Transforming Your Health Journey: Hannah Went on Aging, Lifestyle Choices, and Longevity

This week, hosts Doro and Tricia sit down with Hannah Went, co-founder of TruDiagnostic, to explore the fascinating world of precision medicine and longevity. Driven by her passion for science and technology, Hannah shares her journey into the field and provides valuable insights into the role of personalized health testing in revolutionizing how we approach aging. Together, they delve into groundbreaking concepts like healthspan vs. lifespan, the transformative power of precision medicine, and how personalized lifestyle adjustments can empower individuals to take control of their health.

Listeners will gain an in-depth understanding of how advanced testing can reveal organ-specific aging patterns and disease risks while offering targeted lifestyle recommendations. Tune in to learn how you can unlock your health potential and live your best life, no matter your age. This inspiring episode will change how you view your own health journey.

Thanks to Wild Health for supporting our 5-episode health series. As pioneers in Precision Medicine, they offer tailored health plans based on your genetics and lifestyle, covering diet, exercise, and more. Start your personalized health journey at wildhealth.com.

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Podcast: http://everythingepigenetics.com

Website: http://trudiagnostic.com

Instagram: https://www.instagram.com/everythingepigenetics/

X: https://twitter.com/EverythingEpi


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Quotes:

Your DNA is not your destiny. Food is medicine. You are what you eat. That is the definition of epigenetics without really saying it. - Hannah Went

We probably don't want to live forever, but we want to live a long time. And we want to be healthy for the time we are alive. - Hannah Went

A little bit of stress is good. It means you have a reason to get up in the morning. You have a purpose in life, and that purpose is very important. - Hannah Went

Show Notes:

HANNAH WENT: An epigenetic clock is really or you'll hear the term biological age clock. And usually it's going to be synonymous epigenetic clock. Biological age clock. This is really a you know, molecular biomarker if you will, based on DNA methylation levels. So that's the true scientific term for describing those light switches. How much something is expressed so turned on and turned off. That's really predicting the age of maybe a cell or tissue or organism with a very high precision, at least in our case, or high accuracy. So DNA methylation, to explain that a little bit more is just a little chemical modification that occurs at specific DNA sites. And it's one of the primary mechanisms involved in your epigenetic gene regulation. And you know, that can be again influenced by different things. So these epigenetic clocks are just algorithms or ways that they can predict certain outcomes using machine learning and AI in terms of the creation of those actual clocks.

TRICIA: Tell us all what is Symphony Age and where it came from and the partnership that you've had with Yale.

HANNAH WENT: Yeah, I'm super excited to talk about this one. Tricia. This hasn't even been launched yet at the time of recording.

TRICIA: When will it be launched?

HANNAH WENT: In about a month. Okay. Yeah. So, okay. We're really, really close. And, um, this is a really cool clock because one of the issues previously has always been giving recommendations. Um, usually the biological age clocks in the past give you a number, and it's really hard to know exactly what you need to work on. So the Symphony Age is one that we actually created with Yale. And it's really understanding the idea that everyone ages differently. So I can definitely go go deep into this. But really when we study the science of aging, um, you know, and have created these epigenetic clocks, uh, this is more accurate than even your, your birth date, because, again, we want to be predictive of outcomes. So these types of tools that I'm talking about and that, you know, has been a big part of the conversation is telling us how old our body really is, how fast you're aging, because we know everyone doesn't age at the same rate. But just having that one number, as I mentioned, isn't enough. People live differently, right? Some exercise a lot and keep their bodies younger. Others might keep their mind sharp, for example, but not eat well. And that can make other parts of the body age faster. And if someone smokes or drinks a lot, it could speed up aging in their lungs, their heart, their liver or their brain. So treating everyone the same like we have in the past when it comes to aging just doesn't make sense. And that's why we created what we call this symphony age and Symphony stands for system methylation, proxy of heterogeneous organ years. All right. So it's a mouthful. That's why we we just call it Symphony Age. But it's a new way of looking and examining how different parts of the body age. So again we created this with scientists at Yale. And they use a method to study 11 different body parts and see how that affects people differently. So it this big picture approach really helps us understand aging by putting all the pieces of the puzzle together.

TRICIA: Wow, that is so revolutionary. So basically you're saying that it looks at the different organs. So my lungs may have been have a little different age than maybe my pancreas or something like that.

HANNAH WENT: Yeah, exactly. So if we're thinking again about it in the terms of aging, there are many age related illnesses that come from all different types of biological systems working together. So another example, for instance, would be arthritis, right. Arthritis is going to be the result of both musculoskeletal wear and inflammation. Whereas stroke could happen more due to problems in the cardiovascular system, metabolism, inflammation, brain function. So all of these interconnected pathways can lead to different aging profiles or aging types. People sometimes even call these aging types, so that makes some people more prone to certain age related diseases. And understanding those patterns really help forecast health outcomes and predict further.

TRICIA: Um, can you can you kind of explain like a patient A and then a patient B and how it could be really different.

HANNAH WENT: Yeah, of course we we use this example a lot. Um, and this one's even in the report that I sent over to you beforehand too. So, you know, consider two individuals that are 50 years old and most people who take the true diagnostic test, funny enough, are between like 40 and 60. So this would be like an average patient example. Um, so patient A is a smoker. They have a very unhealthy diet that leads to a higher metabolic and lung age. So maybe their lung age is, you know, nine years older. So 59 in their metabolic age is seven years older at 57. So this patient we know because of these associations is actually going to be at an increased risk for things like lung cancer COPD diabetes and is increased due to that advanced organ aging. Right. Um, so they're they're going to want to take certain therapies or interventions that are going to target that. Right. We'd recommend something more like patient B, which would be a someone who has a healthy diet. They exercise frequently. You know, compared to patient A, they're going to have a decreased lung in metabolic age. So their lung age is going to be six years young or four years younger, let's say at 46 and five years younger for the metabolic age at 45. So patient B is going to be at a decreased risk for those certain diseases. So we're really starting to see again how your entire environment and your behavior, how you're interacting with the world is affecting these biological ages, thus affecting every single outcome that you're actually going to get later on in life.

TRICIA: Wow. So, um, if you were a smoker in your 20s and you stopped smoking, do you detect that? Do you see that or what happens?

HANNAH WENT: Yeah. Oh, that's you know, that's an interesting question. It's a really fun one to talk about. Two. Tricia. Because smoking can actually be detected by epigenetics and DNA methylation. And it's actually more accurate than self- reported smoking status.

TRICIA: You know, I was going to say that. Do you ask them or does the body tell them, okay. Yeah.

HANNAH WENT: The body I mean, we ask them and the body tells us and then we can compare the two, maybe find out if there's if someone's getting a little bit more. Um, no. But you know, it is interesting. I would say smoking has definitely been. If not. If not, you know, in top three, it's probably the number one epidemiological factor that's been studied when it's come to epigenetic aging. Just because again, we have a lot of data on that. So you can actually see signatures. And there's even just one gene. You can really look at one epigenetic modification that you can look at to really tell if someone's a current smoker. You know, a past smoker, um, as well. And how much?

TRICIA: Wow. And then how much damage it's done or how much can you actually see how much it aged you that specific or not yet?

HANNAH WENT: I would say not at an individual level. So we can quantify, hey, how much have they actually smoked? There are larger population studies saying, hey, we know that smoking ages you from a general population standpoint, right? Um, but again, you still need that n of one kind of testing to really understand if you were a past smoker, how is that affecting your aging? Have you really turned your life around or are you still smoking, or are you getting more secondhand smoke too?

TRICIA: Yeah, right. And how does that play? And will it show the difference between secondhand smoke and real smoke? Or is the body just again just see it as the same.

HANNAH WENT: Yeah, just the same for, for now I would say. Yeah. So it's uh, it's still, I would say a little bit, uh, hard um, to, to even differentiate between, um, you know, smoking and even like e-cigarettes as, as well, so or the vaping. So there was A11 study that came out, um, pretty recent that showed e-cigarette users had similar changes to DNA and specific cheek cells as smokers. Um, but again, it's early research. It's it's more correlation. Um, I mean, we're seeing the same type of signatures. And you could probably hypothesize that, you know, despite vaping being marketed as a safer alternative to smoking, it's long term health effects are very uncertain. And that's what we're trying to really dig into in that study.

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