Diabetes Case Reports

Significance of Genetic Biological Indicators for Diabetic Prediction

Yiwen Lin^* Department of Forensic Medicine, Fudan University, Shanghai, China
^*Correspondence: Yiwen Lin, Department of Forensic Medicine, Fudan University, Shanghai, China, Email:

Received: 03-Jul-2023, Manuscript No. DCRS-23-22689; Editor assigned: 06-Jul-2023, Pre QC No. DCRS-23-22689(PQ); Reviewed: 19-Jul-2023, QC No. DCRS-23-22689; Revised: 26-Jul-2023, Manuscript No. DCRS-23-22689(R); Published: 02-Aug-2023, DOI: 10.35841/2572-5629-23.8.175

Description

Biomarkers are biological molecules that can indicate the presence or risk of a disease or condition. They can be used for screening, diagnosis, prognosis, or treatment monitoring of various diseases, including diabetes. Diabetes is a chronic metabolic disorder that affects the body’s ability to produce or use insulin, a hormone that regulates blood glucose levels. Type 1 diabetes is an autoimmune disease that destroys the insulinproducing beta cells in the pancreas, leading to absolute insulin deficiency. Type 2 diabetes is a multifactorial disease that results from a combination of insulin resistance and relative insulin deficiency. Both types of diabetes can cause serious complications, such as cardiovascular disease, kidney failure, nerve damage, and blindness. The current diagnostic criteria for diabetes are based on measuring blood glucose levels or glycated Hemoglobin (HbA1c), which reflects the average blood glucose level over the past 2-3 months. However, these tests have some limitations, such as variability, lack of specificity, and inability to detect the early stages of the disease or its progression. Therefore, there is a need for more reliable and sensitive biomarkers that can predict the onset and progression of diabetes, as well as the response to treatment and the risk of complications.

One of the most potential areas of biomarker research is the identification of autoantibodies that target beta cell antigens in type 1 diabetes. Autoantibodies are antibodies that mistakenly attack the body’s own tissues or cells, causing inflammation and damage. In type 1 diabetes, autoantibodies can be detected in the blood several years before the clinical onset of the disease, indicating an ongoing autoimmune process that gradually destroys the beta cells. The most commonly used autoantibodies for predicting type 1 diabetes are those against Insulin (IAA), Glutamic Acid Decarboxylase (GADA), a Tyrosine Phosphatase- Like Protein (IA-2A), and Zinc Transporter-8 (ZnT8A). These autoantibodies have different sensitivities and specificities, and their presence and number can vary depending on the age, genetic background, and environmental factors of the individual. The detection of multiple autoantibodies (two or more) is considered to be highly predictive of type 1 diabetes development, with a risk of more than 90% within 10 years. However, some individuals may have only one autoantibody or none at all, and still develop type 1 diabetes later in life. Therefore, other biomarkers are needed to improve the accuracy and timeliness of prediction.

Another area of biomarker research is the discovery of novel molecules that reflect the metabolic status and function of the beta cells in both type 1 and type 2 diabetes. These biomarkers can provide information about the beta cell mass, insulin secretion capacity, glucose sensitivity, and stress response. Some examples of these biomarkers are C-peptide, pro-insulin, amylin, Glucagon-Like Peptide-1 (GLP-1), Pancreatic Polypeptide (PP), and Chromogranin A (CgA). These biomarkers can be measured in blood, urine, or saliva samples, and can indicate the degree of beta cell impairment or preservation in different stages of diabetes. For instance, C-peptide is a peptide that is co-secreted with insulin from the beta cells, and its level reflects the endogenous insulin production. C-peptide can be used to distinguish between type 1 and type 2 diabetes, as well as to monitor the residual beta cell function and the response to treatment in type 1 diabetes. Pro-insulin is a precursor molecule that is cleaved into insulin and C-peptide in the beta cells. The ratio of pro-insulin to insulin or C-peptide can indicate the efficiency of insulin processing and secretion in the beta cells. A high pro-insulin ratio can suggest beta cell dysfunction or stress in both type 1 and type 2 diabetes. Amylin is a hormone that is co-secreted with insulin from the beta cells, and it modulates glucose homeostasis by inhibiting glucagon secretion and gastric emptying. Amylin levels can reflect the beta cell secretory capacity and correlate with insulin resistance in type 2 diabetes. GLP-1 is an incretin hormone that stimulates insulin secretion from the beta cells in response to glucose ingestion. GLP-1 levels can indicate the beta cell glucose sensitivity and responsiveness in both type 1 and type 2 diabetes. PP is a hormone that is secreted from the pancreatic F cells in response to food intake. PP levels can reflect the pancreatic function and correlate with insulin resistance in type 2 diabetes.

Conclusion

Biomarkers are valuable tools for predicting diabetes and its complications. They can improve the diagnosis, prognosis, treatment, and prevention of diabetes by providing more accurate and timely information about the disease status and risk. However, there are still many challenges and limitations in the discovery, validation, standardization, and implementation of biomarkers for diabetes. Therefore, more research is needed to identify novel biomarkers with high specificity and sensitivity, to elucidate their biological mechanisms and interactions, to establish their clinical relevance and utility, and to integrate them into personalized medicine approaches for diabetes management. CgA is a protein that is stored and released with insulin from the secretory granules of the beta cells. CgA levels can indicate the beta cell mass and activity in both type 1 and type 2 diabetes.