Blood proteins reveal which aging cells may raise disease risk
A study published in Nature Medicine found that estimating cell-type-specific aging signatures from blood-based plasma proteins can help predict human disease risk. By analyzing over 7,000 proteins in more than 60,000 individuals, researchers identified that accelerated aging in specific cells correlates with higher risks for Alzheimer’s, ALS, and lung cancer.
How does plasma protein analysis predict disease risk?
Researchers used machine learning models to analyze plasma samples from 60,542 individuals. They linked these proteins to specific cell types using the Human Protein Atlas to estimate the biological age of over 40 cell types across the immune, endocrine, musculoskeletal, and nervous systems.

The team utilized two platforms for verification: SomaScan, which measured 7,289 proteins, and Olink, which assessed 2,923 markers. These models were tested across the United Kingdom Biobank (44,458 participants), the Global Neurodegeneration Proteomics Consortium (14,281 participants), and the 1946 National Survey of Health and Development (1,803 participants).
Which cell types correlate with specific illnesses?
Accelerated aging in astrocytes increased the risk of Alzheimer’s disease (AD) for people with the APOE4 genotype. Specifically, participants with two APOE4 alleles and extremely aged astrocytes faced a tripled risk of incident AD.
The research also linked AD to accelerated aging in pancreatic cells, intestinal lining cells, and brain cells providing nerve support. Oligodendrocyte precursor cells and inhibitory neurons showed the strongest associations with cognitive decline and dementia severity scores.
In respiratory health, extreme aging in alveolar type 2 cells and the respiratory epithelial lineage increased lung cancer risk by 58% among current smokers compared to smoking alone.
How does cellular aging affect survival outcomes?
Cellular aging signatures predicted mortality risks over a 15-year follow-up period. The study found that young nerve and immune cells provided a protective effect that improved survival outcomes.
Survival rates varied sharply based on the number of aged cell types. Individuals with normal cellular aging had a survival rate of approximately 90% over 15 years, while those with more than 20 extremely aged cell types saw survival rates drop to about 34%.
What happens next for protein profiling?
The findings suggest that plasma proteomic signatures could help scientists refine risk stratification and identify high-risk groups for closer monitoring. If validated in more diverse populations, clinicians may eventually incorporate these tests into standard care.
Future strategies that prevent or halt cellular aging could potentially lower the overall disease burden and improve longevity. However, researchers noted that current models rely on Caucasian and older populations, meaning results require further validation in broader groups.
Frequently Asked Questions
What is the polycellular aging risk score (PARS)?
PARS is a score developed by the researchers to classify mortality risk based on cellular aging determined through proteomic platforms and datasets.
How does the APOE4 genotype affect Alzheimer’s risk in this study?
People with the APOE4 genotype exhibited older astrocytes. Those with two APOE4 alleles and extremely aged astrocytes had three times the risk of developing Alzheimer’s disease.
Why is plasma protein analysis preferred over other cellular clocks?
While epigenetic and transcriptomic clocks can measure cellular aging, they often require animal experiments, laboratory samples, or invasive tissue biopsies.
Do you believe blood-based aging tests should become part of annual physical exams?