Telomere Length and Gut Microbiota: Integrating Advanced Glycation End Products (Ages) With Artificial Intelligence for Understanding Premature Aging

Abstract

Premature aging is characterized by an accelerated decline in biological functions, increasing the risk of chronic diseases. This review explores the interconnected roles of three critical biomarkers: Telomere Length, gut microbiota composition, and Advanced Glycation End Products (AGEs). These biomarkers exhibit bidirectional relationships, influencing one another and contributing to the aging process. Understanding their interplay provides valuable insights into the mechanisms underlying premature aging. Furthermore, this review discusses the transformative potential of Artificial Intelligence (AI) in integrating these biomarkers for predictive modelling and personalized anti-aging interventions. By analysing complex datasets, AI can identify patterns and correlations that inform targeted therapies. The combined analysis of telomere length, gut microbiota, and AGEs provides a framework for advancing research on premature aging and informing clinical interventions.