Alice L. J. Carr

People with type 1 diabetes are recommended to modify insulin dosing and/or carbohydrate intake before, during and after exercise to manage blood glucose levels and prevent hypoglycaemia. An exercise strategy that produces a more consistent glycaemic response may facilitate glycaemic management around exercise, thereby reducing barriers to exercise related to blood glucose concentration, such as fear of hypoglycaemia, for people with type 1 diabetes. The aim of this study was to compare the consistency of the glycaemic response to resistance exercise performed in the morning while fasted vs in the afternoon after eating. Twelve adults with type 1 diabetes, HbA_1c <85 mmol/mol (10.0%), aged 18-55 years and without contraindications to resistance exercise completed six identical resistance exercise sessions, three in the morning while fasted (AM-FAST) and three in the afternoon in a fed state (PM-FED). The six sessions were completed in a random order in an unblinded, crossover trial, supervised at the Physical Activity and Diabetes Laboratory at the University of Alberta. We compared the within-participant standard deviation (wpSD) of the capillary blood glucose response to AM-FAST vs PM-FED sessions. Capillary glucose was measured pre-exercise, immediately post exercise and 30 min after exercise. Continuous glucose monitoring data were analysed from immediately post exercise up to 24 h after exercise. The wpSD of the change in capillary glucose during exercise was lower for AM-FAST (1.0±1.1 mmol/l) than PM-FED (1.5±1.0 mmol/l; p=0.029). There was no difference in the wpSD between conditions during the subsequent 30 min seated recovery (p=0.76). During exercise capillary glucose increased by 1.4±1.9 mmol/l for AM-FAST and decreased by 0.9±2.3 mmol/l for PM-FED (p=0.017). There was a greater percentage of time in hyperglycaemia in the 6 h post-exercise period following AM-FAST vs PM-FED (56.7% [27.2, 67.9] vs 33.0% [22.6, 41.5]; p=0.003, respectively). The glycaemic response to AM-FAST was more consistent and characterised by increases in glucose concentration, whereas the glycaemic response to PM-FED was less consistent and produced decreases in glucose concentration. Performing resistance exercise while fasted may reduce barriers to exercise for people with type 1 diabetes due to a more consistent glycaemic response that is less likely to cause hypoglycaemia during exercise. ClinicalTrials.gov NCT05168488. Dexcom Canada provided in-kind funding in the form of Dexcom G6 transmitters, sensors and receivers. LifeScan Canada provided in-kind funding in capillary glucose testing strips. JEY was supported by a Heart and Stroke Foundation of Canada Alberta New Investigator Award.

Continuous glucose monitoring (CGM) has transformed diabetes management by providing continuous, real-time insights into glucose dynamics, while enhancing the lived experience of individuals with type 1 diabetes. In established type 1 diabetes, CGM-derived measures of glucose management, such as time in range, time above range, time below range and glycaemic variability, have become integral tools to optimise therapy, reduce episodes of hypoglycaemia and guide clinical decision-making. More recently, CGM has emerged as a promising tool to detect early hyperglycaemia and other glucose abnormalities in individuals with early-stage type 1 diabetes, for whom current screening and staging methods, including fasting glucose, HbA _1c and the OGTT, remain limited by episodic sampling, participant burden and variable reproducibility. This review examines the rationale, evidence and practical considerations for integrating CGM into early-stage type 1 diabetes research and clinical frameworks. We discuss its potential to complement existing metabolic and immunological markers, as well as the technical, analytical and regulatory challenges that must be addressed for CGM to serve as a reliable tool for screening, staging and monitoring and as a clinical endpoint in early-stage type 1 diabetes. Graphical Abstract

The Oral Minimal Model (OMM) analysis offers unique measures of glucose–insulin regulation during glucose challenges. However, its manual test-by-test implementation limits scalability in large studies. We introduce the Automated Oral Minimal Model (AOMM), a tool that streamlines and automates the entire OMM workflow while preserving analytical fidelity, enabling efficient batch processing of large datasets. Built on SAAM II software, AOMM was validated against manually extracted results from Sunehag et al ( Obesity (Silver Spring) , 2008), accurately reproducing key parameters such as insulin sensitivity ( Si ) and beta-cell responsivity ( Φ ) with high precision and substantial time savings. AOMM, with its user-friendly interface, facilitates broader application of minimal modeling in research and clinical studies.

Islet transplantation (ITx) is advancing rapidly, with clinical trials of stem cell derived islets demonstrating short-term insulin independence. However, long-term insulin independence may still require multiple infusions. We examined the effects of sequential ITx on portal venous pressure and factors influencing acute pressure changes across 693 intraportal ITx procedures in 298 adults (44% M); who received up to 5 procedures, at the University of Alberta Hospital over 24 years. We assessed acute portal pressure changes per infusion, using linear mixed-effects models to compare sequential pre-infusion pressures to baseline and assess relationships between pressure changes and packed cell volume (PCV), purity, islet dose (IE/kg) and estimated total liver volume (eTLV). Portal pressure transiently increased, similarly, after each infusion by an overall median 2.0 mmHg (IQR 1.0,4.0). PCV exhibited the strongest relationship with change in pressure, with1mmHg increase per 1 mL of PCV, when adjusted for other parameters (Coefficient = 1.0 [95%CI 0.81,1.21];p < 0.0001). Conversely, higher purity and larger eTLV were associated with smaller increases in pressure. A significant interaction term indicated that the effect that PCV has on pressure change may be moderated at higher purities. Our work provides insights from deceased-donor intraportal ITx that can inform the design of future clinical protocols for ITx.

Aims/hypothesis: TCF7L2 variants are the strongest genetic risk factor for type 2 diabetes. In individuals with type 1 diabetes, these variants are associated with a higher C-peptide AUC, a lower glucose AUC during an OGTT, single autoantibody positivity near diagnosis, particularly in individuals older than 12 years of age, and a lower frequency of type 1 diabetes-associated HLA genotypes. Based on initial observations from clinical cohorts, we tested the hypothesis that type 2 diabetes-predisposing TCF7L2 genetic variants are associated with a higher percentage of residual insulin-containing cells (ICI%) in pancreases of donors with type 1 diabetes, by examining genomic data and pancreatic tissue samples from the Network for Pancreatic Organ donors with Diabetes (nPOD) programme. Methods: We analysed nPOD donors with type 1 diabetes (n=110; mean±SD age at type 1 diabetes onset 12.2±7.9 years, mean±SD diabetes duration 15.3±13.7 years, 53% male, 80% non-Hispanic White, 12.7% African American, 7.3% Hispanic) using data pertaining to residual beta cell number; quantified islets containing insulin-positive beta cells in pancreatic tissue sections; and expressed these values as a percentage of the total number of islets from each donor (mean ± SD ICI% 9.8±21.5, range 0–92.2). Results: Donors with a high ICI% (≥5) (n=30; 27%) vs a low ICI% (n=80; 73%) were older at onset (15.3±6.9 vs 11.1±8 years, p=0.013), had a shorter diabetes duration at donor tissue procurement (7.0±7.4 vs 18.5±14.3 years, pp=0.043) and a lower European ancestry score (0.7±0.3 vs 0.9±0.3, p=0.023). After adjustment for age of onset (p=0.105), diabetes duration (p<0.001), BMI z score (p=0.145), sex (p=0.351) and African American race (p=0.053), donors with the TCF7L2 rs7903146 T allele (TC or TT, 45.5%) were 2.93 times (95% CI 1.02, 8.47) more likely to have a high ICI% than those without it (CC) (p=0.047). Conclusions/interpretation: Overall, these data support the presence of a type 1 diabetes endotype associated with a genetic factor that predisposes to type 2 diabetes, with donors in this category exhibiting less severe beta cell loss. It is possible that in these individuals the disease pathogenesis may include mechanisms associated with type 2 diabetes and thus this may provide an explanation for the poor response to immunotherapies to prevent type 1 diabetes or its progression in a subset of individuals. If so, strategies that target both type 1 diabetes and type 2 diabetes-associated factors when they are present may increase the success of prevention and treatment in these individuals. Graphical

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. Graphical abstract

C-peptide declines in type 1 diabetes, although many long-duration patients retain low, but detectable levels. Histological analyses confirm that β-cells can remain following type 1 diabetes onset. We explored the trends observed in C-peptide decline in the UK Genetic Resource Investigating Diabetes (UK GRID) cohort (N = 4,079), with β-cell loss in pancreas donors from the network for Pancreatic Organ donors with Diabetes (nPOD) biobank and the Exeter Archival Diabetes Biobank (EADB) (combined N = 235), stratified by recently reported age at diagnosis endotypes (<7, 7–12, ≥13 years) across increasing diabetes durations. The proportion of individuals with detectable C-peptide declined beyond the first year after diagnosis, but this was most marked in the youngest age group (<1-year duration: age <7 years: 18 of 20 [90%], 7–12 years: 107 of 110 [97%], ≥13 years: 58 of 61 [95%] vs. 1–5 years postdiagnosis: <7 years: 172 of 522 [33%], 7–12 years: 604 of 995 [61%], ≥13 years: 225 of 289 [78%]). A similar profile was observed in β-cell loss, with those diagnosed at younger ages experiencing more rapid loss of islets containing insulin-positive (insulin+) β-cells <1 year postdiagnosis: age <7 years: 23 of 26 (88%), 7–12 years: 32 of 33 (97%), ≥13 years: 22 of 25 (88%) vs. 1–5 years postdiagnosis: <7 years: 1 of 12 (8.3%), 7–12 years: 7 of 13 (54%), ≥13 years: 7 of 8 (88%). These data should be considered in the planning and interpretation of intervention trials designed to promote β-cell retention and function.

Context High-residual C-peptide in longer-duration type 1 diabetes (T1D) is associated with fewer hypoglycemic events and reduced glycemic variability. Little is known about the impact of C-peptide close to diagnosis. Objective Using continuous glucose monitoring (CGM) data from a study of newly diagnosed adults with T1D, we aimed to explore if variation in C-peptide close to diagnosis influenced glycemic variability and risk of hypoglycemia. Methods We studied newly diagnosed adults with T1D who wore a Dexcom G4 CGM for 7 days as part of the Exercise in Type 1 Diabetes (EXTOD) study. We examined the relationship between peak stimulated C-peptide and glycemic metrics of variability and hypoglycemia for 36 CGM traces from 23 participants. Results For every 100 pmol/L-increase in peak C-peptide, the percentage of time spent in the range 3.9 to 10 mmol/L increased by 2.4% (95% CI, 0.5-4.3), P = .01) with a reduction in time spent at level 1 hyperglycemia (> 10 mmol/L) and level 2 hyperglycemia (> 13.9 mmol/L) by 2.6% (95% CI, –4.9 to –0.4, P = .02) and 1.3% (95% CI, –2.7 to –0.006, P = .04), respectively. Glucose levels were on average lower by 0.19 mmol/L (95% CI, –0.4 to 0.02, P = .06) and SD reduced by 0.14 (95% CI, –0.3 to –0.02, P = .02). Hypoglycemia was not common in this group and no association was observed between time spent in hypoglycemia (P = .97) or hypoglycemic risk (P = .72). There was no association between peak C-peptide and insulin dose–adjusted glycated hemoglobin A_1c (P = .45). Conclusion C-peptide is associated with time spent in the normal glucose range and with less hyperglycemia, but not risk of hypoglycemia in newly diagnosed people with T1D.

The year 2021 marks the centennial of Banting and Best’s landmark description of the discovery of insulin. This discovery and insulin’s rapid clinical deployment effectively transformed type 1 diabetes from a fatal diagnosis into a medically manageable chronic condition. In this Review, we describe key accomplishments leading to and building on this momentous occasion in medical history, including advancements in our understanding of the role of insulin in diabetes pathophysiology, the molecular characterization of insulin and the clinical use of insulin. Achievements are also viewed through the lens of patients impacted by insulin therapy and the evolution of insulin pharmacokinetics and delivery over the past 100 years. Finally, we reflect on the future of insulin therapy and diabetes treatment, as well as challenges to be addressed moving forward, so that the full potential of this transformative discovery may be realized.