Computer models estimate organ biological age
Scientists at CeMM Research Center for Molecular Medicine and the Ludwig Boltzmann Institute used 25,712 high-resolution tissue images from 983 people across 40 tissue types to train AI computer-vision models that estimate the biological age of individual organs. The organ-specific tissue clocks worked with about a 4.9-year average error and age signals correlated with shorter telomeres, more tissue disease signs, and higher chronic disease counts. The team also linked tissue age signals to blood gene activity to build blood-based predictors that detected aging patterns associated with Alzheimer's, Crohn's disease, diabetes and other conditions, though the methods need broader validation.
Tissue clocks estimated organ age with about 4.9 years average error.
Context
Researchers used a large tissue and genetic data set and new AI methods to study aging. The study found organ-level aging patterns and then connected tissue signals to blood gene activity. Next, researchers will need larger and more…
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