June 16, 2026 | Researchers at Stanford University have developed a blood test that reveals the functional age of your organs, predicting the odds of specific organ diseases within ten years, and opening new diagnostic avenues.
“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 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 at Stanford University.
Last year, Wyss-Coray and his lab published a paper in Nature Medicine (DOI: 10.1038/s41591-025-03798-1) outlining how proteins gathered through a blood draw could predict organ health for 11 separate organ systems: brain, muscle, heart, lung, arteries, liver, kidneys, pancreas, immune system, intestine and fat.
In a study published yesterday, also in Nature Medicine (DOI: 10.1038/s41591-026-04446-y), Wyss-Coray and his colleagues showed that not only our organs, but individual cell types within those organs, can be classified by biological rather than chronological age, revealing even more precise data enabling potentially superior diagnostic approaches.
Age According to Protein Signature
The scientists studied 44,498 randomly selected participants, ages 40 to 70, drawn from the UK Biobank. These participants were monitored for up to 17 years for changes in their health status. They used the SomaScan platform from SomaLogic and Olink Proteomics platform to measure the amounts of nearly 3,000 proteins in each participant’s blood. About 15% of these proteins can be traced to single-organ origins, and many of the others to multiple-organ generation.
The researchers fed everybody’s blood-borne protein levels into an algorithm that compared the individual’s blood protein signature to the overall average for people of that age and assigned a biological age to each of the 11 distinct organs or organ systems assessed for each subject. These protein signatures serve as proxies for individual organs’ relative biological conditions. A greater than 1.5 standard deviation from the average put a person’s organ in the “extremely aged” or “extremely youthful” category.
The algorithm also predicted people’s future health, organ by organ, based on their current organs’ biological age. Wyss-Coray and his colleagues checked for associations between extremely aged organs and any of 15 different disorders including Alzheimer’s and Parkinson’s diseases, chronic liver or kidney disease, Type 2 diabetes, two different heart conditions and two different lung diseases, rheumatoid arthritis and osteoarthritis, and more.
Risks for several of those diseases were affected by numerous different organs’ biological age, but the strongest associations were between an individual’s biologically aged organ and the chance that this individual would develop a disease associated with that organ. For example, having an extremely aged heart predicted higher risk of atrial fibrillation or heart failure; having aged lungs predicted heightened chronic obstructive pulmonary disease (COPD) risk; and having an old brain predicted higher risk for Alzheimer’s disease.
Aside from just brain diseases, brain age was the best single predictor of overall mortality.
“The brain is the gatekeeper of longevity,” Wyss-Coray said. “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.”
Having an extremely aged brain increased subjects’ risk of dying by 182% over a roughly 15-year period, while individuals with extremely youthful brains had an overall 40% reduction in their risk of dying over the same duration.
Not Organs but Cell Types
The paper published this week expanded these findings to not just organ system but cell type. The researchers used single-cell transcriptomic data in the Human Protein Atlas to link 60 cell types to their corresponding plasma proteins and classified genes as cell-type specific if they were expressed at least twofold higher in one cell type compared to any other.
Then they analyzed proteins measured in blood from 60,542 individuals from the UK Biobank, Global Neurodegeneration Proteomics Consortium, and the 1946 National Survey of Health and Development. They estimated the biological age of over 40 cell types spanning neuronal, immune, glial, endocrine, epithelial and musculoskeletal cells.
What they found was that cell types age at different rates, and their aging trajectories can be captured through variations in plasma protein abundance. The authors wrote that 20%–25% of individuals exhibited accelerated aging in a single cell type and 1%–3% in 10 or more cell types. “Certain cell populations—such as excitatory neurons, Schwann cells, NK cells, macrophages, skeletal myocytes and fibroblasts—emerged as potential ‘aging hubs’, showing correlations with multiple other cell types,” the authors wrote. “In contrast, epithelial cell types tended to exhibit more isolated or weakly correlated age gap profiles.”
Across cell types, the authors found that cells with accelerate aging were linked to diseases.
For example, individuals with extremely aged compared to youthful skeletal myocytes exhibited a 12.7-fold higher risk of developing amyotrophic lateral sclerosis. For lung cancer, extreme aging in alveolar type 2 cells and the broader respiratory epithelial lineage was most prognostic. For chronic obstructive pulmonary disease (COPD), extreme aging in alveolar type 2 cells and the broader respiratory epithelial lineage showed the most prognostic power. For incident heart failure, extreme aging in muscle cells and fibroblasts was most prognostic.
Alzheimer’s Disease was associated with accelerated aging across a wide range of cell types, but astrocyte aging was a particularly powerful biomarker that stratified AD risk independently of and synergistically with APOE genotype. “Maintaining youthful astrocyte function may be a potential therapeutic strategy to mitigate disease burden, especially in genetically predisposed individuals,” the authors posited.
“The noninvasive blood-based approach presented in this study enables biological aging to be characterized at cellular resolution, providing a new framework for studying aging heterogeneity and potential therapeutically relevant disease mechanisms,” the authors wrote in their discussion. “Future work should explore the sequential progression and genetic basis of cellular aging. Moreover, a complimentary analysis of lifestyle factors and superager cohorts could identify proteomic signatures underlying exceptional longevity, resilience and rejuvenation at the cellular level.”
Although the analytical tool is available only for research purposes now, Wyss-Coray has plans to commercialize it. He is a co-founder and scientific officer of Teal Omics and Vero Bioscience, two companies to whom Stanford University’s Office of Technology Licensing has licensed technology developed in this and related research for commercializing, respectively, screens for new drug targets and a consumer product.
The test could be available in the next two to three years, Wyss-Coray said in a press release. “The cost will come down as we focus on fewer key organs, such as the brain, heart and immune system, to get more resolution and stronger links to specific diseases.”