Steve: Yeah. I mean, just to set the stage, so we have some epigenetic clocks whose purpose is really to measure chronologic age, period. But then we have other epigenetic clocks that are really defined to be lifespan predictors or they are meant to predict time to death or time to major onset of a disease or what people call health span, how long are you healthy? And as you mentioned, we have actually two biomarkers. One is called DNA methylation PhenoAge, but also another one that was named after the grim reaper, so it's called DNA methylation GrimAge. Now, these biomarkers were developed really for that purpose of predicting health span and lifespan as opposed to measuring aging.

And the reason why we have these different tools is that we, of course, plan to use them in human clinical trials of anti-aging interventions, you know, and in that context, you want to see whether an intervention actually resets an epigenetic clock and that resetting then has a benefit in terms of delaying risk for various diseases. And you mentioned heart disease, GrimAge is a pretty good predictor of time to coronary heart disease. Surprisingly, these clocks even predict time to cancer. And that is surprising because it's a measurement based on blood, you know, and so you could ask why would a measurement in blood be predictive of the onset of various types of cancers in other solid tissues? But then...

Rhonda: You can predict it before other clinical diagnostics in some cases?

Steve: Yeah. I mean, let me start out by saying I'm not sure whether this biomarker is clinically useful, okay? Because I'm very scared people think they can now measure their blood and I will predict you will get cancer in 10 years. It's not at that level. However, if you have, for example, a study of 1,000 women and somebody collected their blood in the 1990s, you know, and so for each woman you have follow-up information, whether she developed breast cancer or when she developed breast cancer. And if then analyze the data, you will find that biomarkers such as GrimAge and other biomarkers actually do predict onset to cancer in a statistical fashion. The P-value would be quite significant, you know. But as I said, I wouldn't claim that this is right now ready for prime time in a clinical setting for finding high-risk individuals because the effect sizes are too small. When I predict, for example, that you will develop heart disease in 15 years, you know, there would be a big error bar associated with it, plus, minus six years or so. So, for the individual, it might not be useful.

Rhonda: That's a significant amount of time for a person, six years.

Steve: Yes, exactly.