Scientists have created a new way to measure how quickly a person's body is aging by analyzing two kinds of blood data with artificial intelligence. The method, called gtAge, uses information from the sugars attached to antibodies and from gene activity in blood cells. By combining these data with deep reinforcement learning, the researchers built a model that predicts biological age more accurately than traditional approaches. They say it could one day help track how lifestyle or medical treatments slow aging and reduce disease risk.

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.