Research Paper Volume 12, Issue 5 pp 4394—4406
DNA methylation clocks as a predictor for ageing and age estimation in naked mole-rats, Heterocephalus glaber
- 1 The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- 2 Centre for Genomic Health, Queen Mary University of London, London, UK
- 3 Fondation pour la Recherche en Physiologie, Brussels, Belgium
- 4 Service de Physiologie et Explorations Fonctionnelles, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France
- 5 Université Paris Descartes, Faculté de Médecine, Paris, France
- 6 INSERM UMR_S1151 CNRS UMR8253 Institut Necker-Enfants Malades (INEM), Paris, France
- 7 School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
received: October 25, 2019 ; accepted: February 25, 2020 ; published: March 3, 2020 ;https://doi.org/10.18632/aging.102892
How to Cite
Copyright © 2020 Lowe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The naked mole-rat, Heterocephalus glaber (NMR), the longest-lived rodent, is of significance and interest in the study of biomarkers for ageing. Recent breakthroughs in this field have revealed ‘epigenetic clocks’ that are based on the temporal accumulation of DNA methylation at specific genomic sites. Here, we validate the hypothesis of an epigenetic clock in NMRs based on changes in methylation of targeted CpG sites. We initially analysed 51 CpGs in NMR livers spanning an age range of 39-1,144 weeks and found 23 to be significantly associated with age (p<0.05). We then built a predictor of age using these sites. To test the accuracy of this model, we analysed an additional set of liver samples, and were successfully able to predict their age with a root mean squared error of 166 weeks. We also profiled skin samples with the same age range, finding a striking correlation between their predicted age versus their actual age (R=0.93), but which was lower when compared to the liver, suggesting that skin ages slower than the liver in NMRs. Our model will enable the prediction of age in wild-caught and captive NMRs of unknown age, and will be invaluable for further mechanistic studies of mammalian ageing.