encen100

Elastic-net DNAm-age clock trained only in 184 centenarians aged 100–115; the authors advise against routine use but identify possible utility for evaluating supercentenarians.

Predicts	chronological age
Species	Homo sapiens
Tissue	whole blood, saliva, buccal epithelium
Data type	DNA methylation
Model type	elastic net regression
Year	2023

Use with pyaging

import pyaging as pya

pya.pred.predict_age(adata, ["encen100"])

Browse every clock in the pyaging Clock Catalogue.

Citation

Dec, Eric, et al. "Centenarian clocks: epigenetic clocks for validating claims of exceptional longevity." GeroScience 45 (2023): 1817–1835.

https://doi.org/10.1007/s11357-023-00731-7