A Single Cell Type Ages Faster in 1 in 5 People — and It Tracks Their Disease Risk

Blood does not lie about age — at least not at the cellular level. A study published June 15 in Nature Medicine measured more than 7,000 proteins in plasma samples from 60,542 people and used those molecular signals to build machine-learning clocks capable of estimating the biological age of more than 40 distinct cell types. The findings reveal that aging is far from a uniform process: roughly one in five people is aging unusually fast in a single cell type, and that asymmetry carries measurable consequences for disease risk.

Led by researchers at Stanford University, the team derived cell-type-specific protein signatures from plasma and trained models to infer how quickly neurons, astrocytes, immune cells, skeletal myocytes, respiratory epithelial cells, and dozens of other populations were accumulating biological wear. The work, by Ding, Bot, Chen and colleagues in the lab of Tony Wyss-Coray, was accompanied by a companion paper in the same issue (DOI: 10.1038/s41591-026-04447-x).

What the clocks found

Across the cohort, 20–25% of individuals showed accelerated aging in a single cell type, while 1–3% showed accelerated aging in ten or more cell types simultaneously. The clocks were then used to predict incident disease and mortality over up to 15 years of follow-up — a time window that allowed the team to observe who developed conditions like Alzheimer’s disease and amyotrophic lateral sclerosis (ALS) after the initial blood draw.

The APOE4 genotype produced one of the study’s sharpest signals. Carriers of two APOE4 alleles — a group already known to carry elevated Alzheimer’s risk — showed older astrocytes but paradoxically younger macrophages compared with APOE3 carriers. Critically, among APOE4 homozygotes, those whose astrocytes showed extreme biological aging faced triple the risk of developing incident Alzheimer’s disease over follow-up, while individuals with youthful astrocytes saw a reduced risk. The APOE2 genotype showed inverse associations.

For ALS, the association was even more pronounced. Individuals with extremely aged skeletal myocytes — the muscle cells that motor neurons innervate — had a 12.7-fold higher risk of developing ALS compared with those whose skeletal myocytes appeared biologically youthful.

Limitations

Several caveats apply. This is an observational, prospective cohort study; the associations reported cannot establish causation. The biological-age clocks measure proteins circulating in blood as proxies for what is happening inside specific cell types — an indirect inference, not a direct tissue measurement. Whether intervening on cell-type aging trajectories would alter disease outcomes remains untested.

Nonetheless, the authors report that a composite polycellular aging risk score stratified mortality risk across multiple cohorts and proteomics platforms, suggesting these signatures may be reproducible. The framework, the authors argue, offers a cellular-resolution map of human physiology that could eventually inform risk stratification — though clinical translation remains a future step.