Volume 10 · Issue 06 · 2018

The fasting status index mainly includes insulin resistance index (HOMA-IR) and beta cell function index (HOMA-β) assessed by steady-state model (HOMA), quantitative insulin sensitivity check index (QUICKI), Li Guangwei index and Bennett insulin sensitivity index (ISI). Only FINS and fasting blood glucose (FPG) levels are measured after overnight fasting, and the corresponding indices are calculated according to relevant formulas. These indexes have commonalities, but in some special cases they have their own advantages. Since the determination of insulin has not been standardized, it is not possible to present an optimal cut-off point value for the above indices.

In order to further promote the standardized application and clinical research of global continuous glucose monitoring (CGM) technology, experts from various countries discussed and formulated an international expert consensus on the clinical application of CGM (hereinafter referred to as the consensus) at the 10th International Conference on Advanced Technologies & Treatments for Diabetes held in France in February 2017^[1]。 Consensus was published in December 2017 inDiabetes CareAbove, it represents the latest understanding and application specification of CGM technology today, which mainly discusses and gives suggestions on seven aspects: (1) Glycosylated hemoglobin (HbA_1c) limitations of; (2) Applying blood glucose monitoring methods [self-blood glucose monitoring (SMBG) and CGM] to guide blood glucose management in diabetic patients; (3) Minimum requirements for CGM system performance; (4) the definition and evaluation method of hypoglycemia; (5) Clinical evaluation of blood glucose fluctuations; (6) The definition and clinical application of time in range (TIR) of blood glucose; (7) CGM results report. This consensus emphasizes the importance of the definition of CGM and the standardization of reporting. The following is an interpretation of the hot issues.

Cardiovascular complications are one of the leading causes of death in patients with type 2 diabetes mellitus (T2DM)^[1]As the course of the disease progresses, the cardiovascular risk of T2DM patients shows an upward trend, which is 2 to 4 times higher than that of non-diabetic patients^[2]。 Although elevated blood glucose levels are associated with an increased risk of developing chronic macrovascular complications^[3]However, several subsequent large prospective studies showed that intensive hypoglycemic therapy did not bring significant cardiovascular benefits to patients with T2DM^[4]。 It can be seen that simply reducing glycated hemoglobin (HbA_1c) levels are not the whole thing about glucose management strategies. In recent years, many studies have shown that blood glucose variation is closely related to cardiovascular risk in diabetic patients. HbA_1cPatients with consistent or close levels may have distinct profile of blood glucose fluctuations^[5]As an important part of blood glucose management, multiple assessment indicators of blood glucose variation have also been confirmed to be involved in multiple links in the occurrence and development of cardiovascular complications in diabetic patients^[6]。 However, how to set a reasonable and comprehensive blood sugar control target, which can bring benefits to cardiovascular system while good blood sugar control, is an important issue that needs attention in blood sugar management strategy. This article mainly discusses the relationship between blood glucose variation and cardiovascular risk and the research progress.

Type 2 diabetes mellitus (T2DM) is a major risk factor for cardiovascular diseases (CVD), and CVD is the leading cause of death in T2DM patients. In addition to increased blood sugar and insulin resistance, T2DM is often accompanied by a variety of other CVD risk factors, including obesity, smoking, dyslipidemia and hypertension. CVD risk is significantly increased when multiple risk factors coexist^[1,2]。 Intensive Multivariate Intervention Study in Patients with T2DM with Microalbuminuria^[3]It was suggested that the life span of the intensive comprehensive treatment group was significantly longer than that of the general treatment group by 7.9 years, and the incidence of cardiovascular events was decreased. It has become a consensus and routine to intervene with multiple cardiovascular risk factors in patients with T2DM, and comprehensive management of multiple factors can significantly improve patient prognosis. Specific measures include lifestyle intervention, smoking cessation, weight loss, hypoglycemia, blood pressure, lipid regulation, antiplatelet therapy, etc., in order to minimize the risk of cardiovascular events and death^[4,5,6]。 In recent years, a number of randomized controlled trials (RCTs) with cardiovascular events as the outcome have been published in blood glucose, blood pressure and blood lipid management, which provide a new treatment for the intervention of CVD risk factors in T2DM patients.

To investigate the association between serum potassium homeostasis and glucose metabolism in hospitalized patients with type 2 diabetes.

A total of 362 patients with type 2 diabetes who were admitted to our hospital from January 2016 to December 2016 were enrolled. Glycated hemoglobin A_1c (HbA_1c), blood pressure and fasting, 2 hour postprandial glucose after a standard meal, potassium, insulin and C-peptide were measured. The participants were grouped into 2 groups: ≥4.0 mmol/L (n=183) and <4.0 mmol/L ( n=179) group based on fasting potassium level and another 2 groups [Δ potassium>0 (n=205) and Δ potassium≤0 ( n=157) group] based on the change of serum potassium concentration after a standard diet. The data were compared between the groups with t test or rank sum test and associations between potassium and glucose metabolism characteristics were examined with partial relative analysis.

Compared with the group with fasting serum potassium<4.0 mmol/L, the other group had higher fasting serum insulin, C-peptide and 2 h postprandial serum insulin, C-peptide and lower 2 h postprandial potassium increase [14.1 (7.8, 27.1) vs 10.8 (5.8, 23.3) mU/L,Z=-2.317, P=0.020; 473 (280, 681) vs 331 (229, 535) pmol/L, Z=-3.575, P<0.001; 44.9 (24.2, 75.5) vs 31.7 (18.5, 54.1) mU/L, Z=-3.390, P=0.001; 1 088 (538, 1 646) vs 846 (443, 1 316) pmol/L, Z=-2.698, P=0.007; (-0.02±0.30) vs (0.21±0.25) mmol/L, t=-7.778, P<0.001]. No difference was found in fasting and postprandial glucose, HbA_1c, disease duration and estimated glomerular filtration rate (all P>0.05). Compared with Δ potassium≤0 group, the group with Δ potassium>0 has lower 2 h postprandial serum insulin concentration [32.2 (20.2, 54.3) vs 45.7 (24.7, 74.1) mU/L, Z=-3.143, P=0.002] and higher 2 h postprandial glucose level [(11.9±4.0) vs (10.8±3.9) mmol/L, t=2.487, P=0.013].

In-ward type 2 diabetic patients with lower normal fasting serum potassium level (3.5-4.0 mmol/L) have a worse fasting and postprandial insulin secretion function, higher postprandial glucose excursion.

To investigate the changes of glucose and lipid metabolism and islet function in type 2 diabetic patients with history of malignancy, and provide evidence for clinical prevention and treatment.

A total of 190 cases of type 2 diabetes in our hospital from March 2014 to July 2016 with a history of malignant tumor were included. In addition, 704 age, gender and duration matched type 2 diabetic patients without tumor history were included as control. Markers of glucose metabolism, lipid metabolism, plasma insulin and C peptide levels after 75 g glucose load were detected. The t test, rank sum test and χ ² test were used to compare the differences between two groups.

(1) In patients with history of malignant tumor, glycated hemoglobin A_1c (HbA_1c) was higher than that of the control group (9.0%±1.9% vs 8.4%±1.9%, t=-3.197, P<0.05); total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol were lower than control group. In addition, the area under curve of C-peptide after glucose load in patients with tumor was higher [(12.1±5.1) vs (9.4±4.2) mU, t=-3.490, P<0.05] than that of control group, while the exogenous insulin dose was lower than that of control group [(24±14) vs (31±16) U, t=4.795, P<0.05]. There was no difference in insulin resistance index, islet function index and first phase insulin secretion between the two groups. (2) Logistic regression analysis showed that C peptide the area under curve (OR=1.189, 95%CI 1.056-1.339, P=0.004) and HDL-C (OR=0.031, 95%CI 0.002-0.474, P=0.013) were independently associated with malignant tumor history.

Type 2 diabetic patients with history of malignant tumor have high endogenous insulin levels but poor glycemic control. These patients are also with low HDL-C level.

To evaluate the relationship between QTc interval prolongation and diabetic retinopathy (DR).

A total of 797 inpatients with type 2 diabetes mellitus, from May 2014 to March 2016 at the Department of Endocrinology and Metabolism of Xijing Hospital affiliated to the Fourth Military Medical University, were selected and divided into two groups according to their fundus photography results: patients without diabetic retinopathy (NDR group, n=539) and patients with diabetic retinopathy (DR group, n=258). The general data and biochemical markers including the age, gender, diabetic duration, fasting plasma glucose (FPG) , blood lipid, and the length of the QTc interval were compared and analyzed among two groups. Statistical comparisons were performed using the Student t test or Nonparametric Tests. Pearson correlation analysis between QTc interval prolongation, diabetic retinopathy and various influencing factors. Logistic regression analysis were used to study the influencing factors for QTc interval prolongation and diabetic retinopathy.

The mean QTc interval of all patients was (404±46) ms. The QTc interval in patients with diabetic retinopathy were significantly longer than those in patients without retinopathy [ (417±47) vs (396±44) ms, t=-4.227, P<0.01]. Logistic regression analysis showed that the risk of DR for T2DM patients with QTc>404 ms was 1.659 times higher than those with QTc≤404 ms (OR=1.659, 95%CI: 1.208-2.378, P<0.05), and the risk of DR for T2DM patients with QTc>440 ms was 2.729 time higher than those with QTc≤440 ms (OR=2.729, 95%CI:1.627-4.578, P<0.05).

Electrocardiogram QTc interval length is positively correlated with diabetic retinopathy in type 2 diabetic patients.

To investigate the serum adipsin concentrations in people with different glucose tolerance and analyze its correlation with pancreatic β cell function as well as insulin resistance.

Based on the patient population who visited endocrinology deptartment or conducted health check in the First Afflicated Hospital of Chongqing Medical University from December 2015 to October 2016, 56 patients with newly diagnosed type 2 diabetes mellitus (T2DM group), 36 patients with impaired glucose regulation (IGR group), and 45 subjects with normal glucose tolerance (NGT group) were included. All subjects underwent intravenous glucose tolerance test (IVGTT). Acute insulin response (AIR), the area under the curve (AUC) of 0-10 min insulin secretion, homeostasis model assessments of insulin resistance index (HOMA-IR) and β-cell function index (HOMA-β) were calculated. Serum adipsin and interleukin-1β (IL-1β) were assayed by enzyme linked immunosorbent assay. The relationship between adipsin, AIR, AUC, HOMA-β, HOMA-IR and other metabolic parameters were analyzed. One-way analysis of variance(ANOVA) or nonparametric test were used for groups' comparisons. Pearson correlation analysis was used to determine simple bivariate relationships. Stepwise multiple regression analysis was conducted for adipsin as a dependent variable, including all variables of interest at the same time as independent variables.

The levels of serum adipsin in T2DM group and IGR group were significantly decreased [3 201 (2 542-4 070), 5 159 (2 775-6 501) vs 6 833 (5 587-10 126) μg/L, H=24.372, P<0.05]. Serum adipsin levels were negatively correlated with WHR, FFA, FPG, 2hPG, HbA_1c, HOMA-IR, IL-1β, hs-CRP (r=-0.521--0.285, all P<0.05), and were positively correlated with HOMA-β, HDL-C, AUC, AIR (r=0.325-0.577, all P<0.05). Multiple stepwise regression analysis showed that HOMA-β and AIR were independently associated with adipsin (β_HOMA-β=0.332, P=0.038; β _AIR=0.349, P=0.029).

Serum adipsin concentrations are decreased in T2DM and IGR, and are closely correlated with first-phase insulin secretion. Adipsin might involve in the development of type 2 diabetes mellitus.

To explore the spatiotemporal expression of the long non-coding RNA (lncRNA) Dancr in liver, and further investigate its regulatory relationships and molecular mechanisms with hepatic gluconeogenesis.

Fasting-refeeding and high fat diet (HFD) induced obesity models were built, and the expression levels of Dancr in both models were detected with phosphoenolpyruvate carboxykinase and glucose-6-phosphatase (as positive control group). The expressions of Dancr were also detected in different tissues. The characteristics of Dancr and interactive miRNAs were analyzed by using online databases of NCBI, UCSC, RegRNA, TargetScan, etc. The miRNA target genes of gene ontology, kyoto encyclopedia of genes and genomes enrichment analyses were also preformed. Analysis of variance and student-t were used for comparison in multiple groups.

The expression of Dancr was significantly increased during fasting and reached to peak after fasting for 16 h, and then returned back to normal rapidly after refeeding (1.00±0.23 vs. 4.20±0.27, t=22.10, P<0.01). Moreover, levels of Dancr expression were significantly increased in HFD induced obese mice liver models than those in normal controls (1.00±0.25 vs. 1.69±0.30, t=4.33, P<0.05). With the development of obesity, the hepatic gluconeogenesis was over-activated, indicating that the expression of Dancr may be associated with the activation of hepatic gluconeogenesis. Dancr expressions in tissues of heart, liver, spleen, lung, kidney, skeletal muscle, small intestine, stomach, white adipose tissue, brown adipose tissue and brain were significantly different (F=180.32, P<0.01). The expressions of Dancr in liver were significantly higher than those in other tissues except for spleen and lung (t=6.03–36.19, all P<0.01). Bioinformatic analysis found that Dancr was located on chromosome 5 (chr5:74 093 083-74 090 355) with the nucleic acid length of 1 060 bp including two exons. The results also revealed that Dancr had nine interactive miRNAs (mmu-let-7i-5p, mmu-miR-134-5p, mmu-miR-326-5p, mmu-miR-433-5p, mmu-miR-497-5p, mmu-miR-504-3p, mmu-miR-1906, mmu-miR-432, mmu-miR-5620-5p) and regulated 2 124 downstream target genes, including nine genes related to hepatic gluconeogenesis.

The expression of Dancr is influenced by physiological and pathological gluconeogenesis, and may be involved in the pathophysiologic processes of hepatic gluconeogenesis. Dancr bioinformatic analyses can provide data support for subsequent studies, further reveal the molecular mechanisms of gluconeogenesis.

Autoimmune diseases are diseases caused by genetic and environmental factors that promote the body's immune response to self-antigens. Their modes of action are different-they can directly fight their own tissues or organs, and they can combine with self-antigens to form immune complexes and deposit them in tissues or organs, thus causing a series of pathological reactions and causing damage to tissues and organs of the body. Children with type 1 diabetes mellitus (T1DM) and Henoch-Schönlein purpura (HSP) are both autoimmune diseases. It is rare for them to occur simultaneously or successively in clinical practice, and there are no reports in China. This article reports two cases of diabetic ketoacidosis combined with HSP in Chinese boys, and reviews their clinical data.

The risk of cardiovascular events in diabetic patients is 2~4 times that of non-diabetic people, which is the main cause of death and disability in diabetic patients^[1]Unfortunately, there is insufficient evidence in clinical trials of cardiovascular protective effects of many approved hypoglycemic drugs. In 2008, the U.S. Food and Drug Administration recommended that the development of hypoglycemic drugs must be evaluated for cardiovascular safety. In recent years, the protective effects of novel hypoglycemic drugs, sodium-glucose cotransporter 2 (SGLT2) inhibitors, on cardiovascular^[2]There are many possible mechanisms, which are briefly introduced in this paper.

Islet β cell dysfunction and insulin resistance are the two main pathophysiological links in the pathogenesis of type 2 diabetes mellitus (T2DM). Therefore, the main mechanisms of action of traditional oral hypoglycemic drugs include: promoting insulin release, improving insulin sensitivity, inhibiting liver glucose output, etc. However, traditional oral hypoglycemic drug monotherapy is usually difficult to maintain the ideal glycemic control standard for a long time, and requires the combination of other hypoglycemic drugs or insulin therapy. New targets for T2DM treatment include glucagon-like peptide-1 (GLP-1), sodium-glucose cotransporter 2 (SGLT2), etc. fibroblast growth factor (FGF) 21 is a novel metabolic regulator associated with peroxisome proliferator-activated receptor (PPAR)^[1]A variety of PPAR agonists can up-regulate human plasma FGF-21 levels and play a metabolic regulatory role. In this paper, the role of FGF-21 in the treatment of diabetes mellitus and its related mechanisms are discussed.

Diabetes is a continuous spectrum of diseases. Adult occult autoimmune diabetes mellitus (LADA) is an excessive type between type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Its islet β cell function declines faster than that of T2DM patients, and eventually develops into dependence on insulin therapy. Because the occurrence and development of LADA is slower than that of T1DM, protecting the function of pancreatic islet β cells and delaying the disease progression has become a research hotspot in recent years. This article reviews the progress of pancreatic islet β cell function in patients with LADA.