Researchers have created a new biological-age clock called gtAge that predicts aging more accurately than most existing methods. It works by analyzing two features measurable in a regular blood sample – the sugar patterns attached to antibodies (IgG glycosylation) and gene-activity levels in white blood cells. The team used deep reinforcement learning, an advanced form of artificial intelligence, to combine these data. They hope gtAge may eventually help doctors check whether a patient's diet, medication, or lifestyle changes are genuinely slowing aging and cutting the risk of age-related diseases.

ARTICLE

Xia, Yao, Syed Mohammed Shamsul Islam, Xingang Li, Abdul Baten, Xuerui Tan, and Wei Wang. "Deep Reinforcement Learning – Driven Multi-Omics Integration for Constructing gtAge: A Novel Aging Clock from IgG N-glycome and Blood Transcriptome." Engineering (2025). https://doi.org/10.1016/j.eng.2025.08.016.