Diabetes mellitus represents a heterogenous set of disorders that share one major characteristic – hyperglycaemia. The recommended way of measuring plasma glucose and the threshold used to define what is normal or abnormal have gone through several iterations over the past few decades. These recommendations, and the current definitions and classification of diabetes mellitus and intermediate states of hyperglycaemia, are reviewed here. Differences in approach between the USA and other parts of the world are highlighted.

OBJECTIVE To assess whether initiating metformin at 25 weeks' gestation influences exclusive breastfeeding at 12 weeks postpartum in gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS We performed a prespecified secondary analysis of the Effectiveness of Metformin in Addition to Usual Care in the Reduction of Gestational Diabetes Effects (EMERGE) trial, a multicenter, double-blind, placebo-controlled randomized study. A total of 535 pregnant women (510 with newly diagnosed GDM) were allocated 1:1 to metformin (titrated to 2.5 g/day) or placebo alongside usual care. Infant feeding was prospectively documented at birth and at 4 and 12 weeks postpartum. The primary outcome was exclusive breastfeeding at 12 weeks (intention to treat). Multivariable logistic regression adjusted for race, education, smoking, booking BMI, health care access markers, and diagnostic oral glucose tolerance test (OGTT) glucose levels. RESULTS Twelve-week feeding data were available for 476 pregnancies (236 in the metformin group and 240 in the placebo group). Exclusive breastfeeding at 12 weeks was 27% with metformin and 26% with placebo (absolute difference +1.3%; 95% CI –6.3 to 8.7; P = 0.75). The adjusted odds ratio (OR) for metformin versus placebo was 1.24 (95% CI 0.79–1.96; P = 0.36). Feeding patterns shifted from breastfeeding to formula temporally in both groups (P < 0.001), with no treatment-by-time interaction (P = 0.61). Non-Caucasian ethnicity independently predicted exclusive breastfeeding (adjusted OR 2.37; 95% CI 1.27–4.42). CONCLUSIONS Starting metformin treatment at 25 weeks in the GDM group was not associated with differences in exclusive breastfeeding at 12 weeks postpartum. Where metformin was discontinued at delivery, the results support compatibility of antenatal metformin with breastfeeding objectives. Breastfeeding outcomes were more linked to sociodemographic factors than metabolic ones, highlighting the need for culturally appropriate postpartum support.

Background Male foetal sex is recognised as an independent risk factor for adverse pregnancy outcomes including preterm birth, neonatal care unit admission and lower Apgar scores. Male foetuses appear to increase the risk of maternal gestational diabetes in the mother due to impacts on beta cell function, and in pregnancies impacted by gestational diabetes, male offspring have higher rates of hypoglycaemia, respiratory distress and macrosomia. Metformin exposure in animal models has also demonstrated sex-specific effects with different patterns in adiposity and lipid levels observed between male and female offspring exposed to metformin in utero. The aim of this analysis is to determine whether foetal sex modifies maternal and neonatal outcomes in gestational diabetes, and evaluate the sex-specific response to metformin on insulin usage, fasting glucose at 32 and 38 weeks and foetal size. Methods We conducted a secondary analysis of the Early Metformin in Gestational Diabetes (EMERGE) randomised controlled trial and analysed neonatal outcomes according to sex and metformin exposure. Results At randomisation, women carrying a male foetus had a higher plasma glucose at 60 min on oral glucose tolerance testing (9.69 vs. 9.37 mmol/L, p = 0.039). In exploratory analyses, metformin exposure in male pregnancies was associated with lower fasting glucose at 32 (4.88 vs. 5.01 mmol/L, p = 0.014) and 38 weeks (4.49 vs. 4.69 mmol/L, p = 0.002) and reduced insulin use (38% vs. 53%, p = 0.014), with smaller effects in female pregnancies. Metformin-exposed females had higher rates of birth weight < 2500 g compared to those exposed to placebo (8.3% vs. 1.9%, p = 0.032), which was not observed in metformin-exposed males. More male offspring had a birth weight > 4000 g compared to female offspring regardless of metformin exposure. However, the sex-by-treatment interaction was not significant, so these findings should be regarded as hypothesis-generating. Glucometer data suggested a greater mean glucose reduction in males than females (0.29 mmol/L (95% CI 0.29-0.30) versus 0.21 mmol/L (95% CI 0.20-0.21)). Conclusions Further follow-up is required to determine whether foetal sex influences long-term effects of metformin in pregnancy.

Background: Pregnancy in teenagers and emerging adults is associated with an increased risk of adverse outcomes. Similarly, pregnancies complicated by pregestational and gestational diabetes mellitus (GDM) carry a higher risk of complications. However, limited data exist on the intersection of these two high-risk conditions. Our objective was to establish the prevalence of teenage and emerging adult pregnancies complicated by diabetes in a population-based cohort and compare outcomes to pregnancies uncomplicated by diabetes, noting a background prevalence of GDM of 8.1% and pregestational diabetes of 1.2% across all age groups in the United States. Methods: This is a retrospective cohort study conducted in Olmsted County, Minnesota, USA. It includes female residents aged ≤21 years with a pregnancy ICD-10 code between January 1, 2013, and December 31, 2022. The main outcome measures assessed include maternal characteristics and maternal and fetal pregnancy outcomes. Results: A total of 1491 pregnancies in 1379 individuals were identified and included. In total, 68 (4.6%) pregnancies were complicated by diabetes: 51 (3.4%) with GDM and 17 (1.1%) with pregestational diabetes. In this study, pregnancies with diabetes had higher rates of adverse outcomes including cesarean delivery (GDM 29.4% vs. pregestational 60.0% vs. no diabetes 17.0%, P < 0.001), preeclampsia (GDM 15.7% vs. pregestational 40.0% vs. no diabetes 7.3%, P < 0.001), large-for-gestational-age neonates (GDM 13.7% vs. pre-existing 50.0% vs. no diabetes 5.8%, P < 0.001), and neonatal hypoglycemia (GDM 42.6% vs. pregestational 60.0% vs. no diabetes 13.3%, P < 0.001). Conclusions: The prevalence of pregestational diabetes in our teenage and emerging adult population is similar to that of the general pregnancy population; however, the prevalence of GDM is significantly lower. Overall, diabetes in teenage pregnancy is associated with an elevated risk of adverse maternal and neonatal outcomes. Future research should evaluate interventions aimed at reducing adverse pregnancy outcomes in this vulnerable population.

Early-life nutrition profoundly influences long-term metabolic health, and breast milk not only provides nutrients but also conveys maternal signals shaping infant metabolic development. While postpartum exercise by lactating women benefits maternal health, its impact on milk-borne signaling remains largely undefined. Small extracellular vesicles (sEVs) in breast milk are key mediators of maternal-infant communication because of their selectively packaged bioactive cargo and resistance to infant digestive enzymes and acids, enabling delivery of their cargo to peripheral tissues. Here, we show that a single session of moderate-intensity postpartum aerobic exercise robustly increases human breast milk sEV concentration, which persists for multiple post-exercise milk collections. Exercise enriches breast milk with sEVs containing regulatory metabolic cargo (proteins, miRNAs, and metabolites), which translates into enhanced mitochondrial capacity in neonatal-stage cells. These findings implicate sEVs as an exercise-responsive signaling compartment in breast milk capable of connecting postpartum maternal physical activity to beneficial infant metabolic programming. Highlights:Acute moderate-intensity exercise increases human breast milk sEV concentrationThe exercise-mediated sEV increase lasts for multiple subsequent milk expressionsExercise coordinates a multi-omic enrichment of sEVs in breast milkExercised breast milk sEVs enhance mitochondrial respiration in UC-MSCs.

Pancreatic α-cells secrete glucagon. The glucagon secretion rate (GSR) increases when plasma glucose decreases; conversely, GSR decreases when glucose rises. In addition, amino acids (AAs) stimulate GSR. Impaired GSR suppression by glucose contributes to postprandial hyperglycemia in individuals with impaired glucose tolerance, obesity, and type 2 diabetes (T2D). However, the current method to assess α-cell responsivity to glucose ignores the contribution of AAs and is a two-step approach with some limitations. To address this, we developed a model-based method to quantify α-cell responsivity to glucose during a graded glucose infusion, in the presence and absence of AAs. A total of 52 subjects were studied. Thirty-seven subjects from study 1 [13 M, age = 54 ± 10 yr, body mass index (BMI) = 30 ± 5 kg/m2] were studied once. Fifteen subjects (4 M, age = 47 ± 11 yr, BMI = 28 ± 4 kg/m2) from study 2 were studied twice: once with saline and once with an AA infusion (Clinisol 15%, 0.003 mL/kg/min). Plasma glucagon, glucose, and AA concentrations were measured over 240 min. We tested several mathematical models of GSR, and the best one was selected using standard criteria. The optimal model describes GSR as an exponential decay driven by delayed plasma glucose concentration and modulated by AAs. The model provides an index of α-cell responsivity, G50, i.e., the glucose increase required to suppress GSR by 50%. AA infusion increased G50 compared with the saline infusion. This model-based approach provides an index of α-cell responsiveness under both physiological and AA-stimulated conditions. Its use may help in the early detection of α-cell dysfunction in people at risk of developing T2D.NEW & NOTEWORTHY In this study, we propose two new mathematical models able to quantify glucagon secretion during a graded glucose infusion, in the presence and absence of amino acids. The models provide an index of α-cell responsivity, G50, i.e., the glucose increase required to suppress glucose secretion rate (GSR) by 50%. Results show that the presence of amino acids reduced α-cell responsivity to glucose.

BackgroundPregnancies complicated by gestational diabetes mellitus (GDM) are associated with increased risks of adverse perinatal outcomes and with long-term metabolic and cardiovascular consequences for both mother and child. The original EMERGE randomized controlled trial (RCT) evaluated the effectiveness of early metformin in addition to usual care in women with GDM on glycemic control and perinatal outcomes. The primary objective of the EMERGE Mothers and Kids study is to evaluate long-term maternal cardiometabolic health and child anthropometric and neurodevelopmental outcomes following participation in the EMERGE trial.MethodsThis is a prospective, observational longitudinal cohort follow-up study of women and their children previously enrolled in the EMERGE trial (NCT06327191). Participants are invited to attend a follow-up visit in a single-site hospital-based clinical research setting at the Clinical Research Facility Galway, Ireland. Key inclusion criteria are women and their children who participated in the EMERGE trial and consent to follow-up. Key exclusion criteria include participants who did not provide consent for future follow-up studies. The planned follow-up sample is a pragmatic convenience sample of up to 321 mother-child pairs. A single follow-up visit will be conducted up to 6 years after the index pregnancy. Maternal assessments include anthropometric data, glucose tolerance, and metabolic parameters. Child assessments include growth metrics, adiposity measured via skinfold thickness, and neurodevelopmental status assessed through validated questionnaires. Additional data on quality of life, mental health, breastfeeding, and health economics will also be collected.DiscussionThis study aims to provide insights into the long-term safety and efficacy of metformin use during pregnancy, addressing the evidence gap in maternal cardiometabolic outcomes after metformin-treated GDM while also assessing child anthropometric and neurodevelopmental outcomes.Trial registration ClinicalTrials.gov NCT06327191. Registered on November 21, 2023. First planned enrollment in this follow-up study: July 2024. Trial record available at https://clinicaltrials.gov/study/NCT06327191.

ImportanceUnderstanding the interplay between diabetes risk factors and diabetes development is important to develop individual, practice, and population-level prevention strategies.ObjectiveTo evaluate the progression from normal and impaired fasting glucose levels to diabetes among adults.Design, Setting, and ParticipantsThis retrospective community-based cohort study used data from the Rochester Epidemiology Project, in Olmsted County, Minnesota, on 44 992 individuals with at least 2 fasting plasma glucose (FPG) measurements from January 1, 2005, to December 31, 2017. People who met criteria for diabetes on or before their first FPG measurement were excluded. Data were electronically retrieved in December 2019 with analyses finalized in November 2024.ExposuresThe exposure was baseline FPG level, with covariates including the following measures that are consistently recorded in the electronic health record: body mass index (BMI), age, and sex.Main Outcomes and MeasuresThe cumulative probability of freedom from diabetes was estimated and presented graphically using a Kaplan-Meier curve. Multivariable Cox proportional hazards regression modeling was used to estimate the partial hazard ratios (HRs) for variables of interest. Diabetes was defined as an FPG level greater than 125 mg/dL.ResultsA total of 44 992 individuals (mean [SD] age at baseline, 43.7 [11.8] years; 26 025 women [57.8%]) were included. The baseline mean (SD) BMI was 28.9 (6.6). Over a median follow-up of 6.8 years (IQR, 3.6-9.7 years), 3879 individuals (8.6%) developed diabetes. The Kaplan-Meier 10-year cumulative risk of incident diabetes was 12.8% (95% CI, 12.4%-13.2%). All initial FPG levels outside a range of 80 to 94 mg/dL were associated with increased risk for diabetes (ie, FPG <70 mg/dL: HR, 3.49 [95% CI, 2.19-5.57]; FPG 120-125 mg/dL: HR, 12.47 [10.84-14.34]). Other independent risk factors were male sex (HR, 1.31 [95% CI, 1.22-1.40]), older age (≥60 years: HR, 1.97 [95% CI, 1.71-2.28]), and any abnormal category of BMI, including underweight (BMI <18.5: HR, 2.42 [95% CI, 1.77-3.29]; BMI ≥40: HR, 4.03 [95% CI, 3.56-4.56]). There was a significant additive association of variables, particularly FPG level and BMI. For instance, a woman aged 55 to 59 years with a BMI of 18.5 to 24.9 and an FPG level of 95 to 99 mg/dL had an estimated 10-year diabetes risk of 7.0%. However, an almost doubling of risk to 13.0% was observed if the BMI was 30.0 to 34.9, and risk more than doubled again to 28.0% if FPG level also increased to 105 to 109 mg/dL. A nomogram was generated to facilitate individual classification into one of four 10-year risk categories.Conclusions and RelevanceThis retrospective cohort study of 44 992 individuals suggests that FPG level, age, BMI, and male sex were all associated with development of diabetes, with significant interaction between these variables. These data contribute to understanding the clinical course of diabetes and highlight the substantial individual variation in diabetes risk according to commonly measured clinical variables. The findings facilitate lifestyle and pharmacologic interventions to treat those at highest risk of diabetes to reduce future morbidity and mortality. Further work is needed to validate this risk categorization tool for different populations.

Introduction and Objective: Type 1 diabetes (T1D) is an autoimmune disease that causes loss of β-cell mass and insulin secretion. Early Stage 3 T1D includes β-cell dysfunction and activation of intrinsic stress pathways before clinical diagnosis, making this ‘asymptomatic’ period critical for prediction and prevention. Circulating plasma extracellular vesicles (EVs) are promising non-invasive biomarkers for disease identification and prognosis. Thus, the objective is to determine an early EV-based prognostic indicator of declining β-cell health in T1D. Methods: Adult and pediatric human blood specimens were collected from three groups: 1) Early (E)T1D (<1 year from diagnosis, n=10); 2) Late (L)T1D (>1 year from diagnosis, n=9); 3) age-matched healthy controls (NC, n=7). Blood plasma-derived EVs were isolated using size-exclusion chromatography and differential ultracentrifugation. EVs were characterized through Nanoparticle Tracking Analysis (NTA), western blotting, assessment of EVs on β-cell function, and proteomic analysis using tandem mass spectrometry. Results: NTA revealed a 2-fold increase in plasma EVs from ET1D and LT1D groups compared to NC (p<0.05). Human islets exposed to LT1D EV but not ET1D and NC EVs, showed impaired glucose-stimulated insulin secretion (GSIS) (2 X 109 particles/day for 48 h). Proteomic analysis identified 1,229 enriched EV proteins, and differential expression analysis (log2(fold change) ≥ 1.5) highlighted potential biomarkers for ET1D, including VWF, LBP, and GP1BA (p<0.05). KEGG pathway analysis revealed enriched proteins related to complement and coagulation, extracellular matrix, antigen presentation, and immune system pathways in ET1D and LT1D EVs compared to NC EVs. VWF expression was confirmed by western blotting in both ET1D and LT1D EVs but was absent in NC EVs. Conclusion: Our study characterizes circulating EVs from three patient groups, identifying VWF as a potential biomarker for early Stage 3 T1D. R. Leon-Gutierrez: None. G. Ariyaratne: None. Z. Liang: None. A. Hoff: None. A. Roy: None. M. Tahawi: None. A. Matveyenko: None. A.M. Egan: None. A. Vella: Research Support; Novo Nordisk A/S, Dexcom, Inc. Advisory Panel; Boehringer-Ingelheim, Rezolute. A. Creo: Advisory Panel; Sanofi. N. Javeed: None. NIH (DK129208-01); JDRF (2-SRA-2022-1272-S-B)

Metformin is well-established as a treatment for type 2 diabetes in non-pregnant individuals. The low cost, acceptability and broad tolerability of metformin have also made it an attractive option for research into the treatment of other conditions associated with insulin resistance. Despite almost 50 years of clinical experience with the use of metformin to treat diabetes in pregnancy, many questions remain regarding its precise effectiveness in different maternal subgroups, as well as potential short-term and long-term effects on the offspring. In this narrative review, we present the current evidence for the use of metformin during pregnancy in various maternal subgroups, including women living with overweight and obesity, women at risk of gestational diabetes, women diagnosed with gestational diabetes and women with pregestational diabetes, including type 2 diabetes. Our specific focus is on the impact of metformin on short-term maternal, fetal and neonatal outcomes. We also consider the evidence for other emerging indications for metformin in pregnancy, such as the prevention and management of pre-eclampsia. PLAIN LANGUAGE SUMMARY: This article looks at research on how metformin use in pregnancy affects mothers and newborns in the short term. Doctors have prescribed metformin since the 1970s for the treatment of diabetes in pregnancy. Despite years of use, there are still questions about how safe and effective metformin is for mothers and their children. Metformin taken during pregnancy moves through the placenta into the foetus's bloodstream. The short-term and long-term effects of metformin on offspring need careful attention. The studies that have looked at the link between metformin use and birth defects have not found any strong link between taking metformin in pregnancy and birth defects, however close attention will continue to be paid in this area. Some large studies have examined the use of metformin in pregnant women who do not have diabetes, but who do live with overweight or obesity. The studies are difficult to compare. Some, but not all, of these studies have shown less weight gain for the mother if metformin is taken by these women during pregnancy. Other large studies have looked at whether metformin can prevent gestational diabetes. The results are mostly disappointing. They suggest that metformin does not stop gestational diabetes from developing. However, the participants in these studies were mostly from white backgrounds and metformin may help prevent gestational diabetes in women of different ethnic backgrounds. However, more research is needed. Metformin has been widely studied as an alternative to insulin for the treatment of gestational diabetes. Because different countries diagnose and treat GDM differently, this makes comparing study results difficult. Women with gestational diabetes seem to gain less weight during pregnancy if they use metformin rather than insulin. Using metformin instead of insulin may result in lower average birth weights for babies from these pregnancies. Also, the use of metformin may lead to fewer babies being born abnormally large. Similarly, large trials have examined the use of metformin in pregnant women who are living with type 2 diabetes. These studies show that metformin can lower a mother's insulin needs. It can also help control weight gain and reduce the risk of having a large baby. One study found that metformin use in women living with Type 2 diabetes might increase the risk of having smaller babies. This was especially true if the mother had high blood pressure or kidney disease. This finding requires further investigation. Metformin might help prevent pre-eclampsia, but this is still unclear. Research is ongoing into a potential role for metformin in the treatment of pre-eclampsia. In conclusion, metformin has been studied in many groups of pregnant women. Women with gestational diabetes or type 2 diabetes may see benefits like less weight gain and better blood sugar/glucose control. Current evidence suggests that metformin shouldn't be used if there are foetal growth issues. It is also not recommended for mothers with high blood pressure or kidney disease. Future studies might find specific groups of pregnant women who would benefit the most from metformin.

BACKGROUNDAmino acid (AA) concentrations are increased in prediabetes and diabetes. Since AAs stimulate glucagon secretion, which should then increase hepatic AA catabolism, it has been hypothesized that hepatic resistance (associated with hepatic fat content) to glucagon's actions on AA metabolism leads to hyperglucagonemia and hyperglycemia.METHODSTo test this hypothesis, we therefore studied lean and obese individuals, the latter group with and without hepatic steatosis as defined by proton density fat fraction (PDFF) > 5%. After an overnight fast, femoral vein, femoral artery, and hepatic vein catheters were placed. [3-3H] glucose and l-[1-13C,15N]-leucine were used to measure glucose turnover and leucine oxidation, respectively. During a hyperglycemic clamp, an AA mixture was infused together with insulin and glucagon (1.5 ng/kg/min 0-120 minutes; 3.0 ng/kg/min 120-240 minutes). Tracer-based measurement of hepatic leucine oxidation in response to rising glucagon concentrations and splanchnic balance (measured using arteriovenous differences across the liver) of the other AAs were the main outcomes measured.RESULTSThe presence of hepatic steatosis did not alter hepatic glucose metabolism and leucine oxidation in response to insulin and rising concentrations of glucagon. Splanchnic balance of a few AAs and related metabolites differed among the groups. However, across-group differences of AA splanchnic balance in response to glucagon were unaffected by the presence of hepatic steatosis.CONCLUSIONThe action of glucagon on hepatic AA metabolism is unaffected by hepatic steatosis in humans.TRIAL REGISTRATIONClinical Trials.gov: NCT05500586.FUNDINGNIH National Institute of Diabetes and Digestive and Kidney Diseases DK116231, DK78646, DK116231, DK126206, and DK116231.

CLINICAL IMPACT RATINGS:GIM/FP/GP: [Formula: see text] Endocrinology: [Formula: see text].

Introduction and Objective: Amino acids (AAs) stimulate glucagon which increases hepatic AA catabolism. AA. Glucagon concentrations are increased in prediabetes. This led to the hypothesis that hepatic resistance (associated with hepatic fat content) to glucagon’s actions on AA metabolism leads to hyperglucagonemia and hyperglycemia. Methods: To test this hypothesis, we quantified hepatic fat by MRI as Proton Density Fat Fraction (PDFF) in lean (n = 10) and obese subjects (n = 20). Half of the latter group had a PDFF < 5%; the remainder a PDFF > 5%. After an overnight fast, femoral vein, femoral artery, and hepatic vein catheters were placed. At 0700 (-180 min), infusions of [3-3H] glucose (10 μCi prime, 0.1 μCi/min continuous), indocyanine green and L-[1-13C,15N]-Leucine (7.5μmol/kg prime, 7.5μmol/kg/hour continuous) started. At 1000 (0 min), insulin was infused at 0.8 mU/kg/min (0 - 240 min) alongside glucagon (1.5 ng/kg/min 0 - 120 min; 3.0 ng/kg/min 120 - 240 min). A hyperglycemic clamp maintained peripheral glucose at ~9.0 mmol/L. A mixture of AAs (Clinisol, Baxter, Healthcare, Deerfield, IL; 15%, 0.003ml/kg/min;) was also infused. Results: As expected, the glucose infusion rate necessary to maintain the clamp was lower in obese subjects (15.4 ± 1.3 vs. 4.9 ± 0.7 mg/kg/min, lean vs. obese respectively, p < 0.01). This was also the case for glucose disappearance (93 ± 7 vs. 35 ± 4 μmol/kg/min, p < 0.01) unlike endogenous glucose production (11 ± 2 vs. 9 ± 1 μmol/kg/min, p = 0.04). There was no effect of hepatic fat on these parameters (p > 0.10). Splanchnic extraction of glycine, but not other AAs, was increased (0.04 ± 0.02 vs. 0.23 ± 0.03, p = 0.01) in obesity (independent of PDFF) throughout the study. Conversion of Leucine to α-Keto IsoCaproic acid was unchanged by obesity (at 240 min: 461 ± 53 vs. 381 ± 65 μmol/kg/min, p = 0.42) or PDFF (p = 0.84). Conclusion: We conclude that increases in hepatic fat do not alter hepatic AA metabolic response to glucagon in postprandial conditions. H.E. Christie: None. S. Mohan: None. A.M. Egan: None. M.D. Jensen: Consultant; Novo Nordisk, Dexcom, Inc. K. Nair: None. A. Vella: Research Support; Novo Nordisk A/S, Dexcom, Inc. Advisory Panel; Boehringer-Ingelheim, Rezolute. National Institute of Health (DK116231-06)

Introduction and Objective: Pre-diabetes is characterized by abnormal postprandial suppression of glucagon and circulating amino acid (AA) concentrations. It is unknown if hyperglucagonemia arises from a defective α-cell response to AA or from abnormal metabolism resulting in elevated AA. Methods: Lean (BMI: 23 ± 0.5 Kg/M2, n = 10) and obese (BMI 31 ± 0.5 Kg/M2, n = 20) subjects underwent hepatic MRI to quantify fat content using Proton Density Fat Fraction (PDFF). They were then studied on two occasions in random order after an overnight fast using a graded glucose infusion. On one occasion saline was infused (Saline Day) and on the other an AA mixture [Clinisol (15%, 0.003ml/kg/min); Baxter, Healthcare, Deerfield, IL - AA day]. The glucagon secretion rate (GSR) was derived from peripheral glucagon concentrations using a mathematical model, which also provided G50 - the change in glucose required to reduce GSR by 50% - for each subject. AA and their metabolites (n = 42) were measured by mass spectrometry at 0, 120 and 240 mins. Results: On both occasions, experimental conditions produced a progressive rise in insulin secretion and an inverse-exponential suppression of glucagon. AA infusion did not change G50 (1.4 ± 0.2 vs. 1.3 ± 0.3 mmol/L, AA vs. saline respectively, p = 0.20) in lean subjects. This was not the case in the obese group (2.3 ± 0.4 vs. 1.3 ± 0.2 mmol/L, p = 0.02). On the AA day G50 correlated with alanine (R2 = 0.34) and cysteine (R2 = 0.25) concentrations. Concentrations of alanine (R2 = 0.38), α-aminoadipic acid (R2 = 0.14) and lysine (R2 = 0.34) positively correlated with PDFF irrespective of changing insulin and glucagon concentrations throughout both study days. Conclusion: These experiments demonstrate that α-cell function is modulated by circulating AA. Increased PDFF is associated with increased AA concentrations, but these differences are present regardless of islet hormone concentrations at 0, 120 and 240 mins. S. Mohan: None. F. Boscolo: None. H.E. Christie: None. A.M. Pipkins: None. A.M. Egan: None. M.C. Laurenti: Employee; Angelini Pharma. C. Dalla Man: None. A. Vella: Research Support; Novo Nordisk A/S, Dexcom, Inc. Advisory Panel; Boehringer-Ingelheim, Rezolute. NIH NIDDK (DK116723)

Context: Defects in insulin secretion and action contribute to the progression of prediabetes to diabetes. However, the contribution of alpha-cell dysfunction to this process has been unclear. Objective: This work aimed to understand the relative contributions of alpha-cell and beta-cell dysfunction to declining glucose tolerance. Methods: A longitudinal, community-based observational study was conducted at a clinical research unit at an academic medical center. We studied 96 individuals without diabetes (age 55 +/- 1 years; body mass index 27.7 +/- 0.4) on 2 occasions, 3 years apart using an oral 75-g glucose challenge. Indices for insulin secretion and action were estimated using the oral minimal model. Glucagon secretion rate (GSR) was estimated by deconvolution from peripheral glucagon concentrations. Main outcome measures included glucose tolerance status (categorical variable) and then symmetrical percentage change in peak and 120-minute glucose (post oral glucose tolerance test) concentrations (continuous variables). Results: A total of 32 individuals progressed from normal to impaired glucose tolerance (IGT) or from IGT to type 2 diabetes. The disposition index (DI) declined in the progressors (568 +/- 98 vs 403 +/- 65 10(-4) dL/kg/min per mu U/mL, baseline vs 3 years; P = .04). alpha-Cell suppression by glucose (delta GSR/delta glucose) did not change in the nonprogressors (1.5 +/- 0.1 vs 1.3 +/- 0.1 nmol/min/L; P = .37) but decreased (1.0 +/- 0.2 vs 0.8 +/- 0.2 nmol/min/L; P < .01) in those who progressed. Analysis of the entire cohort showed that DI and delta GSR/delta glucose were independently and inversely correlated with an increase in glycemic excursion. Conclusion: These data show that alpha-cell dysfunction accompanies a decline in beta-cell function as IGT or overt type 2 diabetes develops.

AIMS:Gestational diabetes mellitus (GDM) is a global health problem. Insulin therapy is recommended when lifestyle management fails to control blood glucose. We aim to predict the time to insulin initiation for women with GDM. METHODS:A random survival forest (RSF) model was developed to predict the time to insulin initiation among 413 women from the EMERGE trial, analysed separately for placebo and metformin groups. Maternal characteristics and early glucose data (collected during the two weeks after randomisation) were used as predictors. Decision curve analysis was performed to assess the net benefit of the model compared with default strategies. RESULTS:The RSF model had a concordance index (C-index) of 0.71 (95 % CI: 0.64-0.77), time-dependent AUC ≥0.70 and Brier score ≤0.2 for the placebo group, and a C-index of 0.72 (95 % CI: 0.64-0.80), time-dependent AUC ≥0.75 and Brier score ≤0.2 for the metformin group. The decision curve analysis showed the RSF provided a higher net benefit for both groups compared to default strategies across clinically relevant threshold probabilities. CONCLUSIONS:The RSF model effectively identified women at high risk of requiring insulin. The decision curve analysis could help clinicians to balance insulin initiation decisions. However, prospective validation is needed to confirm the generalisability of the model.

Background: Increasing maternal body mass index (BMI) represents a risk factor for Gestational Diabetes Mellitus (GDM) and adverse obstetrical and perinatal outcomes. Objective: To stratify clinical outcomes for pregnancies affected by GDM according to maternal BMI. Methods: Retrospective cohort study including individuals ≥18 years of age who were diagnosed with GDM from 2018 to 2022. Universal GDM screening was employed with a 50 g oral glucose challenge test ± a 100 g oral glucose tolerance test. Maternal demographics, preexisting medical conditions, and selected obstetric and neonatal morbidities were evaluated. Results: A total of 2193 pregnancies in 2110 women affected by GDM were identified. This included 506 (23.0%) with normal baseline maternal BMI, 596 (27.2%) with overweight, and 1091 (49.7%) with obese BMI. Adverse maternal outcomes were more frequent in the obese compared to overweight or normal BMI categories (cesarean delivery: normal 26.9% vs. overweight 28.5% vs. obese 40.9%; p < 0.001; hypertensive disorders of pregnancy: normal 8.7% vs. overweight 12.1% vs. obese 16.8%; p < 0.001). Postpartum glucose intolerance was higher in women with obesity (normal 7.3% vs. overweight 5.9% vs. obese 14.9%; p < 0.001). Infants born to mothers with obesity had higher birthweights (normal 3.3 kg vs. overweight 3.4 kg vs. obese 3.5 kg; p < 0.001), were more likely to have neonatal hypoglycemia (normal 29.4% vs. overweight 24.3% vs. obese 41.9%; p < 0.001) and require intensive care unit admission (normal 8.1% vs. overweight 5.9% vs. obese 11.9%; p < 0.001). Conclusions: Patients with GDM and baseline BMI in the obese range experienced the highest rate of adverse outcomes, while those with overweight BMI had similar outcomes to individuals who had normal BMI at baseline.

Aims: Identifying participants with type 2 diabetes (T2D) based only on electronic health record (EHR) or self-reported data has limited accuracy. Therefore, the objective of the study was to develop an algorithm using EHR and self-reported data to identify participants with and without T2D. Methods: We included participants enrolled in the Mayo Clinic Biobank. At enrollment, participants completed a baseline questionnaire on health conditions, including T2D, and provided access to their EHR data. T2D status was based on self-report and EHR data (International Classification of Diseases codes, hemoglobin A1c [HbA1c], plasma glucose, and glucose-regulating medications) within 5 years prior to and 2 months after enrollment. Participants who self-reported T2D but lacked corroborating EHR data were categorized separately ("only self-reported T2D"). After identifying participants with T2D, we identified participants without T2D based on normal HbA1c and plasma glucose. Participants who self-reported the absence of T2D but lacked corroborating EHR data were categorized separately ("only self-reported no T2D"). Using manual chart reviews (gold standard), we calculated the positive and negative predictive values (NPV) to identify T2D. Results: Of 57,000 participants, the algorithm classified participants as having T2D (n = 6,238), no T2D (n = 38,883), "only self-reported T2D" (n = 757), and "only self-reported no-T2D" (n = 9,759). The algorithm had a high positive predictive value (96.0% [91.5%-98.5%]), NPV (100% [98.0%-100%]), and accuracy (99.5% [98.3%-99.8%]). Participant age (median [range]) ranged from 52 (18-98) years (only self-reported T2D) to 67 (19-99) years (T2D) (P < 0.0001), and the proportion of women ranged from 45.3% (T2D) to 69.6% (only self-reported no T2D) (P < 0.0001). Most participants were of the White race (84.0%-92.7%) and non-Hispanic ethnicity (97.6%-98.6%). Conclusions: In this study, we developed an algorithm to accurately identify participants with and without T2D, which may be generalizable to cohorts with linked EHR data.