Biological age: definition, measurement methods, and preventive action levers
Biological Age Series — Clinical biomarkers of biological aging (Episode 1)
Chronological age (the number of years since birth) remains a useful reference point, but it does not, on its own, explain the wide diversity of health trajectories. At the same chronological age, meaningful differences can exist across inflammatory, metabolic, hematologic, renal, or hepatic domains. Biological age aims to estimate this physiological aging using measurable indicators associated with clinically meaningful health outcomes. [1]
Medfuture offers the Biological Age Profile, a structured process designed to estimate biological age using research‑recognized longevity models, including DNAm PhenoAge. For a detailed overview of the DNAm PhenoAge approach, you can consult the page DNAm PhenoAge Biological Age Test.
Medfuture Biological Age Profile
A biological age measure is most useful when it is part of a structured prevention approach: understand what science can truly measure, situate a biological trajectory, then track changes over time.
Definition: chronological age and biological age
Chronological age corresponds to time elapsed since birth. It provides a population‑level reference, but does not necessarily reflect an individual’s true biological state.
Biological age aims to estimate physiological aging using measurable indicators: clinical biomarkers (blood tests) and/or molecular signatures such as DNA methylation. Approaches differ, but one idea remains central: capturing inter‑individual differences in aging beyond chronological age. [1]
Why measure biological age for prevention?
In prevention, the goal is not only to extend lifespan, but also to preserve functional health over time. Ideally, a meaningful biological age measure should:
- reflect multiple biological systems (inflammation, metabolism, renal/hepatic function, hematology);
- be associated with clinically relevant outcomes (morbidity, mortality, functional decline);
- enable longitudinal tracking.
This logic explains scientific interest in biomarker‑based models and certain epigenetic clocks, developed and validated in large cohorts. [1]
Measurement methods: clinical biomarkers and epigenetics
Models based on clinical biomarkers
These models combine common laboratory parameters (blood analyses) to produce a statistical score associated with health outcomes. A key clinical advantage is the ability to relate the score to identifiable biological systems.
Epigenetic clocks based on DNA methylation
DNA methylation changes with age and biological state. So‑called “epigenetic clocks” use methylation profiles (CpG sites) to estimate an epigenetic age. Some clocks primarily predict chronological age; others are calibrated to better reflect aging‑related outcomes.
PhenoAge: a biological age built from a blood test
Phenotypic Age (PhenoAge) is a measure expressed in “years” that combines chronological age and nine blood biomarkers selected for their contribution to predicting mortality risk. [2]
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Biomarkers included in the PhenoAge model
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In a study published in PLOS Medicine, a one‑year increase in PhenoAge (after adjustment for chronological age) was associated with approximately a 9% increase in all‑cause mortality risk (hazard ratio ~1.09). [2] This type of result illustrates an important principle: at the same chronological age, some biological signatures correspond to a less favorable risk trajectory.
This series is based on research‑recognized longevity models. The Medfuture Biological Age Profile applies these methods within a structured approach.
Epigenetic clocks: principles and limitations
Foundational epigenetic clocks demonstrated that DNA methylation can estimate chronological age with high accuracy. Two frequently cited landmark papers are:
- Horvath (2013): multi‑tissue clock based on 353 CpG sites. [3]
- Hannum (2013): blood-based model based on 71 CpG sites. [4]
However, predicting chronological age is not equivalent to capturing aging‑related risk. This is why some newer clocks were calibrated to better reflect clinically relevant outcomes.
DNAm PhenoAge: an epigenetic clock calibrated on clinical biomarkers
DNAm PhenoAge directly links clinical biomarkers and epigenetics. The model is built in two steps: (1) a phenotypic age based on biomarkers (PhenoAge), then (2) a DNA methylation model trained to predict this phenotypic age. [5]
DNAm PhenoAge is based on 513 CpG sites. [5] In a pooled analysis across several cohorts, a one‑year increase in DNAm PhenoAge was associated with approximately a 4.5% increase in all‑cause mortality risk, independently of chronological age (HR ~1.045). [5]
These findings support the idea that “epigenetic age acceleration,” as captured by DNAm PhenoAge, is associated with a less favorable risk trajectory in large cohorts—without constituting a medical diagnosis.
Biological age and lifestyle: what the data show
Biological age models such as PhenoAge and DNAm PhenoAge describe a biological snapshot at a given time. Across studied cohorts, a more favorable biological age is generally observed when aging‑related biological parameters fall into a profile consistent with overall good health. [2][5]
Conversely, a higher biological age is more frequently associated with the accumulation of biological risk factors, including chronic inflammation, metabolic imbalances, or certain hematologic alterations. [2][5]
In prevention, the main value of biological age lies in its ability to objectify a multi‑system profile and support longitudinal monitoring of health factors—rather than focusing on a single number.
Clinical interpretation: using a biological age score in a meaningful way
What a score can provide
- a multi‑system summary signal consistent with biological risk factors;
- a prioritization support (inflammation, metabolism, hematology, renal/hepatic function);
- a framework to track a trajectory over time, especially when interpreted alongside its component biomarkers. [1][2][5]
What a score does not replace
- a medical diagnosis;
- individualized interpretation considering symptoms, medical history, and treatments;
- clinical judgment when a result requires follow‑up.
Informational note
This article is provided for educational purposes and does not replace a medical consultation. Laboratory results must be interpreted within a complete clinical context.
How often should you measure biological age?
The value of a biological age measure increases when it is part of longitudinal monitoring rather than a one‑time reading. In prevention, an annual cadence is commonly used to observe a trajectory; the optimal interval nonetheless depends on context and follow‑up goals.
Biological Age Series: biomarkers covered in upcoming articles
This series will analyze the biomarkers included in the PhenoAge model using a consistent structure: definition, plausible biological mechanisms, documented associations, common causes of variation, and realistic prevention levers.
- C‑reactive protein (CRP)
- Albumin
- Creatinine
- Glucose
- Lymphocyte percentage
- Alkaline phosphatase
- Mean corpuscular volume (MCV)
- White blood cell count (WBC)
- Red cell distribution width (RDW)
FAQ — Frequently asked questions about biological age
What is the difference between chronological age and biological age?
Chronological age measures time since birth. Biological age aims to estimate physiological aging using biomarkers and/or molecular signatures, better reflecting individual variability in aging. [1]
Is biological age reliable?
Reliability depends on the method used. Models such as PhenoAge and DNAm PhenoAge were developed and validated in large cohorts, with robust associations to mortality and health indicators. [2][5]
Can you improve your biological age?
Observational studies show that a more favorable biological age (or score) is more often observed in individuals with healthier lifestyles and a biomarker profile compatible with good overall health (for example, lower inflammation and better metabolic balance). Conversely, less favorable scores are more often observed in the presence of biological risk factors such as chronic inflammation or certain metabolic and hematologic imbalances. [1][5]
However, these associations do not, by themselves, prove causality. The most relevant prevention approach remains structured: measure, act on modifiable risk factors, then re‑measure over time. [1][5]
Why analyze individual biomarkers if the score already combines them?
A composite score becomes more useful when interpreted in light of its components. Understanding the biological systems involved helps prioritize coherent prevention actions. [2]
Scientific references
- Jylhävä J, Pedersen NL, Hägg S. Biological Age Predictors. EBioMedicine. 2017;21:29–36. doi:10.1016/j.ebiom.2017.03.046.
- Liu Z, Kuo P‑L, Horvath S, Crimmins E, Ferrucci L, Levine ME. A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study. PLOS Medicine. 2018;15(12):e1002718. doi:10.1371/journal.pmed.1002718.
- Horvath S. DNA methylation age of human tissues and cell types. Genome Biology. 2013;14:R115. doi:10.1186/gb-2013-14-10-r115.
- Hannum G, Guinney J, Zhao L, et al. Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates. Molecular Cell. 2013;49(2):359–367. doi:10.1016/j.molcel.2012.10.016.
- Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573–591. doi:10.18632/aging.101414.