GrimAge

GrimAge is an epigenetic clock and biomarker of aging based on DNA methylation patterns. Introduced by Lu and colleagues in 2019, it aims to estimate an individual's biological age and predict mortality and healthspan more accurately than previous clocks.

It is built from DNA methylation data derived primarily from blood samples, using methylation-based surrogates for two components: lifetime smoking exposure (DNAmPACKYRS) and several plasma protein levels, including PAI-1, TIMP1, and others. These surrogates are combined in a weighted model, along with chronological age, to produce a GrimAge estimate, reported as GrimAge in years. The difference between GrimAge and chronological age, often referred to as GrimAge acceleration, is used to quantify accelerated aging relative to calendar age.

GrimAge has been shown in several cohorts to predict time to death and to associate with risks of cancer, cardiovascular disease, and other aging-related outcomes. It has generally demonstrated stronger associations with mortality than earlier epigenetic clocks. It can be measured from DNA methylation data via microarray platforms (e.g., Illumina 450K/EPIC).

Limitations include reliance on blood-derived methylation data, potential confounding by smoking, and varying performance across populations and technologies. While useful in research on aging biology and intervention studies, GrimAge is not a clinical diagnostic and should be interpreted within the broader context of epigenetic aging research.