Aging is the number one risk factor for almost all chronic diseases. However, the wide phenotypic variation between has always kept chronological age from being a reliable clinical biomarker. As a result, aging has always been difficult to objectively assess.
Now, with the advent of new multi-omic diagnostics such as epigenetics, transcriptomics, and proteomics, we now have ways to effectively assess a patient's aging rates and vet the effect of many anti-aging treatments. In particular, many advances have been made to epigenetic testing and the algorithms that can interpret these DNA markers to health related risks and outcomes.
We can now use these epigenetic algorithms to assess immune system function, telomere length, senescence, instantaneous aging rate, and of course how all of these metrics relate to the risk of developing chronic disease.
Additionally, unlike DNA, changes can be made to reverse the signs of epigenetic aging as a way to improve health. As a result, we can finally treat and test aging with a single test.
In this lecture, we will talk about the history of this new field, how many are using it, and the best ways to reverse epigenetic aging.