Your Liver is a Teenager and Your Heart is a Grandmother

Have you ever been skeptical when people affirm that they feel 20 years younger than their true age? It turns out this might be possible. Chronological age, the number of years we’ve been alive, and biological age, the amount of damage accumulated in cells and tissue over our lifetime, do not always match. People with a healthy lifestyle often have a lower biological age compared to their chronological age, as determined by methods that measure molecular aging in humans at a whole-body level. However, aging occurs at different rates across tissues in mice, raising the possibility that aging is a heterogeneous process in humans too.

To investigate this question, researchers at Stanford University developed models that infer the biological age of 11 organs by analyzing protein patterns found in the blood. Through this non-invasive approach, they found that people with the same whole-body biological age displayed different rates of aging across tissues. In most cases, whole-body aging was driven by one single organ rather than multiple organs. Furthermore, single-organ aging models of the heart, kidney, and brain accurately predicted the presence of their respective diseases, such as hypertension, diabetes, and Alzheimer’s.

These findings suggest that aging models derived from organ-specific plasma proteins can capture the disease-relevant heterogeneity of aging, which is not captured by whole-body aging models. This method could be leveraged to predict more accurately the risk of a specific disease, allowing people to adopt targeted lifestyle interventions to improve their health.

This study was performed by PhD student Hamilton Oh and postdoctoral scholar Jarod Rutledge, and led by Tony Wyss-Coray, Distinguished Professor of Neurology and Neurological Sciences at Stanford University.

Managing Correspondent: Allegra Carlotta Scarpa

Press Article: Are your organs ageing well? The blood holds clues (News from Nature)

Original Journal Article: Organ aging signatures in the plasma proteome track health and disease  (Nature)

Image Credit: Freepik