Year: 2025
Type: article
Abstract: Among the global health challenges, diabetes mellitus—an archetypal meta-bolic disorder—continues to increase in prevalence. According to the World Health Organization, the number of diagnosed patients has more than tripled over the past two decades, making it a significant cause of disability and death. The accelerated ageing of the population, the prevalence of sedentary behaviours, and the problem of over-nutrition are all contributing to the increase in the prevalence of diabetes mellitus. Although conventional interventions such as glucose-lowering medications, dietary modification, and physical exercise can alleviate symptoms, they are unable to overcome the inherent limitations of fluctuating efficacy and poor patient compliance. Modern medicine is undergoing a therapeutic paradigm shift: breakthroughs in genomics technology have made individualised medication possible, artificial intelligence-assisted diagnostic systems have dramatically improved the accuracy of disease typing, and real-time monitoring by wearable devices has provided data support for dynamic adjustments to treatment regimens. By integrating multi-omics data (including genomic features, metabolomic profiles, and the composition of intestinal flora) with patients' behavioural patterns, clinicians are able to build precise treatment models and achieve the transformation from “one person for every patient” to “tailor-made”. This individualised strategy, based on big data, not only optimises glycemic control but also significantly reduces the risk of long-term complications such as retinopathy and nephropathy. In this study, we focus on the cutting-edge advances in precision medicine for diabetes, and systematically discuss the key issues of biomarker screening, development of intelligent diagnostic and treatment systems, and optimisation of personalised intervention plans, with the aim of providing theoretical basis and practical guidance for the construction of the next-generation diabetes management system, and ultimately realising the leap-forward development from disease treatment to health management.
Authors: Zijuan Wen, Qing Li
Institution: Hunan Normal University
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4412504593