Vella, Adrian

We describe a method that lowers the limit of quantification of a glucagon immunoassay thereby enhancing the ability to differentiate between normal and abnormal α-cell responsiveness to glucagon.

Abstract Context Multiple common genetic variants have been associated with type 2 diabetes, but the mechanism by which they predispose to diabetes is incompletely understood. One such example is variation in MTNR1B, which implicates melatonin and its receptor in the pathogenesis of type 2 diabetes. Objective To characterize the effect of diabetes-associated genetic variation at rs10830963 in the MTNR1B locus on islet function in people without type 2 diabetes. Design The association of genetic variation at rs10830963 with glucose, insulin, C-peptide, glucagon, and indices of insulin secretion and action were tested in a cohort of 294 individuals who had previously undergone an oral glucose tolerance test (OGTT). Insulin sensitivity, β-cell responsivity to glucose, and Disposition Indices were measured using the oral minimal model. Setting The Clinical Research and Translation Unit at Mayo Clinic, Rochester, MN. Participants Two cohorts were utilized for this analysis: 1 cohort was recruited on the basis of prior participation in a population-based study in Olmsted County. The other cohort was recruited on the basis of TCF7L2 genotype at rs7903146 from the Mayo Biobank. Intervention Two-hour, 7-sample OGTT. Main Outcome Measures Fasting, nadir, and integrated glucagon concentrations. Results One or 2 copies of the G-allele at rs10830963 were associated with increased postchallenge glucose and glucagon concentrations compared to subjects with the CC genotype. Conclusion The effects of rs10830963 on glucose homeostasis and predisposition to type 2 diabetes are likely to be partially mediated through changes in α-cell function.

The T allele at rs7903146 in TCF7L2 increases the rate of conversion from prediabetes to type 2 diabetes. This has been associated with impaired β-cell function and with defective suppression of α-cell secretion by glucose. However, the temporal relationship of these abnormalities is uncertain. To study the longitudinal changes in islet function, we recruited 128 subjects, with 67 homozygous for the diabetes-associated allele (TT) at rs7903146 and 61 homozygous for the protective allele. Subjects were studied on two occasions, 3 years apart, using an oral 75-g glucose challenge. The oral minimal model was used to quantitate β-cell function; the glucagon secretion rate was estimated from deconvolution of glucagon concentrations. Glucose tolerance worsened in subjects with the TT genotype. This was accompanied by impaired postchallenge glucagon suppression but appropriate β-cell responsivity to rising glucose concentrations. These data suggest that α-cell abnormalities associated with the TT genotype (rs7903146) occur early and may precede β-cell dysfunction in people as they develop glucose intolerance and type 2 diabetes. Article Highlights

Abstract Context The risk of gestational diabetes mellitus (GDM) in twin pregnancies is more than double that of singleton pregnancies. Although twin pregnancies present unique challenges for fetal growth and prenatal management, the approach to GDM diagnosis and treatment is the same regardless of plurality. Data on pregnancy outcomes for individuals with GDM and a twin pregnancy are limited and conflicting. Objective To describe the maternal characteristics associated with GDM in twin pregnancies and to assess the associated pregnancy outcomes compared to twin pregnancies unaffected by GDM. Methods A retrospective cohort study was conducted at Mayo Clinic, Rochester, Minnesota, USA, and included predominantly Causasian women aged 18 to 45 years who received prenatal care for a twin pregnancy from 2017-2022. Maternal characteristics and a broad spectrum of pregnancy outcomes were evaluated. Universal GDM screening involved a 50 g oral glucose challenge test +/− a 100 g oral glucose tolerance test. Results GDM was diagnosed in 23% pregnancies (n = 104/452). Compared to those without, women with GDM had known risk factors including a higher prepregnancy body mass index (31.1vs 26.3 kg/m2; P < .01) and a prior history of GDM (21.7 vs 5.9%; P < .01). There were no differences in maternal pregnancy complications or neonatal outcomes between groups. Attendance at postpartum glucose testing among women with GDM was poor at 27.9% (29/104). Conclusion These data suggest that women with twin pregnancies share a similar GDM risk profile to those with singleton pregnancies and provide reassuring evidence that current management for GDM twin pregnancies produces similar outcomes to twin pregnancies without GDM.

Abstract Context The impact of insulin, particularly exogenous hyperinsulinemia, on insulin secretion in humans is debated. Objective We assessed the effects of exogenous hyperinsulinemia on insulin secretion and whether the response is altered in insulin resistance associated with obesity. Methods Insulin secretion rates (ISRs) during euglycemic hyperinsulinemic clamp studies (52 volunteers) were calculated using a model that employs plasma C-peptide concentrations. One study involved a 2-step insulin clamp and the other study was a single step insulin clamp. For both studies the goal was to achieve plasma glucose concentrations of 95 mg/dL during the clamp irrespective of fasting glucose concentrations. The percent change in ISR from fasting to the end of the insulin clamp interval was the main outcome. Linear regression and analysis of covariance were used to test for the effects of insulin on ISR and to test for group differences. Results ISR was greater in obese volunteers (P < .001) under fasting and hyperinsulinemic clamp conditions. The change in plasma glucose from baseline to the end of the insulin clamp interval was highly correlated with the change in ISR (r = 0.61, P < .001). From baseline to the end of the clamp we observed a 27% (SD 20) suppression of ISR. The participants who underwent a 2-step insulin clamp had greater suppression of ISR during the second step than the first step (P < .001). The proportional suppression of ISR during euglycemic hyperinsulinemia was not different between nonobese and obese groups (P = .19). Conclusion Hyperinsulinemia suppresses endogenous insulin secretion and the relative change in insulin secretion produced by exogenous insulin did not differ between nonobese and obese people.

This experiment studied the effect of changes in overnight concentrations of free fatty acids (FFAs) and glucose on β-cell function and glucose metabolism. In response to elevation of these metabolites, the dynamic component of the β-cell response to glucose was impaired. This suggests that in health overnight hyperglycemia and FFA elevation can deplete preformed insulin granules in the β-cell.

Abstract Context Metformin is the first-line drug for treating diabetes but has a high failure rate. Objective To identify demographic and clinical factors available in the electronic health record (EHR) that predict metformin failure. Methods A cohort of patients with at least 1 abnormal diabetes screening test that initiated metformin was identified at 3 sites (Arizona, Mississippi, and Minnesota). We identified 22 047 metformin initiators (48% female, mean age of 57 ± 14 years) including 2141 African Americans, 440 Asians, 962 Other/Multiracial, 1539 Hispanics, and 16 764 non-Hispanic White people. We defined metformin failure as either the lack of a target glycated hemoglobin (HbA1c) (<7%) within 18 months of index or the start of dual therapy. We used tree-based extreme gradient boosting (XGBoost) models to assess overall risk prediction performance and relative contribution of individual factors when using EHR data for risk of metformin failure. Results In this large diverse population, we observed a high rate of metformin failure (43%). The XGBoost model that included baseline HbA1c, age, sex, and race/ethnicity corresponded to high discrimination performance (C-index of 0.731; 95% CI 0.722, 0.740) for risk of metformin failure. Baseline HbA1c corresponded to the largest feature performance with higher levels associated with metformin failure. The addition of other clinical factors improved model performance (0.745; 95% CI 0.737, 0.754, P < .0001). Conclusion Baseline HbA1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification.