PhenoAge vs GrimAge
Clinical PhenoAge uses routine blood tests. GrimAge uses DNA methylation. Both express a risk-related profile in age units, but they require different data and cannot substitute for one another.
| PhenoAge (Levine Phenotypic Age) | GrimAge | |
|---|---|---|
| Method type | blood-based | epigenetic |
| Published | 2018 | 2019 |
| Sample type | blood (serum/plasma, routine CBC + chemistry panel) | blood (DNA methylation, Illumina array) |
| Open or commercial | open | both |
| Formula publicly available | Yes | No |
What you need
Clinical PhenoAge combines chronological age with nine markers: albumin, creatinine, glucose, CRP, lymphocyte percentage, MCV, RDW, alkaline phosphatase and white blood cell count. It can be calculated from a suitable routine blood panel with the correct units. Calculate clinical PhenoAge.
GrimAge requires blood DNA-methylation measurements. Its original model combines methylation surrogates for seven plasma proteins and smoking pack-years with age and sex. Routine chemistry results alone cannot produce GrimAge; measured protein concentrations cannot simply replace those methylation surrogates.
Clinical PhenoAge is not DNAm PhenoAge
The 2018 study first built the clinical score from mortality-associated blood markers. It then trained a separate DNA-methylation predictor of that score, called DNAm PhenoAge. This site's calculator computes the clinical score, not that epigenetic clock.
What the numbers mean
An older model age reflects a profile associated with greater mortality risk in the training data. It is not a literal measurement of how old every tissue is. A younger result does not establish that a treatment reversed aging. Subtracting chronological age gives a simple difference; research measures of age acceleration often instead use residuals from regression on chronological age.
Which fits your question?
If you already have all nine clinical markers, PhenoAge is the directly calculable option. GrimAge addresses a different measurement task and requires methylation data and its own analysis. Neither result is a diagnosis or a pace-of-aging measurement. Do not average the scores, convert one into the other, or treat disagreement as proof that one test is wrong.
Limits when comparing results
Sample handling, laboratory methods and model population affect interpretation. An acute illness can change blood-marker inputs. GrimAge's mortality associations were evaluated in cohorts, not as a guarantee of an individual's lifespan. Compare repeated results with the same method and comparable conditions; an apparent change alone does not establish a causal benefit.