Biological age measures how old you are based on your cellular health. Find out how to test it (and how to age backwards).
…you’re going to discover how old you really are by taking a dive into the science of epigenetic methylation and biological aging. You’re going to find out about gene function, gene expression and what it has to do with how you age—and why it matters.
Biochemist Ryan Smith co-founded TruDiagnostic, a company focused on methylation array-based diagnostics for life extension and preventive healthcare. TruDiagnostic, a CLIA certified lab and health data company, developed the TRUAGE anti-aging test.
From a small blood test, TruDiagnostic can tell you your biological age—how old your body acts, based on how it’s functioning (as opposed to your chronological age, which is the number of years you’ve been on Earth).
Biological age is one of the most impactful pieces of data you can have about yourself. Age is the number one predictor of death, and your biological age matters more than the number of times you’ve been around the sun.
For example, you could be 42, and if you take great care of yourself, your biological age may be 30… Or, if you take poor care of yourself, your biological age may be 60.
Either way, TruDiagnostic will tell you how old you really are. And their test goes further than that. After you discover your biological age, TruDiagnostic also gives you a list of strategies to reverse aging based on your unique genetics. In other words, you get personalized anti-aging biohacks—and you can test your age over time to see if you’re getting younger, so you know whether or not your anti-aging hacks are working.
If you can turn back the clock on your biological age, you unlock the door to a longer, better life.
It feels like the cusp of a big change in longevity research with science and data now more fully supporting this work. TruDiagnostic currently has over 30 approved clinical research studies underway investigating how epigenetic methylation changes impact how long you live and how well you age.
“New algorithms are coming out on a daily basis, which is both a good and a bad thing because the bar is always being set incrementally higher,” Ryan explains. “And so that is a good thing because it means we’re getting even better at diagnosing the real signal of age and getting rid of any association to disease and just actually getting the age values right. And there are a lot of different methods to do that but all of them involve computer learning. And that is exactly why we’re seeing such a big, I would say, change in this aging research field is because now these computer learning platforms, which previously were unavailable, are being matched with diagnostic methods which are creating data sets, which were previously unavailable. And so we’re sort of opening up and opening up these rooms of analysis.”
In this episode, you’ll also learn:
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