A research team at the Stanford Medicine-based Wu Tsai Neurosciences Institute has developed a blood-based method that can determine the biological age of more than 40 different cell types throughout the body, providing a new way to assess disease risk and longevity years before symptoms emerge. The method, published in Nature Medicine, combines plasma proteomics with machine learning to develop estimates of the biological age of cell types including neuronal, immune, glial, endocrine, epithelial and musculoskeletal systems.
“With this indicator, we can assess the age of an organ today and predict the odds of your getting a disease associated with that organ 10 years later,” said senior author Tony Wyss-Coray, PhD, professor of neurology and neurological sciences and director of the Knight Initiative for Brain Resilience at the Wu Tsai Neurosciences Institute.
Developing this new cellular aging estimate was driven by the understanding that aging is the largest driver of a range of chronic diseases.
“Over 50% of the global disease burden can be attributed to aging,” the researchers wrote noting that while aging increases the risk of neurodegenerative disease, cancer and other chronic illnesses, “aging itself remains poorly understood, and quantifying its biology is therefore an important priority for improving prevention and treatment.”
This new model builds on the lab’s previous work in which the team developed a blood test capable of estimating the biological age of 11 organs and organ systems: the brain, muscle, heart, lung, arteries, liver, kidneys, pancreas, immune system, intestine and fat. In that study, published last July, the investigators analyzed blood samples from 44,498 participants in the UK Biobank and measured nearly 3,000 proteins circulating in the bloodstream. By identifying proteins associated with specific organs and comparing individual protein signatures with age-adjusted population averages, the researchers created algorithms that assigned biological ages to each organ.
Those organ-specific aging profiles revealed that organs age at different rates within the same person. Approximately one-third of participants had at least one organ classified as “extremely aged” or “extremely youthful,” while one in four had multiple organs falling into those categories. The biological age of a person’s organs was strongly associated with future disease risk. For instance, people with an aged heart were more likely to develop atrial fibrillation or heart failure, while aged lungs predicted a greater risk of chronic obstructive pulmonary disease. An aged brain was linked to a substantially higher risk of Alzheimer’s disease.
“The brain is the gatekeeper of longevity,” said Wyss-Coray. “If you’ve got an old brain, you have an increased likelihood of mortality. If you’ve got a young brain, you’re probably going to live longer.”
Participants with extremely aged brains experienced a 182% increase in mortality risk over roughly 15 years of follow-up in the study, while those with extremely youthful brains had a 40% reduction in mortality risk.
This new research goes beyond organ-level measurements to evaluate aging at a cellular level. For this research, the team analyzed more than 7,000 plasma proteins from 60,542 people across three independent cohorts. Using protein signatures mapped to their likely cellular origins, they constructed machine-learning models capable of estimating the biological age of more than 40 cell types.
The findings showed substantial variation in cellular aging patterns. Between 20% and 25% of people showed accelerated aging in a single cell type, while 1% to 3% showed accelerated aging in 10 or more cell types. These cellular aging signatures were associated with disease status and predicted disease development and mortality over a 15-year follow-up period.
One important finding centered on the risk of developing Alzheimer’s disease. The data showed that people carrying two copies of the APOE4 genetic variant, a major risk factor for Alzheimer’s disease, tended to have older astrocytes in the brain. Extreme astrocyte aging tripled the risk of developing Alzheimer’s disease among APOE4 homozygotes, whereas youthful astrocytes appeared to reduce that risk. “Youthful astrocytes seem to powerfully attenuate the detrimental effects of APOE4,” the researchers wrote.
The researchers also found strong links between cellular aging and amyotrophic lateral sclerosis (ALS). Individuals with extremely aged skeletal muscle cells had a 12.7-fold higher risk of developing ALS than those with youthful muscle-cell profiles. According to the researchers, this elevated risk could be detected more than three years before a clinical diagnosis.
Other findings suggest potential applications in cancer prevention and metabolic disease monitoring. The researchers reported that extreme aging of respiratory epithelial cells identified smokers at higher risk of lung cancer, while aging of myeloid immune cells was associated with elevated risk of developing type 2 diabetes.
“Our findings suggest that specific cellular vulnerabilities and cumulative aging burden influence survival,” the researchers wrote. Skeletal muscle-cell aging showed the strongest association with mortality, followed by neurons, fibroblasts, alveolar type 2 lung cells and myeloid lineage immune cells.
The investigators believe these new findings could begin to shift medicine toward earlier intervention. “This is, ideally, the future of medicine,” Wyss-Coray said. “Today, you go to the doctor because something aches, and they take a look to see what’s broken. We’re trying to shift from sick care to health care and intervene before people get organ-specific disease.”
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