Citations

ABSTRACT High-fat diet (HFD)-fed mouse models have been widely used to study early type 2 diabetes. Decreased β-cell glucokinase (GCK) expression has been observed in HFD-induced diabetes. However, owing to its crucial roles in glucose metabolism in the liver and in islet β-cells, the contribution of decreased GCK expression to the development of HFD-induced diabetes is unclear. Here, we employed a β-cell-targeted gene transfer vector and determined the impact of β-cell-specific increase in GCK expression on β-cell function and glucose handling in vitro and in vivo. Overexpression of GCK enhanced glycolytic flux, ATP-sensitive potassium channel activation and membrane depolarization, and increased proliferation in Min6 cells. β-cell-targeted GCK transduction did not change glucose handling in chow-fed C57BL/6 mice. Although adult mice fed a HFD showed reduced islet GCK expression, impaired glucose tolerance and decreased glucose-stimulated insulin secretion (GSIS), β-cell-targeted GCK transduction improved glucose tolerance and restored GSIS. Islet perifusion experiments verified restored GSIS in isolated HFD islets by GCK transduction. Thus, our data identify impaired β-cell GCK expression as an underlying mechanism for dysregulated β-cell function and glycemic control in HFD-induced diabetes. Our data also imply an etiological role of GCK in diet-induced diabetes. This article has an associated First Person interview with the first author of the paper.

Objectives Human pancreatic polypeptide (HPP) is a hormone secreted by the ventral pancreas. While postprandial HPP levels have been studied in chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC), there are limited data on fasting HPP in these diseases. Methods Fasting serum HPP was measured in the following groups of patients: CP with diabetes mellitus (DM) (n = 16), CP without DM (n = 34), PDAC with new-onset DM (n = 50), PDAC without DM (n = 49), new-onset type 2 DM (n = 50), and controls without DM (n = 49). Sixty-six had type 3c DM (CP with DM, n = 16; PDAC with new-onset DM, n = 50). Results Median fasting HPP levels (in picograms per milliliter) were similar among all groups. Median (interquartile range) HPP levels in new-onset type 2 DM (n = 50; 288.3 [80.1–1072.1]) were similar to those in type 3c DM (n = 66; 242.3 [64.9–890.9]) (P = 0.71). In PDAC (n = 99), HPP values were similar in pancreatic head (n = 75) versus body/tail (n = 24) tumors (245.3 [64.3–1091.3] vs 334.7 [136.1–841.5]; P = 0.95), regardless of DM. Conclusions Fasting HPP levels are similar in CP, PDAC, and controls regardless of glycemic status.

Purpose: Thyroid autoimmunity affects approximately 5% of the population, and its investigation relies heavily on the use of autoantibodies. Thyroid stimulating hormone receptor (TSHR) autoantibodies (TRAb) play a central role in the evaluation of Graves disease (GD), Graves ophthalmopathy (GO) and pretibial myxedema (PTM). However, there is still controversy regarding overall TRAb assay diagnostic accuracy and their prognostic utility. Methods: We reviewed and analyzed the literature reporting TRAb assays and their clinical utility. Results: Current assays measure the overall TRAb titer in a competitive manner (TSH binding inhibiting immunoglobulin assay) or biologic activity of the stimulating TSHR autoantibodies (thyroid stimulating immunoglobulin assay). Both types of assays have improved over time with advances in sensitivity and specificity. TRAb are particularly relevant in hyperthyroidism cases where use of iodinated contrast is not an option (e.g., pregnancy or recent use of iodinated contrast) or in cases of euthyroid eye disease, suspicious for GO. Third generation TRAb assays are useful for therapy selection in GD, prognostic predictions in GO and risk prediction for fetal and neonatal thyrotoxicosis. Discussion: Given the pathogenic role of TRAb, we expect that the future will bring useful evidence regarding their predictive role with respect to efficacy of therapeutic modalities for GO and PTM. We also hope to better understand the role of blocking and neutral antibodies against TSHR, and harness that ability for modulation of thyroid function or therapy of differentiated thyroid carcinoma managed with TSH suppression. Conclusions: Thyroid autoimmune diseases have seen tremendous gains in understanding their pathophysiology, largely antibody mediated. Better TRAb testing is becoming a springboard for providing individualized patient care.

Objective: The objective was to investigate the relationship of body mass index (BMI) to differing glycemic responses to psychological stress in patients with type 1 diabetes. Methods: Continuous blood glucose monitor (CGM) data were collected for 1 week from a total of 37 patients with BMI ranging from 21.5-39.4 kg/m 2 (mean = 28.2 ± 4.9). Patients reported daily stress levels (5-point Likert-type scale, 0 = none, 4 = extreme), physical activity, carbohydrate intake, insulin boluses and basal rates. Daily reported carbohydrates, total insulin bolus, and average blood glucose (BG from CGM) were compared among patients based on their BMI levels on days with different stress levels. In addition, daily averages of a model-based “effectiveness index” (quantifying the combined impact of insulin and carbohydrate on glucose levels) were defined and compared across stress levels to capture meal and insulin independent glycemic changes. Results: Analyses showed that patient BMI likely moderated stress related glycemic changes. Linear mixed effect model results were significant for the stress-BMI interaction on both behavioral and behavior-independent glycemic changes. Across participants, under stress, an increase was observed in daily carbohydrate intake and effectiveness index at higher BMI. There was no significant interactive effect on daily insulin or average BG. Conclusion: Findings suggest that (1) stress has both behavioral and nonbehavioral glycemic effects on T1D patients and (2) the direction and magnitude of these effects are potentially influenced by level of stress and patient BMI. Possibly responsible for these observed effects are T1D/BMI related alterations in endocrine response.

Background: Glucose variability (GV) has been increasingly (or more extensively) studied in patients with type 1 diabetes (T1D) in the ambulatory setting; limited data exist on GV in hospitalized patients with T1D. Materials and Methods: Retrospective single center cohort study, we analyzed in-hospital glucose measurements to assess GV in 736 hospitalized patients in different units over a consecutive 5-year period of time. GV was assessed by mean blood glucose (BG), Average daily risk range (ADRR), high BG index, and low BG index. To place our findings in context, we conducted a systematic review using Cochrane collaboration methodology to critically analyze current published literature on GV in hospitalized T1D patients. Results: Overall, glycemic control was suboptimal with mean BG 183 ± 51.5 mg/dL and mean ADRR 35 with only 16% patients being categorized as low risk (ADRR <20) for hypo or hyperglycemia. Patients admitted in medical units had mean BG of 194.4 ± 42.8 mg/dL (95% CI = 101.2–346.6) and ADRR of 39.4 ± 16 (95% CI = 1.3–118.7), which were higher than the patients admitted in the surgical units (mean BG 168.1 ± 35.7 (95% CI = 74.8–301.8) and mean ADRR (28.8 ± 13.1 [95% CI = 0.3–93.1]). For the systematic review, initial search yielded 2336 studies for screening, however, none of them had data specific for T1D. Conclusion: GV is high in hospitalized T1D patients admitted at our tertiary care center. Review of the literature shows paucity of data regarding GV in hospitalized patients with T1D.

OBJECTIVE Artificial pancreas (AP) systems are best positioned for optimal treatment of type 1 diabetes (T1D) and are currently being tested in outpatient clinical trials. Our consortium developed and tested a novel adaptive AP in an outpatient, single-arm, uncontrolled multicenter clinical trial lasting 12 weeks. RESEARCH DESIGN AND METHODS Thirty adults with T1D completed a continuous glucose monitor (CGM)-augmented 1-week sensor-augmented pump (SAP) period. After the AP was started, basal insulin delivery settings used by the AP for initialization were adapted weekly, and carbohydrate ratios were adapted every 4 weeks by an algorithm running on a cloud-based server, with automatic data upload from devices. Adaptations were reviewed by expert study clinicians and patients. The primary end point was change in hemoglobin A1c (HbA1c). Outcomes are reported adhering to consensus recommendations on reporting of AP trials. RESULTS Twenty-nine patients completed the trial. HbA1c, 7.0 ± 0.8% at the start of AP use, improved to 6.7 ± 0.6% after 12 weeks (−0.3, 95% CI −0.5 to −0.2, P &lt; 0.001). Compared with the SAP run-in, CGM time spent in the hypoglycemic range improved during the day from 5.0 to 1.9% (−3.1, 95% CI −4.1 to −2.1, P &lt; 0.001) and overnight from 4.1 to 1.1% (−3.1, 95% CI −4.2 to −1.9, P &lt; 0.001). Whereas carbohydrate ratios were adapted to a larger extent initially with minimal changes thereafter, basal insulin was adapted throughout. Approximately 10% of adaptation recommendations were manually overridden. There were no protocol-related serious adverse events. CONCLUSIONS Use of our novel adaptive AP yielded significant reductions in HbA1c and hypoglycemia.

Aims. Hypoglycemia is a limiting factor for achieving stringent glycemic control in diabetes. This study analyzes the frequency and predictors of hypoglycemia in insulin-treated diabetes in an ambulatory setting. Methods. A retrospective chart review was performed to study self-monitored blood glucose (SMBG) data for 3 months prior to a patient’s HbA1c test. Results. Hypoglycemia occurred more frequently in type 1 than in type 2 diabetes; however, 19% of type 2 diabetes patients did experience at least one episode of severe hypoglycemia. For type 1 diabetes, hypoglycemia had a positive association with glycemic variability and duration of diabetes and a negative association with HbA1c and lowest blood glucose (BG). For type 2 diabetes, a positive association was noted with glycemic variability and a negative association with age and lowest BG. Conclusions. Delineating factors predisposing to hypoglycemia in type 2 diabetes is difficult. Lower HbA1c is a potential predictor of hypoglycemia in type 1 but not in type 2 diabetes. Longer duration of diabetes for type 1 and younger age for type 2 are associated with more hypoglycemia. Glycemic variability portends increased risk for hypoglycemia and should be a focus of further research.