New Blood Test May Reveal The True Age of Your Organs

Not all parts of the body age at the same rate. While some organs remain young for decades, others may show signs of wear and tear much sooner than expected. A new study shows that a simple blood test can identify which cells and organs are aging most rapidly, helping to predict the risk of diseases such as Alzheimer's, amyotrophic lateral sclerosis, and lung cancer many years before the first symptoms appear.

We all know our chronological age, the one counted in years since birth. However, this does not always correspond to the biological age of the organism. While two people may be exactly 60 years old, one may have organs functioning like those of someone much younger, while another may already show signs of accelerated aging.

This difference helps explain why some people remain healthy for decades, while others develop serious diseases relatively early. In recent years, scientists have come to believe that understanding the rate at which each part of the body ages may be one of the keys to preventing diseases before they even appear.

It was precisely this idea that motivated one of the largest studies ever conducted on human aging. Instead of analyzing just one specific organ, the researchers decided to investigate virtually the entire body using only a blood sample. To do this, they gathered information from more than 60,000 people from three large, independent studies. In each sample, more than seven thousand different proteins were analyzed.

Proteins function as tiny messengers produced by cells and released into the bloodstream. Each cell type produces a characteristic set of these molecules, allowing scientists to indirectly identify the health status and aging of different tissues without the need for biopsies or invasive procedures.

After gathering this vast amount of information, researchers used artificial intelligence to search for patterns that are almost impossible to identify manually. The computer programs learned how proteins produced by more than forty different types of cells throughout the body typically behave.

These included cells from the brain, immune system, muscles, skin, lungs, hormone glands, and various other organs. From these patterns, the system was able to estimate the biological age of each cell group separately.

Instead of simply saying "this person is biologically 65 years old," the method could indicate, for example, that neurons exhibited characteristics of an older person, while muscle cells remained relatively young.

The results showed that the aging of the organism occurs much less uniformly than previously thought. About a quarter of people showed accelerated aging in only one type of cell, while a small percentage accumulated signs of premature aging in many tissues at the same time.

This difference had important consequences for health. People whose brain cells, especially astrocytes—cells that help protect and nourish neurons—appeared biologically older had a higher risk of developing Alzheimer's disease over the following years.

In individuals who already carried a genetic variant known to increase this risk, called APOE4, the accelerated aging of these cells practically tripled the likelihood of developing the disease. In contrast, those who had biologically younger astrocytes maintained a much lower risk, even possessing this genetic predisposition.

Other findings were equally noteworthy. When skeletal muscle cells exhibited very accelerated aging, the risk of developing amyotrophic lateral sclerosis (ALS), a disease that causes progressive loss of muscle strength, was more than twelve times higher than among people with biologically young muscle cells.

Among smokers, those whose airway lining cells showed signs of advanced aging had a significantly higher risk of developing lung cancer than smokers whose cells remained biologically younger.

These results show that smoking, by itself, doesn't tell the whole story. How each organism responds to the damage caused by cigarettes can also strongly influence who will develop the disease.

In addition to analyzing cells individually, the researchers created an index capable of bringing together all this information into a single measure of the organism's aging. People who accumulated signs of accelerated aging in various cell types were more likely to develop diseases and also had a higher risk of dying during the fifteen-year follow-up of the study.

On the other hand, individuals who maintained biologically young immune system and brain cells showed greater protection and survival. Although this test is not yet available in clinical practice, the results suggest a profound change in how medicine may assess aging in the coming decades.

Instead of waiting for symptoms to appear, doctors will be able to identify which organs are aging most rapidly, guide lifestyle changes, monitor the response to treatments, and, in the future, personalize interventions to slow aging before it turns into disease.

Researcher Tony Wyss-Coray, responsible for the study. Credit: Stanford Medicine

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Plasma proteomic signatures of cellular aging predict human disease

Daisy Yi Ding, Veronica Augustina Bot, Kenneth L. Chen, James W. Groves, Róbert Pálovics, Daisuke Masuda, Amelia Farinas, Hamilton Se-Hwee Oh, Viktoria Wagner, Nannan Lu, The Global Neurodegeneration Proteomics Consortium (GNPC), Carlos Cruchaga, Alina Isakova, Jonathan M. Schott, and Tony Wyss-Coray

Nature Medicine.  15 June 2026. 32, pages 2060–2072 (2026) 

DOI: 10.1038/s41591-026-04446-y

Abstract: 

Aging is asynchronous across cells and organs. Here we tested whether plasma proteomics can be used to analyze cell type-specific aging. From analyses of over 7,000 plasma proteins measured in 60,542 individuals, we developed machine learning models to estimate the biological age of over 40 cell types spanning neuronal, immune, glial, endocrine, epithelial and musculoskeletal origins. We observed that 20–25% of individuals exhibited accelerated aging in a single cell type and 1–3% in 10 or more cell types. Cellular aging signatures were associated with disease status and predicted incident disease and mortality over 15 years of follow-up. Individuals with the APOE4 genotype showed older astrocytes but younger macrophages compared to APOE3 carriers, whereas the APOE2 genotype had inverse associations. Moreover, extreme astrocyte aging tripled the risk of incident Alzheimer’s Disease in individuals with two APOE4 alleles, while youthful astrocytes reduced risk. Individuals with extremely aged compared to youthful skeletal myocytes exhibited a 12.7-fold higher risk of developing amyotrophic lateral sclerosis. In individuals who smoked, extreme respiratory epithelial cell aging was associated with a 58% higher lung cancer risk compared to smoking alone. Specific cellular vulnerabilities and cumulative cellular aging burden influenced survival, with youthful immune and neuronal cell types conferring protective effects. Finally, we developed a polycellular aging risk score that stratified mortality risk across cohorts and proteomics platforms. These findings establish a framework for quantifying human physiology at cellular resolution, revealing heterogeneous aging trajectories and their impact on disease susceptibility and resilience.