Hypoglycaemia, Abnormal Lipids, and Cardiovascular Disease among Chinese with Type 2 Diabetes

MicroRNA Changes Up to 24 h following Induced Hypoglycemia in Type 2 Diabetes

Hypoglycemia, as a complication of type 2 diabetes (T2D), causes increased morbidity and mortality but the physiological response underlying hypoglycemia has not been fully elucidated. Small noncoding microRNA (miRNA) have multiple downstream biological effects. This pilot exploratory study was undertaken to determine if induced miRNA changes would persist and contribute to effects seen 24 h post-hypoglycemia. A parallel, prospective study design was employed, involving T2D (n = 23) and control (n = 23) subjects. The subjects underwent insulin-induced hypoglycemia (2 mmol/L; 36 mg/dL); blood samples were drawn at baseline, upon the induction of hypoglycemia, and 4 h and 24 h post-hypoglycemia, with a quantitative polymerase chain reaction analysis of miRNA undertaken. The baseline miRNAs did not differ. In the controls, 15 miRNAs were downregulated and one was upregulated (FDR < 0.05) from the induction of hypoglycemia to 4 h later while, in T2D, only four miRNAs were altered (downregulated), and these were common to both cohorts (miR-191-5p; miR-143-3p; let-7b-5p; let-7g-5p), correlated with elevated glucagon levels, and all were associated with energy balance. From the induction of hypoglycemia to 24 h, 14 miRNAs were downregulated and 5 were upregulated (FDR < 0.05) in the controls; 7 miRNAs were downregulated and 7 upregulated (FDR < 0.05) in T2D; a total of 6 miRNAs were common between cohorts, 5 were downregulated (miR-93-5p, let-7b-5p, miR-191-5p, miR-185-5p, and miR-652-3p), and 1 was upregulated (miR-369-3p). An ingenuity pathway analysis indicated that many of the altered miRNAs were associated with metabolic and coagulation pathways; however, of the inflammatory proteins expressed, only miR-143-3p at 24 h correlated positively with tumor necrosis factor-α (TNFa; p < 0.05 and r = 0.46) and negatively with toll-like receptor-4 (TLR4; p < 0.05 and r = 0.43). The MiRNA levels altered by hypoglycemia reflected changes in counter-regulatory glucagon and differed between cohorts, and their expression at 24 h suggests miRNAs may potentiate and prolong the physiological response. Trial registration: ClinicalTrials.gov NCT03102801.

Hypoglycaemia and Cardiovascular Disease Risk in Patients with Diabetes

Hypoglycaemia represents an important side effect of insulin therapy and insulin secretagogues. It can occur in both type 1 and type 2 diabetes mellitus patients. Also, some associations between hypoglycaemia and cardiovascular (CV) risk have been reported. Several mechanisms may be involved, including the sympathoadrenal system, hypokalaemia, endothelial dysfunction, coagulation, platelets, inflammation, atherothrombosis and impaired autonomic cardiac reflexes. This narrative review discusses the associations of hypoglycaemia with CV diseases, including coronary heart disease (CHD), cardiac arrhythmias, stroke, carotid disease and peripheral artery disease (PAD), as well as with dementia. Severe hypoglycaemia has been related to CHD, CV and all-cause mortality. Furthermore, there is evidence supporting an association between hypoglycaemia and cardiac arrhythmias, potentially predisposing to sudden death. The data linking hypoglycaemia with stroke, carotid disease and PAD is limited. Several factors may affect the hypoglycaemia-CV relationships, such as the definition of hypoglycaemia, patient characteristics, co-morbidities (including chronic kidney disease) and antidiabetic drug therapy. However, the association between hypoglycaemia and dementia is bilateral. Both the disorders are more common in the elderly; thus, glycaemic goals should be carefully selected in older patients. Further research is needed to elucidate the impact of hypoglycaemia on CV disease.

Analysis of risk factors and their interactions in type 2 diabetes mellitus: A cross-sectional survey in Guilin, China

Aims/Introduction

Type 2 diabetes is a metabolic disease characterized by insulin resistance, and is associated with the effects of genetic and environmental factors. The present study aimed to not only analyze the influence of a single factor for type 2 diabetes, but also to investigate the interaction effects between risk factors.

Materials and Methods

A total of 6,660 individuals selected by the method of cluster random sampling accepted a cross‐sectional survey (questionnaire investigation, physical measurement, laboratory examination and liver ultrasound examination). The classification tree was used to analyze the risk factors and their interactions in type 2 diabetes. The clinical and metabolic characteristics were compared between type 2 diabetes patients and controls, and the non‐conditional logistic regression model was used to quantitatively analyze the interactions.

Results

A total of 338 participants were classified as type 2 diabetes (217 men and 121 women), the classification tree model showed three variables with close associations with type 2 diabetes: age, triglycerides (TG) and non‐alcoholic fatty liver disease (NAFLD). Type 2 diabetes patients had higher age and incidences of high TG, NAFLD, hypertension, high body mass index, high uric acid, high total cholesterol, high low‐density lipoprotein cholesterol and low high‐density lipoprotein cholesterol. The multivariate logistic regression analysis showed that the following factors had interactions in type2 diabetes: high TG × advanced age (odds ratio 2.499, 95% confidence interval 1.868–3.344, P = 0.000), NAFLD × advanced age (odds ratio 1.250, 95% confidence interval 1.048–1.491, P = 0.013) and NAFLD × high TG (odds ratio 1.349, 95% confidence interval 1.144–1.590, P = 0.000).

Conclusions

The present study showed that type 2 diabetes resulted from the interactions of many factors; the interactions among age, TG and NAFLD are important risk factors for type 2 diabetes.