A whole lifespan mouse multi-tissue DNA methylation clock

Abstract

Age predictors based on DNA methylation levels at a small set of CpG sites, DNAm clocks, have been developed for humans and extended to several other species. Three currently available versions of mouse DNAm clocks were either created for individual tissues or tuned toward young ages. Here, we constructed a robust multi-tissue age predictor based on 435 CpG sites, which covers the entire mouse lifespan and remains unbiased with respect to any particular age group. It can successfully detect the effects of certain lifespan-modulating interventions on DNAm age as well as the rejuvenation effect related to the transition from fibroblasts to iPSCs. We have carried out comparative analyses of available mouse DNAm clocks, which revealed their broad applicability, but also certain limitations to the use of tissue-specific and multi-tissue age predictors. Together, these tools should help address diverse questions in aging research.

Screening for genes that accelerate the epigenetic ageing clock in humans reveals a role for the H3K36 methyltransferase NSD1

“…Our understanding of the ageing process has historically been hampered by the lack of tools to accurately measure it. In recent years, epigenetic clocks have emerged as powerful biomarkers of the ageing process across mammals [5,6], including humans [7][8][9], mouse [10][11][12][13][14], dogs and wolves [15] and humpback whales [16]. Epigenetic clocks are mathematical models that are trained to predict chronological age using the DNA methylation status of a small number of CpG sites in the genome.…”

“…Interestingly, deviations of the epigenetic (biological) age from the expected chronological age (aka epigenetic age acceleration or EAA) have been associated with many conditions in humans, including timeto-death [17,18], HIV infection [19], Down syndrome [20], obesity [21], Werner syndrome [22] and Huntington's disease [23]. In mice, the epigenetic clock is slowed down by dwarfism and calorie restriction [11][12][13][14]24] and is accelerated by ovariectomy and high fat diet [10,13]. Furthermore, in vitro reprogramming of somatic cells into iPSCs reduces epigenetic age to values close to zero both in humans [8] and mice [11,14], which opens the door to potential rejuvenation therapies [25,26] Epigenetic clocks can be understood as a proxy to quantify the changes of the epigenome with age.…”

“…In mice, the epigenetic clock is slowed down by dwarfism and calorie restriction [11][12][13][14]24] and is accelerated by ovariectomy and high fat diet [10,13]. Furthermore, in vitro reprogramming of somatic cells into iPSCs reduces epigenetic age to values close to zero both in humans [8] and mice [11,14], which opens the door to potential rejuvenation therapies [25,26] Epigenetic clocks can be understood as a proxy to quantify the changes of the epigenome with age. However, little is known about the molecular mechanisms that determine the rate of these clocks.…”

Age and life expectancy clocks based on machine learning analysis of mouse frailty

“…In humans, these clocks are highly correlated with chronological age, and are able to predict, at the population level, mortality risk and risk of age-related diseases (Horvath and Levine 2015;Horvath et al , 2016Horvath and Raj 2018;Quach et al 2017;Maierhofer et al 2017;Levine et al 2018). Methylation clocks have also been developed for mice, and shown to correlate with chronological age, and respond to lifespan-increasing interventions such as calorie restriction (Meer et al 2018;Petkovich et al 2017;Cole et al 2017;Stubbs et al 2017), but their association with mortality has not yet been explored. However, the major drawback of these mouse clocks is that they require repeated invasive blood collections and time-consuming and expensive data acquisition and analysis procedures.…”

Reversal of ageing- and injury-induced vision loss by Tet-dependent epigenetic reprogramming

“…Genomic DNA from FACSisolated RGCs was obtained from retinas that are intact or 4-days after axonal injury in the presence or absence of OSK induction and subjected reduced-representation bisulfite sequencing (RRBS). A newly published rDNAme clock 26 provided the best site coverage (70/72 CpG sites) relative to other available mouse clocks 27,28 , and its age estimate remained highly correlated with chronological age of RGCs (Extended Data Fig. 7a and Methods).…”