Blood Test Can Reveal if You Are at Risk From Organs Aging Prematurely

Scientists have figured out a way to test if your organs are at risk of giving out, new research reveals.

The organs in our bodies age at differing rates, with certain organ systems falling apart sooner than others. About 20 percent of otherwise healthy people aged 50 or older have at least one organ aging at an accelerated rate, according to a new paper in the journal Nature.

Now, a blood test may be able to reveal if you are one of the unlucky few and, if so, which organ is causing the problem.

"We can estimate the biological age of an organ in an apparently healthy person," senior study author Tony Wyss-Coray, a professor of neurology at Stanford University, said in a statement. "That, in turn, predicts a person's risk for disease related to that organ."

The researchers studied 5,678 people, looking into how their organs aged, and found that some people's organs age at very different rates.

"We do not know but research in animal models has shown that organs in the same animal can have different aging trajectories and ages," Wyss-Coray told Newsweek.

"Very recent studies in humans integrating imaging and functional data as well as blood chemistry suggested this might be true in humans also. Our method uses a simple molecular approach to show that organ ages differ within a person. We believe a combination of genetic, environmental and lifestyle factors determine which organ may show accelerated aging and experience some sort of a breaking point that may eventually lead to disease."

They also found that those whose organs are aging rapidly, compared with others in their age group, are more at risk of diseases associated with that organ and, therefore, death.

"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 that 18.4 percent 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."

The researchers found that around 1 in 60 people had two or more organs that were aging at an accelerated rate, and "they had 6.5 times the mortality risk of somebody without any pronouncedly aged organ," Wyss-Coray said.

The researchers then figured out a way to test if someone is suffering from an organ system that is aging faster and pinpoint which organs are at fault. Using a machine-learning algorithm, they investigated around 5,000 proteins in the blood of people aged between 20 and 90.

They found that roughly 1,000 of these proteins were associated with a single organ system, with levels of that protein representing the degree of aging that the organ was experiencing.

"Much like our brains have been trained to guess a person's age based on the number of wrinkles and other features in a face the machine learning algorithm starts by determining which protein (that is the concentration of that protein) by itself correlates best with the actual age of a person," Wyss-Coray said.

"It does that with hundreds or thousands of samples that we use to train the algorithm. Once it picks the best protein for a given organ it searches for the next best protein that makes the prediction of age even better and so on until it can't find any additional proteins that improve the prediction of age across all the samples in the training set.

"We then use this trained algorithm and ask it to estimate/test the age of a new person. Sometimes it will predict the exact age of that person/organ and sometimes it will predict the age to be a bit younger or older. This deviation from the actual, chronological age of the person is what we call "age-gap". We find this age-gap can predict the risk for organ specific functional decline and diseases and even death," Wyss-Coray said.

Therefore, by measuring the levels of these proteins in the blood, the researchers were able to tell how aged each of the 11 organ systems that they tested for was—including heart, fat, lung, immune system, kidney, liver, muscle, pancreas, brain, vasculature and intestines. The algorithm could also guess how old the person was based on the 5,000 proteins in the blood, finding that the organs within a person's body often aged at very different rates.

The researchers then developed an organ "age gap" representing the difference between an organ's true biological age and its estimated age based on the algorithm's predictions based on the proteins in the blood.

They discovered that in 10 of the 11 organs (all but the intestines), a larger age gap was associated with an increased risk of death over the next 15 years, both relating to the organ in question and all other reasons. Organs defined as having "accelerated aging" had a 15 to 50 percent higher mortality risk over the next 15 years.

In particular, those with faster-aging hearts were 2.5 times more likely to experience heart failure, and those with faster-aging brains were 1.8 times more likely to experience cognitive decline, one of the major precursors to Alzheimer's disease and other dementias.

"Once applied and tested in 10s and 100s of thousands of people—i.e. validated broadly —organ age measurements could help monitor health and predict future disease; organ age could thus provide a basis for true health care and away from treating people when they are sick (aka "sick care"). Organ age readouts could help monitor lifestyle and therapeutic interventions and allow an individual and their physician to monitor benefits of e.g. exercise, diet or medications," Wyss-Coray said.

"Detecting organ age across large number of diverse individuals could help identify new drug targets and lead to new medications that can maintain organ health as long as possible."

This discovery could help doctors detect organs aging at an accelerated rate and therefore treat problems before they arise—or even find new drug targets—the authors said.

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Update 12/7/2023 11:39 ET: This article was updated to include comment from Wyss-Coray.