| Background and objectives:Diabetes mellitus prevalence is increasing at alarming rates, and this ailment has become a major public health problem worldwide. According to the International Diabetes Federation (IDF),360 million individuals suffered from diabetes in 2011, a number expected to rise to 522 million with a prevalence of 7.7% in 2030. Among which, Asia has the most prominent growth rate. Type 2 diabetes Mellitus, characterized by insulin resistance and pancreatic β cell function defect, makes up about 90% of all cases. Although traditional oral hypoglycemic agents and insulin injections can alleviate hyperglycemia, those treatments could not replenish insulin-producing pancreatic βcell mass and reverse the progression of the disease. Replenishing insulin-producing pancreatic β cell mass and alleviating insulin resistance are considered the ideal ways for diabetes care.Targeting the pathophysiological defects that characterize the onset of diabetes can achieve a durable glucose control and benefit to essential components in disease pathogenesis. Betatrophin, a newly characterized 193-amino-acids endocrine hormone, overexpressed in the liver of insulin receptor antagonist-induced insulin resistance-mouse model, and promote mouse pancreatic β cell proliferation in a dose-dependent manner. Betatrophin was also named as ANGPTL8, RIFL and lipasin because of its function in promoting pancreatic P cell proliferation and regulating lipid metabolism. So far, the relationship between serum betatrophin concentration and diabetes, obesity as well as lipid profiles remain controversial. Some studies revealed that betatrophin could promote pancreatic β cell proliferation in mice and regulate lipid metabolism while others disagreed. Their research found that mouse betatrophin has no effect on human beta cell proliferation and differentiation as well as glucose homeostasis. At the same time, some clinical studies have found circulating betatrophin concentration associated with diabetes, insulin resistance and dyslipidemia, and differed in different population. As a newly discovered pro-metabolic factor, the relationship between betatrophin and Chinese type 2 diabetes has not been clarified. Meanwhile, the correlation between betatrophin with glucose metabolism, lipid profiles, insulin resistance and other metabolic indexs still remains unclear. Whether betatrophin could be a diagnostic biomarker needs to be demonstrated. Therefore, our research compared circulation betatrophin levels between newly diagnosed type 2 diabetes and health controls.Methods:A number of 131 participants were recruited from August 2014 to December 2014 at the Diabetes Clinics of Zhujiang Hospital and Medical Examination Center of Beijiao Hospital. Eligible patients were males and females over 18 years, including 58 non-diabetes-mellitus subjects (NDM:18 lean,22 overweight, and 18 obese individuals) and 73 age-and sex-matched patients with T2DM (22 lean,29 overweight, and 22 obese individuals). Each group was divided into three subgroups (normal weight, overweight and obese) according to the body mass index (BMI). The exclusion criteria are as follows:(1) subjects being treated with oral hypoglycemic agents and those with macrovascular complications; (2) subjects taking any medications known to affect glucose tolerance within one month; (3) individuals with type 1 diabetes or gestational diabetes; (4) subjects with viral hepatitis, cancer, severe psychiatric disturbances, hepatic failure, chronic renal failure on hemodialysis, congestive heart failure, or other known major diseases. All subjects enrolled provided written informed consent. The study protocol was in agreement with the guidelines of the Human Research Ethics Committees of Zhujiang Hospital and performed in accordance with the ethical principles of the Declaration of Helsinki. All subjects underwent comprehensive anthropometric measurements, including height, weight, and waist and hip circumferences, whereby body mass index (BMI) and waist-to-hip ratio (WHR) were calculated. Weights were measured in light clothing without shoes. Heights were obtained with a portable, rigid measuring rod. BMI was derived as body weight divided by body height squared. Waist circumference was measured at the midpoint between the lowest rib margin and the iliac crest in a standing position. Hip circumference was measured at the widest point. Blood samples were collected after 8 hours of fasting without taking any medications, for the assessment of fasting plasma glucose, insulin level, C peptide, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), uric acid, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and betatrophin concentrations. Serum betatrophin levels were determined with a commercially available human ELISA kit (Wuhan Eiaab Science, Wuhan, China; Catalogue number E11644h) according to the manufacturer’s instructions. ELISA was performed in duplicate, and samples with coefficient of variation (CV) values exceeding 5% were excluded. A standard curve was constructed by plotting mean OD450 for each standard against its concentration, generating a best fit curve through the graph points. Fasting plasma glucose amounts were measured by the glucose oxidase method; fasting insulin and C peptide levels were measured by enzyme-amplified chemiluminescence assays. Serum TC, triglycerides, LDL-C, and HDL-C were assessed by enzymatic methods; ALT and AST were quantitated by kinetic methods (Beckman Coulter Inc., Brea, CA); serum uric acid levels were evaluated by the uricase method. Obesity was defined as BMI≥28 kg/m2 and overweight was defined as a BMI between 24 and 28 kg/m2. Insulin resistance was estimated by homeostasis model assessment of insulin resistance (HOMA-IR) and Quantitative Insulin Sensitivity Check Index (QUICKI). Pancreatic β cell function was assessed by homeostasis model assessment of β cell function (HOMA-%β) [15]. HOMA-IR and HOMA-%β were derived using the following equations:HOMA-IR=insulin[lU/ml]*glucose[mmol/l]/22.5;HOMA-%β=20* insulin [lU/ml]/(glucose[mmol/l]-3.5). All statistical analyses were performed using SPSS version 20.0 (SPSS, Inc., Chicago, IL,USA). Normally distributed and continuous variables were presented as mean±standard deviation (SD) and nonnormally distributed variables as median and quartiles (25% and 75%). Comparisons between groups were assessed by independent-samplest-test; alternatively, analysis of variance (ANOVA) followed by LSD tests was conducted as appropriate. Correlations between variables were assessed using Pearson correlation analysis, controlling for covariates. Two tailed P< 0.05 was considered statistically significant. Performance of betatrophin concentration in detecting T2DM was evaluated using receiver operating characteristic (ROC) curve analysis. Based on ROC analysis, the best cut-off value for betatrophin concentration was determined from the highest Youden index, which is defined as sensitivity+specificity-1.Results:Section 1:General characteristics of normal glucose participants and newly diagnosed T2DM patientsA total of 58 NDM subjects and 73 age- and sex-matched T2DM patients were assessed in this study. No significant differences were found in age, gender,BMI, WHR, TG, LDL-C, ALT, and AST levels between the two patient groups. Interestingly, serum betatrophin concentrations were approximately 1.8 times higher in T2DM patients than in NDM individuals (median 747.12 versus 407.41 pg/ml,P< 0.001).Section 2:Serum betatrophin levels in each subgroup2.1 When stratifed by BMI, serum betatrophin levels in each subgroups: While dividing T2DM group and NDM group into three subgroups (normal weight, overweight and obese) according to BMI index, serum betatrophin levels in each subgroups:The results showed that in non-diabetic group, serum betatrophin concentration in overweight and obese patients were significantly higher than those in normal weight subjects (non-diabetic obese vs. non-diabetic overweight vs. non-diabetic normal weight:592.02pg/ml vs.501.57pg/ml vs.155.39 pg/ml, P <0.05), however in T2DM group, serum betatrophin concentration elevated only in obese patients (1003.28 pg/ml). Serum betatrophin concentrations were approximately 6.5 times higher in obese T2DM group than that in non-diabetic controls (median,1003.28 pg/ml vs.155.29 pg/ml, P<0.001).2.2 Serum betatrophin levels in each subgroups when stratifed by waist circumstance:While dividing T2DM group and NDM group into two subgroups (central obesity and none central obesity groups) according to waist circumstance, serum betatrophin levels in each subgroups:The results showed that serum betatrophin concentration in central obesity group were significantly higher than that in non-central obesity group (central obesity T2DM vs. non-central obesity T2DM vs. central obesity control vs. non-central obesity control:1014.89pg/ml vs.551.17pg/ml vs.658.30 pg/ml vs.321.31pg/ml, P<0.05). Serum betatrophin concentrations were approximately 3.2 times higher in central obesity T2DM group than that in non-central obesity control (median,1014.89pg/ml vs.321.31pg/ml, P<0.001).Section 3 Correlation between serum betatrophin concentration and metabolic index3.1 Correlation between serum Betatrophin concentration and blood glucose levels:Bivariate correlation analysis were performed to analyze the relationship between betatrophin concentration and all the metabolic parameters:the results showed that betatrophin concentration was negatively associated with FPG levels in none diabetic patients (P<0.05); whereas in patients with type 2 diabetes, betarophin showed no relation with FPG levels (P>0.05)3.2 Correlation between serum Betatrophin concentration and lipid profiles: Bivariate correlation analysis showed that betatrophin levels did not correlate with TC, TG and LDL-C levels but correlated closely with HDL-C levels in all subject. What is more, this trend also exists when stratified by BMI.3.3 Correlation between serum Betatrophin concentration and other metabolic parameters:Bivariate correlation analysis revealed that in non diabetic group, betatrophin concentration was positively associated with WHR, insulin, C peptide, HOMA-IR, and UA levels, but negatively associated with QUICK index (P<0.05). While in FPG levels in none diabetic patients (P<0.05); whereas in patients with type 2 diabetes, betarophin concentration correlated only with age(P<0.05).Section 4:Performance of Betatrophin Concentration in Detecting T2DMThe ROC curve shown depicts the diagnostic accuracy of betatrophin level for T2DM. The optimal cut-off point (betatrophin concentration) to predict T2DM was 501.23 pg/ml. Using this cut-off value, diagnostic efficiency for T2DM reached the highest value:the area under the ROC curve was 0.824(95% CI 0.748-0.885,P< 0.001), with sensitivity and specificity of 83.56% and 72.41%, respectively.Conclusion:We found that circulating betatrophin concentrations were significantly increased in T2DM and obese patients. Serum betatrophin concentrations were approximately 1.8 times higher in T2DM group than that controls,6.5 times higher in obese T2DM group than that in obese controls and 3.2 times higher in central obesity T2DM group than that in non-central obesity controls. Interestingly, for the first time, this study demonstrated that betatrophin was negatively correlated with HDL-C levels in both NDM and T2DM groups. Using a ROC curve, we found that circulation betatrophin concentration could be a diagnostic biomarker for T2DM, with optimal cut-off point of 501.23 pg/ml. Given data privided by currently available human and animal studies on betatrophin, combined with the results of this study, we suggest that circulating betatrophin concentrations were significantly increased in T2DM and obese patients.Meanwhile, betatrophin was negatively correlated with HDL-C levels.In addition, betatrophin concentration could be a diagnostic biomarker for T2DM. |
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