Exploring Novel Biomarkers for Early Diagnosis, Disease Progression, and Treatment Response in Diabetes

Diabetes (DM) exists as an unending metabolic disorder which presents impaired insulin secretion or action that triggers hyperglycemia. Early identification and complications prediction are limited by the symptomatic techniques that use fasting plasma glucose (FPG) and verbal glucose resistance test (OGTT) and hemoglobin A1C (HBA1C). Advances in atomic science and proteomics and metabolomics and genomics research resulted in developing sensitive and specific modern biomarkers. However, metabolic, incendiary, oxidative push, circulating microRNAs and lipidomics markers make way demonstrative and restorative bits of knowledge. Moreover, counterfeit insights (AI) and machine learning (ML) change biomarkers, prescient modeling, and accuracy pharmaceutical revelations. AI control investigations when combined with multi-amic approaches demonstrate high promise for better diabetes screening success and developing therapeutic strategies.