A new study led by Stanford Medicine scientists demonstrates a simple way of studying organ aging by analyzing distinct proteins, or sets of them, in blood, enabling the prediction of individuals’ risk for diseases.
Like any typical car or house or society, the pace at which parts of our bodies fall apart varies from part to part.
A study of 5,678 people, led by Stanford Medicine investigators, has shown that our organs age at different rates — and when an organ’s age is especially advanced in comparison with its counterpart in other people of the same age, the person carrying it is at heightened risk both for diseases associated with that organ and for dying.
Accelerated Organ Aging and Health Risks
According to the study, about 1 in every 5 reasonably healthy adults 50 or older is walking around with at least one organ aging at a strongly accelerated rate.
The silver lining: It may be possible that a simple blood test can tell which, if any, organs in a person’s body are aging rapidly, guiding therapeutic interventions well before clinical symptoms manifest.
“We can estimate the biological age of an organ in an apparently healthy person,” said the study’s senior author, Tony Wyss-Coray, PhD, a professor of neurology and the D. H. Chen Professor II. “That, in turn, predicts a person’s risk for disease related to that organ.”
Hamilton Oh and Jarod Rutledge, graduate students in Wyss-Coray’s lab, are lead authors of the study, which will be published online on December 6 in the journal Nature.
Biological Versus Chronological Age
“Numerous studies have come up with single numbers representing individuals’ biological age — the age implied by a sophisticated array of biomarkers — as opposed to their chronical age, the actual numbers of years that have passed since their birth,” said Wyss-Coray, who is also the director of the Phil and Penny Knight Initiative for Brain Resilience.
The new study went a step further, coming up with distinct numbers for each of 11 key organs, organ systems or tissues: heart, fat, lung, immune system, kidney, liver, muscle, pancreas, brain, vasculature, and intestine.
“When we compared each of these organs’ biological age for each individual with its counterparts among a large group of people without obvious severe diseases, we found that18.4% of those age 50 or older had at least one organ aging significantly more rapidly than the average,” Wyss-Coray said. “And we found that these individuals are at heightened risk for disease in that particular organ in the next 15 years.”
Only about 1 in 60 people in the study had two organs undergoing aging at that fast clip. But, Wyss-Coray said, “They had 6.5 times the mortality risk of somebody without any pronouncedly aged organ.”
Protein Analysis and Algorithm Use
Using commercially available technologies and an algorithm of their own design, the researchers assessed the levels of thousands of proteins in people’s blood, determined that nearly 1,000 of those proteins originated within one or another single organ, and tied aberrant levels of those proteins to corresponding organs’ accelerated aging and susceptibility to disease and mortality.
They started by checking the levels of nearly 5,000 proteins in the blood of just under 1,400 healthy people ages 20 to 90 but mostly in mid- to late stages of life, and flagging all proteins whose genes were four times more highly activated in one organ compared with any other organ. They found nearly 900 such organ-specific proteins, which they whittled down to 858 for purposes of reliability.
To do this, they trained a machine-learning algorithm to guess people’s age based on the levels of those nearly 5,000 proteins. The algorithm tries to pick proteins that best correlate with a trait of interest (in this case, accelerated biological aging in a person or in a particular organ) by asking, one by one, “Does this protein enhance the correlation?”
The scientists verified the algorithm’s DOI: 10.1038/s41586-023-06802-1
Researchers from Washington University; the University of California, San Francisco; the Albert Einstein College of Medicine; and Montefiore Medical Center contributed to the work.
The study was funded by the