From clock to clock: Therapeutic target discovery for aging and age-related diseases.

Abstract

The aging population worldwide necessitates the development of novel therapeutics that enhance the quality of life by preventing and treating age-related diseases. In this review, we first discuss the advantages of a dual-purpose target identification strategy for aging and age-related diseases, with assessment of the hallmarks of aging as an approach to identify such dual-purpose targets. Resulting from a convergence of aging research with machine learning (ML) and other artificial intelligence (AI) models, aging clocks were initially developed as aging biomarkers, but its value in identifying therapeutic targets is also increasingly recognized. Building on recently published aging clocks, we reestablish a significant proportion of known drug targets by identifying clock-associated genes, highlighting the potential of these clocks for target identification. Lastly, we discuss other applications of aging clocks in drug development such as population stratification and disease and treatment monitoring. With the growing availability of multi-omics data and rapid advancements in ML and AI, we anticipate accelerated progress in aging clock research, paving the way for innovative treatments to meet the healthcare needs of a global aging population.