Search Results (1,143)

(1) Background: Neuropathies are common complications of type 1 diabetes (T1D) and previous research demonstrated concomitant demyelinization involving myelin basic protein (MBP). T1D patients have a significantly increased risk of multiple sclerosis (MS) and vice versa. The causes are unknown. (2) Methods: Proteonomic searches using BLAST were used to identify similarities between T-cell receptor (TCR) sequences from T1D and MS patients. LALIGN was used to explore whether T1D-related proteins mimic MBP. Enzyme-linked immunoadsorption assay (ELISA) was used to test for cross-reactivity between T1D-related antibodies or sera with MBP. Ultraviolet spectroscopy was used to test whether T1D-specific T-cell receptor (TCR) sequences recognized MBP. (3) Results: BLAST revealed that a subset of T1D and MS TCR are nearly identical. Sequence similarities were found by LALIGN between MBP and T1D-associated antigens. Antibodies against insulin, PTPRN(IA-2), and GAD1 recognized MBP. Most TCR sequences derived from T1D patients recognized MBP as an antigen. Most T1D-derived sera recognize MBP, but healthy sera do not. BLAST revealed that coxsackievirus proteins do not mimic MBP, but many Clostridia proteins do. (4) Conclusions: Cross-reactivity between TID-related antibodies and TCR with MBP may help to explain the pathogenesis of T1D neuropathies and the increased co-occurrence of these two diseases. Full article

Stem cell-derived β (SC-β) cells are a promising therapy for type 1 diabetes (T1D), but their long-term efficacy is limited by immune-mediated graft rejection. Platelet-derived exosome product (PEP) has emerged as a novel immunomodulatory agent, although its effect on SC-β cell xenograft rejection remains unclear. Here, we evaluated PEP in stimulated human peripheral blood mononuclear cells (PBMCs) and in an immunocompetent mouse model of SC-β cell transplantation under the kidney capsule. Immune-related gene expression was assessed by quantitative PCR, immune cell infiltration by immunofluorescence, and graft function by circulating human insulin. In vitro, PEP reduced NK-cell-associated gene expression, including NK1.1, EOMES, and KLRK1, and increased IL-10 expression. In vivo, untreated SC-β cell xenografts showed progressive immune infiltration and loss of detectable human insulin by day 14, whereas PEP-treated grafts retained detectable insulin through day 14 across co-transplantation, pretreatment, and systemic administration strategies. PEP co-transplantation delayed, but did not prevent, xenograft rejection, with graft loss observed by day 21. This delay was associated with reduced NK1.1+ cell infiltration and lower expression of selected inflammatory and rejection-associated markers, including NK1.1, Nos2, and Nlrp3. These findings suggest that PEP modulates graft-associated immune responses and may serve as an adjunct immunomodulatory strategy for stem cell-based therapies for type 1 diabetes. Further studies are needed to evaluate sustained graft durability, safety, and translational efficacy. Full article

Background: Diabetic ketoacidosis (DKA) remains a preventable yet frequent complication at the onset of type 1 diabetes (T1D) in children, driven by delayed symptom recognition, socioeconomic disparities, and inconsistent access to care. Early identification of presymptomatic T1D through autoantibody-based screening, together with emerging disease-modifying therapies, may reduce the incidence of DKA. This review synthesizes evidence on epidemiology, risk determinants, screening strategies, and immunological interventions relevant to DKA prevention. Methods: A narrative review was conducted using PubMed, EMBASE, Scopus, Web of Science, and Google Scholar (2011–2026). Eligible sources included clinical studies, guidelines, systematic reviews, meta-analyses, and prevention trials addressing staging, screening, epidemiology, and disease-modifying treatments in pediatric T1D. Landmark publications outside this timeframe were included when essential. Evidence was integrated to identify determinants of DKA and strategies to reduce its occurrence. Results: DKA risk is influenced by younger age, socioeconomic disadvantage, rural residence, misdiagnosis, and limited access to specialized care. Sustained public awareness and community-based education reduce DKA incidence, whereas short-term campaigns show transient effects. Structured screening programs, including TrialNet and TEDDY, demonstrate near-elimination of DKA among monitored children. Teplizumab delayed progression from stage 2 to stage 3 T1D by a median of approximately 24 months in the original TN-10 trial, with extended follow-up demonstrating a median delay of 32.5 months. It is approved for individuals with stage 2 T1D aged ≥ 1 year and has recently gained approval for selected patients with newly diagnosed T1D, expanding opportunities for early disease modification. Global networks such as INNODIA strengthen prevention through coordinated biomarker-driven research. Conclusions: Reducing DKA at T1D onset requires integrated, sustained strategies combining public awareness, systematic autoantibody screening, structured follow-up, and access to emerging immunotherapies. Coordinated care across primary providers, pediatric endocrinologists, and research networks is essential to advance a proactive, prevention-oriented model of pediatric T1D care. Full article

Inflammatory and oxidative stress within the pancreatic islet microenvironment can alter insulin-derived peptides and generate neoepitopes that may reshape autoreactive T cell recognition in type 1 diabetes (T1D). One such modification, C19S, represents a cysteine-to-serine substitution at position 19 of the insulin B-chain and has recently been identified among human leukocyte antigen class II (HLA-II)-associated insulin neoepitopes recognized by autoreactive CD4+ T cells. Although the biological relevance of C19S has been determined, the molecular features that may distinguish C19S-specific T cell receptor (TCR) engagement from native insulin recognition remain incompletely defined. Here, we used comparative protein–protein docking, molecular dynamics (MD) simulations, interface-contact analysis, conformational landscape analysis, and binding-energy calculations to examine TCR engagement of human leukocyte antigen DQ8 (HLA-DQ8) presenting either native insulin peptide or the corresponding C19S insulin peptide. Initial modeling indicated that both peptide-HLA-DQ8 complexes were compatible with TCR-bound ternary complex formation. However, the C19S-containing complex was predicted to exhibit altered peptide-centered dynamics, changes in peptide backbone presentation, and reorganization of both TCR-peptide and TCR-HLA-DQ8 contacts. Comparative molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) analyses further suggested a distinct calculated energetic profile under the applied modeling conditions for the C19S-containing complex, with residue-level decomposition localizing energetic differences to selected interface hotspots. Together, these findings provide a molecular framework for generating hypotheses about how C19S may reshape the HLA-DQ8-presented insulin recognition surface, with implications for future experimental studies of autoreactive CD4+ T cell recognition and antigen-specific tolerogenic strategies in T1D. Full article

Background: Puberty in children with type 1 diabetes (T1D) is associated with increased insulin requirements, reduced insulin sensitivity, and changes in body composition. Objective: To evaluate body mass index (BMI) and body composition in children with T1D and compare the findings with data obtained 20 years earlier. Materials and Methods: This retrospective comparative study included two historical cohorts of children with type 1 diabetes (T1D) examined at the same tertiary diabetes center 20 years apart. A total of 293 participants were included: 145 age-matched children assessed in 2003 and 148 children assessed in 2023 (mean age 12.15 ± 4.42 years). Body mass index (BMI), fat mass (FM), and fat-free mass (FFM) were analyzed using bioelectrical impedance analysis, and the effects of insulin therapy, continuous glucose monitoring (CGM), physical activity, and family history of obesity were evaluated. Results: Mean BMI in 2023 was 19.85 ± 4.47 kg/m²; 85.8% of participants had normal body weight, 6.0% were overweight, and 8.1% had obesity. Children with a family history of obesity had higher BMI values than those without such history (23.2 ± 6.0 vs. 19.4 ± 4.3 kg/m²; p < 0.05). The highest BMI values in both sexes were observed in patients with T1D duration of 5–10 years. Compared with 2003, contemporary prepubertal boys had higher BMI values. Higher FM percentages in girls compared with boys were preserved. CGM use was associated with lower HbA1c, lower insulin dose requirements, and lower BMI values (all p < 0.05). Conclusions: Significant sex- and time-related differences in BMI and body composition were identified in children with T1D. CGM use was associated with better metabolic control and a more favorable body composition profile. Full article

Diabetic retinopathy (DR) reflects retinal microvascular injury and systemic immune-metabolic stress, and most public DR transcriptomic datasets lack paired microbiome/metabolomic profiles. We used gutMGene v2.0 as a curated microbe/metabolite–host gene prior and integrated it with peripheral blood transcriptomics from GSE221521. Candidate genes were refined by weighted gene co-expression network analysis (WGCNA), repeated resampling, cross-dataset assessment, mechanism scoring, peripheral blood mononuclear cell (PBMC) single-cell localization and filamin A (FLNA)-centered single-cell gene regulatory network (GRN) virtual knockout. The gutMGene prior contained 238 host genes; 15 DR-associated genes overlapped this prior, and WGCNA retained ten candidate gut microbe and microbial metabolite-related genes (GMMRGs): FLNA, AKT1, IRAK1, BCL10, CDK6, CTSD, JUP, CXCL1, CXCR2 and IL4R. Resampling prioritized FLNA as the most consistent candidate. Cross-dataset assessment localized the strongest signal to type 2 diabetes (T2D) PBMCs, retinal endothelial cells and advanced proliferative diabetic retinopathy with diabetic macular edema (PDR + DME) retinal tissue, with weaker separation in whole blood, broad retinal tissue and six-donor type 1 diabetes (T1D) PBMCs. FLNA virtual knockout predicted cell-context-dependent perturbation of immune-related transcriptional programs, including IL4R in DR B cells and CTSD in DR monocytes/NK cells. This prior-guided study identifies FLNA within a ten-gene GMMRG set as a circulating host-response signal that links curated microbe/metabolite–host records to immune-vascular and cytoskeletal remodeling in DR. Full article

Despite increasing use of continuous glucose monitoring (CGM) and automated insulin delivery, most children and adolescents living with type 1 diabetes (T1D) in the US do not achieve recommended glycemic targets. Structured, proactive support improves glycemic outcomes, but diabetes teams have historically lacked reimbursement pathways and scalable workflows to support between-visit care. The introduction of remote patient monitoring (RPM) billing codes has created new opportunities to align clinical need with care delivery models, although adoption remains limited. We describe implementation experiences from three pediatric diabetes centers that developed RPM programs across distinct clinical populations and institutional environments. Each site developed workflows for data review, patient outreach, documentation, and billing, supported by digital platforms designed to facilitate population-level management. Common themes emerged around needs for structured patient onboarding, multidisciplinary team alignment, standardized documentation, efficient data aggregation and population health management tools, adaptable communication pathways, and financial alignment. This practice-informed commentary synthesizes common themes across these programs and outlines key considerations for RPM implementation, including workflow design, digital infrastructure, communication strategies, and reimbursement structures. We also highlight practical challenges related to equity, patient engagement, and operational feasibility. This report aims to contextualize early clinical experience with RPM and identify factors that may influence its integration into pediatric diabetes care. Full article

Pancreatic β-cells maintain glucose homeostasis through tightly regulated insulin biosynthesis, storage, and secretion. To prevent pathological accumulation of excess or aging secretory granules (SGs), β-cells use crinophagy, a selective lysosomal degradation pathway in which mature insulin-containing granules fuse directly with lysosomes to form hybrid organelles termed crinosomes. Crinophagy was historically considered a simple mechanism for discarding obsolete, aged SGs. The acidic, protease-rich environment of crinosomes is proposed to generate unconventional insulin-derived epitopes through cathepsin-mediated proteolysis and transpeptidation reactions. These cryptic epitopes, which include hybrid insulin peptides (HIPs) resulting from the covalent fusion of insulin fragments with peptides from co-resident granule proteins, are largely absent from the thymic epitope repertoire. This creates a “peripheral–thymic mismatch” that allows autoreactive CD4+ T cells to escape central tolerance, ultimately driving β-cell destruction in type 1 diabetes (T1D). Recent studies demonstrate that pharmacological or genetic inhibition of crinophagy reduces crinosome abundance, narrows the pathogenic epitope repertoire, and delays the onset of diabetes in preclinical models. In type 2 diabetes (T2D), a related pathway termed stress-induced nascent granule degradation (SINGD) diverts newly synthesized insulin granules to lysosomes under glucolipotoxic conditions, contributing to insulin depletion and progressive β-cell failure. This review summarizes the current understanding of the molecular mechanisms behind crinophagy. It discusses its two main functions: maintaining physiological quality control and generating pathological antigens. Additionally, the review explores how crinophagy interacts with other cellular stress pathways and highlights new therapeutic strategies aimed at targeting this process to protect pancreatic β-cell function and potentially prevent or delay diabetes. Full article

Background/Objectives: Omnipod 5 is a tubeless automated insulin delivery system integrating continuous glucose monitoring (CGM) with algorithm-driven insulin delivery. Clinical trials and real-world studies have shown improved glycemic control and reduced hypoglycemia in people with type 1 diabetes (T1D) previously treated with multiple daily injections (MDI) or non-automated sensor-augmented pump (SAP) therapy. However, long-term real-world data in young adults remain limited. Methods: We conducted a retrospective, single-centre observational study including adults with T1D who started therapy with a tubeless automated insulin delivery system (Omnipod 5). Participants were previously treated with MDI or SAP therapy. Glycemic outcomes were assessed using CGM metrics at baseline, 1, 3, and 12 months after starting the system. The primary outcome was change in time in range of 70–180 mg/dL (TIR) at 12 months. Secondary outcomes included additional CGM metrics, insulin therapy parameters, and the occurrence of diabetic ketoacidosis (DKA) and severe hypoglycaemia (SH) episodes. Results: Fifty-two patients were included (mean age 23.0 ± 4.3 years; diabetes duration 13.8 ± 5.9 years); 51 completed 12-month follow-up. At 12 months, TIR increased from 56.1 ± 11.4% to 67.4 ± 11.0% (+11.3%; p < 0.001), while time in tight range of 70–140 mg/dL (TITR) increased from 34.5 ± 10.9% to 44.8 ± 8.7% (+10.3%; p < 0.001). Time in hypoglycemia also decreased, with no episodes of DKA or SH reported during the study period. Glycemic improvements were evident at 1 month and maintained at 12 months. The proportion of patients achieving recommended targets improved at 12 months, including TIR > 70% (13.5% to 43.1%). Total daily insulin requirements remained unchanged, while basal insulin proportion increased, and daily boluses decreased (both p < 0.001). Conclusions: In this real-world study, Omnipod 5 therapy was associated with improved glycemic control and reduced hypoglycemia over 12 months in young adults with T1D, without increasing insulin requirements. Full article

Type 1 diabetes (T1D) is an autoimmune disease characterized by β-cell destruction as a common trait, in which variability in age at onset, progression rate, and clinical presentation shape heterogeneous phenotypes. Disentangling this heterogeneity is pivotal for a better understanding of clinical risk, evolution and a precision medicine approach to the disease. In this context, circulating islet autoantibodies, including the last discovered Zinc Transporter 8 autoantibodies (ZnT8A), represent crucial tools. This narrative review provides an overview of the current knowledge on ZnT8A in autoimmune diabetes from its structural and pathogenetic basis to its clinical relevance and therapeutic perspectives. A literature search was conducted in PubMed, Scopus, Google Scholar, and ResearchGate up to March 2026, that included preclinical, pediatric, adult, and assay-comparison studies. While the identification of ZnT8-targeted antigenic determinants is still ongoing, we discuss the pathogenic role of a newly identified specific class of antibodies directed against extracellular ZnT8 epitopes (ZnT8ecA). According to this finding, ZnT8ecA could facilitate the identification of an early phase of islet injury process, holding promise to provide a framework for new therapeutic strategies based on masking or modulating surface-exposed ZnT8 epitopes and interfering with the early stages of the disease. Moving from the role of ZnT8A in various clinical settings, we also focus on recent advancements in detection technologies, whose implementation accounts for invaluable contributions to diagnosis, disease risk, and, contextually, to a better understanding of autoimmune diabetes. Finally, we provide future perspectives, in T1D and T1-related diseases, for the potential clinical application of ZnT8A in early diagnosis, risk stratification and profiling, as well as in the development of targeted therapies as part of precision medicine. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a major global health challenge due to its high prevalence and association with chronic complications, highlighting the need for reliable predictive tools to support clinical decision-making. Methods: This study proposes a two-stage hierarchical prediction system based on a Random Forest (RF) classifier. In Stage 1, the model performs multiclass classification into healthy (H), T2DM without complications (D), and T2DM with complications (C). In Stage 2, patients classified as C are further stratified into microvascular or macrovascular complications. The dataset included 31 biochemical, molecular, inflammatory, and oxidative stress variables from Mexican and Spanish cohorts. Feature selection was performed using Pearson correlation, and feature relevance was further assessed using RF importance measures. Model training used stratified cross-validation, with additional evaluation on a hold-out set to approximate real-world performance. Results: The optimized RF achieved an accuracy of 92% and a macro F1-score of 0.92, outperforming baseline models, with an AUC-ROC of 0.89 for complication prediction. Key predictive features included IL-18, miR-126, duration of T2DM, HbA1c, and IL-10. Conclusions: The novelty of this study lies in integrating heterogeneous biomarkers within a hierarchical predictive framework, rather than in the machine learning algorithm itself. This multimodal approach, combined with interpretable machine learning techniques, is designed to deliver clinically meaningful insights for patient stratification and personalized management in T2DM. Full article

Foundation time-series models have recently shown potential for forecasting complex temporal signals, but their behavior in patient-specific continuous glucose monitoring (CGM) forecasting remains insufficiently understood, particularly when only glucose history is available. This study provides a patient-level benchmark of foundation models for 30 min ahead glucose prediction in adults with type 1 diabetes mellitus (T1DM) under a strictly univariate CGM-only setting. Using the HUPA–UCM dataset from 25 individuals, we evaluated TimeGPT, Chronos, and Sundial against representative statistical, machine learning, and deep learning forecasters, including ARIMA, ETS, gradient-boosting models, recurrent networks, and neural forecasting architectures. Models were assessed using a local walk-forward validation strategy over the final 24 h of CGM data for each patient. Foundation models achieved the strongest global performance, with Sundial obtaining the lowest overall MAE ($6.06\mathrm{mg}/\mathrm{dL}$), while TimeGPT and Chronos remained among the most competitive approaches. However, patient-level analyses showed that this advantage was not uniform: ARIMA remained highly competitive in selected individuals, and no single model consistently dominated across the cohort. These findings suggest that foundation time-series models are promising tools for short-horizon CGM forecasting, but their use should be framed within patient-specific model selection rather than as universal replacements for classical forecasting methods. Full article

Background/Objectives: Type 1 diabetes (T1D) is an autoimmune disease characterized by progressive β-cell loss. Apolipoprotein CIII (apoCIII), a lipid metabolism regulator, is elevated in T1D and implicated in β-cell apoptosis. Antisense oligonucleotide–mediated apoCIII reduction delays diabetes onset in diabetes-prone BioBreeding (DPBB) rats. This study examined whether small-interfering RNA (siRNA) targeting apoCIII during the final prediabetic month preserves islet integrity and delays T1D onset. Methods: Two siRNAs targeting rat apoCIII were evaluated in 30-day-old DPBB rats for efficacy and off-target effects. Hepatic and plasma apoCIII levels were measured, and neighboring apolipoprotein gene expression was assessed. The most specific candidate (apoCIII-siRNA2) was selected. Duration of action was determined after a single injection. To study the effects of apoCIII-lowering treatment in vivo, islets from 25-day-old DPBB rats were transplanted into the anterior chamber of the eye of age-matched DPBB recipients. Rats received weekly intravenous injections of apoCIII-siRNA2 from day 30 until diabetes onset. Islet morphology, vascularization, and phagocyte infiltration were assessed by confocal imaging three and five weeks post-transplantation. Results: Both siRNAs reduced apoCIII, but one showed off-target effects and was excluded. A single injection of apoCIII-siRNA2 suppressed plasma apoCIII for approximately one week and weekly treatment maintained low circulating apoCIII levels. Five weeks after transplantation islet morphology and vascularization were preserved, and there was no increase in phagocyte infiltration. This resulted in a delayed onset of diabetes. Conclusions: siRNA-mediated apoCIII reduction delays pancreatic islet deterioration and T1D onset in DPBB rats, supporting apoCIII as a contributing factor to β-cell vulnerability and thereby a potential therapeutic target. Full article

Background/Objectives: Type 2 diabetes (T2D) remission can be defined as a return to a HbA1c < 6.5% (<48 mmol/mol) sustained without ongoing treatment for at least 3 months. Prevalence estimates and factors associated remain unknown for LMIC and resource-limited settings. Methods: We conducted a retrospective observational analysis of electronic medical records from 8463 adults who received multidisciplinary care at Mexico’s primary care specialized units (UNEMES-EC) between 2015 and 2019 and who were referred for inadequate metabolic control. Remission was defined per 2021 ADA criteria as HbA1c <6.5% sustained for ≥3 months without glucose-lowering medications. After estimating the prevalence of T2D remission, logistic regression models were used to evaluate its sociodemographic and clinical predictors, with particular attention to weight change and baseline adiposity interactions. Results: RT2D prevalence was 0.87% (95% CI: 0.68–1.10) over a median 393-day follow-up. Weight loss ≥10% (adjusted OR 2.75; 95% CI: 1.21-6.27) and systolic blood pressure (tertile 3 vs tertile 1: OR 2.49; 95% CI: 1.17–5.26) were positively associated with RT2D, while elevated baseline HbA1c (tertile 3 vs. tertile 1: OR 0.09; 95% CI: 0.02–0.33), triglyceride levels (tertile 3 vs. tertile 1: OR 0.49; 95% CI: 0.24–0.98) and intensive pharmacotherapy were inversely associated with RT2D. No associations with HDL and total cholesterol were found. Age, sex, educational attainment, and income demonstrated no independent associations with remission. Among lifestyle-treated patients achieving ≥5% weight loss, remission prevalence reached approximately 11%. No significant interaction between baseline BMI and weight change was detected (p = 0.60). Conclusions: This first large-scale Mexican study establishes RT2D as an achievable endpoint in patients with poor baseline metabolic control. The findings suggest that remission could be achieved with equity-focused, weight-centered interventions even in resource-constrained health systems and populations. Full article

Background/Objectives: Automated insulin delivery (AID) systems have improved the management of type 1 diabetes (T1D), but exercise and nutrition remain challenging because they rapidly alter glucose flux, substrate oxidation, hepatic glucose output, insulin requirements, and fuel availability. This narrative review aimed to synthesize current evidence on the interaction between AID systems, physical activity, and nutritional strategies from a metabolism-oriented perspective. Methods: A narrative bibliographic approach was used to integrate evidence from clinical trials, observational studies, technical studies, consensus statements, and reviews involving people with T1D across different life stages, including pediatric, adolescent, adult, and pregnancy-related contexts, when available. The review focused on AID systems, exercise physiology, nutritional strategies, meal announcement, bolus adjustment, dual-hormone systems, metabolic biomarkers, and emerging metabolomic approaches. Results: AID systems generally improve time in range and reduce hypoglycemia across several user groups, although most exercise- and nutrition-specific evidence comes from adult and pediatric/adolescent cohorts rather than pregnancy-specific exercise studies. Exercise-related glucose responses remain highly dependent on user input, exercise modality, insulin on board, meal timing, and metabolic state. Planned exercise announcement, prandial bolus reduction before postprandial activity, and individualized carbohydrate intake remain key strategies. Biomarkers such as lactate, ketone bodies, non-esterified fatty acids, and counter-regulatory hormones may help explain interindividual variability and support future personalization. Conclusions: Nutrition and exercise management in AID users should be interpreted as a dynamic metabolic interface among exogenous insulin, endogenous counter-regulation, substrate availability, and algorithmic control. Emerging approaches, including activity sensors, adaptive algorithms, dual-hormone systems, digital twins, and metabolomics-informed personalization, may improve safety and reduce user burden, but several remain exploratory and require further validation in diverse free-living conditions. Full article