- Dec, Eric;
- Clement, James;
- Cheng, Kaiyang;
- Church, George M;
- Fossel, Michael B;
- Rehkopf, David H;
- Rosero-Bixby, Luis;
- Kobor, Michael S;
- Lin, David TS;
- Lu, Ake T;
- Fei, Zhe;
- Guo, Wei;
- Chew, Yap Ching;
- Yang, Xiaojing;
- Putra, Sulistyo E Dwi;
- Reiner, Alex P;
- Correa, Adolfo;
- Vilalta, Adrian;
- Pirazzini, Chiara;
- Passarino, Giuseppe;
- Monti, Daniela;
- Arosio, Beatrice;
- Garagnani, Paolo;
- Franceschi, Claudio;
- Horvath, Steve
Claims surrounding exceptional longevity are sometimes disputed or dismissed for lack of credible evidence. Here, we present three DNA methylation-based age estimators (epigenetic clocks) for verifying age claims of centenarians. The three centenarian clocks were developed based on n = 7039 blood and saliva samples from individuals older than 40, including n = 184 samples from centenarians, 122 samples from semi-supercentenarians (aged 105 +), and 25 samples from supercentenarians (aged 110 +). The oldest individual was 115 years old. Our most accurate centenarian clock resulted from applying a neural network model to a training set composed of individuals older than 40. An epigenome-wide association study of age in different age groups revealed that age effects in young individuals (age < 40) are correlated (r = 0.55) with age effects in old individuals (age > 90). We present a chromatin state analysis of age effects in centenarians. The centenarian clocks are expected to be useful for validating claims surrounding exceptional old age.