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Epigenetic Regulation of VCAM-1 by Lipoxin A4 Is Renoprotective Against Diabetic Kidney Disease

Chronic low-grade inflammation underlies many microvascular complications of diabetes, including diabetic kidney disease (DKD). Lipoxins (LXs), an endogenously produced family of lipid mediators, resolve inflammation and protect against renal scarring as occurs in DKD. This study examined the mechanism by which LXs protect against DKD, focusing on the regulation of VCAM-1 and the recruitment of macrophages to the diabetic glomerulus. LXA4 and two fourth-generation mimetics were assessed in diabetic ApoE knockout mice, followed by in vitro studies in the main renal cell populations, including podocytes, proximal tubular, mesangial, and glomerular endothelial cells. LXs attenuated albuminuria, mesangial expansion, and collagen and fibronectin deposition as both a preventive and delayed intervention in experimental DKD. LXs also consistently attenuated the TNF-α–induced expression of VCAM-1 in all the human and mouse renal cell populations examined. Further analysis identified that the renoprotection was in part mediated by an epigenetic modification of the VCAM-1 gene through H3K4 monomethylation, which did not appear to be dependent on NF-κB activation in human glomerular endothelial cells. LXs protect against DKD by modulating glomerular endothelial cell inflammation and via a novel LX-mediated epigenetic mechanism regulating the VCAM-1 promoter in these cells.Article HighlightsLipoxins (LXs) protect against diabetic kidney disease (DKD) by resolving chronic low-grade inflammation, but the exact mechanism by which this occurs is not known.We investigated the effect of LXs on inflammatory markers and the recruitment of macrophages to the diabetic glomerulus by using LXs as both a preventive and delayed interventional treatment in streptozotocin-induced diabetic ApoE knockout mice.Protection against DKD was associated with reduced glomerular macrophage accumulation. LXs also attenuated the expression of VCAM1 in glomerular endothelial cells.LXs protect against DKD in part by a mechanism that reduces VCAM1 gene expression via H3K4 monomethylation on the VCAM1 gene.

Metabolic Signature of Gestational Diabetes Mellitus and Risk of Adverse Birth Outcomes: A Prospective Birth Cohort Study

Gestational diabetes mellitus (GDM) is a heterogeneous condition diagnosed solely through glucose. It is characterized by profound perturbations in the metabolome, with specific metabolic profiles linked to adverse birth outcomes. Metabolomics can reveal population heterogeneity in health and disease. Here, we used nontargeted metabolomics to systematically profile the circulating metabolome in 2,050 pregnant women during midpregnancy, identifying 30 metabolites that define the GDM metabolic signature (mGDM). Participants were stratified into four groups by distinct glycemic and metabolic profiles, namely normoglycemic non-mGDM, hyperglycemic non-mGDM, normoglycemic mGDM, and hyperglycemic mGDM, and associations with subsequent adverse birth outcomes were assessed. Compared with normoglycemic non-mGDM, normoglycemic mGDM demonstrated nearly a twofold increased risk of preterm birth (odds ratio [OR] 1.93, 95% CI 1.02–3.65) and large for gestational age (OR 2.11, 95% CI 1.53–2.92). Conversely, the hyperglycemic non-mGDM group did not show elevated risks in adverse birth outcomes versus the normoglycemic group. The hyperglycemic mGDM profile was associated with higher risks of preterm birth (OR 2.37, 95% CI 1.04–5.39), large for gestational age (OR 2.28, 95% CI 1.50–3.47), congenital malformations (OR 1.87, 95% CI 1.03–3.39), and neonatal intensive care unit (NICU) admissions (OR 1.69, 95% CI 1.09–2.61). We observed a stepwise increase in adverse outcome risk across the four-level metabolic-glycemic ission). Taken together, our study outlines the metabolic profile of GDM and reveals clinically relevant heterogeneity in adverse pregnancy outcomes by metabolic signature. Integrating blood glucose and metabolomics may improve risk stratification and advance precision maternal care.Article HighlightsWomen diagnosed with gestational diabetes mellitus (GDM) exhibit variability in symptom presentation and pregnancy outcomes. The heterogeneity in metabolic features beyond a GDM diagnosis and their influences on health outcomes is less studied.We aimed to identify the metabolic signatures of GDM, stratify pregnant women by glycemic and metabolic profiles, and further investigate the intergroup heterogeneity and their respective associations with adverse birth outcomes.Maternal metabolic dysregulation, rather than blood glucose alone, exerts more profound associations with adverse outcomes in pregnant women and their offspring.Targeted risk stratification using metabolomics offers a novel opportunity for precision medicine in GDM, potentially improving health management of pregnant women.

Memory Regulatory T Cells as a Biomarker of Early Type 1 Diabetes

Type 1 diabetes (T1D) is the most common chronic autoimmune disease in children, driven by a breakdown in self-tolerance and T cell–mediated immune attack of pancreatic β-cells. There are no biomarkers to effectively diagnose autoimmunity before disease onset and clinical symptom development. Here, we applied deep multiparametric immunophenotyping to compare immune landscapes in 38 patients with new-onset T1D, 24 siblings, and 18 healthy control participants (HCs). Patients with T1D underwent clinical and metabolic evaluations. Immune populations in fresh whole-blood samples were analyzed using a panel of 26 antibodies, detecting 39 different cell populations. Memory regulatory T cells (memory Tregs) were significantly increased in patients with T1D (P < 0.05) and their siblings (P < 0.01) compared with HCs but not between patients with T1D and siblings. Memory Tregs were associated with disease status and age in multivariable analysis. There was a positive correlation between age and memory Tregs in the HC and sibling groups but not in patients with T1D. Baseline memory Treg levels in siblings resembled those of patients with T1D. These findings highlight the existence of an age-independent, disease-specific immune fingerprint that could serve as a minimally invasive biomarker for early diagnosis and personalized immunotherapy. Further studies using functional and single-cells analysis are needed to confirm memory Tregs as a pathogenic trait.Article HighlightsThere are more memory regulatory T cells (Tregs) in individuals with type 1 diabetes (T1D) and siblings than in healthy control (HC) individuals.Individuals with T1D and their siblings share an immunological profile, with siblings displaying an intermediate phenotype that overlaps with both T1D and HC individuals.Memory Tregs increased with age in HC individuals and siblings but not in individuals with T1D.Diabetic ketoacidosis status had no impact on immune cell populations in patients with T1D.

Multiple Mechanisms Contribute to Robust Type 1 Diabetes Protection in Nfkbid - Overexpressing NOD Mice

We previously reported that transgenic overexpression of Nfkbid in NOD mice led to robust type 1 diabetes protection associated with enhanced negative selection of autoreactive T cells and expansion of regulatory T cells (Tregs) with increased suppressive capacity. The goal of this study was to further identify cellular and molecular mechanisms underlying strong protection from type 1 diabetes imbued by overexpressing Nfkbid. Transcript analysis of Tregs from Nfkbid-overexpressing NOD mice show enrichment of cellular replication pathways. Effector T cells from Nfkbid-overexpressing NOD mice have increased indicators of activation-induced exhaustion in pancreatic lymph nodes and islets. This trait is intrinsic to Nfkbid-overexpressing T cells, as ex vivo anti–CD3 stimulation of splenic-derived T cells can reproduce this phenotype. Anti–PD-1 administration breaks the diabetes protective effect. Furthermore, we found that Nfkbid-overexpressing dendritic cells, but not B cells, have an enhanced capacity to stimulate proliferation of diabetogenic AI4 CD8+ T cells (with wild-type levels of Nfkbid). Conversely, B cells, but not dendritic cells, drive enhanced de novo conversion of regulatory T cells from effector T cells. Together, this study documents additional mechanisms that likely synergize to contribute to the diabetes-protective effects of Nfkbid overexpression. Understanding the mechanisms underlying protection from Nfkbid overexpression may lead to novel therapeutic avenues.Article HighlightsT cells from Nfkbid-overexpressing NOD mice have increased evidence of exhaustion, and this feature is intrinsic to T cells following activation.Dendritic cells, but not B cells, overexpressing Nfkbid can drive enhanced CD8+ T-cell activation.Nfkbid-overexpressing B cells, but not dendritic cells, drive enhanced T effector–to–regulator T cell conversion.

Predicting the Timing of the Metabolic Inflection Point in Type 1 Diabetes Progression Using Machine Learning and Survival Analysis Models

An inflection point (IP) marking accelerated β-cell decline occurs ∼1–2 years before type 1 diabetes diagnosis. Precisely determining this timing could optimize clinical intervention. We developed machine learning models to predict proximity to the inferred metabolic IP using oral glucose tolerance test (OGTT) data from islet autoantibody-positive individuals in the TrialNet Pathway to Prevention study. OGTTs were retrospectively labeled by estimating time to the IP using thresholds from 1.2 to 1.6 years. Models were trained on engineered glucose and C-peptide dynamics, slopes, and composite indices, with feature selection by recursive feature elimination (RFE). Classifiers included support vector machines (SVM), random forests, and gradient boosting; a Cox proportional hazards model was also applied to estimate visit-level time to diagnosis and derive time-to-IP predictions. External validation was performed in the independent Diabetes Prevention Trial–Type 1 cohort. The best-performing model—SVM with RFE at the 1.4-year threshold—achieved an area under the curve of 0.77 (95% CI 0.72–0.82). The Cox model provided complementary numeric estimates of time to diagnosis and time to IP, sensitive to the cohort-level lead time offset (Δ). These findings show that machine learning and survival analysis can support early metabolic shift detection, enabling timely risk stratification and personalized monitoring in at-risk individuals.Article HighlightsWe undertook this study to improve early identification of the metabolic inflection point (IP) preceding clinical type 1 diabetes in autoantibody-positive individuals.We aimed to develop and validate machine learning models using oral glucose tolerance test–derived dynamic features to detect proximity to the IP.A support vector machine trained on TrialNet Pathway to Prevention and tested on Diabetes Prevention Trial–Type 1 achieved an area under the curve of 0.77 at 1.4 years prior to diagnosis, with strong calibration and interpretability. Additionally, a Cox proportional hazards model provided numeric estimates of time to IP, offering complementary predictions.These results can support earlier intervention and timely monitoring through personalized oral glucose tolerance test–based risk stratification.

Ketogenic Diet and Exercise Improve Peripheral Neuropathy in a Mouse Model of Metabolic Syndrome

Metabolic syndrome (MetS) is a growing health concern that increases risk for peripheral neuropathy (PN), defined by nerve degeneration and sensory dysfunction. Although lifestyle strategies, like ketogenic diet (KD) and exercise, are known to mitigate MetS, their efficacy in maintaining nerve health or reversing established PN is less clear. First, in a maintenance paradigm, we tested whether long-term KD could maintain nerve health in mice, as opposed to a Western-style high-fat diet (HFD) that induces MetS PN. Second, in an intervention paradigm of mice with established MetS PN, we compared the efficacy of low-fat standard diet, KD, exercise, and combined KD-exercise interventions in reversing MetS PN. Long-term KD maintained body composition, nerve function, and neuromuscular innervation. In mice with established MetS PN, all interventions improved metabolic parameters and nerve function, albeit to varying extents. Transcriptomic profiling revealed that HFD dysregulated genes related to cytoskeletal dynamics and inflammation in sciatic nerve, with interventions partially reversing these changes. In muscle, dietary interventions modulated fatty acid and amino acid metabolism. Notably, exercise generated a unique gene expression signature in nerve and muscle. These findings support KD and exercise as promising approaches for treating MetS PN and offer mechanistic insights into their therapeutic benefits.Article HighlightsMetabolic syndrome (MetS) increases risk for peripheral neuropathy (PN), a progressive nerve disorder with limited treatment options.We examined whether long-term ketogenic diet (KD) could maintain nerve health, and whether KD, exercise, or both could reverse established MetS PN.Maintenance KD preserved body composition, liver health, and nerve function, while all interventions improved metabolic and nerve outcomes to varying degrees. Transcriptomic profiling of sciatic nerve and gastrocnemius muscle revealed partial reversal of MetS-induced inflammatory, cytoskeletal, and metabolic gene alterations.These findings highlight KD and exercise for treating MetS PN.

The Effect of Midpregnancy Screening for Gestational Diabetes Mellitus on Pregnancy Outcomes: The TESGO Randomized Controlled Trial

OBJECTIVENewborns delivered by women with gestational diabetes mellitus (GDM) have accelerated intrauterine growth earlier than the current recommended screening period. We aimed to determine whether universal GDM screening using a single oral glucose intolerance test (OGTT) at 18–20 weeks’ gestation improves pregnancy outcomes compared with standard screening at 24–28 weeks’ gestation.RESEARCH DESIGN AND METHODSWe conducted a dual-center, parallel, randomized controlled trial with a planned interim analysis in singleton pregnant women to compare the effect of midpregnancy screening for GDM at 18–20 weeks’ gestation and standard screening at 24–28 weeks’ gestation. GDM was universally screened and diagnosed using 75-g OGTTs and the International Association of the Diabetes and Pregnancy Study Groups criteria. The primary outcome was a composite measure of primary cesarean delivery, birth weight >90th percentile, neonatal hypoglycemia, cord serum C-peptide >90th percentile, gestational hypertension, preeclampsia, and birth trauma.RESULTSThe trial was stopped early for futility after the interim analysis. Of the 967 women included in the intention-to-treat analysis, the primary outcome was not significantly different between the two groups. Neonatal hypoglycemia was significantly lower and neonatal adiposity in women with GDM was higher in the midpregnancy screening group compared with the standard screening group. Adverse event rates were similar between the two groups.CONCLUSIONSAdvancing universal GDM screening to midpregnancy at 18–20 weeks’ gestation may not improve pregnancy outcomes, except for a reduction in neonatal hypoglycemia. Newborns of women diagnosed with GDM through midpregnancy screening had higher neonatal adiposity.

Generalizability of Progression Risk in the TN-10 Trial to a European Population With or Without a First-Degree Relative With Type 1 Diabetes

OBJECTIVEIn the TrialNet 10 Anti-CD3 Prevention (TN-10) trial, teplizumab delayed onset of stage 3 type 1 diabetes in U.S. and Canadian individuals with stage 2 disease who had a relative with type 1 diabetes. Here, the generalizability of the population risk in TN-10 to a European population with or without first-degree relatives (FDRs) with type 1 diabetes was investigated.RESEARCH DESIGN AND METHODSThis retrospective study used data from participants with stage 2 type 1 diabetes from the TN-10 placebo arm and the Fr1da population-based screening program in Germany (Fr1da group) to investigate time to progression from stages 2–3 type 1 diabetes. The study only had sufficient power to detect large differences.RESULTSRisk of progression to stage 3 type 1 diabetes was comparable between the TN-10 placebo arm (n = 32) and the Fr1da group (n = 152; hazard ratio [HR] = 1.3 [95% CI 0.8–2.1]). Once prognostic factors significantly associated with progression in this study (anti–IA-2 antibodies, HbA1c >5.7%, and 120-min oral glucose tolerance test) were included in the model, the adjusted HR was 1.1 (95% CI 0.6–2.1). Fr1da group participants with (n = 45) and without (n = 107) FDRs with type 1 diabetes had similar time to progression to stage 3. Age-based subanalysis demonstrated minimal impact of age on progression time.CONCLUSIONSTime to progression to stage 3 appeared similar between the TN-10 placebo arm and the Fr1da group and between participants with and without FDRs with disease. Results suggest progression risk from the TN-10 trial may be generalizable to European populations with or without FDRs with type 1 diabetes.

Toward Disease-Modifying Therapies in Type 1 Diabetes: Focus on Teplizumab

The worldwide incidence of type 1 diabetes continues to rise at an alarming rate. One hundred years after the introduction of insulin, the long-entertained hope of moving from symptomatic treatment to disease-modifying therapies is finally taking shape with regulatory approval of teplizumab to delay the onset of stage 3 disease. Here we review teplizumab’s mechanism of action, setting it against the background of emerging disease-modifying therapies for clinical practice, in language accessible to practicing clinicians. A clinical diagnosis of type 1 diabetes and insulin dependence results from progressive autoimmune destruction of pancreatic β-cells as part of a complicated dialogue between the immune system and the islet. Infusion with teplizumab, a humanized monoclonal antibody that binds the ε-chain of the T lymphocyte CD3 molecule, delays progression from stage 2 to clinical stage 3 type 1 diabetes by almost 3 years. The mechanism of action of teplizumab involves partial agonistic signaling via CD3/TCR and subsequent deactivation, promoting exhaustion of pancreatic β-cell-reactive CD8+ T lymphocytes and induction of regulatory T lymphocytes, thereby restoring self-tolerance. With regulatory approval of this agent, clinical practice has entered a new era for treating people with type 1 diabetes, in which disease modification can become the new standard of care. Implementation of global screening for autoantibodies and dysglycemia is underway, enabling efforts to intervene during asymptomatic stages of the disease before insulin treatment is required.

Real-World Prospective Validation and Economic Evaluation of Deep Learning– Based Diabetic Retinopathy Detection From Fundus Photographs: A Systematic Review and Meta-analysis

BACKGROUNDDeep learning (DL) has shown promise in delivering diagnostic and economic benefits for detecting diabetic retinopathy (DR) from fundus photographs (FPs). However, evidence synthesis of model validation in prospective, real-world settings remains limited.PURPOSETo assess the feasibility of implementing DL-DR systems using FPs across different countries by synthesizing prospective validation and economic evidence.DATA SOURCESFive databases were searched until 13 August 2025.STUDY SELECTIONStudies prospectively assessing diagnostic performance and/or studies conducting economic analyses of DL-DR systems using FPs were selected.DATA EXTRACTIONCharacteristics of all studies, performance parameters of prospective validation studies, and economic outcomes of economic analysis studies were extracted.DATA SYNTHESISForty-seven studies were included in the meta-analysis. The pooled performance was the highest in detecting vision-threatening DR (area under the receiver operating characteristic curve [AUROC] 0.974), followed by any DR (AUROC 0.965), then referable DR (RDR) (AUROC 0.959). Study region, clinical pathway, mydriasis, image quality control, sample size, grading criteria, reference standard, and model architecture significantly affected model performance in RDR detection. Fifteen studies were included in the economic commentary, showing that DL-based DR screening was cost-effective in high-income countries, whereas results in middle-income countries were mixed, depending on compliance rates, glycemic control, and initial costs.LIMITATIONSA paucity of studies assessing multiple severities of DR or diabetic macular edema restricted our ability to perform subgroup analyses. Insights into low-income countries were limited by a lack of studies in these regions.CONCLUSIONSDL-DR systems using FPs had high discriminative performance in prospective real-world settings and hold promise to improve cost-effectiveness, especially in high-income countries.

Safety and Feasibility of a Fully Automated Insulin Delivery System: FCL@Home, a Multicenter Randomized Clinical Trial in Individuals With Type 1 Diabetes

OBJECTIVEAutomated insulin delivery (AID) requiring manual premeal boluses are the standard of care for people with type 1 diabetes (T1D). We evaluated the safety and feasibility of the Automated Insulin Delivery as an Adaptive NETwork (AIDANET) system used without meal announcements in both supervised and home settings across a diverse population of people with T1D.RESEARCH DESIGN AND METHODSAdults (age >25 years), young adults (age 18–25 years), and adolescents (age 14–18 years) were enrolled at three sites in the U.S. to compare the AIDANET system used in fully closed-loop (FCL) with usual care (UC) in a randomized crossover study. Participants spent ∼5 days using FCL in a supervised environment followed by ∼7 days of use at home. The prespecified primary outcome was defined as the change in mean sensor glucose (MSG) between the 2nd week of UC and the week of the FCL at-home period.RESULTSOverall, 34 participants (12 adults, 10 young adults, 12 adolescents; mean age 25.4 ± 12.6 years; 62% female; mean HbA1c 8.0 ± 1.1%; 94% hybrid closed loop users during UC) completed the study. MSG improved from 178 to 164 mg/dL (UC vs. FCL P = 0.0058). The percentages of time in range (70–180 mg/dL), time in tight range (70–140 mg/dL), and time above range (>180 mg/dL and >250 mg/dL) also significantly improved, primarily overnight. The percentage of time <70 and <54 mg/dL were significantly noninferior in FCL compared with UC.CONCLUSIONSFCL therapy with the AIDANET system can significantly improve average glycemic control while removing the need for mealtime bolusing for a broad population of people with T1D.

Interoceptive Awareness Moderates the Relationship Between Hypoglycemia Exposure and Symptom Recognition in Adults With Type 1 Diabetes

OBJECTIVEHypoglycemia exposure lowers the glycemic threshold for symptom recognition, contributing to impaired awareness of hypoglycemia (IAH). Interoceptive awareness, the ability to sense and interpret internal bodily sensations, is associated with a lower risk of IAH. We tested the hypothesis that interoceptive awareness moderates the association between hypoglycemia exposure and glycemic threshold for autonomic symptom recognition.RESEARCH DESIGN AND METHODSAdults with type 1 diabetes completed validated surveys assessing interoceptive awareness (Multidimensional Assessment of Interoceptive Awareness, Version 2 [MAIA-2]) and the glycemic threshold for autonomic symptom recognition (Hypoglycemia Awareness Questionnaire Symptom Level subscale) and provided 30-day continuous glucose monitoring data. We used proportional odds logistic regression to examine whether the MAIA-2 Attention Regulation scale score (measuring the ability to sustain and control attention to bodily sensations) moderated the association between hypoglycemia exposure (percent time [%-time] <60 mg/dL) and symptom level, adjusting for covariates.RESULTSAmong 717 participants (94% White, 52% female, mean [SD] age 44 [15] years; diabetes duration 25 [15] years; 17% with IAH), 30-day hypoglycemia exposure (%-time <60 mg/dL) was 0.8 (1.4%) (11.5 [20.2] min/day). Higher hypoglycemia exposure was associated with lower symptom levels (odds ratio [OR] 0.45; 95% CI 0.31, 0.66; P < 0.001). Interoceptive awareness alone was not associated with symptom level (OR 0.93; 95% CI 0.78, 1.12), but higher interoceptive awareness attenuated the association between hypoglycemia exposure and symptom level (OR 1.14; 95% CI 1.01, 1.27; P < 0.05).CONCLUSIONSInteroceptive awareness moderated the association between hypoglycemia exposure and glycemic threshold for symptom recognition. Research is needed to examine whether interventions can improve interoceptive awareness and, thereby, restore awareness of hypoglycemia.

Metabolic Factors Modulating the Connection Between Diabetes and Pulmonary Alterations

OBJECTIVEType 1 and 2 diabetes have been variably associated with reduced forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), but mechanisms remain unclear. This study examined the role of glucose and insulin metabolism for pulmonary function across diabetes (sub)types and normal glucose tolerance as the control (CON) in the German Diabetes Study (GDS) and assessed causality by Mendelian randomization (MR) analyses in independent cohorts.RESEARCH DESIGN AND METHODSIn GDS, 426 spirometry measurements of participants with type 1 diabetes, 482 of participants with type 2 diabetes, and 244 of CON were cross-sectionally analyzed after phenotyping, including Botnia clamps for insulin sensitivity (M value), secretion, and clearance. Associations between metabolic measures and lung function were assessed using generalized linear models, adjusting for confounders. MR analysis used data from the MAGIC (Meta-Analyses of Glucose and Insulin-Related Traits Consortium) consortium (HOMA-insulin resistance [IR], n = 37,037) and the UK Household Longitudinal Study (pulmonary function, n = 321,047).RESULTSIn GDS, higher M value (all β > 0.18, P < 0.0001) and insulin clearance (all β = 0.05, P < 0.050) were associated with higher FEV1 and FVC. Compared with type 1 diabetes and CON, type 2 diabetes had lower FEV1 and FVC, which associated with M value (all β > 0.17, P < 0.050). FEV1 was associated with daily insulin doses in type 1 diabetes (β = −0.21, P = 0.0006). FEV1 was associated with type 2 diabetes (β = −0.19, P = 0.0052), severe insulin resistant (β = −0.27, P = 0.039), and mild age-related diabetes (β = −0.23, P = 0.0033). MR supported a causal association between HOMA-IR and lower FEV1 (β = −0.13, P = 0.0018).CONCLUSIONSLower FEV1 and FVC in diabetes are linked to insulin resistance, impaired clearance, and higher insulin doses, all of which result in higher insulinemia and likely represent underlying pathogenic mechanisms.

MiniMed 780G Advanced Hybrid Closed-Loop System Use During Days Without User-Initiated Boluses

OBJECTIVETo evaluate glycemic metrics and insulin delivery during real-world use of the MiniMed 780G (MM780G) system on days when users did not administer boluses.RESEARCH DESIGN AND METHODSGlobal CareLink personal data of consenting MM780G users (N = 369,467) uploaded from 2 January 2020 to 31 March 2025 were analyzed. Among these individuals, 54,553 users experienced ≥10 days without any user-initiated boluses. Evaluated key metrics included time in range (TIR; 70–180 mg/dL), time below range (TBR; <70 mg/dL), time above range (>180 mg/dL), the glucose management indicator (GMI), and total insulin delivered. These were analyzed for the overall population who did not initiate boluses and for those who used and did not use recommended optimal settings (ROS; defined as a 100 mg/dL glucose target and a 2-h active insulin time). Subgroup analyses were conducted by age (≤15 or >15 years) and diabetes type (type 1 or 2).RESULTSOn days when boluses were missed, ROS users had a mean sensor glucose (SG) of 149.2 mg/dL, with mean TIR, TBR, and GMI of 76.3%, 0.8%, and 6.9%, respectively, whereas non-ROS users had a mean SG of 159.7 mg/dL with mean TIR, TBR, and GMI of 69.3%, 0.9%, and 7.1%, respectively. ROS use was associated with more individuals achieving consensus TIR, TBR, and GMI goals.CONCLUSIONSThese data demonstrate effective glycemic control with the MM780G system on days when some users did not initiate boluses. A greater proportion of real-world users achieved glycemic goals when ROS were used.

Impact of Maternal Diabetes in Pregnancy on Newborn IgG Antibody Repertoire and Infection Risk in the First 6 Months of Life

OBJECTIVETo investigate whether maternal diabetes in pregnancy was associated with altered neonatal global IgG repertoire and early-life infections in offspring.RESEARCH DESIGN AND METHODSThis study included 2,702 mother-infant pairs enrolled at birth and followed longitudinally at the Boston Medical Center. Maternal diabetes and infant infections were extracted from electronic medical records. Cord blood IgG antibodies against a wide range of microbes were quantified using Phage ImmunoPrecipitation Sequencing.RESULTSOverall, 327 infants (12.1%) were born to mothers with gestational diabetes mellitus (GDM) and 138 (5.1%) to mothers with pregestational diabetes mellitus (PDM). Of these, 416 infants (15.4%) and 1,425 infants (52.7%) had at least one infection in the neonatal period and the first 6 months of life, respectively. Compared with no diabetes, both maternal GDM (risk ratio [RR] 1.20, 95% CI 1.09–1.32) and PDM (RR 1.28, 95% CI 1.12–1.47) were significantly associated with an elevated risk of infections in infants during the first 6 months. These associations were particularly pronounced among infants born preterm, delivered via cesarean section, or with lower IgG repertoire diversity. Additionally, PDM was associated with a lower newborn’s global IgG repertoire diversity, compared with no diabetes, with the effect more marked among infants whose mothers had prepregnancy overweight or obesity.CONCLUSIONSThis study provides strong evidence of an increased infection risk in the infants of mothers with diabetes and a reduced IgG repertoire diversity in those of PDM mothers. Lower IgG diversity exacerbated the diabetes-infection link. These findings suggest that maternal metabolic conditions may impact an infant’s passive immunity and susceptibility to infections.