UCLA

It has been observed that the epigenome exhibits significant changes with increased age. These changes are so consistent that they have been used to develop "epigenetic clock" models which can predict chronological age with high accuracy and have been shown to be independent predictors of age-related disease outcomes. In this dissertation, I investigate the relationship between epigenetic aging and lifestyle and transcriptomic factors in order to elucidate the underlying biology of this phenomenon. I find that epigenetic aging in blood is multifactorial and is consistent with modern notions of health. My experiences with poor sample annotations associated with high dimensional genomics data led me to develop a new assay to simultaneously measure proteins, lipids, metabolites, and other molecules.