A multi-tissue full lifespan epigenetic clock for mice.

Michael J Thompson,Karolina Chwiałkowska,Steve Horvath,Liudmilla Rubbi,Richard C Davis,Matteo Pellegrini,Ron Korstanje,Anuj Srivastava,Aldons J Lusis,Gary A Churchill

doi:10.18632/aging.101590

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.

Highlights

Our understanding of age-related epigenetic changes in DNA-methylation in humans has progressed rapidly with the technical advancement of genomic platforms [1,2,3,4,5,6,7,8,9,10,11,12,13,14]
Based on calculations and criteria described in the Methods section, we constructed a matrix of high confidence methylation levels for 1189 mouse samples at 193,651 CpG sites
Based on multiple tissue samples taken from previous studies and our own in-house collection we compiled a dataset of 1189 mouse DNA methylation measurements across hundreds of thousands of CpGs

Summary

Introduction

Our understanding of age-related epigenetic changes in DNA-methylation in humans has progressed rapidly with the technical advancement of genomic platforms [1,2,3,4,5,6,7,8,9,10,11,12,13,14]. Recent studies have taken advantage of this relationship to accurately estimate chronological age based on the methylation levels of multiple CpG www.aging‐us.com dinucleotides [10, 13, 24]. We and others have shown that human epigenetic age relates to biological age, not just chronological age This is demonstrated by the finding that the discrepancy between DNAm age and chronological age (what we term “epigenetic age acceleration”) is predictive of allcause mortality even after adjusting for a variety of known risk factors [25,26,27,28,29]. Moving beyond primates into the broader mammalian arena, we recently constructed an epigenetic clock for canids using DNA-methylation data from Canis familiaris (domesticated dog) and Canis lupus (wolf) [42]

Objectives

Methods

Results

Conclusion