1. Underlying features of epigenetic aging clocks in vivo and in vitro
- Author
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Wei Zhao, Luigi Ferrucci, Diana Leung, Jennifer A. Smith, Kyra Thrush, Scott M. Ratliff, Zuyun Liu, Toshiko Tanaka, Lauren Schmitz, and Morgan E. Levine
- Subjects
0301 basic medicine ,Senescence ,Epigenomics ,Male ,Aging ,CD14 ,Computational biology ,Mitochondrion ,Biology ,03 medical and health sciences ,0302 clinical medicine ,In vivo ,Biological Clocks ,Humans ,cellular senescence ,Epigenetics ,DNA methylation ,Autophagy ,Cell Biology ,Original Articles ,In vitro ,mitochondria ,030104 developmental biology ,biological aging ,Female ,Original Article ,030217 neurology & neurosurgery ,epigenetic clock - Abstract
Epigenetic clocks, developed using DNA methylation data, have been widely used to quantify biological aging in multiple tissues/cells. However, many existing epigenetic clocks are weakly correlated with each other, suggesting they may capture different biological processes. We utilize multi‐omics data from diverse human tissue/cells to identify shared features across eleven existing epigenetic clocks. Despite the striking lack of overlap in CpGs, multi‐omics analysis suggested five clocks (Horvath1, Horvath2, Levine, Hannum, and Lin) share transcriptional associations conserved across purified CD14+ monocytes and dorsolateral prefrontal cortex. The pathways enriched in the shared transcriptional association suggested links between epigenetic aging and metabolism, immunity, and autophagy. Results from in vitro experiments showed that two clocks (Levine and Lin) were accelerated in accordance with two hallmarks of aging—cellular senescence and mitochondrial dysfunction. Finally, using multi‐tissue data to deconstruct the epigenetic clock signals, we developed a meta‐clock that demonstrated improved prediction for mortality and robustly related to hallmarks of aging in vitro than single clocks., We compared 11 existing epigenetic clocks on the basis of their functional characteristics, transcriptional associations, and ability to capture hallmarks of aging. We then decomposed their signals and recombined them into a “meta‐clock.” This meta‐clock showed stronger prediction of all‐cause mortality than any one epigenetic clock and was able to distinguish tumor from normal tissue and capture epigenetic changes in two types of senescence (replicative and oncogene induced).
- Published
- 2020