A large international study has found that the cells in the human body do not age at a uniform rate, and that a single blood test can now estimate the biological age of more than 40 distinct cell types — a finding that researchers say could allow certain diseases to be predicted years before symptoms appear. The study was published in the journal Nature Medicine on June 15.
The research, led by scientists at Stanford University working with the Global Neurodegeneration Proteomics Consortium and University College London, drew on more than 7,000 blood proteins measured in 60,542 individuals across three independent populations, including the UK Biobank and Britain’s 1946 National Survey of Health and Development, regarded as the longest continuously followed birth cohort in the world.
Using gene expression data from the Human Protein Atlas, the researchers identified blood proteins that are disproportionately released by particular cell types, ranging from astrocytes and neurons in the brain to skeletal muscle cells and the epithelial cells of the respiratory tract. Machine learning models were then trained to estimate, from the abundance of these proteins, the biological age of each cell type independently. A cell type was classified as ageing faster than expected, or “extremely”, if its estimated age substantially exceeded a person’s actual age, and as ageing youthfully if it fell well below it.
The findings indicated that nearly a quarter of healthy individuals studied showed accelerated ageing confined to a single cell type, while a smaller proportion, between 1% and 3%, showed accelerated ageing spread across ten or more cell types at once. The researchers also found that lifestyle had a measurable bearing on these patterns, with individuals who smoked and were obese showing widespread cellular acceleration, while those with healthier habits, including regular exercise and adequate sleep, showed comparatively younger cellular profiles overall.
A notable finding concerned the APOE gene, long known to influence Alzheimer’s disease risk. Carriers of the APOE4 variant, associated with higher risk of the disease, were found to have older-than-expected astrocytes but younger-than-expected macrophages, a class of immune cell, while carriers of the protective APOE2 variant displayed the opposite pattern. The authors suggested this may point to an evolutionary trade-off between immune defence and brain ageing.
Following participants for 15 years, the researchers reported that astrocyte ageing was among the strongest predictors of incident Alzheimer’s disease identified in the study, comparable in strength to APOE4 carrier status and stronger than either polygenic risk scores or chronological age. Among individuals carrying two copies of APOE4, those whose astrocytes showed extreme ageing were found to have nearly three times the risk of developing the disease compared with those of the same genotype whose astrocytes aged normally, while almost none of the APOE4 homozygotes with youthful astrocytes went on to develop Alzheimer’s during the study period.
For amyotrophic lateral sclerosis, the strongest association was found not in nerve cells but in skeletal muscle: individuals with extremely aged muscle cells were found to be nearly 13 times more likely to develop the disease over the following 15 years than those with youthful muscle-cell ageing. Among smokers, those who additionally showed accelerated ageing in respiratory epithelial cells had a 58% higher risk of lung cancer than smokers without such acceleration, suggesting the measure added predictive value beyond smoking history alone.
The study further found that overall survival was closely tied to the number of cell types showing accelerated ageing. Individuals with no extremely aged cell types had an estimated 90% chance of surviving the 15-year follow-up period, compared with around 34% among those with more than 20 such cell types. Based on this pattern, the researchers developed a composite measure, termed the polycellular ageing risk score, which they said reliably stratified mortality risk across different cohorts and proteomic measurement methods.
The authors cautioned that the cell-type classifications used in the study were limited by the scope of existing reference databases, and that the populations examined were predominantly older adults of European ancestry, making further validation in younger and more diverse populations necessary before any clinical application could be considered. They concluded that the findings nonetheless establish a new framework for studying human ageing at the level of individual cell types, with implications for the early detection of age-related disease.
-Rashmi Kumari
