HOMA2-B enhances assessment of type 1 diabetes risk among TrialNet Pathway to Prevention participants.

AIMS/HYPOTHESIS: Methods to identify individuals at highest risk for type 1 diabetes are essential for the successful implementation of disease-modifying interventions. Simple metabolic measures are needed to help stratify autoantibody-positive (Aab+) individuals who are at risk of developing type 1 diabetes. HOMA2-B is a validated mathematical tool commonly used to estimate beta cell function in type 2 diabetes using fasting glucose and insulin. The utility of HOMA2-B in association with type 1 diabetes progression has not been tested. METHODS: Baseline HOMA2-B values from single-Aab+ (n = 2652; mean age, 21.1 ± 14.0 years) and multiple-Aab+ (n = 3794; mean age, 14.5 ± 11.2 years) individuals enrolled in the TrialNet Pathway to Prevention study were compared. Cox proportional hazard models were used to determine associations between HOMA2-B tertiles and time to progression to type 1 diabetes, with adjustments for age, sex, HLA status and BMI z score. Receiver operating characteristic (ROC) analysis was used to test the association of HOMA2-B with type 1 diabetes development in 1, 2, 5 and 10 years. RESULTS: At study entry, HOMA2-B values were higher in single- compared with multiple-Aab+ Pathway to Prevention participants (91.1 ± 44.5 vs 83.9 ± 38.9; p < 0.001). Single- and multiple-Aab+ individuals in the lowest HOMA2-B tertile had a higher risk and faster rate of progression to type 1 diabetes. For progression to type 1 diabetes within 1 year, area under the ROC curve (AUC-ROC) was 0.685, 0.666 and 0.680 for all Aab+, single-Aab+ and multiple-Aab+ individuals, respectively. When correlation between HOMA2-B and type 1 diabetes risk was assessed in combination with additional factors known to influence type 1 diabetes progression (insulin sensitivity, age and HLA status), AUC-ROC was highest for the single-Aab+ group's risk of progression at 2 years (AUC-ROC 0.723 [95% CI 0.652, 0.794]). CONCLUSIONS/INTERPRETATION: These data suggest that HOMA2-B may have utility as a single-time-point measurement to stratify risk of type 1 diabetes development in Aab+ individuals.

The effects of cannabis and cannabinoids on the endocrine system.

With the increase in cannabis use due to policy changes and areas of decriminalization, it is important to recognize the potential impact of these substances on endocrine processes. Cannabinoids have many effects by activating the endocannabinoid system. This system plays a role in the normal functioning of nearly every organ and consists of the body's natural endocannabinoids, the cannabinoid receptors, and the enzymes and processes that regulate endocannabinoids. Exogenous cannabinoids such as Δ9-tetrahydrocannabinol (THC) are known to act through cannabinoid type 1 and 2 receptors, and have been shown to mimic endocannabinoid signaling and affect receptor expression. This review summarizes the known impacts of cannabis on thyroid, adrenal, and gonadal function in addition to glucose control, lipids, and bone metabolism, including: reduced female fertility, increased risk of adverse pregnancy outcomes, reduced sperm counts and function, lower thyroid hormone levels with acute use, blunting of stress response with chronic use, increased risk of prediabetes but lower risk of diabetes, suggested improvement of high density lipoproteins and triglycerides, and modest increase in fracture risk. The known properties of endocannabinoids, animal data, population data, and the possible benefits and concerns of cannabinoid use on hormonal function are discussed. The interconnectivity of the endocrine and endocannabinoid systems suggests opportunities for future therapeutic modalities which are an area of active investigation.

Cell-Free DNA Fragments as Biomarkers of Islet ß-Cell Death in Obesity and Type 2 Diabetes.

Type 2 diabetes (T2D) typically occurs in the setting of obesity and insulin resistance, where hyperglycemia is associated with decreased pancreatic ß-cell mass and function. Loss of ß-cell mass has variably been attributed to ß-cell dedifferentiation and/or death. In recent years, it has been proposed that circulating epigenetically modified DNA fragments arising from ß cells might be able to report on the potential occurrence of ß-cell death in diabetes. Here, we review published literature of DNA-based ß-cell death biomarkers that have been evaluated in human cohorts of islet transplantation, type 1 diabetes, and obesity and type 2 diabetes. In addition, we provide new data on the applicability of one of these biomarkers (cell free unmethylated INS DNA) in adult cohorts across a spectrum from obesity to T2D, in which no significant differences were observed, and compare these findings to those previously published in youth cohorts where differences were observed. Our analysis of the literature and our own data suggest that ß-cell death may occur in subsets of individuals with obesity and T2D, however a more sensitive method or refined study designs are needed to provide better alignment of sampling with disease progression events.

BIOTIN INTERFERENCE WITH ROUTINE CLINICAL IMMUNOASSAYS: UNDERSTAND THE CAUSES AND MITIGATE THE RISKS.

OBJECTIVE: The objectives of this report are to review the mechanisms of biotin interference with streptavidin/biotin-based immunoassays, identify automated immunoassay systems vulnerable to biotin interference, describe how to estimate and minimize the risk of biotin interference in vulnerable assays, and review the literature pertaining to biotin interference in endocrine function tests. METHODS: The data in the manufacturer's "Instructions for Use" for each of the methods utilized by seven immunoassay system were evaluated. We also conducted a systematic search of PubMed/MEDLINE for articles containing terms associated with biotin interference. Available original reports and case series were reviewed. Abstracts from recent scientific meetings were also identified and reviewed. RESULTS: The recent, marked, increase in the use of over-the-counter, high-dose biotin supplements has been accompanied by a steady increase in the number of reports of analytical interference by exogenous biotin in the immunoassays used to evaluate endocrine function. Since immunoassay methods of similar design are also used for the diagnosis and management of anemia, malignancies, autoimmune and infectious diseases, cardiac damage, etc., biotin-related analytical interference is a problem that touches every area of internal medicine. CONCLUSION: It is important for healthcare personnel to become more aware of immunoassay methods that are vulnerable to biotin interference and to consider biotin supplements as potential sources of falsely increased or decreased test results, especially in cases where a lab result does not correlate with the clinical scenario. ABBREVIATIONS: FDA = U.S. Food & Drug Administration FT3 = free tri-iodothyronine FT4 = free thyroxine IFUs = instructions for use LH = luteinizing hormone PTH = parathyroid hormone SA/B = streptavidin/biotin TFT = thyroid function test TSH = thyroid-stimulating hormone.

The relationship between BMI and insulin resistance and progression from single to multiple autoantibody positivity and type 1 diabetes among TrialNet Pathway to Prevention participants.

AIMS/HYPOTHESIS: The incidence of type 1 diabetes is increasing at a rate of 3-5% per year. Genetics cannot fully account for this trend, suggesting an influence of environmental factors. The accelerator hypothesis proposes an effect of metabolic factors on type 1 diabetes risk. To test this in the TrialNet Pathway to Prevention (PTP) cohort, we analysed the influence of BMI, weight status and insulin resistance on progression from single to multiple islet autoantibodies (Aab) and progression from normoglycaemia to diabetes. METHODS: HOMA1-IR was used to estimate insulin resistance in Aab-positive PTP participants. Cox proportional hazards models were used to evaluate the effects of BMI, BMI percentile (BMI%), weight status and HOMA1-IR on the progression of autoimmunity or the development of diabetes. RESULTS: Data from 1,310 single and 1,897 multiple Aab-positive PTP participants were included. We found no significant relationships between BMI, BMI%, weight status or HOMA1-IR and the progression from one to multiple Aabs. Similarly, among all Aab-positive participants, no significant relationships were found between BMI, weight status or HOMA1-IR and progression to diabetes. Diabetes risk was modestly increased with increasing BMI% among the entire cohort, in obese participants 13-20 years of age and with increasing HOMA1-IR in adult Aab-positive participants. CONCLUSIONS/INTERPRETATION: Analysis of the accelerator hypothesis in the TrialNet PTP cohort does not suggest a broad influence of metabolic variables on diabetes risk. Efforts to identify other potentially modifiable environmental factors should continue.

A primer on concentrated insulins: what an internist should know.

The common insulin concentration in most preparations of insulin is 100 units per mL or U-100. Human regular U-500 insulin was the first concentrated insulin introduced and it has been available in the United States since the 1950s. Humulin R is the only human regular U-500 available on the market. Human regular U-500 is five times more concentrated than U-100 and because of its pharmacodynamic properties, works as both a basal and a bolus insulin. Human regular U500 allows for delivery of a larger insulin dose with a smaller volume leading to better absorption compared to U-100 and has traditionally been used in patients with moderate to severe insulin resistance. More recently other forms of concentrated insulin have become available and the newer concentrated insulin preparations can be used in diabetic patients with or without insulin resistance. Our intent is to provide primary care physicians with a review of the pharmacology and current literature on concentrated insulins as well as recommendations for patient selection, dose initiation, and dose adjustment.

Insulin tactics in type 2 diabetes.

Insulin is the most powerful glycemic control agent available. However, its use as a therapeutic modality requires education of the patient and regimentation of food intake, exercise, and frequent glucose monitoring. Such regimentation is particularly important when using a basal-bolus therapy approach. The introduction of many novel noninsulin drugs in the past decade has resulted in better glycemic control and often a need to reduce previously instituted insulin therapy. Although many of these novel therapies by themselves do not cause hypoglycemia, by reducing the overall glycemic burden through a myriad of mechanisms, they function in an insulin-sparing fashion. The doses of exogenously administered insulin may therefore need to be reduced in the presence of these new drugs to mitigate hypoglycemia. For insulin therapy (or any other drug treatment) to be successful, it is critical that the physician not only establish glycemic goals, but communicate these goals to the patient. The measurement of HbA1c helps in achieving a long-term goal, but on a day-today basis, patients need to be cognizant of their own BG goals and what they need to do if falling outside of target. The patients' understanding of self-management skills and empowerment are therefore foundational to insulin therapy.