Citations

Localized insulinoma is an uncommon entity that can result in substantial morbidity due to the associated hypoglycemia. Recent studies have suggested an increase in the incidence of insulinoma in recent decades that may possibly be secondary to increased awareness, incidental diagnoses, and better diagnostic methods. Diagnosing and localizing insulinoma within the pancreas can be challenging, but advances in nuclear imaging may improve diagnostic accuracy. Delays in diagnosis are common, but once a localized insulinoma is diagnosed and appropriately treated, the long-term prognosis is excellent. Surgical resection is considered the standard of care management option for localized insulinoma, but tumor ablation with endoscopic ultrasound guidance has also been shown to be an effective and safe method for therapy.

Abstract Background In the United States, rare disease (RD) is defined as a condition that affects fewer than 200,000 individuals. Collectively, RD affects an estimated 30 million Americans. A significant portion of RD has an underlying genetic cause; however, this may go undiagnosed. To better serve these patients, the Mayo Clinic Program for Rare and Undiagnosed Diseases (PRaUD) was created under the auspices of the Center for Individualized Medicine (CIM) aiming to integrate genomics into subspecialty practice including targeted genetic testing, research, and education. Methods Patients were identified by subspecialty healthcare providers from 11 clinical divisions/departments. Targeted multi-gene panels or custom exome/genome-based panels were utilized. To support the goals of PRaUD, a new clinical service model, the Genetic Testing and Counseling (GTAC) unit, was established to improve access and increase efficiency for genetic test facilitation. The GTAC unit includes genetic counselors, genetic counseling assistants, genetic nurses, and a medical geneticist. Patients receive abbreviated point-of-care genetic counseling and testing through a partnership with subspecialty providers. Results Implementation of PRaUD began in 2018 and GTAC unit launched in 2020 to support program expansion. Currently, 29 RD clinical indications are included in 11 specialty divisions/departments with over 142 referring providers. To date, 1,152 patients have been evaluated with an overall solve rate of 14.1% and as high as 66.7% depending on the phenotype. Noteworthy, 42.7% of the solved or likely solved patients underwent changes in medical management and outcome based on genetic test results. Conclusion Implementation of PRaUD and GTAC have enabled subspecialty practices advance expertise in RD where genetic counselors have not historically been embedded in practice. Democratizing access to genetic testing and counseling can broaden the reach of patients with RD and increase the diagnostic yield of such indications leading to better medical management as well as expanding research opportunities.

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.

Data from transgenic rodent models suggest that glucagon acts as an insulin secretagogue by signaling through the glucagon-like peptide 1 receptor (GLP-1R) present on β-cells. However, its net contribution to physiologic insulin secretion in humans is unknown. To address this question, we studied individuals without diabetes in two separate experiments. Each subject was studied on two occasions in random order. In the first experiment, during a hyperglycemic clamp, glucagon was infused at 0.4 ng/kg/min, increasing by 0.2 ng/kg/min every hour for 5 h. On one day, exendin-9,39 (300 pmol/kg/min) was infused to block GLP-1R, while on the other, saline was infused. The insulin secretion rate (ISR) was calculated by nonparametric deconvolution from plasma concentrations of C-peptide. Endogenous glucose production and glucose disappearance were measured using the tracer-dilution technique. Glucagon concentrations, by design, did not differ between study days. Integrated ISR was lower during exendin-9,39 infusion (213 ± 26 vs. 191 ± 22 nmol/5 h, saline vs. exendin-9,39, respectively; P = 0.02). In the separate experiment, exendin-9,39 infusion, compared with saline infusion, also decreased the β-cell secretory response to a 1-mg glucagon bolus. These data show that, in humans without diabetes, glucagon partially stimulates the β-cell through GLP-1R.

Importance US rural vs nonrural populations have striking disparities in diabetes care. Whether rurality contributes to disparities in diabetes mortality is unknown. Objective To examine rates and trends in diabetes mortality based on county urbanization. Design, Setting, and Participants In this observational, cross-sectional study, the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database was searched from January 1, 1999, to December 31, 2018, for diabetes as a multiple cause and the underlying cause of death among residents aged 25 years or older in US counties. County urbanization was categorized as metro, medium-small, and rural. Weighted multiple linear regression models and jackknife resampling, with a 3-segment time component, were used. The models included exposures with up to 3-way interactions and were age standardized to the 2009-2010 population. The analyses were conducted from July 1, 2020, to February 1, 2022. Exposures County urbanization (metro, medium-small, or rural), gender (men or women), age group (25-54, 55-74, or ≥75 years), and region (Midwest, Northeast, South, or West). Main Outcomes and Measures Annual diabetes mortality rate per 100 000 people. Results From 1999-2018, based on 4 022 238 309 person-years, diabetes was a multiple cause of death for 4 735 849 adults aged 25 years or older. As a multiple cause, diabetes mortality rates in 2017-2018 vs 1999-2000 were highest and unchanged in rural counties (157.2 [95% CI, 150.7-163.7] vs 154.1 [95% CI, 148.2-160.1]; P = .49) but lower in medium-small counties (123.6 [95% CI, 119.6-127.6] vs 133.6 [95% CI, 128.4-138.8]; P = .003) and urban counties (92.9 [95% CI, 90.5-95.3] vs 109.7 [95% CI, 105.2-114.1]; P < .001). In 2017-2018 vs 1999-2000, mortality rates were higher in rural men (+18.2; 95% CI, 14.3-22.1) but lower in rural women (−14.0; 95% CI, −17.7 to −10.3) ( P < .001 for both). In the 25- to 54-year age group, mortality rates in 2017-2018 vs 1999-2000 showed a greater increase in rural counties (+9.4; 95% CI, 8.6-10.2) compared with medium-small counties (+4.5; 95% CI, 4.0-5.0) and metro counties (+0.9; 95% CI, 0.4-1.4) ( P < .001 for all). Of all regions and urbanization levels, the mortality rate in 2017-2018 vs 1999-2000 was higher only in the rural South (+13.8; 95% CI, 7.6-20.0; P < .001). Conclusions and Relevance In this cross-sectional study, US rural counties had the highest overall diabetes mortality rate. The determinants of persistent rural disparities, in particular for rural men and for adults in the rural South, require investigation.

Abstract Context Diabetic ketoacidosis (DKA) in pregnancy is an obstetric emergency with risk of maternofetal death. Objective This work aimed to evaluate DKA events in pregnant women admitted to our inpatient obstetric service, and to examine associated clinical risk factors, presentation, and pregnancy outcomes. Methods A retrospective cohort study was conducted at the Mayo Clinic, Rochester, Minnesota, USA, and included women aged 17 to 45 years who were treated for DKA during pregnancy between January 1, 2004 and December 31, 2021. Main outcome measures included maternal and fetal death along with a broad spectrum of maternal and fetal pregnancy outcomes. Results A total of 71 DKA events were identified in 58 pregnancies among 51 women, 48 (82.8%) of whom had type 1 diabetes. There were no maternal deaths, but fetal demise occurred in 10 (17.2%) pregnancies (6 miscarriages and 4 stillbirths). Maternal social stressors were frequently present (n = 30, 51.0%), and glycemic control was suboptimal (median first trimester glycated hemoglobin A1c = 9.0%). Preeclampsia was diagnosed in 17 (29.3%) pregnancies. Infants born to women with DKA were large for gestational age (n = 16, 33.3%), suffered from neonatal hypoglycemia (n = 29, 60.4%) and required intensive care unit admission (n = 25, 52.1%). Conclusion DKA is associated with a high rate of maternofetal morbidity and fetal loss. Prenatal education strategies for women with diabetes mellitus should include a strong focus on DKA prevention, and clinicians and patients should have a high index of suspicion for DKA in all pregnant women who present with symptoms that could be attributed to this condition.

Abstract Objective This study aimed to determine the effects of a long‐acting glucagon‐like peptide‐1 (GLP‐1) receptor agonist, liraglutide, and placebo subcutaneously over 16 weeks on weight and gastric functions and to evaluate associations of single‐nucleotide polymorphisms in GLP1R (rs6923761) and TCF7L2 (rs7903146) with effects of liraglutide. Methods The study conducted a randomized, parallel‐group, placebo‐controlled, 16‐week trial of liraglutide, escalated to 3 mg subcutaneously daily in 136 otherwise healthy adults with obesity. Weight, gastric emptying of solids (GES), gastric volumes, satiation, and body composition measured at baseline and after treatment were compared in two treatment groups using analysis of covariance. Results Liraglutide ( n = 59) and placebo ( n = 65) groups completed treatment. Relative to placebo, liraglutide increased weight loss at 5 and 16 weeks (both p < 0.05), slowed time to half GES (T 1/2 ) at 5 and 16 weeks (both p < 0.001), and increased fasting gastric volume ( p = 0.01) and satiation ( p < 0.01) at 16 weeks. GES T 1/2 was positively correlated with weight loss on liraglutide (both p < 0.001). After 16 weeks of liraglutide, GLP1R rs6923761 (AG/AA vs. GG) was associated with reduced percent body fat ( p = 0.062), and TCF7L2 rs7903146 (CC vs. CT/TT) was associated with lower body weight ( p = 0.015). Conclusions Liraglutide, 3 mg, induces weight loss with delay in GES T 1/2 and reduces calorie intake. Slowing GES and variations in GLP1R and TCF7L2 are associated with liraglutide effects in obesity.