Biomarker

Epigenetic Clock

The algorithm that reads your DNA and calculates how old your cells really are

Definition

An epigenetic clock is a bioinformatics algorithm that estimates biological age from DNA methylation patterns at specific genomic positions (CpG sites). They were discovered by Steve Horvath (UCLA) in 2013, who published the first clock that worked across all human tissues with an error margin of ±3.6 years. Epigenetic clocks predict mortality and disease onset more accurately than chronological age.

Detailed explanation

The main current epigenetic clocks are:

Horvath Clock (2013): the first pan-tissue clock, using 353 CpG sites. Measures cumulative biological age.

PhenoAge (Levine, 2018): trained on mortality biomarkers. The best predictor of chronic diseases.

GrimAge (Lu, 2019): the most predictive of mortality. Correlates with CRP, cholesterol, and smoking history. Error margin <1 year in older populations.

DunedinPACE (Belsky, 2022): measures the current PACE of ageing — how many biological years you age per chronological year. 1.0 = normal rate; >1.2 = accelerated ageing. It is the most sensitive to changes from interventions.

Companies offering epigenetic clock tests accessible from Spain: TruDiagnostic (DunedinPACE + GrimAge), Chronomics, and Elysium Health Index. Price: 200–600 EUR. Sample: saliva or blood on blotting paper sent by post.

Scientific sources

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Content created by the LongevityMap editorial team based on peer-reviewed scientific literature. Sources: PubMed, Cochrane Library. This content does not replace professional medical advice. Our team · Methodology