We recently developed a DNA methylation based biomarker of aging known as the epigenetic clock, which can be used to measure the DNA methylation (DNAm) age of any human (or chimpanzee) tissue, cell type, or fluid that contains DNA (with the exception of sperm). DNA methylation age of blood has been shown to predict all-cause mortality in later life, even after adjusting for known risk factors, which suggests that it relates to the biological aging process. Similarly, markers of physical and mental fitness are also found to be associated with the epigenetic clock (lower abilities associated with age acceleration). These published data suggest that we may be close to achieving a long standing milestone in aging research: the development of an accurate measure of tissue age or even biological age. However, a major challenge still exists. We have yet to determine what precisely is being measured by the epigenetic clock, since the underlying biological processes remain poorly understood. The development of an epigenetic clock for mice will enable us to conduct mechanistic studies in order to dissect cause and effect relationships. As mice are the most widely used model system for studying human biology and disease, we will be able to address critical issues, including the determination of genetic and environmental effects on the rate of aging and its ramifications for chronic diseases. To develop an epigenetic clock that applies to most mouse models/tissues, we will generate unprecedented, epigenome-wide DNA methylation data from a large number of tissues/organs from several mouse strains. We will use Reduced Representation Bisulfite Sequencing (RRBS) to profile methylation, as we have previously shown that it generates accurate and cost effective measurements. We will also leverage the existing resource called the Hybrid Mouse Diversity Panel (HMDP) to integrate our aging model with additional phenotypes. Since we have achieved a similar goal in humans based on relatively noisy data, we have no doubt that we can achieve the same in mice, for which data tend to be cleaner. The price tag for achieving such a critical milestone in aging research would be relatively cheap (modular R21 grant). As part of this proposal, we will not only develop an epigenetic clock for mice but also characterize its relationship to various functional genomics data (transcriptomics, proteomics, metabolomics), genetic data, and clinical traits. Comparative epigenetic studies will allow us to compare humans to mice to identify common mechanisms in normal aging and aging-related diseases. Our team is uniquely positioned to develop an epigenetic clock that applies to many mouse strains and tissues. Dr Horvath developed the epigenetic clock for humans. Dr Pellegrini is a pioneer and expert user of RRBS and has applied it to the HMDP. Dr Lusis has expertise in mouse genetics, chronic disease genetics, and led the development of the HMDP. All researchers have collaborated on genomics, mouse models, and age related diseases for over 10 years.
Recently we have shown that epigenetic data can be used to measure the age of human tissues and cell types. In order to compare aging effects in mice with those in humans, and to eventually be able to manipulate the rate of aging, we aim to develop a comparable measure in mice.
| Thompson, Michael J; Chwia?kowska, Karolina; Rubbi, Liudmilla et al. (2018) A multi-tissue full lifespan epigenetic clock for mice. Aging (Albany NY) 10:2832-2854 |
| Thompson, Michael J; vonHoldt, Bridgett; Horvath, Steve et al. (2017) An epigenetic aging clock for dogs and wolves. Aging (Albany NY) 9:1055-1068 |
