Biomarkers of biological age
Measurement technologies
Health implications
Commercial adoption
Ethical and practical challenges
Conclusion
Chronological age reflects the number of years a person has lived. In contrast, biological age estimates the functional state of the body based on molecular and physiological markers, such as blood tests and Deoxyribonucleic Acid (DNA) methylation. Although often used interchangeably, the distinction between the two is critical.
A person may be 65 years old chronologically but biologically resemble someone much older or younger depending on their health, lifestyle, and underlying diseases. This gap has real-world consequences: recent studies show that biological age is a stronger predictor of health outcomes, including mortality in critically ill patients.
Those who are biologically older than their chronological age face significantly higher risks of death, regardless of their actual age or comorbidities. This difference highlights why healthcare should look beyond birth dates. Recognizing biological age allows for more accurate risk assessment, personalized care, and interventions that could improve longevity and quality of life by targeting the aging process itself.1
This article explores how biological age is measured and explains why it offers a more accurate prediction of health span and disease risk than chronological age.
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Biomarkers of biological age
Biomarkers of biological age provide a more accurate reflection of how the body is aging than simply counting years. Among the most studied are telomere length, epigenetic clocks, and inflammation markers.
Telomeres are protective sequences at the ends of chromosomes that shorten every time a cell divides. When they become too short, the cell either stops dividing or dies, making telomere length a useful indicator of cellular aging. Epigenetic clocks measure changes in DNA methylation at specific sites in the genome.
Clocks such as DNAmAge, Hannum, PhenoAge, and GrimAge can estimate biological age and are associated with health risks and lifespan. In particular, PhenoAge and GrimAge show stronger connections to telomere length and predict age-related decline better than clocks based only on chronological age.2
Inflammation markers, like C-reactive protein and various cytokines, also serve as indicators of biological aging. Chronic low-level inflammation is a common feature of aging and contributes to many diseases.
These biomarkers each reflect different aspects of aging, such as cellular stress, epigenetic changes, and immune system activity. When combined, they provide a fuller picture of an individual’s biological state and may help guide early interventions to promote healthy aging.2,3
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Measurement technologies
Measurement technologies for estimating biological age have advanced significantly, with DNA methylation tests and wearable diagnostics becoming central tools. DNA methylation profiling tracks chemical changes at specific cytosine-phosphate-guanine (CpG) sites in the genome to estimate biological age.
Well-established models like the Horvath and Hannum clocks are widely used for adults. In contrast, a child-specific methylation-based model has recently shown 98% accuracy with an error margin of just 6.7 months.
This model, developed using over 700 blood samples, helps detect early biological changes and assess the impact of environmental factors, such as lead exposure or autism, on aging patterns during childhood.4,5
Wearable diagnostic tools offer a complementary, noninvasive approach. Wireless sensors and smartphone apps can collect real-time mobility metrics such as gait speed, grip strength, and endurance. These metrics are used to assess the frailty phenotype, which correlates strongly with biological aging.
An eHealth system now integrates these data streams into a cloud-based platform to calculate biological age efficiently in older adults. This combined approach of molecular biomarkers and sensor-driven diagnostics enables early, individualized monitoring and intervention across all stages of life.4,5
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Health implications
Cardiovascular disease, cancer, and aging are tightly linked through shared biological mechanisms and risk factors. As individuals age, structural and functional changes in the cardiovascular system- exacerbated by conditions like hypertension, diabetes, and obesity- raise the risk of both heart disease and cancer.
Chronic inflammation, a hallmark of aging often termed "inflammaging," contributes to atherosclerosis and tumor development. Aging also triggers cellular senescence, mitochondrial dysfunction, and telomere shortening, processes that underlie both cardiovascular and cancer pathogenesis.
Notably, cancer therapies can accelerate these aging mechanisms, increasing the risk of cardiovascular toxicity and frailty in older adults. Studies show that cancer survivors, particularly those over age 65, face a significantly higher risk of cardiovascular complications, which are now a leading cause of non-cancer-related death in this group.
These findings highlight the need for integrated care models that assess cardiovascular risk alongside cancer treatment to optimize outcomes and preserve the quality of life in aging populations.6
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Commercial adoption
The commercial adoption of age-tracking and health optimization tools has expanded rapidly in recent years, fueled by rising consumer interest in longevity and personalized wellness. Direct-to-consumer products now offer users accessible, technology-driven insights into their biological age using wearable devices, epigenetic clocks, blood-based biomarker panels, and multi-omics data.
Companies provide DNA methylation-based aging assessments, while apps and services track fitness, sleep, nutrition, and stress metrics to offer personalized aging recommendations. This shift empowers users to monitor age-related changes in real-time and make lifestyle adjustments aimed at slowing their biological aging.7
Moreover, multi-parameter platforms combine molecular data with Artificial Intelligence (AI) algorithms to generate individualized health score scores, making the science of aging more actionable and engaging for the general public.
These tools not only facilitate self-optimization but also promote early detection of health risks, thereby supporting preventive care. As demand grows, the emphasis is shifting from reactive treatment to proactive aging management, making aging a trackable, modifiable process for younger and middle-aged users- not just the elderly.7
Ethical and practical challenges
DNA methylation-based epigenetic clocks offer promising tools for estimating biological age, but they present several ethical and practical challenges.
A key issue is variability- different clocks trained on diverse tissues and populations often produce inconsistent results, limiting their use as standardized biomarkers for aging diagnostics. Over-reliance on a single epigenetic clock as a universal measure of biological age can be misleading, as no clock fully captures the complexity of aging or reliably predicts health span across all individuals.
This becomes especially problematic when such measures are used to guide interventions or assess age-related disease risk. The integration of these clocks into clinical or forensic settings further raises regulatory concerns. Without clear validation and standardized protocols, premature use may lead to misuse, misdiagnosis, or discrimination.8
Additionally, the commercialization of epigenetic age tests without transparency about limitations and error margins can erode public trust. To ensure ethical adoption, researchers and regulators must work together to improve the accuracy, reproducibility, and contextual interpretation of these biomarkers.
Developing population-specific and disease-specific aging diagnostics, along with open-access algorithms, will be crucial in safely leveraging biological age to enhance health span and guide personalized care.8
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Conclusion
The future integration of biological age in personalized medicine and research holds significant potential for advancing healthcare. As epigenetic markers of biological age, such as DNA methylation, continue to gain precision, they could offer a more accurate understanding of an individual's health status compared to chronological age.
This integration could pave the way for personalized interventions targeting individuals at higher biological risk even before clinical symptoms arise. Early identification of age acceleration can help prioritize healthcare resources and tailor prevention strategies.
Additionally, it may enhance predictive models for disease progression, enabling earlier, more precise treatments and ultimately improving outcomes.
This evolution could also optimize healthcare expenditure by focusing on those most likely to require intensive care in the future, ensuring a more efficient allocation of resources.
As research progresses, these biological age insights may transform medical practices, guiding decisions across various specialties, from preventive medicine to chronic disease management.
References
- Ho, K. M., Morgan, D. J., Johnstone, M., & Edibam, C. (2023). Biological age is superior to chronological age in predicting hospital mortality of the critically ill. Internal and emergency medicine, 18(7), 2019-2028. https://doi.org/10.1007/s11739-023-03397-3
- Pearce, E.E., Alsaggaf, R., Katta, S., Dagnall, C., Aubert, G., Hicks, B.D., Spellman, S.R., Savage, S.A., Horvath, S. and Gadalla, S.M (2022). Telomere length and epigenetic clocks as markers of cellular aging: a comparative study. Geroscience, 44(3), 1861-1869.
- Ferrucci, L., & Fabbri, E. (2018). Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nature Reviews Cardiology, 15(9), 505-522.
- Wu, X., Chen, W., Lin, F., Huang, Q., Zhong, J., Gao, H., Song, Y. and Liang, H. (2019). DNA methylation profile is a quantitative measure of biological aging in children. Aging (Albany NY), 11(22), 10031.
- Pierleoni, P., Belli, A., Concetti, R., Palma, L., Pinti, F., Raggiunto, S., Sabbatini, L., Valenti, S. and Monteriù, A.(2021). Biological age estimation using an eHealth system based on wearable sensors. Journal of Ambient Intelligence and Humanized Computing, 12, 4449-4460 https://doi.org/10.1007/s12652-019-01593-8
- Ioffe, D., Bhatia-Patel, S. C., Gandhi, S., Hamad, E. A., & Dotan, E. (2024). Cardiovascular Concerns, Cancer Treatment, and Biological and Chronological Aging in Cancer: JACC Family Series. Cardio Oncology, 6(2), 143-158.
- Silva, N., Rajado, A.T., Esteves, F., Brito, D., Apolónio, J., Roberto, V.P., Binnie, A., Araújo, I., Nóbrega, C., Bragança, J. and Castelo-Branco, P., (2023). Measuring healthy ageing: current and future tools. Biogerontology, 24(6), 845-866.
- Bell, C.G., Lowe, R., Adams, P.D., Baccarelli, A.A., Beck, S., Bell, J.T., Christensen, B.C., Gladyshev, V.N., Heijmans, B.T., Horvath, S. and Ideker, T., 2019. DNA methylation aging clocks: challenges and recommendations. Genome biology, 20, pp.1-24. (2019). DNA methylation aging clocks: challenges and recommendations. Genome biology, 20, 1-24. https://doi.org/10.1186/s13059-019-1824-y
Further Reading