The immune system accidentally targets the body's tissues, causing inflammation and tissue damage, the root causes of autoimmune illnesses. In recent studies, non-coding RNAs have been shown to significantly control gene expression and metabolic pathways linked to autoimmune diseases. This review investigates the effects of non-coding RNA on glucose metabolism, a route frequently dysregulated in autoimmune illnesses such as multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus, and diabetes. We review how non-coding RNA affects immune cell activity modulation, glucose absorption, glycolysis, and other metabolic processes critical to immune function. We also investigate the possibility of using non-coding RNA-mediated metabolic pathway targeting as a new therapeutic approach to treat autoimmune disorders. By clarifying the complex interplay of non-coding RNA, glucose metabolism, and immune dysregulation, this study endeavors to enhance comprehension of autoimmune etiology and facilitate the creation of focused therapies.

To prevent chronic disease from getting worse, it is important to detect and predict it at an early stage. Therefore, the accuracy of the prediction is particularly important. To investigate the accuracy of different methods, this study compares the out-of-sample errors of machine learning algorithms and traditional econometric methods in predicting diabetes. The object of prediction in this study is fasting blood glucose, and the machine learning algorithms used are stepwise selection, bagging, random forests and support vector machine (SVM). In addition, we demonstrate the linear combination of above machine learning algorithms in this study. The findings indicate that the combined model outperforms both traditional econometric models and individual machine learning algorithms. However, the predictive performance of individual machine learning models does not consistently surpass that of traditional econometric approaches. Based on the data characteristics analyzed in this study, a possible explanation for this finding is that traditional econometric methods may exhibit superior performance in linear data prediction. Finally, the analysis of variable importance suggests that medical indicators and physical condition may play a more significant role in determining fasting blood glucose compared to hereditary factors. To further validate our results, we applied the same methodology to predict hypertension using the same dataset. The findings similarly indicated that the predictive ability of individual machine learning algorithms does not always surpass that of traditional econometric models. And a linear combination of the four machine learning algorithms enhances the predictive accuracy for hypertension.

This study analyzes the global and China trends in the prevalence, disease burden, and future projections of Type 1 Diabetic Nephropathy (T1DN) over the past three decades, providing data to inform public health policies and clinical interventions.

Data from the Global Burden of Disease (GBD) 2021 database were used to analyze the incidence, prevalence, mortality, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life years (DALYs) of T1DN globally and in China from 1990 to 2021. Trend analysis was conducted using R and Joinpoint software, and the ARIMA model was applied to predict future trends in T1DN prevalence for the next 20 years. A significance level of p<0.05 was applied.

Globally, deaths from T1DN increased from 49,300(95% CI: 39,088-61,207) in 1990 to 94,020 (95% CI: 71,456-119,984)in 2021, with the age-standardized mortality rate remaining stable. DALYs rose from 2,227,518(95% CI: 1,835,372-2,679,207) in 1990 to 3,875,628 (95% CI: 3,062,395-4,845,503) in 2021, though the age-standardized rate slightly decreased. In China, the mortality rate declined significantly, and DALYs decreased, with the age-standardized DALYs dropping from 80.915/100,000(95% CI: 65.121-98.391)to 47.953/100,000(95% CI: 36.9-60.734). Globally, both incidence and prevalence increased, with global incidence reaching 95,140(95% CI: 82,236-111,471) cases and prevalence rising to 6,295,711 (95% CI: 5,459,693-7,114,345)cases. In China, incidence showed a declining trend, but prevalence continued to rise. The ARIMA model forecasts global incidence will reach 115,000 cases, with prevalence reaching 7,000,000 by 2041. In China, incidence is expected to stabilize, while prevalence may increase to approximately 2,500,000 cases.

The burden of T1DN is rising globally, especially in terms of prevalence, while China has made progress in reducing mortality and disease burden. However, challenges remain in chronic disease management. Over the next 20 years, global prevalence is projected to continue increasing, while China's prevalence may stabilize. Targeted interventions for different age groups and genders will be essential in reducing the T1DN burden.

To explore how serum diabetes autoantibodies are related to the development of early diabetic retinopathy in children with type 1 diabetes mellitus.

In this prospective and observational study, 62 patients with type 1 diabetes mellitus who had not yet developed clinical diabetic retinopathy were followed up for at least 5 years. Healthy volunteers aged 10 to 20 years were also included. Insulin, pancreatic islet cells, and glutamic acid decarboxylase (GAD) autoantibodies were measured with an RIA kit at the time of type 1 diabetes mellitus diagnosis. Optical coherence tomography angiography (OCTA) was used to evaluate the foveal avascular zone (FAZ) and parafoveal vascular density (PVD) for the development of early diabetic retinopathy among the groups. Patients' OCTA findings were compared with those of healthy volunteers. The obtained data were analyzed via IBM SPSS Statistics for Windows, version 27.0. Spearman's rank correlation test and regression analysis were performed to determine independent predictors of OCTA and type 1 diabetes mellitus parameters.

Eighteen boys and 44 girls with type 1 diabetes mellitus with a median age of 15.6 years (range: 10.08 to 20.88 years) were evaluated. Healthy control participants with a median age of 15.3 years (range: 14.2 to 18.2 years) were also included. The mean FAZ was greater in the type 1 diabetes mellitus group than in the healthy control group (P = .013 and .119, respectively). The mean PVD was significantly lower in the type 1 diabetes mellitus group than in the healthy control group. There was no significant correlation between serum diabetes autoantibodies (GAD and insulin autoantibodies) and FAZ or PVD (FAZ and GAD; r = 0.138, P = .286, FAZ and anti-insulin; r = 0.100, P = .441, PVD and GAD; r = -0.151, P = .24, PVD and anti-insulin; r = -0.087, P = .499).

Type 1 diabetes mellitus in children without clinically detectable diabetic retinopathy is associated with impaired retinal microcirculation and irregularities at the FAZ margin. Impaired retinal microcirculation and irregularities were associated with glycated hemoglobin levels in the study group. Thus, studies with larger patient series are needed. [J Pediatr Ophthalmol Strabismus. 2025;62(2):135-142.].

Many studies of type 1 diabetes pathogenesis focus on individuals with high-risk HLA haplotypes. We tested the hypothesis that, among islet autoantibody-positive individuals, lacking HLA-DRB1*04-DQA1*03-DQB1*0302 (HLA-DR4-DQ8) and/or HLA-DRB1*0301-DQA1*0501-DQB1*0201 (HLA-DR3-DQ2) is associated with phenotypic differences, compared with those who have these high-risk HLA haplotypes.

We classified autoantibody-positive relatives of individuals with type 1 diabetes into four groups based on having both HLA-DR4-DQ8 and HLA-DR3-DQ2 (DR3/DR4; n=1263), HLA-DR4-DQ8 but not HLA-DR3-DQ2 (DR4/non-DR3; n=2340), HLA-DR3-DQ2 but not HLA-DR4-DQ8 (DR3/non-DR4; n=1607) and neither HLA-DR3-DQ2 nor HLA-DR4-DQ8 (DRX/DRX; n=1294). Group comparisons included demographics, metabolic markers and the prevalence of autoantibodies against GAD65 (GADA%), IA-2 (IA-2A%) or insulin (IAA%) at enrolment. A p value <0.01 was considered statistically significant.

IA-2A% was lower in the DRX/DRX group (20.9%) than in the DR4/non-DR3 (38.5%, p<0.001) and DR3/DR4 (44.8%, p<0.001) groups, but similar to the DR3/non-DR4 group (20.0%). Conversely, IAA% was similar in the DRX/DRX (43.4%), DR4/non-DR3 (41.1%) and DR3/DR4 (41.0%) groups, but lower in the DR3/non-DR4 group (30.1%, p<0.001). Participants in the DRX/DRX group were older, with a lower prevalence of White participants and a higher prevalence of overweight/obesity, and higher preserved C-peptide (as measured by a lower Index60) than those in the DR3/DR4 group (all comparisons, p<0.005), a lower prevalence of White or non-Hispanic participants and a lower Index60 than those in the DR4/non-DR3 group, and younger age, a higher prevalence of Hispanic participants and a lower Index60 than those in the DR3/non-DR4 group (all comparisons, p<0.005). Among the 1292 participants who progressed to clinical type 1 diabetes, those in the DR3/non-DR4 group had higher GADA%, lower IA-2A% and lower IAA% than the other groups (all comparisons, p<0.01), and those in the DR3/DR4 group had the youngest age at diagnosis (all comparisons, p<0.001).

Autoantibody-positive individuals who lack both high-risk HLA haplotypes (DRX/DRX) or have HLA-DR3-DQ2 but lack HLA-DR4-DQ8 (DR3/non-DR4) have phenotypic differences compared with DR3/DR4 and DR4/non-DR3 individuals, suggesting that there is aetiological heterogeneity in type 1 diabetes.

Serum lactate levels have been recognized as a robust marker for predicting disease severity and survival in many critically ill children but consensus is lacking regarding its utility in diabetic ketoacidosis. This study aimed to investigate the relationship between initial lactate levels and disease severity in pediatric patients presenting with diabetic ketoacidosis.

This single-center retrospective descriptive study involved pediatric patients with diabetic ketoacidosis in the pediatric emergency department between January 2022 and April 2023. Patients were diagnosed using the International Society for Pediatric and Adolescent Diabetes 2022 guidelines.

Among the 112 patients included in the study, 41 (36.6%) were classified as mild, 42 (34.8%) as moderate and 32 (28.6%) as severe acidosis. A statistically significant difference was observed between the time to resolution and clinical severity of diabetic ketoacidosis (p < 0.001). Elevated lactate levels of 2.5 mmol/L or above were detected in 37.5% (42/112) of our patients and a significant increase in clinical severity was observed as lactate levels increased (p < 0.001). Correlation analysis revealed no significant relationship between lactate levels and time to resolution of diabetic ketoacidosis or length of intensive care unit stay. Multivariate analysis demonstrated a significant association between lactate levels and severity of acidosis (p: 0.046).

Although there is an association between the severity of acidosis and lactate levels in diabetic ketoacidosis, contrary to expectations, this relationship was not found to be associated with adverse outcomes. An important point not to be overlooked by pediatricians is that elevated lactate levels in diabetic ketoacidosis may not always herald poor outcomes.

The gut microbiome influences immune and metabolic homeostasis. Our research using non-obese diabetic (NOD) mice revealed that early-life antibiotic exposure remodels the gut microbiome affecting metabolism and accelerating type 1 diabetes (T1D) incidence, with cecal material transplant (CMT) mitigating the damage. Now examining murine intestinal lipidomic profiles, we identified 747 compounds. Comparing the lipidomic profiles of cecal contents of conventional and germ-free mice and their diets, we identified 87 microbially-produced lipids reduced by antibiotic exposure but CMT-restored. Parallel analysis of human fecal lipid profiles after azithromycin-exposure showed significant alterations with substantial overlap with mice. In vitro co-culture with mouse macrophages or small intestinal epithelial cells and human colonic epithelial cells identified phospholipids that repress inflammation through the NFκB pathway. Oral administration of these phospholipids to antibiotic-treated NOD mice reduced expression of ileal genes involved in early stages of T1D pathogenesis. These findings indicate potential therapeutic anti-inflammatory roles of microbially-produced lipids.

This study sought to elucidate the interactions among physical activity (PA) patterns, mean glucose concentrations, and the incidence of nocturnal hypoglycemia events in children and adolescents with type 1 diabetes, examining the moderating influence of daily dosage on these associations.

Eighty-two participants aged 6 to 18 years (43.9% girls) from the Diactive-1 Cohort Study, diagnosed with type 1 diabetes, were included. Data collection involved continuous glucose monitoring, accelerometry to assess real-world PA, as well as documentation of daily insulin doses and carbohydrate counting over the same 7 days.

A total of 19 participants experienced at least 1 nocturnal hypoglycemia event over a span of 574 measurement days (106 days with and 451 days without nocturnal hypoglycemia). Higher levels of vigorous PA (VPA) were associated with lower same-day mean glucose levels (P = .014). Additionally, higher levels of moderate PA (P = .023), VPA (P = .011), and moderate-to-vigorous PA (P = .010) were associated with a greater number of nocturnal hypoglycemia events. Specifically, a significant association was identified between VPA and nocturnal hypoglycemia events when the daily insulin dose was at or above 1.04 units per kilogram of body weight per day (P = .016).

Daily VPA is associated with glucose reductions, potentially leading to more hypoglycemic episodes, particularly when there is an excess of daily insulin. This highlights the need for careful insulin management in children and adolescents with type 1 diabetes engaging in VPA.

Previous studies have shown that dyslipidemia is significantly associated with primary frozen shoulder and may be a risk factor for the development of primary frozen shoulder. However, these findings may be biased by a number of confounding factors. We investigated the association between serum lipids and primary frozen shoulder by retrospective analysis and two-sample Mendelian randomization (MR) methods.

This retrospective observational study included 284 patients with primary frozen shoulder diagnosed from October 2020 to October 2023 at four centers as the experimental group. Patients with diabetes and thyroid dysfunction were excluded. The control group consisted of age- and sex-matched people who underwent a health checkup. We compared total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) between the two groups. Genetic variants for the serum lipids and frozen shoulder were then extracted from large-scale genome-wide association studies. Causal effects were assessed using Inverse variance weighting (IVW), Weighted median, MR-Egger, simple and weighted models in MR analysis.

The analysis showed that after excluding patients with diabetes and thyroid dysfunction, the serum lipids (TC, TG, HDL, and LDL) in the primary frozen shoulder group were no different from those of normal individuals. None of the MR methods found significant causal evidence between them.

Dyslipidemia in patients with primary frozen shoulder may be influenced by confounding factors such as diabetes and thyroid dysfunction. These findings deepen our understanding of primary frozen shoulder risk factors.

In this study, we aimed to study the role of extracellular proteins as biomarkers associated with newly diagnosed Type 1 diabetes (NT1D) diagnosis and prognosis.

We retrieved and analyzed the GSE55098 microarray dataset from the Gene Expression Omnibus (GEO) database. Using R software, we screened out the extracellular protein-differentially expressed genes (EP-DEGs) through several protein-related databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to describe the role and function of these EP-DEGs. We used the STRING database to construct the interaction of proteins, Cytoscape software to visualize the protein-protein interaction (PPI) networks, and its plugin CytoHubba to identify the crucial genes between PPI networks. Finally, we used the comparative toxicogenomics database (CTD) to evaluate the connection between NT1D with the potential crucial genes and we validated our conclusions with another dataset (GSE33440) and some clinical samples.

We identified 422 DEGs and 122 EP-DEGs from a dataset that includes (12) NT1D patients compared with (10) healthy people. Protein digestion and absorption, toll-like receptor signaling, and T cell receptor signaling were the most meaningful pathways defined by KEGG enrichment analyses. We recognized nine important extracellular genes: GZMB, CCL4, TNF, MMP9, CCL5, IFNG, CXCL1, GNLY, and LCN2. CTD analyses showed that LCN2, IFNG, and TNF had higher levels in NT1D and hypoglycemia; while TNF, IFNG and MMP9 increased in hyperglycemia. Further verification showed that LCN2, MMP9, TNF and IFNG were elevated in NT1D patients.

The nine identified key extracellular genes, particularly LCN2, IFNG, TNF, and MMP9, may be potential diagnostic biomarkers for NT1D. Our findings provide new insights into the molecular mechanisms and novel therapeutic targets of NT1D.

Gamma aminobutyric acid (GABA) is synthesized from glutamate by glutamic decarboxylase (GAD). The entero-pancreatic biology of GABA, which is produced by pancreatic islets, GAD-expressing microbiota, enteric immune cells, or ingested through diet, supports an essential physiologic role of GABA in the health and disease. Outside the central nervous system (CNS), GABA is uniquely concentrated in pancreatic β-cells. They express GAD65, which is a type 1 diabetes (T1D) autoantigen. Glutamate constitutes 10% of the amino acids in dietary protein and is preeminently concentrated in human milk. GABA is enriched in many foods, such as tomato and fermented cheese, and is an over-the-counter supplement. Selected microbiota in the midgut have the enzymatic capacity to produce GABA. Intestinal microbiota interact with gut-associated lymphoid tissue to maintain host defenses and immune tolerance, which are implicated in autoimmune disease. Although GABA is a widely known inhibitory neurotransmitter, oral GABA does not cross the blood brain barrier. Three diabetes-related therapeutic actions are ascribed to GABA, namely, increasing pancreatic β-cell content, attenuating excess glucagon and tamping down T-cell immune destruction. These salutary actions have been observed in numerous rodent diabetes models that usually employed high or near-continuous GABA doses. Clinical studies, to date, have identified positive effects of oral GABA on peripheral blood mononuclear cell cytokine release and plasma glucagon. Going forward, it is reassuring that oral GABA therapy has been well-tolerated and devoid of serious adverse effects.

Exercise is one of the preferred management strategies for diabetic patients, but the exercise mode including type, intensity, and duration time is quite different for each patient because of individual differences. Inadequate exercise has no effect on the blood glucose control, while overexercise may cause serious side effects, such as hypoglycemia and loss of blood glucose control. In this work, we report a closed-loop feedback mode for exercise management in diabetes. A minimally invasive, biocompatible microneedle electrode patch was fabricated and used for continuously monitoring the glucose in the interstitial fluid. Further, in conjunction with using a wireless electrochemical device, the glucose signals can be analyzed to output the potency of exercise and give advice on exercise management. A custom exercise given by this closed-loop feedback mode can reduce the used dose of insulin and avoid side effect during and after exercise. We believe that this work can provide a novel comprehensive guidance for diabetic patients.

The aim of this study was to develop and validate explainable prediction models based on continuous glucose monitoring (CGM) and baseline data to identify a week-to-week risk of CGM key metrics (hyperglycemia, hypoglycemia, glycemic variability). By having a weekly prediction of CGM key metrics, it is possible for the patient or health care personnel to take immediate preemptive action.

We analyzed, trained, and internally tested three prediction models (Logistic regression, XGBoost, and TabNet) using CGM data from 187 type 1 diabetes patients with long-term CGM monitoring. A binary classification approach combined with feature engineering deployed on the CGM signals was used to predict hyperglycemia, hypoglycemia, and glycemic variability based on consensus targets (time above range ≥5%, time below range ≥4%, coefficient of variation ≥36%). The models were validated in two independent cohorts with a total of 223 additional patients of varying ages.

A total of 46 593 weeks of CGM data were included in the analysis. For the best model (XGBoost), the area under the receiver operating characteristic curve (ROC-AUC) was 0.9 [95% confidence interval (CI) = 0.89-0.91], 0.89 [95% CI = 0.88-0.9], and 0.8 [95% CI = 0.79-0.81] for predicting hyperglycemia, hypoglycemia, and glycemic variability in the interval validation, respectively. The validation test showed good generalizability of the models with ROC-AUC of 0.88 to 0.95, 0.84 to 0.89, and 0.80 to 0.82 for predicting the glycemic outcomes.

Prediction models based on real-world CGM data can be used to predict the risk of unstable glycemic control in the forthcoming week. The models showed good performance in both internal and external validation cohorts.

Autoimmune patients have a significantly increased risk of developing coronary artery disease (CAD) compared to the general population. However, autoimmune patients often lack traditional risk factors for CAD and there is increasing recognition of inflammation in CAD development. In this study, we leveraged genome-wide association study (GWAS) data to understand whether there is a genetic relationship between CAD and autoimmunity. Statistical genetic comparison methods were used to identify correlated and causal SNPs between various autoimmune diseases and CAD. Pleiotropic SNPs were identified by cross-phenotype association analysis (CPASSOC) and overlap between GWAS. Causal SNPs were identified using Mendelian Randomization (MR) and Colocalization (COLOC). Using SNP-to-gene mapping, we additionally identified pleiotropic and causal genes and pathways associated between autoimmunity and CAD, which were contextualized by documentation of enrichment in individual cell types identified from coronary atherosclerotic plaques by single-cell RNA sequencing. These results provide insight into potential inflammatory therapeutic targets for CAD.

The transplantation of islet beta cells offers an alternative to heterotopic islet transplantation for treating type 1 diabetes mellitus (T1DM). However, the use of systemic immunosuppressive drugs in islet transplantation poses significant risks to the body. To address this issue, we constructed an encapsulated hybrid scaffold loaded with islet beta cells. This article focuses on the preparation of the encapsulated structure using 3D printing, which incorporates porcine pancreas decellularized extracellular matrix (dECM) to the core scaffold. The improved decellularization method successfully preserved a substantial proportion of protein (such as Collagen I and Laminins) architecture and glycosaminoglycans in the dECM hydrogel, while effectively removing most of the DNA. The inclusion of dECM enhanced the physical and chemical properties of the scaffold, resulting in a porosity of 83.62% ± 1.09% and a tensile stress of 1.85 ± 0.16 MPa. In teams of biological activity, dECM demonstrated enhanced proliferation, differentiation, and expression of transcription factors such as Ki67, PDX1, and NKX6.1, leading to improved insulin secretion function in MIN-6 pancreatic beta cells. In the glucose-stimulated insulin secretion experiment on day 21, the maximum insulin secretion from the encapsulated structure reached 1.96 ± 0.08 mIU ml-1, representing a 44% increase compared to the control group. Furthermore, conventional capsule scaffolds leaverage the compatibility of natural biomaterials with macrophages to mitigate immune rejection. Here, incorporating curcumin into the capsule scaffold significantly reduced the secretion of pro-inflammatory cytokine (IL-1β, IL-6, TNF-α, IFN-γ) secretion by RAW264.7 macrophages and T cells in T1DM mice. This approach protected pancreatic islet cells against immune cell infiltration mediated by inflammatory factors and prevented insulitis. Overall, the encapsulated scaffold developed in this study shows promise as a natural platform for clinical treatment of T1DM.

Diabetes mellitus affects 537 million adults around the world. Adropin is expressed in different cell types. Our aim was to investigate the cellular localization in the endocrine pancreas and its effect on modulating pancreatic endocrine hormone release in streptozotocin (STZ)-induced diabetic rats. Adropin expression in the pancreas was investigated in normal and diabetic rats using immunohistochemistry and immunoelectron microscopy. Serum levels of insulin, glucagon pancreatic polypeptide (PP), and somatostatin were measured using a Luminex® χMAP (Magpix®) analyzer. Pancreatic endocrine hormone levels in INS-1 832/3 rat insulinoma cells, as well as pancreatic tissue fragments of normal and diabetic rats treated with different concentrations of adropin (10-6, 10-9, and 10-12 M), were measured using ELISA. Adropin was colocalized with cells producing either insulin, glucagon, or PP. Adropin treatment reduced the number of glucagon-secreting alpha cells and suppressed glucagon release from the pancreas. The serum levels of GLP-1 and amylin were significantly increased after treatment with adropin. Our study indicates a potential role of adropin in modulating glucagon secretion in animal models of diabetes mellitus.

The gut microbiome plays an important role in honeybee hormonal regulation and growth, but the underlying mechanisms are poorly understood. Here, we showed that the depletion of gut bacteria resulted in reduced expression of insulin-like peptide gene (ilp) in the head, accompanied by metabolic syndromes resembling those of Type 1 diabetes in humans: hyperglycemia, impaired lipid storage, and decreased metabolism. These symptoms were alleviated by gut bacterial inoculation. Gut metabolite profiling revealed that succinate, produced by Lactobacillus Firm-5, played deterministic roles in activating ilp gene expression and in regulating metabolism in honeybees. Notably, we demonstrated that succinate modulates host ilp gene expression through stimulating gut gluconeogenesis, a mechanism resembling that of humans. This study presents evidence for the role of gut metabolite in modulating host metabolism and contributes to the understanding of the interactions between gut microbiome and bee hosts.

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors affecting T1D and their influence on the development and progression of the disease. To fill these knowledge gaps, we constructed a model to find biomarker from gut microbiota in patients with T1D. We first identified microbial markers using Linear discriminant analysis Effect Size (LEfSe) and random forest (RF) methods. Furthermore, by constructing co-occurrence networks for gut microbes in T1D, we aimed to reveal all gut microbial interactions as well as major beneficial and pathogenic bacteria in healthy populations and type 1 diabetic patients. Finally, PICRUST2 was used to predict Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways and KO gene levels of microbial markers to investigate the biological role. Our study revealed that 21 identified microbial genera are important biomarker for T1D. Their AUC values are 0.962 and 0.745 on discovery set and validation set. Functional analysis showed that 10 microbial genera were significantly positively associated with D-arginine and D-ornithine metabolism, spliceosome in transcription, steroid hormone biosynthesis and glycosaminoglycan degradation. These genera were significantly negatively correlated with steroid biosynthesis, cyanoamino acid metabolism and drug metabolism. The other 11 genera displayed an inverse correlation. In summary, our research identified a comprehensive set of T1D gut biomarkers with universal applicability and have revealed the biological consequences of alterations in gut microbiota and their interplay. These findings offer significant prospects for individualized management and treatment of T1D.

Childhood-onset type 1 diabetes (T1D) is associated with substantial psychiatric morbidity in later life, but it remains unknown whether these associations are due to common underlying biological mechanisms or the impacts of living with the condition and its treatment. Here, using Czech national register data, we identified children with T1D aged ≤14 years between 1994 and 2007 and estimated the risk of psychiatric disorders up to 24 years later. We found that children diagnosed with T1D had an elevated risk of developing substance use, mood, anxiety and personality disorders, and behavioral syndromes. Conversely, we found that children with T1D had a lower risk of developing psychotic disorders. In Mendelian randomization analysis, we found an association with schizophrenia, which, however, did not persist following multiple testing adjustment. The combined observational and Mendelian randomization evidence suggests that T1D diagnosis in childhood predisposes to far-reaching, extensive psychiatric morbidity, which is unlikely to be explicable by common underlying biological mechanisms. The findings of this study highlight that monitoring and addressing the mental health needs of children with T1D is imperative, whereas glucose dysregulation and/or inflammation implicated in schizophrenia pathogenesis warrants future research.

Aim: The aim of this study was to develop and validate a prediction model based on continuous glucose monitoring (CGM) data to identify a week-to-week risk profile of excessive hypoglycemia. Methods: We analyzed, trained, and internally tested two prediction models using CGM data from 205 type 1 diabetes patients with long-term CGM monitoring. A binary classification approach (XGBoost) combined with feature engineering deployed on the CGM signals was utilized to predict excessive hypoglycemia risk defined by two targets (time below range [TBR] >4% and the upper TBR 90th percentile limit) of TBR the following week. The models were validated in two independent cohorts with a total of 253 additional patients. Results: A total of 61,470 weeks of CGM data were included in the analysis. The XGBoost models had an area under the receiver operating characteristic curve (ROC-AUC) of 0.83-0.87 (95% confidence interval; 0.83-0.88) in the test dataset. The external validation showed ROC-AUCs of 0.81-0.90. The most discriminative features included the low blood glucose index, the glycemic risk assessment diabetes equation (GRADE), hypoglycemia, the TBR, waveform length, the coefficient of variation and mean glucose during the previous week. This highlights that the pattern of hypoglycemia combined with glucose variability during the past week contains information on the risk of future hypoglycemia. Conclusion: Prediction models based on real-world CGM data can be used to predict the risk of hypoglycemia in the forthcoming week. The models showed good performance in both the internal and external validation cohorts.

The available evidence on the impact of specific non-pharmacological interventions on glycaemic control is currently limited. Consequently, there is a need to determine which interventions could provide the most significant benefits for the metabolic health of young individuals with type 1 diabetes mellitus. The aim of this study was to identify optimal nonpharmacological interventions on glycaemic control, measured by glycated haemoglobin (HbA1c), in children and adolescents with type 1 diabetes. Systematic searches were conducted in PubMed, Web of Science, Scopus, and SPORTDiscus from inception to July 1, 2023. Randomised clinical trials (RCT) investigating nonpharmacological interventions (e.g., physical activity, nutrition, and behavioural therapies) were included. Primary outcome was change in HbA1c levels. Secondary outcome was change in daily insulin dose requirement. Seventy-four RCT with 6,815 participants (49.43% girls) involving 20 interventions were analysed using a network meta-analysis. Most interventions showed greater efficacy than standard care. However, multicomponent exercise, which includes aerobic and strength training (n = 214, standardised mean difference [SMD] =- 0.63, 95% credible interval [95% CrI] - 1.09 to - 0.16) and nutritional supplements (n = 146, SMD =- 0.49, - 0 .92 to - 0.07) demonstrated the greatest HbA1c reductions. These interventions also led to the larger decreases in daily insulin needs (n = 119, SMD =- 0.79, 95% CrI -  1.19 to - 0.34) and (n = 57, SMD =- 0.62, 95% CrI -  1.18 to - 0.12, respectively). The current study underscores non-pharmacological options such as multicomponent exercise and nutritional supplements, showcasing their potential to significantly improve HbA1c in youth with type 1 diabetes. Although additional research to confirm their efficacy is required, these approaches could be considered as potential adjuvant therapeutic options in the management of type 1 diabetes among children and adolescents.

Automated delivery of insulin based on continuous glucose monitoring is revolutionizing the way insulin-dependent diabetes is treated. However, challenges remain for the widespread adoption of these systems, including the requirement of a separate glucose sensor, sophisticated electronics and algorithms, and the need for significant user input to operate these costly therapies. Herein, a user-centric glucose-responsive cannula is reported for electronics-free insulin delivery. The cannula-made from a tough, elastomer-hydrogel hybrid membrane formed through a one-pot solvent exchange method-changes permeability to release insulin rapidly upon physiologically relevant varying glucose levels, providing simple and automated insulin delivery with no additional hardware or software. Two prototypes of the cannula are evaluated in insulin-deficient diabetic mice. The first cannula-an ends-sealed, subcutaneously inserted prototype-normalizes blood glucose levels for 3 d and controls postprandial glucose levels. The second, more translational version-a cannula with the distal end sealed and the proximal end connected to a transcutaneous injection port-likewise demonstrates tight, 3-d regulation of blood glucose levels when refilled twice daily. This proof-of-concept study may aid in the development of "smart" cannulas and next-generation insulin therapies at a reduced burden-of-care toll and cost to end-users.

Type 1 diabetes (T1D)-associated hyperglycemia develops, in part, from loss of insulin-secreting beta cells. The degree of glycemic dysregulation and the age at onset of disease can serve as indicators of the aggressiveness of the disease. Tracking blood glucose levels in prediabetic mice may demonstrate the onset of diabetes and, along with animal age, also presage disease severity. In this study, an analysis of blood glucose levels obtained from female NOD mice starting at 4 weeks until diabetes onset was undertaken. New onset diabetic mice were orally vaccinated with a Salmonella-based vaccine towards T1D-associated preproinsulin combined with TGFβ and IL10 along with anti-CD3 antibody. Blood glucose levels were obtained before and after development of disease and vaccination. Animals were classified as acute disease if hyperglycemia was confirmed at a young age, while other animals were classified as progressive disease. The effectiveness of the oral T1D vaccine was greater in mice with progressive disease that had less glucose excursion compared to acute disease mice. Overall, the Salmonella-based vaccine reversed disease in 60% of the diabetic mice due, in part, to lessening of islet inflammation, improving residual beta cell health, and promoting tolerance. In summary, the age of disease onset and severity of glucose dysregulation in NOD mice predicted response to vaccine therapy. This suggests a similar disease categorization in the clinic may predict therapeutic response.

Type 1 diabetes (T1D) is an autoimmune disease caused by destruction of the pancreatic β-cells. Genome-wide association (GWAS) and fine mapping studies have been conducted mainly in European ancestry (EUR) populations. We performed a multi-ancestry GWAS to identify SNPs and HLA alleles associated with T1D risk and age at onset. EUR families (N = 3223), and unrelated individuals of African (AFR, N = 891) and admixed (Hispanic/Latino) ancestry (AMR, N = 308) were genotyped using the Illumina HumanCoreExome BeadArray, with imputation to the TOPMed reference panel. The Multi-Ethnic HLA reference panel was utilized to impute HLA alleles and amino acid residues. Logistic mixed models (T1D risk) and frailty models (age at onset) were used for analysis. In GWAS meta-analysis, seven loci were associated with T1D risk at genome-wide significance: PTPN22, HLA-DQA1, IL2RA, RNLS, INS, IKZF4-RPS26-ERBB3, and SH2B3, with four associated with T1D age at onset (PTPN22, HLA-DQB1, INS, and ERBB3). AFR and AMR meta-analysis revealed NRP1 as associated with T1D risk and age at onset, although NRP1 variants were not associated in EUR ancestry. In contrast, the PTPN22 variant was significantly associated with risk only in EUR ancestry. HLA alleles and haplotypes most significantly associated with T1D risk in AFR and AMR ancestry differed from that seen in EUR ancestry; in addition, the HLA-DRB1*08:02-DQA1*04:01-DQB1*04:02 haplotype was 'protective' in AMR while HLA-DRB1*08:01-DQA1*04:01-DQB1*04:02 haplotype was 'risk' in EUR ancestry, differing only at HLA-DRB1*08. These results suggest that much larger sample sizes in non-EUR populations are required to capture novel loci associated with T1D risk.

This meta-analysis includes the systematic literature review and meta-analysis involving clinical trials to assess the efficacy and safety of mesenchymal stem cell (MSC) transplantation for treating T1DM and T2DM.

We searched PubMed, ScienceDirect, Web of Science, clinicaltrials.gov, and Cochrane Library for "published" research from their inception until November 2023. Two researchers independently reviewed the studies' inclusion and exclusion criteria. Our meta-analysis included 13 studies on MSC treatment for diabetes.

The MSC-treated group had a significantly lower HbA1c at the last follow-up compared to the baseline (MD: 0.95, 95% CI: 0.33 to 1.57, P-value: 0.003< 0.05), their insulin requirement was significantly lower (MD: 0.19, 95% CI: 0.07 to 0.31, P-value: 0.002< 0.05), the level of FBG with MSC transplantation significantly dropped compared to baseline (MD: 1.78, 95% CI: -1.02 to 4.58, P-value: 0.212), the FPG level of the MSC-treated group was significantly lower (MD: -0.77, 95% CI: -2.36 to 0.81, P-value: 0.339 > 0.05), and the fasting C-peptide level of the MSC-treated group was slightly high (MD: -0.02, 95% CI: -0.07 to 0.02, P-value: 0.231 > 0.05).

The transplantation of MSCs has been found to positively impact both types of diabetes mellitus without signs of apparent adverse effects.

Novel biomarkers have been suggested for the diagnosis and prognosis of diabetes mellitus. The biomarker utility of netrin-1 in diabetes as an extracellular protein has been investigated. In this systematic review and meta-analysis, we reviewed the role of netrin-1 as a biomarker in prediabetes, diabetes, and complications of diabetes.

PubMed, Embase, Scopus, and Web of Science were systematically searched for studies that measured circulatory and/or urinary netrin-1 levels in diabetes and compared them with non-diabetic patients or evaluated the prognostic role of this marker. Standardized mean difference (SMD) and 95% confidence interval (CI) were calculated using random-effect meta-analysis to compare netrin-1 levels between groups. The impact of mean age, male sex percentage, sample size, mean body mass index, and publication year on the overall heterogeneity was assessed using meta-regression.

Among 413 records from international databases, 19 original studies were included with 2061 cases (1137 diabetics, 196 prediabetics, and 728 healthy controls). Meta-analysis of eight studies measuring netrin-1 in patients with diabetes and comparing it with healthy controls showed no significant difference between the two groups (SMD 0.69, 95% CI -0.78 to 2.16, I2 = 98%, p-value = 0.36). On the other hand, a meta-analysis of netrin-1 levels in patients with prediabetes in comparison with healthy controls revealed that they had lower levels (SMD -0.51, 95% CI -0.81 to -0.21, p-value < 0.01). Diabetic patients with microalbuminuria and macroalbuminuria had significantly higher circulatory netrin-1 levels compared to normoalbuminuric group SMD 1.18, 95% CI 0.83 to 1.53, p-value < 0.01 and SMD 1.67, 95% CI 0.76 to 2.58, p-value < 0.01, respectively). Moreover, no difference in urinary netrin-1 levels was found between micro-, macro-, and normoalbuminuric groups (p-value > 0.05).

Netrin-1 showed promising results as a biomarker in diabetes prognosis. However, more studies are required to confirm our findings, and higher sample size studies are needed to evaluate the diagnostic utility of this marker.

Islet autoantibodies predict type 1 diabetes (T1D) but can be transient in murine and human T1D and are not thought to be directly pathogenic. Rather, these autoantibodies signal B cell activity as antigen-presenting cells (APCs) that present islet autoantigen to diabetogenic T cells to promote T1D pathogenesis. Disrupting B cell APC function prevents T1D in mouse models and has shown promise in clinical trials. Autoantigen-specific B cells thus hold potential as sophisticated T1D biomarkers and therapeutic targets. B cell receptor (BCR) somatic hypermutation is a mechanism by which B cells increase affinity for islet autoantigen. High-affinity B and T cell responses are selected in protective immune responses, but immune tolerance mechanisms are known to censor highly autoreactive clones in autoimmunity, including T1D. Thus, different selection rules often apply to autoimmune disease settings (as opposed to protective host immunity), where different autoantigen affinity ceilings are tolerated based on variations in host genetics and environment. This review will explore what is currently known regarding B cell signaling, selection, and interaction with T cells to promote T1D pathogenesis.

Diabetes, hypertension, obesity, and chronic kidney disease (CKD) are major public health challenges globally, contributing significantly to morbidity and mortality. The co-occurrence and interplay among these conditions exacerbate health outcomes, highlighting the need for an integrated understanding and approach to management. This narrative review aims to explore the complex relationships between diabetes, hypertension, obesity, and CKD, elucidating their collective impact on health. It discusses the epidemiological trends, underlying pathophysiological mechanisms, genetic predispositions, current treatment strategies, and the future direction of research and therapy. An extensive review of current literature was conducted, focusing on the epidemiology, pathophysiology, risk factors, diagnosis, and treatment of diabetes, hypertension, obesity, and CKD. Additionally, the review delves into the genetic and molecular biology underlying these conditions, the potential for personalized medicine, and the importance of a multidisciplinary approach to care. The review identifies key areas where these conditions intersect, enhancing disease progression and complicating management. It highlights the role of genetic and environmental factors in disease etiology, the critical need for personalized treatment strategies, and the gaps in current management approaches. Innovations in pharmacotherapy, monitoring technologies, and the potential of pharmacogenomics are discussed as avenues for advancing patient care. Diabetes, hypertension, obesity, and CKD are intricately linked, necessitating an integrated, patient-centered approach to care that goes beyond traditional treatment modalities. Future research should focus on collaborative models and interdisciplinary strategies to address the multifaceted challenges posed by these conditions. Emphasizing personalized medicine and leveraging technological advancements offer promising pathways to improve outcomes and reduce the global health burden of these metabolic disorders.

The incidence of Type 1 Diabetes Mellitus (T1DM) is on the rise. Since there is no curative treatment, it is urgent to look for therapies that can delay disease progression and protect pancreatic β-cells. Dipeptidyl peptidase-4 inhibitors (DPP-4i) have shown potential in modulating inflammation and preventing β-cell destruction. This protocol describes an upcoming trial to evaluate the effectiveness of the DPP-4i alogliptin in delaying the progression of stage 2 (presymptomatic) to stage 3 (symptomatic) T1DM.

We propose a two-year, two-arm, multicenter, randomized, open-label clinical trial targeting Brazilian patients aged 18 to 35 with stage 2 T1DM. The study, facilitated by the custom-developed "PRE1BRAZIL" web application, aims to enroll 130 participants. They will be randomly assigned in a 1:1 ratio to either a treatment group (alogliptin 25 mg daily plus regular clinical and laboratory assessments) or a control group (regular assessments only). The primary outcome is the rate of progression to stage 3 T1DM. Secondary outcomes include changes in A1c levels, glucose levels during a 2-hour oral glucose tolerance test (OGTT), C-peptide levels, exogenous insulin requirements, Insulin-Dose Adjusted A1c (IDAA1c), and the incidence of diabetic ketoacidosis (DKA) in those advancing to stage 3.

This protocol outlines the first randomized clinical trial (RCT) to investigate the impact of a DPP-4i in the presymptomatic stage of T1DM. The trial is designed to provide critical insights into the role of DPP-4i in the secondary prevention of T1DM. Utilizing the "PRE1BRAZIL" web application is expected to enhance participant enrollment and reduce operational costs.

Brazilian Registry of Clinical Trials.

Osteopontin (OPN) is a multifunctional protein that plays a pivotal role in the immune system. It is involved in various biological processes, including cell adhesion, migration and survival. The study of the immunomodulatory effects of OPN is of paramount importance due to its potential therapeutic applications. A comprehensive understanding of how OPN regulates the immune response could pave the way for the development of novel treatments for a multitude of diseases, including autoimmune disorders, infectious diseases and cancer. Therefore, in the following paper, we provide a systematic overview of OPN and its immunoregulatory roles in various diseases, laying the foundation for the development of OPN-based therapies in the future.

Autoimmune diseases are a diverse set of conditions defined by organ damage due to abnormal innate and acquired immune system responses. The pathophysiology of autoimmune disorders is exceedingly intricate and has yet to be fully understood. The study of long non-coding RNAs (lncRNAs), non-protein-coding RNAs with at least 200 nucleotides in length, has gained significant attention due to the completion of the human genome project and the advancement of high-throughput genomic approaches. Recent research has demonstrated how lncRNA alters disease development to different degrees. Although lncRNA research has made significant progress in cancer and generative disorders, autoimmune illnesses are a relatively new research area. Moreover, lncRNAs play crucial functions in differentiating various immune cells, and their potential relationships with autoimmune diseases have received growing attention. Because of the importance of Th17/Treg axis in auto-immune disease development, in this review, we discuss various molecular mechanisms by which lncRNAs regulate the differentiation of Th17/Treg cells. Also, we reviewed recent findings regarding the several approaches in the application of lncRNAs in the diagnosis and treatment of human autoimmune diseases, as well as current challenges in lncRNA-based therapeutic approaches to auto-immune diseases.

The utilization of nanotechnology-based herbal medication delivery systems is gaining attention as a novel approach to treating diabetes mellitus. The incorporation of nanotechnology into herbal medicine provides benefits such as enhanced Stability, solubility, and bioavailability of herbal medications. The purpose of this paper is to summarise the present status of research on herbal medicine delivery systems based on nanotechnology for the treatment of diabetic patients. The paper evaluates the various nanocarriers and herbal drugs used, the challenges and opportunities in the development of these systems, and their potential efficacy and safety. Additionally, the paper highlights the need for further research to optimize the formulation and delivery of these systems. This review's overarching objective is to provide a complete understanding of the possibilities of herbal medication delivery systems based on nanotechnology in diabetes mellitus treatment.

Nowadays, diabetes mellitus has emerged as a significant global public health concern with a remarkable increase in its prevalence. This review article focuses on the definition of diabetes mellitus and its classification into different types, including type 1 diabetes (idiopathic and fulminant), type 2 diabetes, gestational diabetes, hybrid forms, slowly evolving immune-mediated diabetes, ketosis-prone type 2 diabetes, and other special types. Diagnostic criteria for diabetes mellitus are also discussed. The role of inflammation in both type 1 and type 2 diabetes is explored, along with the mediators and potential anti-inflammatory treatments. Furthermore, the involvement of various organs in diabetes mellitus is highlighted, such as the role of adipose tissue and obesity, gut microbiota, and pancreatic β-cells. The manifestation of pancreatic Langerhans β-cell islet inflammation, oxidative stress, and impaired insulin production and secretion are addressed. Additionally, the impact of diabetes mellitus on liver cirrhosis, acute kidney injury, immune system complications, and other diabetic complications like retinopathy and neuropathy is examined. Therefore, further research is required to enhance diagnosis, prevent chronic complications, and identify potential therapeutic targets for the management of diabetes mellitus and its associated dysfunctions.

The adrenal glands are small endocrine glands located on top of each kidney, producing hormones regulating important functions in our body like metabolism and stress. There are several underlying causes for adrenal insufficiency, where an autoimmune attack by the immune system is the most common cause. A number of genes are known to confer early onset adrenal disease in monogenic inheritance patterns, usually genetic encoding enzymes of adrenal steroidogenesis. Autoimmune primary adrenal insufficiency is usually a polygenic disease where our information recently has increased due to genome association studies. In this review, we go through the physiology of the adrenals before explaining the different reasons for adrenal insufficiency with a particular focus on autoimmune primary adrenal insufficiency. We will give a clinical overview including diagnosis and current treatment, before giving an overview of the genetic causes including monogenetic reasons for adrenal insufficiency and the polygenic background and inheritance pattern in autoimmune adrenal insufficiency. We will then look at the autoimmune mechanisms underlying autoimmune adrenal insufficiency and how autoantibodies are important for diagnosis. We end with a discussion on how to move the field forward emphasizing on the clinical workup, early identification, and potential targeted treatment of autoimmune PAI.

Extracellular (e)ATP, a potent proinflammatory molecule, is released by dying/damaged cells at the site of inflammation and is degraded by the membrane ectonucleotidases CD39 and CD73. In this study, we sought to unveil the role of eATP degradation in autoimmune diabetes. We then assessed the effect of soluble CD39 (sCD39) administration in prevention and reversal studies in NOD mice as well as in mechanistic studies. Our data showed that eATP levels were increased in hyperglycemic NOD mice compared with prediabetic NOD mice. CD39 and CD73 were found expressed by both α- and β-cells and by different subsets of T cells. Importantly, prediabetic NOD mice displayed increased frequencies of CD3+CD73+CD39+ cells within their pancreata, pancreatic lymph nodes, and spleens. The administration of sCD39 into prediabetic NOD mice reduced their eATP levels, abrogated the proliferation of CD4+- and CD8+-autoreactive T cells, and increased the frequency of regulatory T cells, while delaying the onset of T1D. Notably, concomitant administration of sCD39 and anti-CD3 showed a strong synergism in restoring normoglycemia in newly hyperglycemic NOD mice compared with monotherapy with anti-CD3 or with sCD39. The eATP/CD39 pathway plays an important role in the onset of T1D, and its targeting might represent a potential therapeutic strategy in T1D.

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

The P2X7 receptor (P2X7R) is an ATP-gated nonselective cationic channel that, upon intense stimulation, can progress to the opening of a pore permeable to molecules up to 900 Da. Apart from its broad expression in cells of the innate and adaptive immune systems, it is expressed in multiple cell types in different tissues. The dual gating property of P2X7R is instrumental in determining cellular responses, which depend on the expression level of the receptor, timing of stimulation, and microenvironmental cues, thus often complicating the interpretation of experimental data in comprehensive settings. Here we review the existing literature on P2X7R activity in autoimmunity, pinpointing the different functions in cells involved in the immunopathological processes that can make it difficult to model as a druggable target.