Scientists find way to determine the biological age of a person’s organs through a blood test

Scientists have announced a breakthrough in determining the biological age of internal organs through a blood test, as reported by a team from Stanford University. The research claims the ability to assess the age of 11 major organs, including the heart, brain, and lungs, utilizing a machine-learning algorithm. The study, encompassing over 5,000 patients and published in the journal Nature, delves into the analysis of more than 4,000 proteins present in the blood to make predictions about the condition of various organs.

The authors assert that nearly 20% of the population experiences accelerated organ aging, often correlating with an elevated mortality risk ranging between 20 and 50%. According to their findings, one to two individuals in every 100 may exhibit several organs aging beyond their chronological years. The researchers believe their method could be instrumental in identifying organs undergoing rapid decline, potentially unveiling underlying health issues.

The predictions based on the algorithm are particularly significant, as organs aging faster than an individual’s biological age may indicate a higher susceptibility to specific health concerns. For instance, an older heart age compared to one’s actual age might elevate the risk of heart failure, while an aging brain could be more prone to dementia.

The study reveals that individuals with one or more organs aging rapidly face an increased risk of certain diseases and mortality over the subsequent 15 years. Dr. Tony Wyss-Coray, one of the investigators, highlighted that over 18% of individuals aged 50 or above exhibited at least one organ aging significantly faster than the average, putting them at heightened risk for diseases in that specific organ in the next 15 years.

The potential impact of this research extends to patenting the test methodology, paving the way for future use and commercialization. However, the team emphasizes the necessity for additional studies to validate the accuracy of the model in predicting organ age and health.