Volume 08 · Issue 10 · 2016

The prevalence of type 1 diabetes mellitus (T1DM) is on the rise worldwide. According to the International Diabetes Federation (IDF) in 2011, 190 million<Among 15-year-old children, there are about 490,100 cases of T1DM. The IDF 7th Diabetes Map released in 2015 shows that there are about 542,000 children with T1DM worldwide, and about 3% of T1DM patients increase every year^[1]。 The epidemiological study of T1DM in China, in the last century, only the WHO Type 1 Diabetes Incidence Survey (DIAMOND) project conducted from 1985 to 1994 in China^[2]The results of the study at that time showed that Chinese children with T1DM (<15 years of age) has a standardized incidence rate of 0.57/100,000, one of the lowest in the world. Twenty years after the DIAMOND study, it is still unknown how many T1DM patients there are in China. Considering the huge population base in China, the absolute number of T1DM should not be underestimated. Epidemiological survey from Shanghai^[3]It was found that from 1997 to 2011, the incidence of T1DM in children (under 15 years old) in Shanghai increased at a rate of 14.2% every year. Twenty years ago, the incidence of T1DM in children in Shanghai was only 0.7/100,000. In 2011, the incidence rate exceeded 6/100,000. In the past 15 years, the average incidence of T1DM in children was 3.1/100,000, which was significantly higher than the international average. At present, we are facing a special period: the detection rate of new cases of T1DM has increased, the survival of children and adolescents with T1DM onset has prolonged, children and adolescents have gradually transitioned to adulthood, and the number of adults with T1DM has increased, making the management of adult T1DM a new challenge. Based on this, the Diabetes Branch of Chinese Medical Association launched the China T1DM Registration Management Project in 2014, aiming at understanding the epidemiological status of T1DM at all ages in China.

Type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) are both chronic non-communicable diseases. Early screening, early prevention and control of high-risk groups of T2DM with insulin resistance as the main feature can effectively reduce the incidence of T2DM. Similarly, early identification of high risk of T1DM is beneficial to improve the early screening rate, early diagnosis rate and early treatment rate of the disease. Multiple studies^[1,2]It was shown that subjects enrolled in a follow-up study of genetically susceptible populations for T1DM had glycated hemoglobin (HbA) at clinical onset_1c) and the incidence of diabetic ketoacidosis (DKA) were lower than those who did not receive surveillance follow-up, suggesting that early prediction and screening of high-risk groups of T1DM and close follow-up are important to improve the prognosis of the disease.

Type 1 diabetes mellitus (T1DM) is a metabolic disease characterized by insulin deficiency and glucose metabolism disorders caused by autoimmune-mediated selective islet beta cell damage. It is mainly divided into two types: Type 1A, that is, immune-mediated T1DM, which is prominently characterized by the presence of islet autoantibodies and isletitis and selective islet β cell destruction, producing autoantibodies including glutamate decarboxylase antibodies, islet cell antibodies and insulin antibodies, etc. These antibodies reflect the autoimmune process that leads to β cell destruction^[1]； Type 1B, that is, idiopathic diabetes, refers to diabetes with severe insulin deficiency without evidence of islet β-cell autoimmunity. It is especially common in African and Asian people. The pathological basis of this subtype of insulin deficiency is not yet clear^[2]。

The 7th edition of the Diabetes Map released by the International Diabetes Federation (IDF) in December 2015 shows that there are about 542,000 children with type 1 diabetes (T1DM) worldwide, and about 3% of T1DM patients increase every year^[1]。 At present, there is no definite epidemiological data of T1DM in China.

The experts who wrote this guide:Yang Tao (First Affiliated Hospital of Nanjing Medical University), Guo Lixin (Beijing Hospital of Ministry of Health), Weng Jianping (Third Hospital of Sun Yat-sen University), Zhou Zhiguang (Second Xiangya Hospital of Central South University)

To develop a satisfactory clinical diagnosis model of type 1 diabetes mellitus (T1DM) for diagnosis and etiological classification of uncertain cases, achieve quantitative criteria for initial judgment without the standard autoantibody test results and identify specific patients needing accurate islet autoantibody assay.

532 newly-diagnosed diabetic patients (diagnosed less than 1 year) were retrospectively studied, including 203 patients were diagnosed as T1DM, 329 patients were diagnosed as type 2 diabetes mellitus (T2DM), who were hospitalized in Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University between Jun 2012 to Apr 2016. Eligible patients underwent randomization in a 2∶1 ratio to establish(n=355) or validate (n=177) diagnosis models.Logistic regression with common variable to identify T1DM and T2DM was applied to establish clinical diagnosis model of type 1 diabetes(CODE). The receiver operator characteristic (ROC) curves were analyzed to test the model performance.

Three models(CODE-C₀, CODE-C₁₂₀, CODE-C_auc) containing age at diagnosis time, body mass index (BMI), C-peptide (fasting C-peptide, C₀; 120 min postprandial C-peptide, C₁₂₀; area of the curve of C-peptide, C_auc, respectively) were created. In the establish cohort, the area of the ROC curve(AUC) of these three models were 0.832(95% CI 0.786- 0.878), 0.840(0.793- 0.887) and 0.846(0.799- 0.892), respectively. In the validation cohort, AUC of these three models were 0.825(0.753- 0.897), 0.848(0.782- 0.914) and 0.851(0.785- 0.917), respectively. With two cut off points, 10.80 and 7.30, the specificity of CODE-C₀ diagnosing T1DM and T2DM was 95%.In the CODE-C₁20 and CODE-C_auc models, both CODE-C₁₂₀>10.91 and CODE-C_auc>10.85 were indicative of T1DM (95% specificity). A low CODE-C₁₂₀ (<7.65) and low CODE-C_auc (<7.87) were indicative of T2DM (95% specificity). Patients with scores between high and low cut off points were undetermined type needing further examination of autoantibody and long-term follow-up.

Through three clinical diagnosis models based on age at diagnosis time, BMI and C-peptide under the circumstance without high-sensitive islet autoantibody results, the specificity of diagnosing T1DM from T2DM can be improved.

To investigate the distribution characteristic of major histocompatibility complex (MHC) classⅠchain-related gene A (MICA) genotypes in different subgroups of autoimmune type 1 diabetes mellitus(T1DM) and its interaction with human leukocyte antigen (HLA)-DQ genotypes.

MICA and HLA-DQ genotypes were tested by PCR sequencing-base typing in patients with T1DM (n=338) and normal controls (n=258). The T1DM patients can be further diagnosed as T1ADM (n=193) and latent autoimmune diabetes in adults (LADA, n=145), who were outpatients in Institute of Metabolism Endocrinology and Department of Endocrinology or healthy subjects from physical examination, Second Xiangya Hospital, Central South University. Different alleles of MICA 4, 5, 5.1, 6, 9 were determined by the repeat sequence of GCT polymorphism in transmembrane domain at exon 5 of MICA gene. Chi square test was used to compare the frequencies of MICA gene in different subtypes of type 1 diabetes. Svejgaard Ryder test was used to analyze the interaction between MICA and HLA-DQ.

(1)Some types of MICA alleles and genotypes were more frequent in early-onset T1ADM (<20 years old) than in normal controls, those were MICA4 （20.3% vs 13.2% ，χ²=6.501，P<0.05）, MICA9 （26.8% vs 13.2% ，χ²=21.419 ，P<0.01 ）, MICA4/9 （13.0% vs 3.5% ，χ²=12.312，P<0.01）and MICA9/9 （6.5% vs 1.9% ，χ²=5.269，P<0.05). (2)There were no difference in MICA gene frequency between adult-onset T1ADM (>20 years old) （χ²=0.067-3.078, χ²＝0.000- 3.954, all P>0.05）, LADA （χ²=0.000- 3.954, all P>0.05）and normal controls.(3)There was no linkage disequilibrium between MICA and HLA-DQ gene. Svejgaard Ryder test showed that the effect of MICA gene was weaker than HLA-DQ(OR(95%CI) ：0.266(0.114-0.625)), which can only have extra function when combined with susceptible HLA-DQ gene(3.037(1.448-6.370)). When HLA-DQ genes were protective or neutral, MICA gene show no susceptible effect （all P>0.05）.

MICA gene plays a role in T1ADM patients with susceptible HLA-DQ gene. The polymorphism of MICA gene is related to early-onset T1ADM, but not related to late-onset T1ADM and LADA.

To explore the interaction of T cell and insulinoma-associated protein 2(IA-2) conformation and peptide primary sequence on B and T lymphocyte.

We designed and synthesized four types of IA-2 epitope peptides, parental β-fold structure IA-2 _843-855 peptide, α-helical IA-2 _843-855 peptide (conformation variability), random coil IA-2_843-855 peptide (sequence variance) and further β-fold structure IA-2 _843-855 peptide which incorporated three hydrophobic amino acid. Patients who were diagnosed as type 1 diabetes mellitus (T1DM, n=12) within 1 year and with high titer IA-2 autoantibodies, T2DM (n=12) and healthy control(n=12) were recruited from the second hospital of Jilin university. Their peripheral blood mononuclear cell (PBMC) cells were stimulated with four types of IA-2_843-855 antigens (10 μg/ml）and nonspecific mitogen PHA (5 μg/ml) was added as positive control. Cellular proliferation was expressed as the stimulation index(SI). The suspensions collected from culture medium after centrifuged were used to test the levels of cytokines interleukin (IL)-2 and IL-4. T-test was used to compare the means between groups.

The SI of T1DM stimulated by parental β-fold structure IA-2_843-855 peptide, the α-helical IA-2_843-855 peptide, the random coil IA-2_843-855 peptide and the further β-fold structure IA-2₈43-855 peptide were significantly higher than those in T2DM(1.33 ± 0.05 vs 1.13 ± 0.06, 1.27 ± 0.06 vs 1.19 ± 0.05, 1.31 ± 0.07 vs 1.21 ± 0.05, 1.20 ± 0.07 vs 1.11 ± 0.05, respectively,t=-11.6--2.71,P<0.05), and also significantly higher than that in the healthy group (t=-12.6--2.12,P<0.05). The IL-4 level of T1DM stimulated by the four types of IA-2_843-855 peptide were significantly lower than that in T2DM and the healthy group(t=2.43-11.75, all P<0.05). The IL-2 level of T1DM stimulated by the four types of IA-2_843-855 peptide were significantly higher than that in T2DM and the healthy group(t=-7.20--2.14, all P<0.05).The IL-2 level stimulated by the further β-fold structure of IA-2_843-855 peptide and IL-4 cytokines level was lower than the other three peptides(t=-11.9-4.91, all P<0.01).

The four types of IA-2_843-855 peptides we designed and synthesized can specifically make the T lymphocyte proliferate, the further β-fold structure IA-2_843-855 peptide is different from the parental peptide in effect on proliferation and cytokines secretion. The level of amino acid sequence plays an important role between T and B lymphocyte cross talk.

To explore the effects of different treatment on pancreatic β-cell function and insulin resistance after initial intensive insulin therapy in newly diagnosed type 2 diabetes.

One hundred and twenty five newly diagnosed type 2 diabetes patients were enrolled as the subjects from January 2014 to December 2014 in Department of Endocrinology, the People's Hospital of Qingyuan city. These patients were administered with 14 days of continuous subcutaneous insulin infusion with metformin. After the blood sugar reached the standard levels(fasting blood glucose:4.4-6.1 mmol/L and 2 h postprandial blood glucose<8 mmol/L), these patients were randomized divided into the three subsequent treatment groups for 3 months follow-up treatment through the random number table: group A (44 patients): basal insulin analogues; group B(39 patients): premixed insulin analogues; group C(42 patients): sulfonylureas insulin secretagogue. The body mass index(BMI), fasting plasma glucose (FPG), glycosylated hemoglobin(HbA_1c), lipids were measured in each group before and after treatment, and the different time's blood C-peptide levels were measured during intravenous glucose tolerance test. Acute insulin response (AIR), C-peptide area under curve, homeostasis model assessment for β cell function (HOMA-β), homeostasis model assessment-insulin resistance(HOMA-IR) were calculated. The least significant difference t-test and one-way ANONA were used to analyze the quantitative variables between groups. Correlation analysis was used test the relationship among variables.

The HOMA-β significant improved（9.7±1.4 vs 2.3±1.2, 10.0 ± 1.7 vs 2.7 ± 1.3, 7.3 ± 1.8 vs 2.3 ± 1.4，F=28.620，all P<0.01), HOMA-IR(0.28 ± 0.16 vs 0.48 ± 0.33, 0.28±0.13 vs 0.40 ± 0.23, 0.24±0.12 vs 0.39±0.23，F=39.162，all P<0.01) was decreased in each group. HOMA-β in group A and group B were significantly different from that in Group C (9.7 ± 1.4 vs 7.3 ± 1.8, t=-3.23, 10.0±1.7 vs 7.3 ± 1.8, t=2.53, all P<0.01).

After initial intensive insulin treatment in newly diagnosed type 2 diabetes patients, the efficacy in the insulin intensive therapy groups is significant better in improving the β-cell function.

To investigate the effect of allopurinol on the endothelial function of patients with impaired fasting glucose (IFG) complicated with hyperuricemia.

From June 2015 to September 2015, 90 outpatients with IFG combined with hyperuricemia were recruited. All the subjects were randomly assigned into allopurinol treatment group or control group by using random number table method. Besides the lifestyle intervention, the subjects were treated with allopurinol or placebo respectively for 12 weeks. Flow-mediated dilation (FMD) as well as systolic blood pressure (SBP), diastolic blood pressure(DBP), serum uric acid, serum creatinine, C-reactive protein (CRP), fasting plasma glucose (FPG), fasting insulin (FINS), total cholesterol (TC) and triglyceride (TG) were measured before and after treatment. Independent-sample t test was used to compare measurement data between two groups. Categorical data were compared using the Chi-Square test. Correlation coefficients of changes between serum uric acid and FMD were calculated by partial correlation analysis.

After treatment, in the allopurinol group, serum uric acid, SBP, DBP, CRP, TC, and TG were significantly decreased when compared with that before treatment (t=2.31-14.05, all P<0.05), and FMD was significantly increased after allopurinol treatment (4.1± 0.6 vs 5.0 ± 0.7, t=- 6.58, P<0.05). After 12 weeks, serum uric acid, SBP, DBP, CRP and TG decreased obviously (t=- 15.21-- 2.35, all P<0.05) for patients treated with allopurinol when compared with that in control group. Moreover, FMD increased significantly in subjects of allopurinol group (4.3±0.4 vs 5.0±0.7, t= 6.00, P<0.05). Additionally, the changes of serum uric acid, SBP, DBP, CRP, FNS, HOMA-IR, and TG were more obvious in allopurinol group when compared with that in control group （t=-15.53--1.35，all P<0.05). There was a greater increase in FMD in allopurinol group （t=22.79，P<0.05).

The endothelial function could improve after urate-reducing treatment with allopurinol in patients with impaired fasting glucose complicated with hyperuricemia.

To explore the effect and underlying mechanism of exenatide on the cardiomyocytes through evaluating its impact on adiponectin and its receptors(AdipoR), oxidative stress and endoplasmic reticulum stress in cardiomyocytes cultured with high glucose.

H9C2 cardiomyocytes were randomly divided into following four groups (n=3): group A: cardiomyocytes were cultured in normal glucose concentration (5.6 mmol/L); group B: cardiomyocytes were cultured in high glucose concentration (25.5 mmol/L); group C: cardiomyocytes were cultured in high glucose concentration and 10 nmol/L GLP-1; group D: cardiomyocytes were cultured in high glucose concentration and 100 nmol/L GLP-1. Four groups were continued to be cultured for 24 h. The expression of adiponectin, AdipoR1, nicotinamide adenine dinucleotide (NADPH) oxidase subunit (p22phox) nuclear factor E2-related factor2 (Nrf2), and C/EBP homologous protein(CHOP) were analyzed. Differences among groups were compared by one-way analysis of variance, pairwise comparison were conducted using LSD-t test.

(1)The level of adiponectin, the protein expression of AdipoR1, and the mRNA expression of Nrf2 were significantly decreased in group B than those in group A (760±145 vs 1 490±168; 0.59±0.08 vs 0.91±0.07; 0.56±0.02 vs 1.00 ± 0.00, t= 7.942, 6.922, 10.689; all P<0.05). The protein expression of p22phox, and the mRNA expression of CHOP were significantly increased in group B than those in group A(0.87±0.02 vs 0.56±0.09; 1.58 ± 0.16 vs 1.00 ± 0.00; t=7.591, 5.994; all P<0.05). (2)The levels of adiponectin, AdipoR1 protein expression and the Nrf2 mRNA expression of group C(1 070±142, 0.69±0.02, 0.71±0.09) were significantly higher than those of group B(t=3.372, 2.263, 3.633; all P<0.05). The p22phox protein (0.66 ± 0.04）and CHOP mRNA (1.26 ± 0.28）of group C were markedly lower than those of group B(t=4.716, 3.272，all P< 0.05). (3)The level of adiponectin(1 306 ± 178), the protein expression of AdipoR1(0.82 ± 0.09), and the mRNA expression of Nrf2 (0.91±0.11) were increased in group D than that in group C(t=2.575, 2.349, 4.792; all P<0.05). The mRNA expression of CHOP was decreased in group D than that in group C(t=3.185, P< 0.05).

Exenatide plays protective role on cardiomyocytes cultured with high glucose. It may abate cardiomyocyte damage induced by oxidative stress and endoplasmic reticulum stress through regulating adiponectin and its signaling pathways.

With the progress of society and the change of lifestyle, people's sleep patterns are changing, and the number of people with sleep disorders is gradually increasing. Prospective studies have found that sleep disorders are independent risk factors for diabetes, and sleep disorders also affect the blood sugar control of diabetic patients. At present, there are many studies on type 2 diabetes and sleep disorders, while there are few studies on the relationship between type 1 diabetes (T1DM) and sleep. The prevalence of T1DM is on the rise. For T1DM patients, sleep disorders not only affect blood sugar control and quality of life, but also may lead to sudden death. T1DM-related complications are related to sleep disorders. Therefore, the sleep problem of T1DM deserves attention.

Type 1 diabetes mellitus (T1DM) is an autoimmune disease that causes absolute insulin deficiency due to specific destruction of pancreatic islet β cells. It has the characteristics of relatively rapid onset and difficult to reverse once the islet function is lost^[1]。 Immunotherapy is currently recognized as a pathogenic treatment^[2]However, a large number of studies have shown that immune intervention treatment after diagnosis has little effect on the protection of residual islet function^[2]。 Therefore, early prediction is very important for the prevention, treatment and prognosis of T1DM. Among them, the prediction of gene susceptibility and immune challenge is the most fundamental etiological prediction^[2]。 In this paper, the latest progress of T1DM prediction research will be summarized from three aspects: gene prediction, immune prediction and other index prediction.

Diabetes and cardiovascular disease have become the leading causes of human death worldwide. About 1.5 million people died from diabetes worldwide in 2012^[1]About 80% of diabetic patients die from myocardial infarction or stroke^[2]。 It is urgent to pay attention to the cardiovascular safety of diabetic patients, reduce cardiovascular complications and reduce mortality. In recent years, new hypoglycemic drugs have emerged in an endless stream. Exploring the influence of these drugs on cardiovascular risk factors or events in diabetic patients has important guiding significance for clinical practice.

From June 20 to July 2, 2016, as the third group of visiting members of the Outstanding Young Diabetes Specialist Training Program (CIDE) of the Diabetology Branch of Chinese Medical Association, we visited and studied at the International Diabetes Center (IDC) in Minneapolis, Minnesota, USA and the Mayo Clinic in Rochester.