Reviewed by Lexie CornerJun 10 2025
A new blood-based proteomic signature that can predict healthspan (the number of years a person is likely to live in good health) was published in the Proceedings of the National Academy of Sciences.
Dr. Chia-Ling Kuo et al. demonstrate the Healthspan Proteomic Score (HPS), derived from chronological age and the expression levels of 86 proteins, is a strong predictor of disease and mortality risk. Lower HPS values are associated with higher risks of disease and mortality. Pictured is a “biological clock” representation hinting that proteins inform the HPS, which can inform our healthspan. Here, the clock’s hand is a 3D rendering of growth/differentiation factor 15 (GDF15), a protein predictor of healthspan. Image credit: Bernard L. Cook III, PhD, who conceptualized, illustrated, and composed the final image, and Illustrate, the software used to render GDF15 (Goodsell DS, Autin L, Olson AJ (2019) Illustrate: Software for Biomolecular Illustration. Structure 27, 1716-1720).
The Healthspan Proteomic Score (HPS) was developed by researchers at the UConn School of Medicine, working with colleagues at the University of Helsinki and the University of Exeter (UK). It serves as a tool for understanding biological aging and assessing the risk of chronic diseases.
The team analyzed proteomic data from over 53,000 participants in the UK Biobank. They identified a group of proteins that, taken together, reflect a person's biological health.
Lower HPS values, based on the levels of these proteins, were strongly associated with higher risks of death and age-related diseases. These included heart failure, diabetes, dementia, and stroke. This association held even after adjusting for age and other health indicators.
The score was also tested in a separate group from Finland. It outperformed other current methods for measuring biological aging.
Our findings underscore the importance of shifting the focus from lifespan to healthspan. The HPS captures early biological changes in the body and may help inform interventions that promote healthier aging.
Dr. Chia-Ling Kuo, Study Lead Author and Associate Professor, Public Health Sciences, School of Medicine, University of Connecticut
Kuo is also affiliated with The Cato T. Laurencin Institute for Regenerative Engineering.
Dr. Breno S. Diniz, the Senior Author and Associate Professor of Psychiatry at UConn School of Medicine and UConn Center on Aging, added, “By integrating proteomic signals of biological aging, HPS offers a promising tool for identifying individuals at risk for age-related diseases and for guiding personalized prevention strategies.”
While aging is inevitable, researchers are finding that the rate and pattern of aging can vary widely between individuals. The NIA-funded UConn Older Americans Independence Pepper Center focuses on this variability through its theme of Precision Gerontology. Its goal is to improve independence in older adults by studying these differences.
This research adds to evidence that aging can be measured and possibly influenced. The HPS may serve as a useful outcome measure in clinical trials testing anti-aging treatments and strategies aimed at extending healthy lifespan.
The study marks progress in predicting how people age and in designing more targeted interventions. The team is now testing HPS in clinical trial settings. Although it is not yet ready for general use, the findings lay the groundwork for future tools that could help individuals and healthcare providers track and support healthy aging.
Source:
Journal reference:
Kuo, C.-L., et al. (2025) A proteomic signature of healthspan. Proceedings of the National Academy of Sciences. doi.org/10.1073/pnas.2414086122.
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