An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems.

In hybrid automatic insulin delivery (HAID) systems, meal disturbance is compensated by feedforward control, which requires the announcement of the meal by the patient with type 1 diabetes (DM1) to achieve the desired glycemic control performance. The calculation of insulin bolus in the HAID system is based on the amount of carbohydrates (CHO) in the meal and patient-specific parameters, i.e. carbohydrate-to-insulin ratio (CR) and insulin sensitivity-related correction factor (CF). The estimation of CHO in a meal is prone to errors and is burdensome for patients. This study proposes a fully automatic insulin delivery (FAID) system that eliminates patient intervention by compensating for unannounced meals. This study exploits the deep reinforcement learning (DRL) algorithm to calculate insulin bolus for unannounced meals without utilizing the information on CHO content. The DRL bolus calculator is integrated with a closed-loop controller and a meal detector (both previously developed by our group) to implement the FAID system. An adult cohort of 68 virtual patients based on the modified UVa/Padova simulator was used for in-silico trials. The percentage of the overall duration spent in the target range of 70-180 mg/dL was 71.2 % and 76.2 % , < 70 mg/dL was 0.9 % and 0.1 % , and > 180 mg/dL was 26.7 % and 21.1 % , respectively, for the FAID system and HAID system utilizing a standard bolus calculator (SBC) including CHO misestimation. The proposed algorithm can be exploited to realize FAID systems in the future.

Clinical serum lipidomic profiling revealed potential lipid biomarkers for early diabetic retinopathy.

Diabetic retinopathy (DR) is a serious complication of diabetes featuring abnormal lipid metabolism. However, the specific lipid molecules associated with onset and progression remain unclear. We used a broad-targeted lipidomics approach to assess the lipid changes that occur before the proliferative retinopathy stage and to identify novel lipid biomarkers to distinguish between patients without DR (NDR) and with non-proliferative DR (NPDR). Targeted lipomics analysis was carried out on serum samples from patients with type I diabetes, including 20 NDRs and 20 NPDRs. The results showed that compared with the NDR group, 102 lipids in the NPDR group showed specific expressions. Four lipid metabolites including TAG58:2-FA18:1 were obtained using the Least Absolute Shrink And Selection Operator (LASSO) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) methods. The four-lipid combination diagnostic models showed good predictive ability in both the discovery and validation sets, and were able to distinguish between NDR patients and NPDR patients. The identified lipid markers significantly improved diagnostic accuracy within the NPDR group. Our findings help to better understand the complexity and individual differences of DR lipid metabolism.

Nonpharmacological interventions on glycated haemoglobin in youth with type 1 diabetes: a Bayesian network meta-analysis.

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.

Glycemic variability through the perspective of the glycemia risk index and time in range and their association with glycated hemoglobin A1c in pediatric patients on sensor-augmented pump therapy.

Introduction: From the introduction of continuous glucose monitoring (CGM) in treatments of type 1 diabetes, particularly its integration with insulin pumps, there has been a quest for new parameters that describe optimal glycemic control. As of the consensus reached in 2019, the ambulatory glucose profile (AGP) has become the standard, with time in range (TIR) emerging as a fundamental parameter for metabolic control assessment. However, with technological advancements, new parameters, such as the glycemia risk index (GRI), have been introduced and clinically utilized. Therefore, exploring the relationships between traditional and novel parameters to understand metabolic control comprehensively is imperative. Materials and methods: This study was conducted at the Pediatric Clinic of the University Hospital of the Republic of Srpska Banja Luka between January and July 2023. The participants were randomly selected, with the inclusion criteria specifying an age greater than eight years and a diabetes type 1 duration exceeding two years. All participants were required to use a sensor-augmented insulin pump for the next three months (90 days), irrespective of prior use, with the suspend-before-low option activated. Results: Of the 35 participants, 30 completed the study, 14 (46.7%) of whom were male. The mean age of the subjects was 14.90 ± 2.88 years, and the mean duration of diabetes was 7.83 ± 4.76 years. Over the 90-day period, HbA1c increased to an average of 7.31%. The analysis revealed significant effects of TIR (ß=-0.771) and GRI (ß=0.651) on HbA1c. Furthermore, GRI and TIR strongly correlated (ß=-0.953). Discussion and conclusion: New parameters generated from the ambulatory glucose profile (AGP) can help clinicians create a complete picture of a patient's metabolic control in relation to HbA1c levels. Additionally, the GRI is a mathematically tailored parameter that incorporates all components of the ambulatory glucose profile and demonstrates strong correlations with laboratory-measured HbA1c and TIR. The GRI potentially can become a valuable statistical parameter for evaluating and managing patients in routine clinical practice.

Emergent inequity of glycaemic metrics for Maori children with type 1 diabetes is negated by early use of continuous glucose monitoring.

AIM: We investigated if continuous glucose monitoring (CGM) in children with type 1 diabetes (T1D) within 12 months of being diagnosed modifies the development of glycaemic outcome inequity on the basis of either ethnicity or socio-economic status (SES). METHOD: De-identified clinical and SES data from the KIWIDIAB data network were collected 12 months after diagnosis in children under 15 years diagnosed with T1D between 1 October 2020 and 1 October 2021. RESULTS: There were 206 children with new onset T1D: CGM use was 56.7% for Maori and 77.2% for Europeans. Mean (SD) HbA1c was 62.4 (14.2) mmol/mol at 12 months post diagnosis, but Maori were 9.4mmol/mol higher compared to Europeans (p<0.001). For those without CGM, Maori had an HbA1c 10.8 (95% CI 2.3 to 19.4, p=0.013) mmol/mol higher than Europeans, whereas there was no evidence of a difference between Maori and Europeans using CGM (62.1 [9.3] mmol/mol vs 58.5 [12.4] mmol/mol p=0.53 respectively). Comparing quintiles of SES, HbA1c was 10.8 (95% CI 4.7 to 16.9, p<0.001) mmol/mol higher in the lowest quintile of SES compared to the highest. CONCLUSION: These observational data suggest CGM use ameliorates the ethnic disparity in HbA1c at 12 months in new onset T1D.

Protein glycation products associate with progression of kidney disease and incident cardiovascular events in individuals with type 1 diabetes.

BACKGROUND: Despite improved glycemic treatment, the impact of glycation on pathological consequences may persist and contribute to adverse clinical outcomes in diabetes. In the present study we investigated the association between serum protein glycation products and progression of kidney disease as well as incident major adverse cardiovascular events (MACE) in type 1 diabetes. METHODS: Fructosamine, advanced glycation end products (AGEs), and methylglyoxal-modified hydro-imidazolone (MG-H1) were measured from baseline serum samples in the FinnDiane study (n = 575). Kidney disease progression was defined as steep eGFR decline (> 3 mL/min/1.73 m2/year) or progression of albuminuria (from lower to higher stage of albuminuria). MACE was defined as acute myocardial infarction, coronary revascularization, cerebrovascular event (stroke), and cardiovascular death. RESULTS: Fructosamine was independently associated with steep eGFR decline (OR 2.15 [95% CI 1.16-4.01], p = 0.016) in the fully adjusted model (age, sex, baseline eGFR). AGEs were associated with steep eGFR decline (OR 1.58 per 1 unit of SD [95% CI 1.07-2.32], p = 0.02), progression to end-stage kidney disease (ESKD) (HR 2.09 per 1 unit of SD [95% CI 1.43-3.05], p < 0.001), and pooled progression (to any stage of albuminuria) (HR 2.72 per 1 unit of SD [95% CI 2.04-3.62], p < 0.001). AGEs (HR 1.57 per 1 unit of SD [95% CI 1.23-2.00], p < 0.001) and MG-H1 (HR 4.99 [95% CI 0.98-25.55], p = 0.054) were associated with incident MACE. MG-H1 was also associated with pooled progression (HR 4.19 [95% CI 1.11-15.89], p = 0.035). Most AGEs and MG-H1 associations were no more significant after adjusting for baseline eGFR. CONCLUSIONS: Overall, these findings suggest that protein glycation products are an important risk factor for target organ damage in type 1 diabetes. The data provide further support to investigate a potential causal role of serum protein glycation in the progression of diabetes complications.

HbA1c and the risk of developing peripheral neuropathy in childhood-onset type 1 diabetes: A follow-up study over 3 decades.

AIMS: We have evaluated long-term weighted mean HbA1c (wHbA1c), HbA1c variability, diabetes duration, and lipid profiles in relation to the development of diabetic peripheral neuropathy (DPN), nephropathy, and retinopathy in childhood-onset type 1 diabetes. MATERIALS AND METHODS: In a longitudinal cohort study, 49 patients (21 women) with childhood-onset type 1 diabetes were investigated with neurophysiological measurements, blood tests, and clinical examinations after a diabetes duration of 7.7 (±3.3) years (baseline) and followed with repeated examinations for 30.6 (±5.2) years. We calculated wHbA1c by integrating the area under all HbA1c values since the diabetes diagnosis. Lipid profiles were analysed in relation to the presence of DPN. Long-term fluctuations of HbA1c variability were computed as the standard deviation of all HbA1c measurements. Data regarding the presence of other diabetes complications were retrieved from medical records. RESULTS: In this follow-up study, 51% (25/49) of the patients fulfilled electrophysiological criteria for DPN. In nerve conduction studies, there was a deterioration in the amplitudes and conduction velocities for the median, peroneal, and sural nerves over time. Patients with DPN had a longer duration of diabetes, higher wHbA1c, and increased HbA1c variability. The lowest wHbA1c value associated with the development of DPN was 62 mmol/mol (7.8%). The presence of albuminuria and retinopathy was positively correlated with the presence of neuropathy. CONCLUSIONS: More than half of the patients had developed DPN after 30 years. None of the patients who developed DPN had a wHbA1c of less than 62 mmol/mol (7.8%).

Does metabolic control of the disease related with bone turnover markers in children with type 1 diabetes mellitus in Turkey?

BACKGROUND: The aim was to evaluate the effect of metabolic control on bone biomarkers in children with type I diabetes. MATERIALS AND METHODS: The children were divided into two groups according to their glycated hemoglobin (HbA1c) (%) levels: a group with HbA1c levels < 8% (n = 16) and: a group with HbA1c levels > 8% (n = 18). The serum total oxidative status (TOS) (µmol/L), total antioxidant status (TAS) (mmol/L), alkaline phosphatase (ALP) (IU/L), osteocalcin (OC) (ng/ml), procollagen type-1-N-terminal peptide (P1NP) (ng/ml), and vitamin D (IU) levels and food consumption frequencies were determined. RESULTS: When patients were classified according to HbA1c (%) levels, those with HbA1c levels < 8% were found to have lower TOS (µmol/L) values (8.7 ± 6.16, 9.5 ± 5.60) and higher serum OC (ng/mL) (24.2 ± 16.92, 22.0 ± 6.21) levels than those with HbA1c levels > 8% (p < 0.05). Regardless of the level of metabolic control, there was a statistically significant association between serum TOS (µmol/L) and P1NP (ng/ml) (p < 0.05) levels, with no group-specific relationship (HbA1c levels <%8 or HbA1c levels >%8). CONCLUSION: HbA1c and serum TOS levels had an effect on bone turnover biomarkers in individuals with type I diabetes.

The association of thyroid autoimmunity with ovarian reserve in women with type 1 diabetes with and without polycystic ovary syndrome.

The aim of the study was to investigate the relation between thyroid autoimmunity (TAI), reflected as the presence of thyroid peroxidase antibodies (TPOAb), and parameters of ovarian reserve in women with type 1 diabetes (T1DM) and polycystic ovary syndrome (PCOS). We studied 83 euthyroid women with T1DM (age - 26 ± 5 years, BMI - 24 ± 3 kg/m2) - 12 with PCOS and positive TPOAb (PCOS + TPOAb), 29 with PCOS with negative TPOAb (PCOS + noTPOAb), 18 without PCOS with positive TPOAb (noPCOS + TPOAb), 24 without PCOS with negative TPOAb (noPCOS + noTPOAb). Serum concentrations of anti-Müllerian hormone (AMH), sex hormones, TSH, thyroid hormones and TPOAb were assessed. The prevalence of TAI was comparable between PCOS and noPCOS. We did not observe differences in hormonal profile or AMH concentration between two PCOS groups-PCOS + TPOAb and PCOS + noTPOAb (p > 0.05). Women with PCOS + TPOAb had lower FSH concentration and higher LH/FSH index than noPCOS + noTPOAb (p = 0.027; p = 0.019, respectively). Moreover, PCOS + TPOAb had lower oestradiol level than noPCOS + TPOAb (p = 0.041). AMH concentration was higher in both groups with PCOS, independent of TPOAb presence, than in noPCOS + noTPOAb (both p < 0.001). The presence of positive TPOAb titre was not related to the studied parameters of ovarian reserve - AMH and ovarian follicle number. In multiple linear regression analysis, the only significant predictor of AMH in the whole studied group with T1DM was total daily insulin dose U/kg (ß = - 0.264; p = 0.022). The presence of TAI did not affect the hormonal profile or ovarian reserve in women with T1DM with and without PCOS.

Pregnancy Outcomes in Women with Poorly Controlled Pregestational Diabetes Mellitus.

BACKGROUND: The prevalence of pregestational diabetes mellitus (PGDM) in women of reproductive age has surged globally, contributing to increased rates of adverse pregnancy outcomes. Hemoglobin A1c (HbA1c) is a crucial marker for diagnosing and monitoring PGDM, with periconceptional levels influencing the risk of congenital anomalies and complications. OBJECTIVES: To evaluate the association between periconceptional HbA1c levels and perinatal complications in pregnant women with poorly controlled PGDM. METHODS: We conducted a retrospective analysis of prospectively collected data of pregnancies between 2010 and 2019, HbA1c > 6% at 3 months prior to conception or during the first trimester. Outcomes of periconceptional HbA1c levels were compared. RESULTS: The cohort included 89 women: 49 with HbA1c 6-8%, 29 with HbA1c 8-10%, and 11 with HbA1c > 10%. Higher HbA1c levels were more prevalent in type 1 diabetics and were associated with increased end-organ damage risk. Women with elevated HbA1c levels tended toward unbalanced glucose levels during pregnancy. The cohort exhibited high rates of preterm delivery, hypertensive disorders, cesarean delivery, and neonatal intensive care unit admission. Overall live birth rate was 83%. While a significant correlation was found between HbA1c levels and preterm delivery, no consistent association was observed with other adverse outcomes. CONCLUSIONS: Periconceptional glycemic control in PGDM pregnancies is important. Elevated HbA1c levels are associated with increased risks of adverse outcomes. Beyond a certain HbA1c level, risks of complications may not proportionally escalate.

Are soluble E-selectin, ICAM-1, and VCAM-1 potential predictors for the development of diabetic retinopathy in young adults, 15-34 years of age? A Swedish prospective cohort study.

The aim of this study was to determine plasma levels of three adhesion molecules that may contribute to the development of diabetic retinopathy; soluble endothelial selectin (sE-selectin), soluble intercellular adhesion molecule-1 (sICAM-1), and soluble vascular cell adhesion molecule-1 (sVCAM-1), in young adults, aged 15-34 years at diagnosis of diabetes, to find potential predictors for development of retinopathy, and to evaluate their relation to diabetes associated autoantibodies. Participants with type 1 (n = 169) and type 2 diabetes (n = 83) were selected from the complications trial of the Diabetes Incidence Study in Sweden and classified in two subgroups according to presence (n = 80) or absence (n = 172) of retinopathy as determined by retinal photography at follow-up 8-10 years after diagnosis of diabetes. Blood samples were collected at diagnosis in 1987-88. The levels of sE-selectin, sICAM-1, and sVCAM-1 were analysed by enzyme-linked immunosorbent assay and islet cell antibodies by a prolonged two-colour immunofluorescent assay. Mean HbA1c (p<0.001) and clinical characteristics: mean body mass index (p = 0.019), systolic blood pressure (p = 0.002), diastolic blood pressure (p = 0.003), male gender (p = 0.026), and young age at diagnosis of diabetes (p = 0.015) remained associated with development of retinopathy in type 1 diabetes. However, in a multivariate analysis only HbA1c remained as a risk factor. sE-selectin was significantly higher in the group with type 2 diabetes and retinopathy, compared to the group with type 2 diabetes without retinopathy (p = 0.04). Regarding sE-selectin, sICAM-1, and sVCAM-1 in participants with type 1 diabetes, no differences were observed between the groups with or without retinopathy. This trial confirmed the role of HbA1c and clinical characteristics as predictors for development of retinopathy in type 1 diabetes. sE-selectin stands out as a potential predictor for development of retinopathy in type 2 diabetes, whereas a predictive role for sICAM-1 and sVCAM-1 could not be identified neither for type 1 nor type 2 diabetes.

Exploring early DNA methylation alterations in type 1 diabetes: implications of glycemic control.

Background: Prolonged hyperglycemia causes diabetes-related micro- and macrovascular complications, which combined represent a significant burden for individuals living with diabetes. The growing scope of evidence indicates that hyperglycemia affects the development of vascular complications through DNA methylation. Methods: A genome-wide differential DNA methylation analysis was performed on pooled peripheral blood DNA samples from individuals with type 1 diabetes (T1D) with direct DNA sequencing. Strict selection criteria were used to ensure two age- and sex-matched groups with no clinical signs of chronic complications according to persistent mean glycated hemoglobin (HbA1c) values over 5 years: HbA1c<7% (N=10) and HbA1c>8% (N=10). Results: Between the two groups, 8385 differentially methylated CpG sites, annotated to 1802 genes, were identified. Genes annotated to hypomethylated CpG sites were enriched in 48 signaling pathways. Further analysis of key CpG sites revealed four specific regions, two of which were hypermethylated and two hypomethylated, associated with long non-coding RNA and processed pseudogenes. Conclusions: Prolonged hyperglycemia in individuals with T1D, who have no clinical manifestation of diabetes-related complications, is associated with multiple differentially methylated CpG sites in crucial genes and pathways known to be linked to chronic complications in T1D.

Germline-like TCR-α chains shared between autoreactive T cells in blood and pancreas.

Human type 1 diabetes (T1D) is caused by autoimmune attack on the insulin-producing pancreatic beta cells by islet antigen-reactive T cells. How human islet antigen-reactive (IAR) CD4+ memory T cells from peripheral blood affect T1D progression in the pancreas is poorly understood. Here, we aim to determine if IAR T cells in blood could be detected in pancreas. We identify paired αß (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new-onset, and established T1D donors, and measured sequence overlap with TCRs in pancreata from healthy, at risk and T1D organ donors. We report extensive TRA junction sharing between IAR T cells and pancreas-infiltrating T cells (PIT), with perfect-match or single-mismatch TRA junction amino acid sequences comprising ~29% total unique IAR TRA junctions (942/3,264). PIT-matched TRA junctions were largely public and enriched for TRAV41 usage, showing significant nucleotide sequence convergence, increased use of germline-encoded versus non-templated residues in epitope engagement, and a potential for cross-reactivity. Our findings thus link T cells with distinctive germline-like TRA chains in the peripheral blood with T cells in the pancreas.

Influence of obesity on blood glucose control using continuous glucose monitoring data among patients with type 1 diabetes.

INTRODUCTION: The global increase in the prevalence rates of overweight or obesity has also affected patients with type 1 diabetes (T1D), where this disease had traditionally been associated with a lean phenotype. On the other hand, the effect of obesity on new glycemic control metrics obtained from continuous glucose monitoring (CGM) in T1D is poorly understood. We wanted to assess whether there is any relationship between BMI (body mass index) and the different CGM metrics or HbA1c. METHODS: Two hundred and twenty-five patients with T1D (47.1% ♀, mean age 42.9±14.7 years) with a CGM for a minimum of 6 months were analysed by downloading their CGM and collecting clinical and anthropometric variables. RESULTS: 35.1% (79/225) of the T1D patients had overweight and 17.3% (39/225) lived with obesity, while the remaining 47.6% had a normal weight. A negative correlation was found between GMI (glucose management indicator) and BMI (-0.2; p=0.008) and HbA1c (-0.2; p=0.01). In contrast, a positive correlation was observed between the total dose of insulin and the BMI (0.3; p<0.0001). No significant correlations were found between BMI and other CGM metrics. CONCLUSIONS: Overweight or obesity do not imply worse glycemic control in patients with T1D or less use of CGM. Possibly, and in order to achieve a good glycemic control, more units of insulin are necessary in these patients which, in turn, makes weight control more difficult.

The Effect of Microbiome-Modulating Agents (MMAs) on Type 1 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Gut microbiome-modulating agents (MMAs), including probiotics, prebiotics, postbiotics, and synbiotics, are shown to ameliorate type 1 diabetes (T1D) by restoring the microbiome from dysbiosis. The objective of this systematic review and meta-analysis was to assess the impact of MMAs on hemoglobin A1c (HbA1c) and biomarkers associated with (T1D). A comprehensive search was conducted in PubMed, Web of Science, Embase, Cochrane Library, National Knowledge Infrastructure, WeiPu, and WanFang Data up to 30 November 2023. Ten randomized controlled trials (n = 630) were included, with study quality evaluated using the Cochrane risk-of-bias tool. Random-effect models with standardized mean differences (SMDs) were utilized. MMA supplementation was associated with improvements in HbA1c (SMD = -0.52, 95% CI [-0.83, -0.20]), daily insulin usage (SMD = -0.41, 95% confidence interval (CI) [-0.76, -0.07]), and fasting C-peptide (SMD = 0.99, 95% CI [0.17, 1.81]) but had no effects on FBG, CRP, TNF-α, IL-10, LDL, HDL, and the Shannon index. Subgroup analysis of HbA1c indicated that a long-term intervention (>3 months) might exert a more substantial effect. These findings suggest an association between MMAs and glycemic control in T1D. Further large-scale clinical trials are necessary to confirm these findings with investigations on inflammation and gut microbiota composition while adjusting confounding factors such as diet, physical activity, and the dose and form of MMA intervention.

What Is the Tech Missing? Nutrition Reporting in Type 1 Diabetes.

INTRODUCTION: Type 1 Diabetes (T1D) presents self-management challenges, requiring an additional 180 daily decisions to regulate blood glucose (BG) levels. Despite the potential, T1D-focused applications have a 43% attrition rate. This work delves into the willingness of people living with T1D (PwT1D) to use technology. METHOD: An online questionnaire investigated the current practices for carbohydrate estimation, nutritional tracking, and attitudes towards technology engagement, along with hypothetical scenarios and preferences regarding technology use. RESULTS: Thirty-nine responses were collected from PwT1D (n = 33) and caregivers (n = 6). Nutrition reporting preferences varied, with 50% favoring 'type and scroll' while 30% preferred meal photographing. Concerning the timing of reporting, 33% reported before meals, 55% after, and 12% at a later time. Improved Time in Range (TIR) was a strong motivator for app use, with 78% expressing readiness to adjust insulin doses based on app suggestions for optimizing TIR. Meal descriptions varied; a single word was used in 42% of cases, 23% used a simple description (i.e., "Sunday dinner"), 30% included portion sizes, and 8% provided full recipes. CONCLUSION: PwT1D shows interest in using technology to reduce the diabetes burden when it leads to an improved TIR. For such technology to be ecologically valid, it needs to strike a balance between requiring minimal user input and providing significant data, such as meal tags, to ensure accurate blood glucose management without overwhelming users with reporting tasks.

A set of circulating microRNAs belonging to the 14q32 chromosome locus identifies two subgroups of individuals with recent-onset type 1 diabetes.

Circulating microRNAs (miRNAs) are linked to the onset and progression of type 1 diabetes mellitus (T1DM), thus representing potential disease biomarkers. In this study, we employed a multiplatform sequencing approach to analyze circulating miRNAs in an extended cohort of prospectively evaluated recent-onset T1DM individuals from the INNODIA consortium. Our findings reveal that a set of miRNAs located within T1DM susceptibility chromosomal locus 14q32 distinguishes two subgroups of individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, confirming the identification of these subgroups, which we have named cluster A and cluster B. Remarkably, cluster B T1DM individuals, who exhibit increased expression of a set of 14q32 miRNAs, show better glycemic control and display a different blood immunomics profile. Our findings suggest that this set of circulating miRNAs can identify two different T1DM subgroups with distinct blood immunomics at baseline and clinical outcomes during follow-up.

Cohort profile: the 'Biomarkers of heterogeneity in type 1 diabetes' study-a national prospective cohort study of clinical and metabolic phenotyping of individuals with long-standing type 1 diabetes in the Netherlands.

PURPOSE: The 'Biomarkers of heterogeneity in type 1 diabetes' study cohort was set up to identify genetic, physiological and psychosocial factors explaining the observed heterogeneity in disease progression and the development of complications in people with long-standing type 1 diabetes (T1D). PARTICIPANTS: Data and samples were collected in two subsets. A prospective cohort of 611 participants aged ≥16 years with ≥5 years T1D duration from four Dutch Diabetes clinics between 2016 and 2021 (median age 32 years; median diabetes duration 12 years; 59% female; mean glycated haemoglobin (HbA1c) 61 mmol/mol (7.7%); 61% on insulin pump; 23% on continuous glucose monitoring (CGM)). Physical assessments were performed, blood and urine samples were collected, and participants completed questionnaires. A subgroup of participants underwent mixed-meal tolerance tests (MMTTs) at baseline (n=169) and at 1-year follow-up (n=104). Genetic data and linkage to medical and administrative records were also available. A second cross-sectional cohort included participants with ≥35 years of T1D duration (currently n=160; median age 64 years; median diabetes duration 45 years; 45% female; mean HbA1c 58 mmol/mol (7.4%); 51% on insulin pump; 83% on CGM), recruited from five centres and measurements, samples and 5-year retrospective data were collected. FINDINGS TO DATE: Stimulated residual C-peptide was detectable in an additional 10% of individuals compared with fasting residual C-peptide secretion. MMTT measurements at 90 min and 120 min showed good concordance with the MMTT total area under the curve. An overall decrease of C-peptide at 1-year follow-up was observed. Fasting residual C-peptide secretion is associated with a decreased risk of impaired awareness of hypoglycaemia. FUTURE PLANS: Research groups are invited to consider the use of these data and the sample collection. Future work will include additional hormones, beta-cell-directed autoimmunity, specific immune markers, microRNAs, metabolomics and gene expression data, combined with glucometrics, anthropometric and clinical data, and additional markers of residual beta-cell function. TRIAL REGISTRATION NUMBER: NCT04977635.

Imbalance of APOB Lipoproteins and Large HDL in Type 1 Diabetes Drives Atherosclerosis.

BACKGROUND: Individuals with type 1 diabetes (T1D) generally have normal or even higher HDL (high-density lipoprotein)-cholesterol levels than people without diabetes yet are at increased risk for atherosclerotic cardiovascular disease (CVD). Human HDL is a complex mixture of particles that can vary in cholesterol content by >2-fold. To investigate if specific HDL subspecies contribute to the increased atherosclerosis associated with T1D, we created mouse models of T1D that exhibit human-like HDL subspecies. We also measured HDL subspecies and their association with incident CVD in a cohort of people with T1D. METHODS: We generated LDL receptor-deficient (Ldlr-/-) mouse models of T1D expressing human APOA1 (apolipoprotein A1). Ldlr-/-APOA1Tg mice exhibited the main human HDL subspecies. We also generated Ldlr-/-APOA1Tg T1D mice expressing CETP (cholesteryl ester transfer protein), which had lower concentrations of large HDL subspecies versus mice not expressing CETP. HDL particle concentrations and sizes and proteins involved in lipoprotein metabolism were measured by calibrated differential ion mobility analysis and targeted mass spectrometry in the mouse models of T1D and in a cohort of individuals with T1D. Endothelial transcytosis was analyzed by total internal reflection fluorescence microscopy. RESULTS: Diabetic Ldlr-/-APOA1Tg mice were severely hyperglycemic and hyperlipidemic and had markedly elevated plasma APOB levels versus nondiabetic littermates but were protected from the proatherogenic effects of diabetes. Diabetic Ldlr-/-APOA1Tg mice expressing CETP lost the atheroprotective effect and had increased lesion necrotic core areas and APOB accumulation, despite having lower plasma APOB levels. The detrimental effects of low concentrations of larger HDL particles in diabetic mice expressing CETP were not explained by reduced cholesterol efflux. Instead, large HDL was more effective than small HDL in preventing endothelial transcytosis of LDL mediated by scavenger receptor class B type 1. Finally, in humans with T1D, increased concentrations of larger HDL particles relative to APOB100 negatively predicted incident CVD independently of HDL-cholesterol levels. CONCLUSIONS: Our results suggest that the balance between APOB lipoproteins and the larger HDL subspecies contributes to atherosclerosis progression and incident CVD in the setting of T1D and that larger HDLs exert atheroprotective effects on endothelial cells rather than by promoting macrophage cholesterol efflux.

Effect of Wearable Technology on Metabolic Control and the Quality of Life in Children and Adolescents with Type 1 Diabetes: A Systematic Review and Meta-Analysis

Background: Type 1 diabetes is one of the most common chronic diseases in children. Wearable technology (insulin pumps and continuous glucose monitoring devices) that makes diabetes management relatively simple, in addition to education and follow-ups, enhances the quality of life and health of individuals with diabetes. Aims: To evaluate the impact of wearable technology on metabolic management and the quality of life in children and adolescents with type 1 diabetes. Study Design: Systematic review and meta-analysis. Methods: The Preferred Reporting System for Systematic Reviews and Meta-Analyses was used to conduct a systematic review and meta-analysis. PubMed, Web of Science, MEDLINE, Cochrane Library, EBSCO, Ulakbim and Google Scholar were searched in July 2022 and July 2023 using predetermined keywords. The methodological quality of the studies was evaluated using the Joanna Briggs Institute's Critical Appraisal Checklists for randomized controlled experimental and cross-sectional studies. The meta-analysis method was used to pool the data. Results: Eleven studies published between 2011 and 2022 were included. The total sample size of the included studies was 1,853. The meta-analysis revealed that the decrease in hemoglobin A1C (HbA1c) level in those using wearable technology was statistically significant [mean difference (MD): -0.33, Z = 2.54, p = 0.01]. However, the technology had no effect on the quality of life [standardized mean difference (SMD): 0.44, Z = 1.72, p = 0.09]. The subgroup analyses revealed that the decrease in the HbA1c level occurred in the cross-sectional studies (MD: -0.49, Z = 2.54, p = 0.01) and the 12-19 (MD = 0.59, Z = 4.40, p < 0.001) and 4-18 age groups (MD: -0.31, Z = 2.56, p = 0.01). The subgroup analyses regarding the quality of life revealed that there was no difference according to the research design. However, the quality of life was higher in the wearable technology group than in the control group in the 8-12 and 4-18 age groups (SMD: 1.32, Z = 2.31, p = 0.02 and SMD: 1.00, Z = 5.76, p < 0.001, respectively). Conclusion: Wearable technology effectively reduces the HbA1c levels in children and adolescents with type 1 diabetes in some age groups. However, it does not affect the quality of life.