brings glucometric results closer to those recommended by consensus, especially in age at T1D onset >4 years. However, the management in pediatrics continues to be a challenge even after the implementation of these systems, especially in terms of hyperglycemia and glycemic variability.

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review

BACKGROUND

Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification.

METHODS

To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument.

RESULTS

We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings.

CONCLUSIONS

While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

Islet cells in human type 1 diabetes: from recent advances to novel therapies - a symposium-based roadmap for future research

There is a growing understanding that the early phases of type 1 diabetes (T1D) are characterised by a deleterious dialogue between the pancreatic beta cells and the immune system. This, combined with the urgent need to better translate this growing knowledge into novel therapies, provided the background for the JDRF-DiabetesUK-INNODIA-nPOD symposium entitled 'Islet cells in human T1D: from recent advances to novel therapies', which took place in Stockholm, Sweden, in September 2022. We provide in this article an overview of the main themes addressed in the symposium, pointing to both promising conclusions and key unmet needs that remain to be addressed in order to achieve better approaches to prevent or reverse T1D.

Type 1 Diabetes Prevention: a systematic review of studies testing disease-modifying therapies and features linked to treatment response

Background

Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Efforts to prevent T1D have focused on modulating immune responses and supporting beta cell health; however, heterogeneity in disease progression and responses to therapies have made these efforts difficult to translate to clinical practice, highlighting the need for precision medicine approaches to T1D prevention.

Methods

To understand the current state of knowledge regarding precision approaches to T1D prevention, we performed a systematic review of randomized-controlled trials from the past 25 years testing disease-modifying therapies in T1D and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument.

Results

We identified 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss in individuals at disease onset. Seventeen agents tested, mostly immunotherapies, showed benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employed precision analyses to assess features linked to treatment response. Age, measures of beta cell function and immune phenotypes were most frequently tested. However, analyses were typically not prespecified, with inconsistent methods reporting, and tended to report positive findings.

Conclusions

While the quality of prevention and intervention trials was overall high, low quality of precision analyses made it difficult to draw meaningful conclusions that inform clinical practice. Thus, prespecified precision analyses should be incorporated into the design of future studies and reported in full to facilitate precision medicine approaches to T1D prevention.

Plain Language Summary

Type 1 diabetes (T1D) results from the destruction of insulin-producing cells in the pancreas, necessitating lifelong insulin dependence. T1D prevention remains an elusive goal, largely due to immense variability in disease progression. Agents tested to date in clinical trials work in a subset of individuals, highlighting the need for precision medicine approaches to prevention. We systematically reviewed clinical trials of disease-modifying therapy in T1D. While age, measures of beta cell function, and immune phenotypes were most commonly identified as factors that influenced treatment response, the overall quality of these studies was low. This review reveals an important need to proactively design clinical trials with well-defined analyses to ensure that results can be interpreted and applied to clinical practice.

A perspective on treating type 1 diabetes mellitus before insulin is needed

Type 1 diabetes mellitus (T1DM) is a progressive autoimmune disease that starts long before a clinical diagnosis is made. The American Diabetes Association recognizes three stages: stage 1 (normoglycaemic and positive for autoantibodies to β-cell antigens); stage 2 (asymptomatic with dysglycaemia); and stage 3, which is defined by glucose levels consistent with the definition of diabetes mellitus. This Perspective focuses on the management of the proportion of individuals with early stage 3 T1DM who do not immediately require insulin; a stage we propose should be termed stage 3a. To date, this period of non-insulin-dependent T1DM has been largely unrecognized. Importantly, it represents a window of opportunity for intervention, as remaining at this stage might delay the need for insulin by months or years. Extending the insulin-free period and/or avoiding unnecessary insulin therapy are important goals, as there is no risk of hypoglycaemia during this period and the adherence burden on patients of glycaemic monitoring and daily adjustments for diet and exercise is substantially reduced. Recognizing the pressing need for guidance on adequate management of children and adults with stage 3a T1DM, we present our perspective on the subject, which needs to be tested in formal and adequately powered clinical trials.

Precision medicine in type 1 diabetes

First envisioned by early diabetes clinicians, a person-centred approach to care was an aspirational goal that aimed to match insulin therapy to each individual's unique requirements. In the 100 years since the discovery of insulin, this goal has evolved to include personalised approaches to type 1 diabetes diagnosis, treatment, prevention and prediction. These advances have been facilitated by the recognition of type 1 diabetes as an autoimmune disease and by advances in our understanding of diabetes pathophysiology, genetics and natural history, which have occurred in parallel with advancements in insulin delivery, glucose monitoring and tools for self-management. In this review, we discuss how these personalised approaches have improved diabetes care and how improved understanding of pathogenesis and human biology might inform precision medicine in the future.

Beta cell and immune cell interactions in autoimmune type 1 diabetes: How they meet and talk to each other

Background

Scope of review

Major conclusions