Researchers develop AI tissue clocks to measure biological age

New research is advancing the ability to measure biological age through AI-driven tissue analysis and improved epigenetic models. An Austrian study utilizing artificial intelligence analyzed over 25,000 tissue samples from 40 different types, including the brain, heart, and lungs. By examining tissue structure rather than just molecular changes, researchers developed “tissue clocks” capable of estimating the biological age of individual organs with an average error of only 4.9 years.

Complementing this, researchers from the Leibniz Institute on Aging (FLI), in collaboration with international partners, have addressed the “black box” of epigenetic clocks. They developed the TFMethyl Clock, a model designed to combine high predictive accuracy with better biological interpretability. While traditional epigenetic clocks use DNA methylation patterns to predict age, this new model aims to clarify the specific biological processes these markers reflect, helping scientists better understand how lifestyle and environment influence the aging process.