What is the underlying cause of type II diabetes? – Are cells protecting themselves against the reactivity of glucose?

Impact of COVID-19 on Children and Young Adults With Type 2 Diabetes: A Narrative Review With Emphasis on the Potential of Intermittent Fasting as a Preventive Strategy

Background: The world is still struggling to control the COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The level of uncertainty regarding the virus is still significantly high. The virus behaves differently in children and young adults. Most children and adolescents are either asymptomatic or have mild symptoms. They generally have a very good prognosis. However, it is not well-known whether children and young adults with type 2 diabetes are at risk of getting a severe infection of COVID-19. Many Muslim children with type 2 diabetes have been performing dawn to dusk fasting during the month of Ramadan, before and during the COVID-19 pandemic, and the impact of this on their health has not been well investigated. Previous studies in adults have suggested that intermittent fasting may be beneficial in different ways including reversal of type 2 diabetes and prevention of COVID-19 infection. Objective: The primary aim of this narrative review is to summarise the impacts of the COVID-19 pandemic on children and young adults with type 2 diabetes, and to identify the knowledge gaps in the literature. It also explores the potential of intermittent fasting in reversing the pathogenesis of diabetes and highlighting how this approach could prevent these patients from developing chronic complications. Methods: This narrative review has been produced by examining several databases, including Google Scholar, Research Gate, PubMed, Cochrane Library, MEDLINE (EBSCO), and Web of Science. The most common search terms used were "COVID-19 AND Children", "SARS-CoV-2 AND/OR Children", "COVID-19 AND Diabetes" "COVID-19 Epidemiology", "COVID-19 AND Ramadan fasting", "COVID-19 and Intermittent fasting." All the resources used are either peer-reviewed articles/reports and/or official websites of various media, governmental and educational organisations. Results: Having reviewed the currently limited evidence, it has been found that the incidence of COVID-19 among children with type 2 diabetes seems to be not much different from children without diabetes. However, these patients are still vulnerable to any infection. Several studies have reported that prevention programmes such as intermittent fasting are effective to protect these groups of patients from developing any complications. Moreover, observing Ramadan fasting as a type of intermittent fasting could be beneficial for some children with established diabetes, prediabetes and people at risk. Conclusion: Children and young adults with type 2 diabetes are not at risk of severe COVID-19 infection as the case in adults with diabetes. More research is needed to identify the impact of COVID-19 and to investigate the efficacy and safety of intermittent fasting, including Ramadan fasting, among these age groups. Implementing these cost-effective programmes may have a great impact in minimising the incidence of diabetes. Moreover, this could be effective particularly at prediabetes stage by preventing these people from going onto develop type 2 diabetes and taking medications for the rest of their life and protecting people from complications linked to disease and infection.

Chaos, mitochondria and type 2 diabetes; does type 2 diabetes arise from a metabolic dysrhythmia?

The increasing incidence of type 2 diabetes transcends all cultures, largely due to populations transitioning from traditional diets and manual occupations, to sedentary, calorific lifestyles. Excess calorie intake leads to intramuscular fat accumulation and insulin resistance. Physical inactivity causes underutilization of mitochondria causing dysfunction and inflammation. Both insulin resistance and mitochondrial dysfunction mechanisms are known to be closely related and to antagonise one another, although the precise nature of the relationship has eluded characterization. It is poorly understood why this mutual dysfunction progresses on to clinical diabetes in only some patients, why progression is often stepwise and why diabetes control only weakly predicts future cardiovascular disease in individuals. Clinical prediction in patients is therefore currently unsatisfactory and current linear assumptions require challenging. Cells contain networks of oscillating ionic fluxes. Cellular activity is characterised by complex patterns of fluctuation with sudden transitions between patterns. The non-linear nature of these oscillations is well characterised in neuronal activity, cardiac impulses and more recently mitochondria, but not previously in relation to diabetes. Cells under metabolic stress demonstrate complex fluctuations of mitochondrial distribution, coupling strength and synchronisation resulting in periodic or chaotic oscillations of function, causing accumulation of intracellular fat and excess reactive oxygen species (ROS), which exacerbates insulin resistance. Glucose, insulin and HbA1c in patients are also known to oscillate in complex patterns but the mechanisms and significance are largely unknown. Drawing on existing evidence and models from other diseases, a nonlinear, dynamical hypothesis of diabetes onset and progression is proposed. Insulin receptor pathways and mitochondria are treated as two populations of coupled, phase oscillators. Health or disease states depend on system stability or instability and reflect the balance of substrate supply and energy demand. The implication of this novel mechanism is that diabetes and the complications are not the consequence of a distinct pathological agent or pathway, but more an evolving dysrhythmia of normal cellular energetics systems, resulting from accumulated adverse lifestyle conditions. This hypothesis is proposed with the intention of stimulating research into non-linear dynamical constructs as an alternative to current linear models, to improve risk prediction and trajectory analysis in type 2 diabetes.