Differentially Methylated Regions (Dmrs) Regulates Glp-1 Analogue in Glucose Control and Clinical Response

Background: In patients with poorly controlled type 2 diabetes, glucagon-like peptide-1 (GLP-1) analogues are clinically used and treated with other hypoglycemic agents. GLP-1 analogues are known to be associated with blood glucose control. But the clinical effect is not the same for every patient. It is hoped that in the way of drug gene susceptibility, a tailor-made optimal treatment combination will be provided for each diabetic patients. However, in the past, it was difficult to assess drug response due to drug-to-drug interaction effects. According to our previously established model of continuous subcutaneous insulin injection (CSII) and continuous glucose monitoring (CGM), we can effectively screen patients with poor response of GLP-1 analogues. Further studies have found that differentially methylated regions (DMRs) play a role in glucose control and clinical response of GLP-1 analogues in patients with type 2 diabetic. Therefore, this study will further validate the DMR genes and drug response as well as develop a new anti-diabetic drug screening platform based on this novel model.Methods: Subjects: Patients with type 2 diabetes who have received GLP-1 analogues in our hospital. It is expected to recruit 200 patients.Study period: 3 years.Clinical evaluation: Clinical evaluation will be used to test whether GLP-1 analogues are responsive. The blood samples of patients will be collected for genetic analysis. The relationship between the mean amplitude of blood glucose excursion (MAGE) and the VTRNA2-1 gene methylation status will be analyzed. Patients and general measures to control blood sugar are no different, and do not have to bear the risk.Laboratory analysis: Further research on molecular biology of cell lines will be carried out for candidate genes.Data analysis: Basic data of patient demographics, including: age, gender, height, weight, etc.; changes in blood glucose, glycated hemoglobin and related endocrine metabolism indicators before and after treatment, to compare the average (t test, variance) Analysis), the chi-square test of the category variables, the Pearson correlation coefficient comparison, and the logistic complex regression forward method to determine which independent variables should be included in the model for statistical method analysis. In vivo study with cell lines will be conducted on validation of the candidate genes.Expected Results: How to select an anti-diabetic drug tailored to the individual becomes more and more important because of the enormously increasing classes of treatment modality will be developed. This study could be of great help in recommending the best possible agent for an individual, improving the possibility of treatment success, and justifying if the need of expensive drugs in a given patient.

Project ID:PC10907-1547
External Project ID:MOST109-2314-B182-049-MY3