Research Paper Volume 10, Issue 10 pp 2832—2854
A multi-tissue full lifespan epigenetic clock for mice
- 1 Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA 90095, USA
- 2 Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, Bialystok, Poland
- 3 Department of Microbiology, Immunology and Molecular Genetics, Department of Medicine, and Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
- 4 The Jackson Laboratory, Farmington, CT 06032, USA
- 5 The Jackson Laboratory, Bar Harbor, Maine 04609, USA
- 6 Department of Human Genetics and Biostatistics, University of California Los Angeles, Los Angeles, CA 90095, USA
Received: August 16, 2018 Accepted: October 5, 2018 Published: October 21, 2018
https://doi.org/10.18632/aging.101590How to Cite
Abstract
Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.