Smart blood test uses AI to decode the biology of aging

Updated

A team of researchers from the University of Vienna and Nankai University by combining advanced metabolomics, machine learning, and a novel network modeling tool, they have identified key molecular processes that link physical activity with healthier aging. Their work highlights aspartate as a dominant biomarker of physical fitness and points to new opportunities for monitoring and supporting active aging.

The researchers first created a Body Activity Index (BAI) by combining data from walking distance, chair-rise, grip strength, and balance tests. This composite score provides a robust picture of endurance, strength, and coordination. In parallel, they developed a Metabolomics Index based on the blood concentrations of 35 small molecules. Analysis of 263 samples from older adults showed a striking correlation between the two indices.

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