ABSTRACT Introduction: Type 2 diabetes mellitus (T2DM), also known as non-insulin-dependent diabetes mellitus (NIDDM), accounts for more than 90% of the total number of diabetes mellitus cases and often occurs in middle-aged and elderly people. Objective: To investigate the effect of exercise intervention on insulin resistance in obese type 2 diabetes patients. Methods: Eighty-six obese diabetic patients were screened as experimental subjects in physical examinations and randomly divided into observation and control groups. Visceral fat volume, fasting blood glucose, and fasting insulin of all subjects were measured before and after completion of the 6-month experimental implementation. The insulin resistance was calculated for both groups and the values for each indicator were compared statistically between groups. Results: Control of body weight, body mass index, blood glucose, blood lipids and insulin resistance index were better in the observation group than in the control group, and the difference was statistically significant (P < 0.05). Conclusions: Basal intervention with quantitative exercise can significantly improve insulin resistance in obese type 2 diabetes patients and the effect is better than treatment with diet and conventional exercise. Level of evidence II; Therapeutic studies - investigation of treatment results.
Abstract Diabetes mellitus (DM) is a non-communicable disease throughout the world in which there is persistently high blood glucose level from the normal range. The diabetes and insulin resistance are mainly responsible for the morbidities and mortalities of humans in the world. This disease is mainly regulated by various enzymes and hormones among which Glycogen synthase kinase-3 (GSK-3) is a principle enzyme and insulin is the key hormone regulating it. The GSK-3, that is the key enzyme is normally showing its actions by various mechanisms that include its phosphorylation, formation of protein complexes, and other cellular distribution and thus it control and directly affects cellular morphology, its growth, mobility and apoptosis of the cell. Disturbances in the action of GSK-3 enzyme may leads to various disease conditions that include insulin resistance leading to diabetes, neurological disease like Alzheimer’s disease and cancer. Fluoroquinolones are the most common class of drugs that shows dysglycemic effects via interacting with GSK-3 enzyme. Therefore, it is the need of the day to properly understand functions and mechanisms of GSK-3, especially its role in glucose homeostasis via effects on glycogen synthase.
Insulin resistance is a hallmark of Alzheimer’s disease (AD), type II diabetes (T2D), and Parkinson’s disease (PD). Emerging evidence indicates that these disorders are typically characterized by alterations in the gut microbiota composition, diversity, and their metabolites. Currently, it is understood that environmental hazards including ionizing radiation, toxic heavy metals, pesticides, particle matter, and polycyclic aromatic hydrocarbons are capable of interacting with gut microbiota and have a non-beneficial health effect. Based on the current study, we propose the hypothesis of “gut microenvironment baseline drift”. According to this “baseline drift” theory, gut microbiota is a temporarily combined cluster of species sharing the same environmental stresses for a short period, which would change quickly under the influence of different environmental factors. This indicates that the microbial species in the gut do not have a long-term relationship; any split, division, or recombination may occur in different environments. Nonetheless, the “baseline drift” theory considers the critical role of the response of the whole gut microbiome. Undoubtedly, this hypothesis implies that the gut microbiota response is not merely a “cross junction” switch; in contrast, the human health or disease is a result of a rich palette of gut-microbiota-driven multiple-pathway responses. In summary, environmental factors, including hazardous and normal factors, are critical to the biological impact of the gut microbiota responses and the dual effect of the gut microbiota on the regulation of biological functions. Novel appreciation of the role of gut microbiota and environmental hazards in the insulin resistance would shed new light on insulin resistance and also promote the development of new research direction and new overcoming strategies for patients.
The aim of the study was to determine the prevalence of metabolic syndrome (MetS), type 2 diabetes mellitus (T2DM), and other comorbidities in overweight and obese children in Malatya, Turkey.
Retrospective cross-sectional study. We studied 860 obese and overweight children and adolescents (obese children Body mass index (BMI) >95th percentile, overweight children BMI >85th percentile) aged between 6 and 18 years. The diagnosis of MetS, impaired glucose tolerance (IGT), impaired fasting glucose (IFG), and T2DM were defined according to modified the World Health Organization criteria adapted for children. Other comorbidities were studied.
Subjects (n=860) consisted of 113 overweight and 747 obese children of whom 434 (50.5%) were girls. MetS was significantly more prevalent in obese than overweight children (43.8 vs. 2.7%, p<0.001), and in pubertal than prepubertal children (41.1 vs. 31.7%, p<0.001). Mean homeostasis model assessment for insulin ratio (HOMA-IR) was 3.6 ± 2.0 in the prepubertal and 4.9 ± 2.4 in pubertal children (p<0.001). All cases underwent oral glucose tolerance test and IGT, IFG, and T2DM were diagnosed in 124 (14.4%), 19 (2.2%), and 32 (3.7%) cases, respectively. Insulin resistance (IR) was present in 606 cases (70.5%).
Puberty and obesity are important risk factors for MetS, T2DM, and IR. The prevalence of MetS, T2DM, and other morbidities was high in the study cohort. Obese children and adolescents should be carefully screened for T2DM, insulin resistance, hyperinsulinism, dyslipidemia, hypertension, IGT, and IFG. The prevention, early recognition, and treatment of obesity are essential to avoid associated morbidities.
The risk of obesity in adulthood is subject to programming in the womb. Maternal obesity contributes to programming of obesity and metabolic disease risk in the adult offspring. With the increasing prevalence of obesity in women of reproductive age there is a need to understand the ramifications of maternal high-fat diet (HFD) during pregnancy on offspring’s metabolic heath trajectory. In the present study, we determined the long-term metabolic outcomes on adult male and female offspring of dams fed with HFD during pregnancy. C57BL/6J dams were fed either Ctrl or 60% Kcal HFD for 4 weeks before and throughout pregnancy, and we tested glucose homeostasis in the adult offspring. Both Ctrl and HFD-dams displayed increased weight during pregnancy, but HFD-dams gained more weight than Ctrl-dams. Litter size and offspring birthweight were not different between HFD-dams or Ctrl-dams. A significant reduction in random blood glucose was evident in newborns from HFD-dams compared to Ctrl-dams. Islet morphology and alpha-cell fraction were normal but a reduction in beta-cell fraction was observed in newborns from HFD-dams compared to Ctrl-dams. During adulthood, male offspring of HFD-dams displayed comparable glucose tolerance under normal chow. Male offspring re-challenged with HFD displayed glucose intolerance transiently. Adult female offspring of HFD-dams demonstrated normal glucose tolerance but displayed increased insulin resistance relative to controls under normal chow diet. Moreover, adult female offspring of HFD-dams displayed increased insulin secretion in response to high-glucose treatment, but beta-cell mass were comparable between groups. Together, these data show that maternal HFD at pre-conception and during gestation predisposes the female offspring to insulin resistance in adulthood.
(R)-5-hydroxy-1,7-diphenyl-3-heptanone (DPHC) from the natural plant Alpinia officinarum has been reported to have antioxidation and antidiabetic effects. In this study, the therapeutic effect and molecular mechanism of DPHC on type 2 diabetes mellitus (T2DM) were investigated based on the regulation of oxidative stress and insulin resistance (IR) in vivo and in vitro. In vivo, the fasting blood glucose (FBG) level of db/db mice was significantly reduced with improved glucose tolerance and insulin sensitivity after 8 weeks of treatment with DPHC. In vitro, DPHC ameliorated IR because of its increasing glucose consumption and glucose uptake of IR-HepG2 cells induced by high glucose. In addition, in vitro and in vivo experiments showed that DPHC could regulate the antioxidant enzyme levels including superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px), thereby reducing the occurrence of oxidative stress and improving insulin resistance. Western blotting and polymerase chain reaction results showed that DPHC could promote the expressions of nuclear factor erythroid 2-related factor 2 (Nrf2), the heme oxygenase-1 (HO-1), protein kinase B (AKT), and glucose transporter type 4 (GLUT4), and reduced the phosphorylation levels of c-Jun N-terminal kinase (JNK) and insulin receptor substrate-1 (IRS-1) on Ser307 both in vivo and in vitro. These findings verified that DPHC has the potential to relieve oxidative stress and IR to cure T2DM by activating Nrf2/ARE signaling pathway in db/db mice and IR-HepG2 cells.
Background: Insulin resistance is a common etiology of metabolic syndrome, but receiver operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using a machine learning (ML) approach, we aimed to generate the best model for predicting insulin resistance in Korean adults aged > 40 of the Ansan/Ansung cohort using a machine learning (ML) approach. Methods: The demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8842 participants were included. The polygenetic risk scores (PRS) generated by a genome-wide association study were added to represent the genetic impact of insulin resistance. They were divided randomly into the training (n = 7037) and test (n = 1769) sets. Potentially important features were selected in the highest area under the curve (AUC) of the ROC curve from 99 features using seven different ML algorithms. The AUC target was ≥0.85 for the best prediction of insulin resistance with the lowest number of features. Results: The cutoff of insulin resistance defined with HOMA-IR was 2.31 using logistic regression before conducting ML. XGBoost and logistic regression algorithms generated the highest AUC (0.86) of the prediction models using 99 features, while the random forest algorithm generated a model with 0.82 AUC. These models showed high accuracy and k-fold values (>0.85). The prediction model containing 15 features had the highest AUC of the ROC curve in XGBoost and random forest algorithms. PRS was one of 15 features. The final prediction models for insulin resistance were generated with the same nine features in the XGBoost (AUC = 0.86), random forest (AUC = 0.84), and artificial neural network (AUC = 0.86) algorithms. The model included the fasting serum glucose, ALT, total bilirubin, HDL concentrations, waist circumference, body fat, pulse, season to enroll in the study, and gender. Conclusion: The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.