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Audio Interview

Decoding aging: how a proteomic clock predicts mortality and disease across populations

Published on May 29, 2025   17 min

A selection of talks on Genetics & Epigenetics

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Interviewer: Dr. Austin Argentieri, thank you very much for taking the time to discuss your recent publication with colleagues in nature medicine. The publication describes the development of a proteomic age clock using plasma proteins to estimate biological age and predict age-related diseases and mortality across diverse populations. Could you start by summarizing your research goals and the main approach that your team took to meet them? Dr. Argentieri: Absolutely. Thank you for having me. It's a pleasure to discuss these. The motivation for our study comes from the fact that age-related diseases are some of the major killers globally. If you look at the global population above 70 years old, nine out of the top ten global causes of death are all age-related diseases. Our motivation was to try to see if we could find some biology that's common to these diseases that might help us develop very effective and strategic precision medicine and preventative health tools. It just so happens that if you look at the history of the field of aging and if you look at what we know so far about the biological hallmarks of aging that many different age-related chronic diseases share the same aging biology and the same aging-related biological mechanisms. Of course, loss of proteostasis and protein stability is one of the core biological hallmarks of aging. So we started with this idea that if we could capture something about aging biology through, in this case, plasma proteins, it might allow us to capture something that's a common biological aging signal across many of these different common chronic diseases

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