Insulin secretion from human beta cells is heterogeneous and dependent on cell-to-cell contacts

Aims/hypothesis: We assessed the heterogeneity of insulin secretion from human isolated beta cells and its regulation by cell-to-cell contacts. Methods: Insulin secretion from single and paired cells was assessed by a reverse haemolytic plaque assay. The percentage of plaque-forming cells, the mean plaque area and the total plaque development were evaluated after 1h of stimulation with different secretagogues. Results: Not all beta cells were surrounded by a haemolytic plaque under all conditions tested. A small fraction of the beta cell population (20%) secreted more than 90% and 70% of total insulin at 2.2 and 22.2mmol/l glucose, respectively. Plaque-forming cells, mean plaque area and total plaque development were increased at 12.2 and 22.2 compared with 2.2mmol/l glucose. Insulin secretion of single beta cells was similar at 12.2 and 22.2mmol/l glucose. Insulin secretion of beta cell pairs was increased compared with that of single beta cells and was higher at 22.2 than at 12.2mmol/l glucose. Insulin secretion of beta cells in contact with alpha cells was also increased compared with single beta cells, but was similar at 22.2 compared with 12.2mmol/l glucose. Delta and other non-beta cells did not increase insulin secretion of contacting beta cells compared with that of single beta cells. Differences in insulin secretion between 22.2 and 12.2mmol/l glucose were observed in murine but not in human islets. Conclusions/interpretation: Human beta cells are highly heterogeneous in terms of insulin secretion so that a small fraction of beta cells contributes to the majority of insulin secreted. Homologous and heterologous intercellular contacts have a significant impact on insulin secretion and this could be related to the particular architecture of human islet

Respective Contributions of Glycemic Variability and Mean Daily Glucose as Predictors of Hypoglycemia in Type 1 Diabetes: Are They Equivalent?

To evaluate the respective contributions of short-term glycemic variability and mean daily glucose (MDG) concentration to the risk of hypoglycemia in type 1 diabetes. People with type 1 diabetes (n = 100) investigated at the University Hospital of Montpellier (France) underwent continuous glucose monitoring (CGM) on two consecutive days, providing a total of 200 24-h glycemic profiles. The following parameters were computed: MDG concentration, within-day glycemic variability (coefficient of variation for glucose [%CV]), and risk of hypoglycemia (presented as the percentage of time spent below three glycemic thresholds: 3.9, 3.45, and 3.0 mmol/L). MDG was significantly higher, and %CV significantly lower (both P < 0.001), when comparing the 24-h glycemic profiles according to whether no time or a certain duration of time was spent below the thresholds. Univariate regression analyses showed that MDG and %CV were the two explanatory variables that entered the model with the outcome variable (time spent below the thresholds). The classification and regression tree procedure indicated that the predominant predictor for hypoglycemia was %CV when the threshold was 3.0 mmol/L. In people with mean glucose ≤7.8 mmol/L, the time spent below 3.0 mmol/L was shortest (P < 0.001) when %CV was below 34%. In type 1 diabetes, short-term glycemic variability relative to mean glucose (i.e., %CV) explains more hypoglycemia than does mean glucose alone when the glucose threshold is 3.0 mmol/L. Minimizing the risk of hypoglycemia requires a %CV below 34%

Real world hypoglycaemia related to glucose variability and Flash glucose scan frequency assessed from global FreeStyle Libre data.

Flash glucose monitoring provides a range of glucose metrics. In the current study, we aim to identify those that indicate that glycaemic targets can be consistently met and contrast the total (t-CV) and within-day coefficient of variation (wd-CV) to guide the assessment of glucose variability and hypoglycaemia exposure. De-identified data from Flash readers were collected. The readers were sorted into 10 equally sized groups of scan frequency followed by quartiles of estimated A1c (eA1c). A similar grouping was performed for the total coefficient of variation (t-CV) and within-day coefficient of variation (wd-CV). In addition, analysis of the association of time below 54 mg/dl and glucose variability measured by t-CV and wd-CV was performed. The dataset included 1 002 946 readers. Readers sorted by 10 equal groups of scan rate and quartiles by eA1c, t-CV and wd-CV represented 25 074 readers per group. The association of lower eA1c with higher time in range and reduced time above range was clear. The correlation of eA1c quartiles and time below range was not consistent. An association between glucose variability and hypoglycaemia was found. Both wd-CV and t-CV were associated with time below range. For achieving the consensus target of <1% time below 54 mg/dl, the associated wd-CV and t-CV values were 33.5% and 39.5%, respectively. The type of CV reported by the different continuous glucose monitoring systems should be acknowledged. CV <36% might not be adequate to ensure low hypoglycaemia exposure. To our knowledge, the majority of continuous glucose monitoring reports the t-CV. Appropriate thresholds should be used to identify patients that would probably meet time below range targets (t-CV <40% or wd-CV <34%)

Precision medicine in the era of artificial intelligence: implications in chronic disease management.

Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflammatory pathway. Inflammation is the natural reaction of the immune system to a variety of stimuli, such as pathogens, damaged cells, and harmful substances. Metabolically triggered inflammation, also called metaflammation or low-grade chronic inflammation, is the consequence of a synergic interaction between the host and the exposome-a combination of environmental drivers, including diet, lifestyle, pollutants and other factors throughout the life span of an individual. Various levels of chronic inflammation are associated with several lifestyle-related diseases such as diabetes, obesity, metabolic associated fatty liver disease (MAFLD), cancers, cardiovascular disorders (CVDs), autoimmune diseases, and chronic lung diseases. Chronic diseases are a growing concern worldwide, placing a heavy burden on individuals, families, governments, and health-care systems. New strategies are needed to empower communities worldwide to prevent and treat these diseases. Precision medicine provides a model for the next generation of lifestyle modification. This will capitalize on the dynamic interaction between an individual's biology, lifestyle, behavior, and environment. The aim of precision medicine is to design and improve diagnosis, therapeutics and prognostication through the use of large complex datasets that incorporate individual gene, function, and environmental variations. The implementation of high-performance computing (HPC) and artificial intelligence (AI) can predict risks with greater accuracy based on available multidimensional clinical and biological datasets. AI-powered precision medicine provides clinicians with an opportunity to specifically tailor early interventions to each individual. In this article, we discuss the strengths and limitations of existing and evolving recent, data-driven technologies, such as AI, in preventing, treating and reversing lifestyle-related diseases

Proteasomal degradation of the histone acetyl transferase p300 contributes to beta-cell injury in a diabetes environment

In type 2 diabetes, amyloid oligomers, chronic hyperglycemia, lipotoxicity, and pro-inflammatory cytokines are detrimental to beta-cells, causing apoptosis and impaired insulin secretion. The histone acetyl transferase p300, involved in remodeling of chromatin structure by epigenetic mechanisms, is a key ubiquitous activator of the transcriptional machinery. In this study, we report that loss of p300 acetyl transferase activity and expression leads to beta-cell apoptosis, and most importantly, that stress situations known to be associated with diabetes alter p300 levels and functional integrity. We found that proteasomal degradation is the mechanism subserving p300 loss in beta-cells exposed to hyperglycemia or pro-inflammatory cytokines. We also report that melatonin, a hormone produced in the pineal gland and known to play key roles in beta-cell health, preserves p300 levels altered by these toxic conditions. Collectively, these data imply an important role for p300 in the pathophysiology of diabetes

The Use of Biomaterials in Islet Transplantation

Pancreatic islet transplantation is a therapeutic option to replace destroyed β cells in autoimmune diabetes. Islets are transplanted into the liver via the portal vein; however, inflammation, the required immunosuppression, and lack of vasculature decrease early islet viability and function. Therefore, the use of accessory therapy and biomaterials to protect islets and improve islet function has definite therapeutic potential. Here we review the application of niche accessory cells and factors, as well as the use of biomaterials as carriers or capsules, for pancreatic islet transplantation

Place de la pompe à insuline pour le traitement des patients avec un diabète de type 2 [Place of the insulin pump for the treatment of type 2 diabetic patients]

Continuous subcutaneous insulin infusion devices, commonly called insulin pumps, have been used for the treatment of patients with type 1 diabetes for several years. The benefits on glycemic control and on the quality of life of these patients are clear and well documented in the literature. On the other hand, their use in insulin-requiring patients with type 2 diabetes is less widespread. However, studies have shown that this therapeutic option is safe and effective for this population as well. In all cases, individualized assessment and follow-up by a specialized multidisciplinary care team is necessary to support patients with type 2 diabetes for whom an insulin pump is considered. We propose to describe here the current state of this clinical practice

Le diabète : une pandémie oubliée ? []

International audienc

Diabète : et si on se mettait à la place du patient? []

International audienceLe diabète est une des maladies chroniques les plus fréquentes dans nos sociétés modernes: en Suisse, 7,4% de la population en souffre. Mais, finalement, que veut dire exactement vivre avec une maladie chronique ?Une des premières conséquences pour un « malade chronique » est la nécessité d’un suivi médical régulier : c’est donc trouver un médecin en qui remettre sa confiance, c’est vieillir et évoluer avec lui. Nos patients, en effet, vivent avec nous les évolutions (et révolutions ?) actuelles de la diabétologie. Elles ont été riches dans le domaine de l’éducation thérapeutique, dans la relation humaine avec les soignants; elles ont été importantes en pharmacologie et restent en constante progression dans le domaine de la technologie. Par exemple, pour les patients diabétiques de type 2, depuis quinze années maintenant, les traitements ne cessent d’évoluer. La mise à jour récente – par l’American Diabetes Association/European Association for the Study of Diabetes et la Société Suisse d’Endocrinologie et de Diabétologie1,2 – des recommandations concernant la prise en charge du diabète met clairement en avant les inhibiteurs du SGLT2 et les agonistes du GLP-1. Ces recommandations bouleversent nos pratiques, et parfois déstabilisent nos patients. La place des inhibiteurs de la DPP-4, classe médicamenteuse d’utilisation confortable, sans risque majeur de mauvaise tolérance, sans induction d’hypoglycémie mais également sans effet cardiovasculaire positif démontré, est peut-être plus difficile à trouver actuellement. Cependant, ne faut-il pas oublier les recommandations modernes devant nos patients intolérants, à risque, dénutris, ou ayant présenté des complications sous les nouveaux médicaments stars de la diabétologie