Revolutionary Innovations in Diabetes Research: From Biomarkers to Genomic Medicine

Tamer Addissouky; Majeed Ali; Ibrahim El Tantawy El Sayed; Yuliang Wang

doi:10.18502/ijdo.v15i4.14556

Tamer Addissouky Al-Hadi University College, Baghdad, Iraq.
Majeed Ali Al-Hadi University College, Baghdad, Iraq.
Ibrahim El Tantawy El Sayed Science Faculty, Menoufia University, Menoufia, Egypt
Yuliang Wang Joint International Research Laboratory of Metabolic and Developmental Sciences, Key Laboratory of Urban Agriculture (South) Ministry of Agriculture, Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China.

DOI: https://doi.org/10.18502/ijdo.v15i4.14556

Keywords: Diabetes mellitus; Molecular biomarkers; Genomic medicine; pharmaceutical advances; gene therapy, Artificial intelligence

Abstract

Diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia resulting from inadequate insulin signaling. Current management relies on biomarkers such as hemoglobin A1c (HbA1c) to guide therapy, but emerging tools offer opportunities to transform care through more personalized approaches. Molecular biomarkers, including microRNAs, metabolites, and proteins, may enable better prediction of disease course and risk of complications in individuals. Genomic medicine leverages knowledge of genetic architecture to guide tailored prevention and treatment based on an individual’s genomic profile. Stem cell research differentiates functional insulin-secreting cells for transplantation into patients as an alternative to exogenous insulin. Gene silencing techniques such as RNA interference can restore defective insulin production and secretion pathways by inhibiting dysregulated gene expression. Artificial intelligence applications automate glucose monitoring, insulin delivery, diagnostic screening for complications, and digital health coaching. Despite barriers to translation, these technologies have disruptive potential for predictive, preventive, precise, and participatory care paradigms in diabetes management. Continued research on molecular biomarkers, pharmacogenomics, stem cell therapies, gene editing, and artificial intelligence (AI) aims to improve patient outcomes through more personalized approaches tailored to the specific biological vulnerabilities underlying each individual’s diabetes.