Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease marked by the destruction of pancreatic β-cells, resulting in lifelong dependence on exogenous insulin. Despite advances in insulin delivery and glucose monitoring technologies, patients remain at risk for acute and long-term complications, underscoring the need for curative strategies. Gene therapy and gene-editing technologies are emerging as transformative approaches capable of restoring β-cell function, modulating immune responses and potentially achieving durable remission. This review synthesizes basic science foundations and clinical trial evidence, focusing on five key protocols (NCT03162237, NCT05210530, NCT05241444, NCT05565248 and NCT06938334). Strategies include immune modulation (PD-L1, FOXP3), β-cell replacement (CRISPR-edited progenitors, xenotransplantation) and combination approaches. Early-phase clinical trials have demonstrated feasibility and safety; however, long-term efficacy, durability and scalability remain uncertain. Critical challenges include potential off-target effects in CRISPR editing, risks of insertional mutagenesis, safety concerns in xenotransplantation and achieving a balance between immune tolerance and protective immunity. Future directions emphasize combination therapies, personalized medicine and next-generation editing tools such as base and prime editing. Together, these efforts represent a paradigm shift from symptomatic insulin replacement toward curative interventions, while highlighting the considerable translational hurdles that must be overcome before routine clinical application.

Two faces of autoimmune hyperinsulinemia: contrasting Type B insulin resistance syndrome and exogenous insulin antibody syndrome.

Emerging modalities in drug development including adeno-associated virus (AAV) and other viral-mediated gene therapy, targeted protein degraders, oligonucleotide, and chimeric antigen receptor-T cell (CAR-T) therapies require updated approaches in strategy and context for meaningful human carcinogenicity risk assessment. This may involve, but is not be limited to, traditional genetic toxicology and rodent bioassays. Speakers provided unique perspectives on these topics as well as an applicable and real-world case study that interrogated whether rat mammary gland cell proliferation was a useful tool with which to evaluate the carcinogenic potential of exogenous insulin.

BACKGROUNDSimultaneous pancreas-kidney transplantation (SPKT), an established treatment for patients with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) and end-stage renal disease (ESRD), provides metabolic stabilization and improved survival. Although perioperative glycemic control is crucial for graft viability; intraoperative management remains understudied, and standardized phase-specific protocols are lacking.AIMTo explore the feasibility, safety, and immediate outcomes of a six-phase intraoperative glycemic control algorithm for SPKT.METHODSThis retrospective case series included 11 patients with T1DM or T2DM and ESRD who underwent SPKT at a quaternary care center between January 2024 and May 2025. All patients were managed using a six-phase institutional glycemic control algorithm that maintains intraoperative blood glucose levels within predefined targets. Data on clinical, metabolic, surgical variables; complications; and early outcomes were collected.RESULTSIn most cases, intraoperative blood glucose levels were maintained within target ranges; however variations were observed [range: 63-453 mg/dL (3.5-25.2 mmol/L)]. No severe hypoglycemia or ketoacidosis occurred. During the first 24 postoperative hours, seven patients (63.6%) achieved euglycemia without exogenous insulin, whereas two required transient insulin therapy. Six patients (54.5%) had postoperative complications, including thrombotic (n = 4), infectious (n = 2), and reperfusion syndrome (n = 1). One patient experienced more than one event. All events were successfully managed, without graft loss, acute rejection, or in-hospital mortality.CONCLUSIONThe phase-specific intraoperative glycemic protocol for SPKT is feasible and safe. However, prospective studies with larger cohorts are warranted to assess its long-term impact on graft survival and patient outcomes.

To be, or not to be, on insulin for simultaneous kidney-pancreas transplant: Is that the question?

Insulin acts as a central anorexigenic signal in vertebrates, but its precise neuropharmacological mechanisms in avian species remain largely unelucidated. This study sought to delineate the involvement of specific central adrenergic receptor subtypes in the mechanism through which insulin suppresses feed intake in broiler chickens. To achieve this objective, six experiments were conducted using 264 neonatal broiler chicks receiving intracerebroventricular injections. The experimental design consisted of: 1) establishing a dose-response relationship for insulin (2.5, 5, and 10ng), followed by 2) investigating potential interactions between insulin (10ng) and selective adrenergic receptor antagonists including prazosin (α1, 10nmol), yohimbine (α2, 13nmol), metoprolol (β1, 24nmol), ICI 118,551 (β2, 5nmol), and SR59230R (β3, 20nmol). Total feed intake was assessed at three specific time points: 30, 60, and 120min after the infusion of the treatment. Exogenous insulin administration elicited a robust, dose-responsive inhibition of feeding behavior in the subjects (P < 0.05). Co-infusion with the β2-adrenergic receptor antagonist ICI 118,551 markedly attenuated insulin's hypophagic effects (P < 0.05), whereas the administration of antagonists for alternative adrenergic receptor subtypes did not result in a statistically significant modulation of insulin's action (P ≥ 0.05). This investigation provides evidence supporting a central role for β2-adrenergic receptors in the mediation of insulin's appetite-suppressing actions in broiler chickens. The results contribute to understanding of the neurochemical substrates governing avian feeding behavior and indicate potential targets for further investigation into metabolic regulation.

People with diabetes rely on exogenous insulin to reduce blood glucose levels, compensating for insulin resistance or impaired pancreatic β‐cell function. Despite being essential for diabetes management, insulin formulations exhibit inconsistent performance due to their relatively fragile stability. This instability carries significant cost implications: Some individuals spend over $1000 per month on insulin, and these high prices influence one in six Americans with diabetes to ration their insulin supplies. Environmental stressors can induce conformational changes that cause insulin to misfold and aggregate into fibrils, which are inactive structures that contribute to long‐term diabetic complications. Although insulin′s instability is well‐documented, no test currently exists outside of laboratory settings to determine whether an insulin formulation has fibrillated. Here, we compare biochemical techniques for assessing bioactivity and structural integrity in three commercial insulin analogs exposed to physiologically relevant stress conditions, showing that fibril formation precedes measurable loss of bioactivity in insulin and that fibrillation depends on both the stressor type and the insulin formulation tested. We then demonstrate proof‐of‐concept testing for antibody‐based fibrillation detection using commercial monoclonal antibody candidates. Together, these findings underscore the critical need for accessible insulin quality testing and demonstrate the feasibility of antibody‐based detection of insulin fibrillation.

This review aimed to summarize the most up-to-date evidence (up to August 2025) on the efficacy, safety, and predictors of response to mesenchymal stem cell (MSC)–based therapy in type 2 diabetes mellitus (T2DM), and to provide research perspectives and practical recommendations. A systematic search was conducted in PubMed, Cochrane Library, Web of Science, and relevant medical journals (December 2023–August 2025) using the keywords “mesenchymal stem cells,” “umbilical cord,” “bone marrow,” “type 2 diabetes,” “randomized,” and “meta-analysis.” Ten eligible studies were included in the qualitative synthesis: two randomized controlled trials, one non-randomized clinical study, one retrospective study, one post-hoc analysis, and five meta-analyses or systematic reviews. MSC therapy, particularly umbilical cord–derived MSC (UC-MSC), reduced mean HbA1c by 0.6–0.9% after 12 months, improved C-peptide and glucose infusion rate (GIR), and decreased exogenous insulin requirements. Long-term follow-up data demonstrated reduced rates of macrovascular and peripheral neuropathic complications. Recent pooled analyses reported no serious MSC-related adverse events, confirming a favorable safety profile. Current clinical evidence supports MSC therapy as a safe and promising adjunct for selected T2DM patients. However, large multicenter randomized trials with standardized cell sources, doses, delivery routes, and ≥24-month follow-up are needed to validate long-term efficacy and define its role in diabetes management.

Aim. To analyze current research data on the use of genetically modified insulin- producing cells, including genome editing technologies (Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)), in the treatment of type 1 diabetes (T1D), and to assess their potential efficacy, safety, and prospects for practical implementation. Material and methods. We conducted an analytical review of publications, clinical trials, systematic reviews, and reports from international organizations on cell therapy and genetic engineering in the context of T1D treatment. A search of electronic databases (PubMed, eLibrary, Scopus) was conducted using the following keywords: diabetes mellitus, genetic engineering, and clustered regularly interspaced short palindromic repeats. Priority was given to publications from the last decade, reflecting the most relevant advances in regenerative medicine. The selected sources were analyzed, systematized, and organized into following thematic sections: technologies for obtaining insulin-producing cells, genetic modification methods, clinical results, risks, and limitations of use. Results. Analysis of the sources revealed that transplantation of genetically modified insulin- producing cells is a promising approach to treating type 1 diabetes, aimed at restoring endogenous insulin secretion. Using CRISPR technology, the immunogenicity of transplanted cells can be reduced, potentially avoiding lifelong immunosuppressive therapy. This first clinical study demonstrates the ability of transplanted cells to provide glycemic control and reduce patients' dependence on exogenous insulin. Conclusion. Unresolved issues remain related to long-term safety, the risk of tumor transformation, ethical aspects, and the high cost of therapy. Further research and technological advancements are needed in these areas.

The global rise in obesity prevalence poses a major health challenge due to its links to hypertension, stroke, type 2 diabetes, cardiovascular disease, depression, and cancer. Effective non-pharmacological strategies are essential to curb this epidemic. Insulin is a major regulator of body weight. It not only mediates glucose uptake but also inhibits hepatic glucose production, lipolysis, and enhances lipogenesis. Type 1 diabetes provides insights on insulin's role in weight regulation. Prior to diagnosis, insulin deficiency commonly produces unintentional weight loss, whereas initiation of exogenous insulin therapy typically restores body mass. Scientific research in non-diabetic populations, including Mendelian randomization studies, has identified elevated insulin secretion as a key contributor to weight gain. Conversely, reductions in insulin secretion have been shown to facilitate weight loss, even in the absence of caloric restriction. One strategy to keep circulating insulin concentrations low is the application of carbohydrate unit tables to estimate expected postprandial glucose excursions in insulin-deficient patients and anticipated insulin responses in non-diabetic individuals. This approach facilitates avoidance of foods that provoke large insulin responses. A complementary approach is postprandial self-monitoring of blood glucose (SMBG). In non-diabetic individuals, this allows for personalized assessment of glycemic and insulin responses to meals. The effectiveness of this approach in promoting weight reduction has been demonstrated across multiple studies. During fasting or adherence to low-carbohydrate diets, circulating insulin concentrations remain low, permitting unrestrained adipose tissue lipolysis and promoting fatty acid oxidation for energy production. Self-monitoring of breath acetone (SMBA) provides a simple, non-invasive biomarker of this metabolic state. Recent findings indicate that a single carbohydrate-rich meal during a ketogenic state suppresses fat mobilization for several days-a phenomenon suggestive of a "memory effect" of insulin on lipolysis inhibition. Although underlying mechanisms remain to be elucidated, awareness of this effect may improve dietary regimens. Insights from type 1 diabetes offer advice for managing weight development by minimizing episodes of hyperinsulinemia. Effective non-pharmacological measures include the use of carbohydrate unit tables combined with SMBG for avoiding post-meal hyperglycemia and hyperinsulinemia. Additionally, SMBA provides a non-invasive marker of sustained fat mobilization and can help identify and prevent periods of insulin-induced fat accumulation.

As care for type 1 diabetes (T1D) advances, the number of adults with T1D living into older adulthood (ages ≥65 years) continues to grow. The population of older adults with T1D is highly heterogeneous, and over the life span, various factors may change over time while others may not, necessitating an individualized approach to management. A key care consideration for people with T1D is the ongoing need for exogenous insulin replacement intensive self-monitoring for effective management. At the same time, growing older may bring changes such as increased risk of misdiagnosis of T1D as type 2 diabetes, greater vulnerability to hypoglycemia, accumulating comorbidities and complications, declining independence due to geriatric syndromes, and a growing need for support in using diabetes technologies and navigating complex care transitions. Given the unique clinical and management needs of this population, we sought to present key care challenges in this population and suggest strategies to optimize quality of care in older adults with T1D, including 1) integrating geriatric screenings, age-friendly care frameworks, and regular reassessments into routine T1D management; 2) developing tailored care approaches for cognitive impairment; 3) establishing support systems for diabetes technology use in primary and long-term care settings; and 4) ensuring insurance coverage and access to diabetes technologies and therapies. Forward-thinking strategies to optimize care include individualized glycemic goal setting, the development and adoption of care models that support continuity of diabetes technology use, and individualized management strategies that consider of the goals and capabilities of the person living with T1D and care partners.

Type 1 diabetes is a chronic autoimmune disease involving the specific destruction of pancreatic β-cells and consequent absolute insulin deficiency. Although exogenous insulin replacement aids in hyperglycemic management, it does not cure the disease and increases the risks of hypoglycemia. Recent breakthroughs in disease-modifying therapies aim to delay, halt, or reverse disease progression via immune modulation or cell replacement. This narrative review systematically summarizes key therapeutic advances from 2023 to 2025. In immunotherapy, anti-CD3 monoclonal antibodies such as teplizumab have become the first Food and Drug Administration-approved agents to delay clinical onset in high-risk individuals. Inhibitors targeting pathways such as Janus kinase-STAT and engineered cell therapies such as chimeric antigen receptor-Tregs have also demonstrated potential for preserving residual β-cell function. For gene therapy and cell replacement, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) editing has generated "hypoimmune" stem cell-derived β-cells, with early clinical trials reporting instances of insulin independence without immunosuppression. Encapsulation technologies further provide a physical immune barrier for transplanted cells. Collectively, these advances mark a paradigm shift from symptomatic control to addressing core disease mechanisms through immune repair and functional restoration. Although challenges in long-term efficacy, safety, and accessibility persist, the ongoing development of combination strategies and precision medicine contributes to long-term remission and potentially a cure within reach.

Individuals with type 1 diabetes mellitus (T1DM) must deliver insulin into the peripheral circulation rather than more physiologically into the hepatic portal circulation, leading to a chronic state of underinsulinization in the liver. Previous research suggests that decreased hepatic insulin perturbs the growth hormone-IGF-1 system in these patients. We tested whether short-term carbohydrate restriction, by lowering exogenous insulin requirements and exacerbating hepatic underinsulinization, modifies IGF axis hormones, binding proteins, and vascular function. We performed a secondary analysis of plasma samples collected during a single-blind crossover study of twelve adults with T1DM using automated insulin delivery. In random order, the participants consumed a one-week reduced carbohydrate diet (RCD) and an isocaloric standard carbohydrate diet (SCD), each followed by a study visit. We measured total and free IGF-1 and IGF-binding proteins (IGFBP-1, IGFBP-2, and IGFBP-3) after overnight fasting and during the final 30min of a hyperinsulinemic-euglycemic clamp. We also measured endothelial function using brachial artery flow-mediated dilation (FMD). The RCD lowered the total daily insulin dose versus SCD (16% during the week and 24% in the 24h before testing), with similar glucose levels across diets. Compared with SCD, RCD reduced total IGF-1 and IGFBP-3 and increased IGFBP-1 and IGFBP-2 at baseline. These patterns also persisted during insulin-stimulated conditions. Free IGF-1 was more variable and did not differ significantly between diets. Despite clear shifts in the IGF axis, FMD did not differ between diets and did not correlate with IGF axis markers after either intervention. In adults with T1DM studied under nearly matched glycemia, one week of carbohydrate reduction lowered insulin requirements and shifted the IGF axis in a pattern akin to reduced portal insulin exposure, without detectable changes in conduit artery endothelial function. These findings identify the IGF axis as a sensitive physiologic readout of insulin exposure. Longer-term studies are needed to determine whether sustained changes in the IGF axis impact vascular biology or cardiometabolic risk. ClinicalTrials.gov NCT04118374.

BackgroundInsulin autoimmune syndrome (IAS) is a rare hypoglycemic disorder often confused with insulinoma or insulin overdose. Patients with diabetes on insulin therapy increasingly show insulin autoantibodies (IAAs), presenting symptoms similar to classic IAS, termed exogenous insulin antibody syndrome (EIAS). This study examines EIAS clinical features and risk factors.MethodsPatients with diabetes with IAA test results, admitted to our hospital between June 2023 and March 2024 were retrospectively enrolled. Participants were stratified into control and EIAS groups on the basis of IAA status. Clinical characteristics were compared between groups, independent risk factors for EIAS were identified by multivariate logistic regression, and the diagnostic utility of fasting insulin for predicting EIAS was assessed with receiver-operating-characteristic (ROC) curve analysis.ResultsOf 120 patients with diabetes and available IAAs results, 37 met criteria for EIAS. Compared with controls, EIAS patients were older, had longer diabetes duration, were more often treated with insulin aspart or premixed human insulin, and received higher daily insulin doses. Paradoxically, EIAS patients had markedly lower levels of fasting blood glucose and HbA1c, while higher fasting and 2-h post-prandial insulin concentrations, as well as HOMA-IR. Multivariate logistic regression analysis showed that elevated fasting insulin levels were independently associated with increased risk of EIAS. For every 1 uU/mL increase in fasting insulin, the risk of EIAS increased by 3% (OR = 1.03, 95% CI: 1.00–1.05). The fasting insulin level demonstrated high overall diagnostic and predictive efficacy for EIAS, with an area under the curve (AUC) of 0.782 (95% CI: 0.691–0.872). The optimal diagnostic cutoff value was 6.975 uU/mL, with a sensitivity of 73.0% and a specificity of 81.9%.ConclusionEIAS patients were identified with advanced age, prolonged diabetes duration, high insulin dosage, hypoglycemia, and hyperinsulinemia. Fasting insulin level is independently associated with EIAS risk and demonstrates good diagnostic performance.

Accurate prediction and control of blood glucose levels are essential for the management of type 1 diabetes, where patients rely on exogenous insulin and are vulnerable to both hypoglycemia and hyperglycemia. The widespread adoption of continuous glucose monitoring systems, insulin pumps, and wearable devices has generated large volumes of physiological and behavioral data, creating new opportunities for computational modeling and intelligent decision support. This review surveys recent advances in glucose prediction and control models, with a primary focus on type 1 diabetes. We examine three major classes of approaches: mechanistic models based on physiological principles, data-driven machine learning methods, and hybrid or biology-informed frameworks that integrate mechanistic knowledge with learning-based techniques. We also discuss the growing role of multimodal data, deep learning architectures, and reinforcement learning for automated insulin dosing and adaptive control in artificial pancreas systems. Despite significant progress, important challenges remain, including handling noisy and heterogeneous data, improving predictive reliability and uncertainty quantification, and enabling real-time deployment on resource-constrained medical devices. Emerging strategies such as edge computing, efficient model design, and hardware–algorithm co-optimization may help bridge this gap. Continued progress will require interdisciplinary collaboration, standardized evaluation on public datasets, and rigorous clinical validation to translate emerging modeling approaches into practical tools that improve patient outcomes.

Due to insufficient insulin secretion, patients with type 1 diabetes mellitus (T1DM) are prone to blood glucose fluctuations ranging from hypoglycemia to hyperglycemia. While dangerous hypoglycemia may lead to coma immediately, chronic hyperglycemia increases patients' risks for cardiorenal and vascular diseases in the long run. In principle, an artificial pancreas - a closed-loop insulin delivery system requiring patients to manually input insulin dosage according to the upcoming meals - could supply exogenous insulin to control the glucose levels and hence reduce the risks from hyperglycemia. However, insulin overdosing in some type 1 diabetic patients, who are physically active, can lead to unexpected hypoglycemia beyond the control of the common artificial pancreas. Therefore, it is important to take into account the glucose decrease due to physical exercise when designing the next-generation artificial pancreas. In this work, we develop a framework integrating systems biology-informed neural networks (SBINN), deep reinforcement learning (RL) algorithms, and T1DM data collected from wearable devices, to automate insulin dosing for patients. In particular, we build patient-specific computational models using SBINN to mimic the glucose-insulin dynamics for a few patients from the dataset, by simultaneously considering patient-specific carbohydrate intake and physical exercise intensity. Our patient-specific artificial pancreas, based on two deep RL algorithms, provided better insulin dosage, leading to safer glucose levels compared to those in the original dataset.

We had a patient with type 2 diabetes (patient A) who suffered from hyperglycemia and frequent episodes of nocturnal hypoglycemia. He had a high titer of insulin antibodies (> 50.0 U/mL) and a very high serum insulin concentration (19,516 µU/mL). The aims of this study were (1) establishing a non-isotopic method to identify insulin analogs that bind less to the antibodies and validating its clinical usage and (2) elucidating the mechanism of his nocturnal hypoglycemia and its management. The optimal conditions for binding study were determined using seven exogenous insulin preparations (human insulin, lispro, aspart, glulisine, glargine, degludec, and detemir) via polyethylene glycol method. The effect of pH on binding of endogenous insulin to its antibodies was examined via gel filtration chromatography (GFC) on different pH. Several times higher concentration of exogenous insulin was most appropriate in binding study. It revealed that all seven insulin preparations significantly bound to the insulin antibodies in patient A. Among the other 53 serum samples containing insulin antibodies, about 70% of them had at least one insulin analog that did not significantly bind to their insulin antibodies. GFC revealed that reducing the pH from 7.4 to 7.2 partially dissociated antibody-bound insulin leading to increased unbound insulin. We established and validated a non-isotopic method to identify suitable insulin preparations that bound less to insulin antibodies. Correcting respiratory acidosis during sleep might be effective to prevent nocturnal hypoglycemia in some patients with diabetes having insulin antibodies.

People with diabetes rely on exogenous insulin to reduce blood glucose levels, compensating for insulin resistance or impaired pancreatic β-cell function. Despite being essential for diabetes management, insulin formulations exhibit inconsistent performance due to their relatively fragile stability. This instability carries significant cost implications: some individuals spend over $1,000 USD per month on insulin, and these high prices influence one in six Americans with diabetes to ration their insulin supplies. Environmental stressors can induce conformational changes that cause insulin to misfold and aggregate into fibrils, which are inactive structures that contribute to long-term diabetic complications. Although insulin's instability is well-documented, no test currently exists outside of laboratory settings to determine whether an insulin formulation has degraded. Here, we compare biochemical techniques for assessing bioactivity and structural integrity in three commercial insulin analogs exposed to physiologically relevant stress conditions, showing that fibril formation precedes measurable loss of bioactivity in insulin and that fibrillation depends on both the stressor type and the insulin formulation tested. We then demonstrate proof-of-concept testing for antibody-based degradation detection using commercial monoclonal antibody candidates. Together, these findings underscore the critical need for accessible insulin quality testing and demonstrate the feasibility of antibody-based detection of insulin fibrillation.

Type 1 diabetes (T1D) is an autoimmune disease in which T cells mediate the elimination of the insulin-producing beta cells in the pancreatic islets, resulting in the need for exogenous insulin. Studies of T1D in both patients and the nonobese diabetic (NOD) mouse model of the disease illustrate that beta cell-specific CD8+ T cells are central contributors to the beta cell destruction characterizing the disease. Compared to HLA-A and HLA-B, relatively little is known about the participation of HLA-C-restricted T cells in T1D. To tackle this question, we developed and characterized an NOD-based model of spontaneous T1D that transgenically expresses HLA-C*03:04, a common and enriched allotype in T1D patients. Using an unbiased screen of an exhaustive peptide library comprised of 8- to 11-mer peptides derived from the key autoantigen insulin, islet-infiltrating T cells from the mice were found to recognize the insulin A-chain peptides A11-19 and A13-21 presented by HLA-C*03:04. Guided by these findings, T-cell lines were established from the islets of HLA-C*03:04-positive human donors with T1D, including a donor with demise at onset of T1D. These human islet-derived T cells also responded to the conserved A11-19 and A13-21 peptides. The presence of HLA-C*03:04-restricted insulin-specific T cells in both mouse and human islets suggests the participation of peptides presented by HLA-C molecules in T1D pathogenesis. This work also demonstrates the utility of the mouse model in identifying human disease-relevant HLA-C-restricted epitopes and suggests a general strategy for the exploration and manipulation of HLA-C-restricted T cells in autoimmune diseases.

Falling insulin requirements during pregnancy in women with diabetes mellitus in pregnancy raise concerns regarding placental insufficiency and adverse pregnancy outcome. A case of a rapid fall in insulin requirements in a woman with type 2 diabetes mellitus, obesity, hypertension and chronic kidney disease at 23 weeks' gestation with high titres of insulin antibodies is presented. The possibility of exogenous insulin autoimmune syndrome as a cause for hypoglycaemia and reduction in insulin requirements is discussed.