Enhancing Type 1 Diabetes Immunological Risk Prediction with Continuous Glucose Monitoring and Genetic Profiling.

Early identification of individuals at high risk for type 1 diabetes (T1D) is essential for timely intervention. Islet autoantibodies (AB) and continuous glucose monitoring (CGM) reveal early signs of glycemic dysregulation, while T1D genetic risk scores (GRS) further improve disease prediction. We use CGM data and T1D GRS to develop an AB classifier (1 AB vs.

Novel Detection and Progression Markers for Diabetes Based on Continuous Glucose Monitoring Data Dynamics.

Context: Static measures of continuous glucose monitoring (CGM) data, such as time spent in specific glucose ranges (70-180 mg/dL or 70-140 mg/dL), do not fully capture the dynamic nature of blood glucose, particularly the subtle gradual deterioration of glycemic control over time in individuals with early-stage type 1 diabetes.

Objective: Develop a diabetes diagnostic tool based on 2 markers of CGM dynamics: CGM entropy rate (ER) and Poincaré plot (PP) ellipse area (S).

Methods: A total of 5754 daily CGM profiles from 843 individuals with type 1, type 2 diabetes, or healthy individuals with or without islet autoantibody status were used to compute 2 individual dynamic markers: ER (in bits per transition; BPT) of daily probability matrices describing CGM transitions between 8 glycemic states, and the area S (mg2/dL2) of individual CGM PP ellipses using standard PP descriptors.

Predicting the Risk of Developing Type 1 Diabetes Using a One-Week Continuous Glucose Monitoring Home Test With Classification Enhanced by Machine Learning: An Exploratory Study.

Background: Detection of two or more autoantibodies (Ab) in the blood might describe those individuals at increased risk of developing type 1 diabetes (T1D) during the following years. The aim of this exploratory study is to propose a high versus low T1D risk classifier using machine learning technology based on continuous glucose monitoring (CGM) home data.

Methods: Forty-two healthy relatives of people with T1D with mean ± SD age of 23.

Predicting Immunological Risk for Stage 1 and Stage 2 Diabetes Using a 1-Week CGM Home Test, Nocturnal Glucose Increments, and Standardized Liquid Mixed Meal Breakfasts, with Classification Enhanced by Machine Learning.

Predicting the risk for type 1 diabetes (T1D) is a significant challenge. We use a 1-week continuous glucose monitoring (CGM) home test to characterize differences in glycemia in at-risk healthy individuals based on autoantibody presence and develop a machine-learning technology for CGM-based islet autoantibody classification. Sixty healthy relatives of people with T1D with mean ± standard deviation age of 23.

Influence of Sleep Stage on LH Pulse Initiation in the Normal Late Follicular Phase and in Polycystic Ovary Syndrome.

Objective: During the early follicular phase, sleep-related luteinizing hormone (LH) pulse initiation is positively associated with brief awakenings but negatively associated with rapid eye movement (REM) sleep. The relationship between sleep architecture and LH pulse initiation has not been assessed in other cycle stages or in women with polycystic ovary syndrome (PCOS).

Design And Methods: We performed concomitant frequent blood sampling (LH pulse analysis) and polysomnography on 8 normal women (cycle day 7-11) and 7 women with PCOS (at least cycle day 7).

Recent Exposure to Hypoglycemia Increases Glucose Variability Following a Hyper/Hypoglycemic Metabolic Challenge in T1D.

Aims: In type 1 diabetes (T1D), repeated hypoglycemic episodes may reduce hormonal defenses and increase the risk for severe hypoglycemia. In this work, we investigate the effect of a structured hyper/hypoglycemic metabolic challenge on the postintervention glucose variability in T1D subjects studied at home.

Methods: Thirty T1D subjects using insulin pump were monitored with blood glucose meters (SMBG) during a 1-month observation period.

Population-Specific Models of Glycemic Control in Intensive Care: Towards a Simulation-Based Methodology for Protocol Optimization.

Stress-induced hyperglycemia is common in critically ill patients, where elevated blood glucose and glycemic variability have been found to contribute to infection, slow wound healing, and short-term mortality. Early clinical studies demonstrated improvement in mortality and morbidity resulting from intensive insulin therapy targeting euglycemia. Follow-up clinical studies have shown mixed results suggesting that the risk of hypoglycemia may outweigh the benefits of aggressive glycemic control.

Glucagon - the new 'insulin' in the pathophysiology of diabetes.

Purpose Of Review: Autoimmune destruction of the β cells is considered the key abnormality in type 1 diabetes mellitus and insulin replacement the primary therapeutic strategy. However, a lack of insulin is accompanied by disturbances in glucagon release, which is excessive postprandially, but insufficient during hypoglycaemia. In addition, replacing insulin alone appears insufficient for adequate glucose control.

The level of circulating octanoate does not predict ghrelin O-acyl transferase (GOAT)-mediated acylation of ghrelin during fasting.

Background: Acyl-ghrelin is a 28-amino acid peptide released from the stomach. Ghrelin O-acyl transferase (GOAT) attaches an 8-carbon medium-chain fatty acid (MCFA) (octanoate) to serine 3 of ghrelin. This acylation is necessary for the activity of ghrelin.

Four-hour infusion of hydrocortisone does not suppress the nocturnal increase of circulating acyl- or desacyl-ghrelin concentrations in healthy young adults.

Background: Ghrelin is a 28-amino acid peptide released from the stomach. Ghrelin is found in the circulation in two forms: acyl- and desacyl-ghrelin. Acyl- and desacyl-ghrelin concentrations increase at night, when cortisol concentrations are low.

Age-dependent decline in acyl-ghrelin concentrations and reduced association of acyl-ghrelin and growth hormone in healthy older adults.

Background: Acyl-ghrelin is thought to have both orexigenic effects and to stimulate GH release. A possible cause of the anorexia of aging is an age-dependent decrease in circulating acyl-ghrelin levels.

Objectives: The purpose of the study was to compare acyl-ghrelin and GH concentrations between healthy old and young adults and to examine the relationship of acyl-ghrelin and GH secretion in both age groups.

Pharmacokinetics modeling of exogenous glucagon in type 1 diabetes mellitus patients.

Background: Insulin-induced hypoglycemia is as a critical barrier in the treatment of type 1 diabetes mellitus patients and may lead to unconsciousness, brain damage, or even death. Clinically, glucagon is used as a rescue drug to treat severe hypoglycemic episodes. More recently, in a bihormonal closed-loop glucose control, glucagon has been used subcutaneously along with insulin for protection against hypoglycemia.

Association of Basal hyperglucagonemia with impaired glucagon counterregulation in type 1 diabetes.

Glucagon counterregulation (GCR) protects against hypoglycemia, but is impaired in type 1 diabetes (T1DM). A model-based analysis of in vivo animal data predicts that the GCR defects are linked to basal hyperglucagonemia. To test this hypothesis we studied the relationship between basal glucagon (BasG) and the GCR response to hypoglycemia in 29 hyperinsulinemic clamps in T1DM patients.

Average daily risk range as a measure of glycemic risk is associated with mortality in the intensive care unit: a retrospective study in a burn intensive care unit.

Background: Although tight glycemic control has been associated with improved outcomes in the intensive care unit (ICU), glycemic variability may be the influential factor in mortality. The main goal of the study was to relate blood glucose (BG) variability of burn ICU patients to outcomes using a sensitive measure of glycemic variability, the average daily risk range (ADRR).

Method: Data from patients admitted to a burn ICU were used.

Models of glucagon secretion, their application to the analysis of the defects in glucagon counterregulation and potential extension to approximate glucagon action.

This review analyzes an interdisciplinary approach to the pancreatic endocrine network-like relationships that control glucagon secretion and glucagon counterregulation (GCR). Using in silico studies, we show that a pancreatic feedback network that brings together several explicit interactions between islet peptides and blood glucose reproduces the normal GCR axis and explains its impairment in diabetes. An α-cell auto-feedback loop drives glucagon pulsatility and mediates triggering of GCR by hypoglycemia by a rapid switch-off of β-cell signals.

Validation of a deconvolution procedure (AutoDecon) for identification and characterization of fasting insulin secretory bursts.

Background: Insulin secretion is pulsatile, and has been shown to be altered in both physiologic and pathophysiologic conditions. The identification and characterization of such pulses have been challenging, partially because of the low concentrations of insulin during fasting and its short half-life. Existing pulse detection algorithms used to identify insulin pulses either cannot separate hormone pulses into their secretory burst and clearance components, or have been limited by both the subjective nature of initial peak selection and a lack of statistical verification of bursts.

System-level control to optimize glucagon counterregulation by switch-off of α-cell suppressing signals in β-cell deficiency.

Background: Glucagon counterregulation (GCR) is a key protection against hypoglycemia that is compromised in diabetes. In β-cell-deficient rats, GCR pulsatility can be amplified if insulin (INS) or somatostatin (SS) are infused in the pancreatic artery and then switched off during hypoglycemia. The data indicate that these signals act by different mechanisms, and here we analyze the differences between the two switch offs (SOs) and predict the GCR-amplifying effect of their individual or combined application.

Pancreatic network control of glucagon secretion and counterregulation.

Glucagon counterregulation (GCR) is a key protection against hypoglycemia compromised in insulinopenic diabetes by an unknown mechanism. In this work, we present an interdisciplinary approach to the analysis of the GCR control mechanisms. Our results indicate that a pancreatic network which unifies a few explicit interactions between the major islet peptides and blood glucose (BG) can replicate the normal GCR axis and explain its impairment in diabetes.

AutoDecon: a robust numerical method for the quantification of pulsatile events.

This work presents a new approach to the analysis of aperiodic pulsatile heteroscedastic time-series data, specifically hormone pulsatility. We have utilized growth hormone (GH) concentration time-series data as an example for the utilization of this new algorithm. While many previously published approaches used for the analysis of GH pulsatility are both subjective and cumbersome to use, AutoDecon is a nonsubjective, standardized, and completely automated algorithm.

Biomathematical modeling of pulsatile hormone secretion: a historical perspective.

Shortly after the recognition of the profound physiological significance of the pulsatile nature of hormone secretion, computer-based modeling techniques were introduced for the identification and characterization of such pulses. Whereas these earlier approaches defined perturbations in hormone concentration-time series, deconvolution procedures were subsequently employed to separate such pulses into their secretion event and clearance components. Stochastic differential equation modeling was also used to define basal and pulsatile hormone secretion.

Identifying small pulsatile signals within noisy data: a fluorescence application.

One of the most challenging scientific data analysis quandaries is the identification of small intermittent irregularly spaced pulsatile signals in the presence of large amounts of heteroscedastic experimental measurement uncertainties. We present an application of the use of AutoDecon to a typical fluorescence and/or spectroscopic data sampling paradigm, which is to detect a single fluorophore in the presence of high background emission. Our calculations demonstrate that single events can be reliably detected by AutoDecon with a signal-to-noise ratio of 3/20.

AutoDecon, a deconvolution algorithm for identification and characterization of luteinizing hormone secretory bursts: description and validation using synthetic data.

Hormone signaling is often pulsatile, and multiparameter deconvolution procedures have long been used to identify and characterize secretory events. However, the existing programs have serious limitations, including the subjective nature of initial peak selection, lack of statistical verification of presumed bursts, and user-unfriendliness of the application. Here we describe a novel deconvolution program, AutoDecon, which addresses these concerns.

Amplification of pulsatile glucagon counterregulation by switch-off of alpha-cell-suppressing signals in streptozotocin-treated rats.

Glucagon counterregulation (GCR) is a key protection against hypoglycemia that is compromised in diabetes via an unknown mechanism. To test the hypothesis that alpha-cell-inhibiting signals that are switched off during hypoglycemia amplify GCR, we studied streptozotocin (STZ)-treated male Wistar rats and estimated the effect on GCR of intrapancreatic infusion and termination during hypoglycemia of saline, insulin, and somatostatin. Times 10 min before and 45 min after the switch-off were analyzed.