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[00:00:00.320 --> 00:00:02.000] Coming up on this episode of the Dr.
[00:00:02.000 --> 00:00:02.880] Hyman Show.
[00:00:02.880 --> 00:00:11.440] When you start talking about preventing Alzheimer's and picking it up early, how early can you start to see the PTAU changes?
[00:00:11.440 --> 00:00:18.800] PTAW217 is the very first one that goes up and it starts 20 years before mild cognitive impairment.
[00:00:18.800 --> 00:00:19.680] 20 years.
[00:00:19.680 --> 00:00:20.000] Dr.
[00:00:20.000 --> 00:00:30.400] Eric Topol is a world-renowned physician using data, tech, and deep insight to transform how we detect and prevent diseases like Alzheimer's before they even start.
[00:00:30.400 --> 00:00:38.640] There's so much data to show that that social isolation is a risk factor for neurodegenerative and cardiovascular and even cancer.
[00:00:38.640 --> 00:00:41.760] Strength training is a powerful drug and sleep is a powerful drug.
[00:00:41.760 --> 00:00:44.480] They're better than most of the drugs we have, actually.
[00:00:48.240 --> 00:00:50.800] In functional medicine, we always start with the gut.
[00:00:50.800 --> 00:00:56.000] It's at the core of nearly every aspect of health, from digestion and immune function to brain and skin health.
[00:00:56.000 --> 00:01:01.440] Your gut microbiome regulates inflammation, absorbs nutrients, and maintains the integrity of your gut barrier.
[00:01:01.440 --> 00:01:07.680] That's why I take and recommend SEAD's DSO1 Daily Symbiotic, a next-level probiotic designed to go beyond digestion.
[00:01:07.680 --> 00:01:17.840] With 24 clinically studied probiotic strains and a pomegranate-based prebiotic, DSO1 supports gut immune function, gut barrier integrity, and even heart health through the gut-liver axis.
[00:01:17.840 --> 00:01:19.600] But here's what's really exciting.
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[00:01:29.680 --> 00:01:33.600] As a member of SEED's clinical board, I've seen the science behind their formulations.
[00:01:33.600 --> 00:01:40.960] And new research shows DSO1 supports short-chain fatty acid production, which is key for gut barrier function, immune health, and healthy aging.
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[00:01:53.840 --> 00:02:00.440] I'm incredibly intentional about how I feel my brain because whether I'm with patients, writing, or leading a team, focus and clarity matter.
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[00:02:45.080 --> 00:02:48.360] That's p-i-q-u-e-life.com/slash hyman.
[00:02:48.680 --> 00:02:53.240] Before we jump into today's episode, I want to share a few ways you can go deeper on your health journey.
[00:02:53.240 --> 00:02:57.080] While I wish I could work with everyone one-on-one, there just isn't enough time in the day.
[00:02:57.080 --> 00:02:59.960] So I built several tools to help you take control of your health.
[00:02:59.960 --> 00:03:08.200] If you're looking for guidance, education, and community, check out my private membership, The Hyman Hive, for live QA's, exclusive content, and direct connection.
[00:03:08.200 --> 00:03:12.600] For real-time lab testing and personalized insights into your biology, visit Function Health.
[00:03:12.600 --> 00:03:17.960] You can also explore my curated doctor-trusted supplements and health products at drhyman.com.
[00:03:17.960 --> 00:03:24.200] And if you prefer to listen without any breaks, don't forget you can enjoy every episode of this podcast ad-free with Hyman Plus.
[00:03:24.200 --> 00:03:28.760] Just open Apple Podcasts and tap try free to start your seven-day free trial.
[00:03:28.760 --> 00:03:30.440] Welcome back to the podcast, Dr.
[00:03:30.440 --> 00:03:31.080] Topols.
[00:03:30.960 --> 00:03:32.040] It's good to have you again.
[00:03:32.040 --> 00:03:32.760] Thanks, Mark.
[00:03:32.760 --> 00:03:33.560] Good to be with you.
[00:03:33.560 --> 00:03:39.480] Well, last time, you know, we talked a lot about AI and health and medicine and gotten some pretty cool topics.
[00:03:39.480 --> 00:03:45.680] Since then, you've written a book called Super Agers, which I think is a great title.
[00:03:46.000 --> 00:03:56.880] When you start talking about preventing Alzheimer's and picking it up early, how early can you start to see the PTAU changes, for example, or the proteomic cocktail change?
[00:03:57.200 --> 00:03:57.520] Yeah.
[00:03:58.080 --> 00:03:59.840] Is it five years before they get symptoms?
[00:03:59.840 --> 00:04:00.800] Is it 10, 20 years?
[00:04:01.040 --> 00:04:01.840] Yeah, I'm so glad you guys.
[00:04:02.000 --> 00:04:03.040] What do we know about that?
[00:04:03.200 --> 00:04:12.080] PTAU217 is the very first one that goes up and it starts 20 years before mild cognitive impairment.
[00:04:12.080 --> 00:04:13.200] 20 years.
[00:04:13.200 --> 00:04:14.160] I mean, it's incredible.
[00:04:14.720 --> 00:04:15.520] That's pre-dementia.
[00:04:15.840 --> 00:04:16.080] Yeah.
[00:04:16.080 --> 00:04:16.320] Yeah.
[00:04:16.320 --> 00:04:21.440] I mean, you got another few years before when you go from MCI to actual Alzheimer's.
[00:04:21.600 --> 00:04:28.880] Yeah, it reminds me of this patient I had who had APOE double four, and that's the high-risk Alzheimer's gene.
[00:04:28.880 --> 00:04:32.800] It doesn't mean you're going to get it, but it really dramatically increases the rest.
[00:04:33.040 --> 00:04:37.920] She was a patient of mine at Canyon Ranch like 25 years ago, and she was in her 90s.
[00:04:37.920 --> 00:04:38.720] She was a dentist.
[00:04:38.720 --> 00:04:41.840] She was still working and she had been a health nut her whole life.
[00:04:41.840 --> 00:04:44.640] Here she was in her 90s, completely cognitively intact.
[00:04:44.640 --> 00:04:50.160] Not sure I'd want her to be my dentist at 95, but still she was all there.
[00:04:50.160 --> 00:04:55.920] And I was like, wow, it was a very, it was one of those memorable patients that, you know, teaches you a lesson about what's possible.
[00:04:55.920 --> 00:05:01.120] And I was like, wait, just because you have a genetic risk doesn't mean you're going to get the disease.
[00:05:01.120 --> 00:05:11.040] Like everybody in my mother's side of the family on her dad's side all had severe heart disease in their 50s, heart attacks, you know, bypasses and so forth.
[00:05:11.040 --> 00:05:13.360] And I thought, oh boy, I'm going to be in trouble.
[00:05:13.360 --> 00:05:17.280] But it turns out that they might have a predisposition, but they're not predestined.
[00:05:17.440 --> 00:05:30.440] You've kind of started, I think, and you can correct me if I'm wrong, down this road by doing this study of elderly people who you end up calling welderly, which were people that lived a long time.
[00:05:29.840 --> 00:05:34.040] And you dove into a lot of things, genetics, lifestyle.
[00:05:34.200 --> 00:05:38.440] And I would love you to sort of unpack some of the myths that got busted there.
[00:05:38.440 --> 00:05:48.440] Because I think everybody thinks that, you know, there's a longevity gene, or if you just, you know, had a good hand dealt you with your genetic cards that you're going to live a long time.
[00:05:48.760 --> 00:05:51.400] And if you don't, you're kind of stuck with whatever you got.
[00:05:51.400 --> 00:05:56.760] You know, oh, my father got heart disease, my mother had diabetes, and my grandma got Alzheimer's.
[00:05:56.920 --> 00:06:00.360] I'm just kind of destined to be getting some disease in the future.
[00:06:00.360 --> 00:06:03.560] But you kind of found some surprising things when you did this study.
[00:06:03.880 --> 00:06:07.080] Can you unpack that study a little bit, what you found and what was surprising about it?
[00:06:07.080 --> 00:06:09.240] So it was called the Welderly Study.
[00:06:09.240 --> 00:06:20.920] And it took seven years to find 1,400 people who were average age near 90 and up to 102 who had never had a chronic illness, age-related or otherwise.
[00:06:20.920 --> 00:06:29.640] So it was a very unique cohort that has not yet ever been replicated in terms of that type of demographic.
[00:06:29.640 --> 00:06:32.760] And we did whole genome sequencing on all of them.
[00:06:32.760 --> 00:06:37.160] And surprisingly, we thought we'd find, as you said, all these genetic underpinnings.
[00:06:37.160 --> 00:06:38.680] And we found almost nothing.
[00:06:38.680 --> 00:06:49.640] This is also consistent with so many of these people had relatives, like the patient I present in the book, Lee Rushall, who is 98.
[00:06:49.640 --> 00:06:52.840] And her parents died in their 50s and 60s.
[00:06:52.840 --> 00:06:54.600] Her brothers, the same.
[00:06:54.600 --> 00:06:56.600] And so it is a genetic story.
[00:06:56.600 --> 00:07:02.200] And for many people, like myself, with a terrible family history, it's quite liberating.
[00:07:02.520 --> 00:07:04.520] But of course, some of it's genetics.
[00:07:04.520 --> 00:07:08.040] But for the most part, it's much less than we thought.
[00:07:08.040 --> 00:07:09.640] It was a big surprise to us.
[00:07:09.640 --> 00:07:13.640] It was a disappointment because we thought we're going to find all these important things.
[00:07:13.960 --> 00:07:18.880] And it's really in contrast to the elderly, which is, as you know, the elderly.
[00:07:19.520 --> 00:07:20.640] Elderly, I like that.
[00:07:20.640 --> 00:07:21.280] I like that.
[00:07:14.840 --> 00:07:22.000] Yeah, elderly.
[00:07:22.400 --> 00:07:27.200] The elderly are the people over 60 that have all these chronic age-related diseases.
[00:07:27.200 --> 00:07:34.480] The contrast is striking, and the genetic story is much less important than I think we had forecasted.
[00:07:34.720 --> 00:07:39.680] And also, of course, if you talk to these people, they really did take care of themselves.
[00:07:39.680 --> 00:07:41.600] They really had good lifestyles.
[00:07:41.600 --> 00:07:43.200] I think we learned a lot from them.
[00:07:43.200 --> 00:07:44.320] Can you talk a little bit about that?
[00:07:44.320 --> 00:07:52.960] Because that's part of what your work is really focused on: the polygenic risk, which means what are the patterns of genes that put you at risk, but don't necessarily make you predestined?
[00:07:52.960 --> 00:08:03.280] Yeah, that's really important that you're bringing up because there are several studies I review in the book of polygenic risk and how that's neutralized by lifestyle factors.
[00:08:03.280 --> 00:08:13.280] That's another way to support what we found on the welderly, whatever genetic load there is or burden, that there's ways to titrate that by taking care of ourselves.
[00:08:13.280 --> 00:08:15.520] But there's another point that's really interesting.
[00:08:15.520 --> 00:08:19.200] Some of the people in that welderly group did not take care of themselves.
[00:08:19.200 --> 00:08:23.840] I remember one fellow 99 years old who was still smoking two packs a day.
[00:08:23.840 --> 00:08:24.400] Wow.
[00:08:24.400 --> 00:08:32.320] Nothing, of course, is 100%, but there's a lot to titration of risk with really good lifestyle behaviors.
[00:08:32.320 --> 00:08:42.560] But there's another factor here, whether it's random or whether I do think, as I get into it later in the book, our immune system is so critical.
[00:08:42.560 --> 00:08:48.240] And that is giving us that resilience to withstand the threat of age-related diseases.
[00:08:48.200 --> 00:08:56.080] And I think we're only scratching the surface right now because clinically, we don't have a way to get the metrics of our immune system.
[00:08:56.080 --> 00:09:04.360] We're just starting to do that now, and we need to really get something that would be part of our assessment, whether it's annual checkup or whatever, particularly as we get older.
[00:09:04.680 --> 00:09:12.440] As you well know, we have this problem with immunosenescence or immune system starting to really let our guard down as we get older.
[00:09:12.440 --> 00:09:14.120] And it's highly variable.
[00:09:14.120 --> 00:09:23.640] Some people, it's entirely intact all the way through their 90s, and other people, it's already starting to lose some of its integrity in their 50s and 60s.
[00:09:23.640 --> 00:09:31.640] Yeah, so a lot of what people think of as the normal age-related diseases, heart disease, cancer, diabetes, dementia, these are all inflammatory diseases.
[00:09:31.640 --> 00:09:34.600] And there's a term for this called inflammaging.
[00:09:34.600 --> 00:09:35.080] Yes.
[00:09:35.080 --> 00:09:36.840] And that we tend to get more inflamed as we get older.
[00:09:36.840 --> 00:09:43.160] So on one hand, our immune system works less well to fight against infections, but on the other hand, it's overactive and causing inflammation.
[00:09:43.160 --> 00:09:51.240] And I think, you know, one of the things you talked about in the book is your epigenetic clocks, biological clocks, and how do we look at organ clocks and overall clocks.
[00:09:51.240 --> 00:09:57.640] And, you know, I was thinking about the other day, it occurred to me that when we measure a lot of the biological clocks, we do it through a blood test.
[00:09:57.960 --> 00:10:06.600] And the cells we're looking at, because there's no cells except for white blood cells, because red cells have no nucleus or no DNA.
[00:10:06.600 --> 00:10:09.640] So white blood cells are the things we're actually measuring these clocks on.
[00:10:09.640 --> 00:10:12.600] So are we actually indirectly measuring our immune age?
[00:10:12.600 --> 00:10:26.040] Yeah, so this is really important: that the epigenetic methylation clock, that is a body-wide assessment of biological age, but it doesn't, as you say, it doesn't get to the crux of the matter.
[00:10:26.040 --> 00:10:38.280] And so that's why it's so exciting on these proteins or proteomic scores, where you take up to 11,000 plasma proteins and you get eight organ clocks, including the immune system.
[00:10:38.280 --> 00:10:41.000] So, brain, heart, liver, kidney.
[00:10:41.000 --> 00:10:44.760] This is really great because now this can be done very inexpensively.
[00:10:45.520 --> 00:10:54.000] We're doing it in our research these days, and the costs for us have come down from what was it, eight or nine hundred dollars to less than a hundred dollars.
[00:10:54.640 --> 00:11:00.000] And the biobank, UK Biobank, is doing it for $50 for in 500,000 people.
[00:11:00.000 --> 00:11:02.240] They've already done it in 50, some thousand.
[00:11:02.240 --> 00:11:15.120] And so, when you have those protein clocks, you know, with AI separates out what's tagged to each organ, that's getting at your point, Mark, because it's no longer relying on just some white cells.
[00:11:15.120 --> 00:11:20.240] It's actually getting to the crux of the proteins that are associated with each organ.
[00:11:20.240 --> 00:11:29.360] So, it's our first cut of a way to inexpensively get a readout on the aging of each organ and also our immune system.
[00:11:29.360 --> 00:11:31.440] And that's a, I think that's a breakthrough.
[00:11:31.440 --> 00:11:37.120] And it's going to be part of our routine assessment in patients going forward.
[00:11:37.120 --> 00:11:38.240] And it's critical.
[00:11:38.240 --> 00:12:01.280] To me, the science of aging has brought these things forward, not just these ideas of reversing aging with fancy things like partial epigenetic reprogramming or centolytics or telomeres lengthening and all kinds of stem cells, but rather the metrics that have come in these recent years, like organ clocks and other things we'll talk about.
[00:12:01.280 --> 00:12:09.200] That's what's so exciting, giving us this real opportunity to prevent age-related diseases like we've never done before.
[00:12:09.200 --> 00:12:11.200] Yeah, I just want to unpack that because it's so important.
[00:12:11.200 --> 00:12:12.640] I'm sure most people will get it.
[00:12:12.640 --> 00:12:28.320] So, normally, when we look at biological age, quote, biological age, and the way it's been measured in the past, it's been by looking at your your genes and the epigenome, which is basically the control mechanism over your genes that determines which genes get turned on or off or expressed.
[00:12:28.320 --> 00:14:05.120] And we're looking at the patterns in that epigenome that give us a sense of your biological age and that's kind of an expensive somewhat nonspecific way to check but you're talking about this new technology using the tens of thousands of proteins in our blood that can be measured very easily and cheaply that show patterns that can give you clues about the specific rate of aging of different organs in your body is that right yeah and that's the key because it's not just you know with polygenic risk score or genome sequencing or things like you know apo e4 that you mentioned that just said that just told us yes or no that just told us you are maybe at risk for this type of cancer or alzheimer's whatever now we're getting at the point of not just what organ but when so the three major age related diseases uh take more than 20 years uh cancer for almost all cancers uh cardiovascular and certainly alzheimer's uh neurodegenerative they take more than 20 years and we've never really been able to get on top of that with all this runway that we have to work with it's incredible and so yeah you're right you know now we have a way to be ahead of it uh and that these metrics uh these uh ways of seeing what in what person what organ if if one is uh aging too fast out of pace with that person um and also, what is the trajectory or arc of that?
[00:14:05.120 --> 00:14:10.480] So, this is, I think um an opportunity that we've never had before and it's a it's a really big advantage.
[00:14:10.480 --> 00:14:19.760] Yeah, I mean you you you're a cardiologist, so you you were taught in you know plumbing 101, basically, and waiting until things happen.
[00:14:19.760 --> 00:14:26.560] And yes, you could give a statin, but that's a very, you know, kind of, I would say, weak tool.
[00:14:26.560 --> 00:14:32.800] I mean, it's a tool, but you know, the benefits marginal, like it's not like a panacea or a magic pill.
[00:14:32.800 --> 00:14:37.440] Yeah, it works well, you know, someone's already had a heart attack, secondary prevention.
[00:14:37.440 --> 00:14:39.120] But we're not making big inroads.
[00:14:39.120 --> 00:14:43.760] There's still plenty of people having heart attacks and bypass surgery and stents and everything else.
[00:14:43.760 --> 00:14:45.680] So we have to do better.
[00:14:45.920 --> 00:14:52.800] And as you know, cardiovascular is the most preventable of these three diseases, 80-90%.
[00:14:53.040 --> 00:14:58.800] Our colleagues, former colleagues from Cleveland Clinic, came out with that's 90%, others 80%.
[00:14:58.800 --> 00:15:05.040] But then cancer and neurodegenerative are 40-50% preventable through lifestyle.
[00:15:05.440 --> 00:15:12.400] So we know some things, even without these new metrics and new capabilities, to be able to prevent these diseases.
[00:15:12.400 --> 00:15:13.440] We're just not doing it.
[00:15:13.440 --> 00:15:17.840] And did you find out in that study of the welderly, what were those things that you found?
[00:15:17.840 --> 00:15:18.800] What was surprising?
[00:15:18.960 --> 00:15:22.800] What did you sort of see that you were surprised at or unexpected?
[00:15:23.280 --> 00:15:32.640] Well, it was interesting, the disposition of these people, very almost all of them, remarkably upbeat people.
[00:15:32.960 --> 00:15:38.560] You did not see people that were complaining or misanthropes or anything like that.
[00:15:38.560 --> 00:15:46.880] You know, they had a relatively sunny disposition, like Lee Russol and the other fellow who I present in the book, two patients of mine.
[00:15:47.120 --> 00:15:48.960] They were kind of prototypic.
[00:15:48.960 --> 00:15:56.080] So that's one thing, you know, it's hard to, there's not hard science on personality and being optimistic.
[00:15:56.080 --> 00:16:01.240] Of course, they're very grateful for how well they've healthily aged, but it's more than that.
[00:16:01.240 --> 00:16:03.560] They've been that way, you know, throughout their lives.
[00:16:03.880 --> 00:16:05.320] They're physically active.
[00:16:05.320 --> 00:16:08.040] You know, they're not sitting around.
[00:16:08.760 --> 00:16:17.720] I remember when I was getting back in touch with my 98-year-old, she's so busy with her art gallery, oil paintings.
[00:16:18.040 --> 00:16:20.920] It was hard to get her, you know, an appointment to go visit her.
[00:16:21.880 --> 00:16:25.560] So these people, they stay busy, they stay active.
[00:16:26.040 --> 00:16:27.560] They're not socially isolated.
[00:16:27.560 --> 00:16:29.240] They don't live in a cave, you know.
[00:16:29.240 --> 00:16:31.240] And they're relatively thin.
[00:16:31.720 --> 00:16:40.360] You don't see much obesity in people who are well into their 90s who have staved off any major age-related disease.
[00:16:40.360 --> 00:16:44.600] So they have a profile that's pretty typical among this group.
[00:16:44.600 --> 00:16:46.200] And they're not common.
[00:16:46.200 --> 00:16:48.920] I mean, really, it took seven years to find this cohort.
[00:16:48.920 --> 00:16:54.680] So yeah, we're talking about well less than 1% of people in that age group.
[00:16:54.680 --> 00:16:56.120] Yeah, I mean, less common in America.
[00:16:56.680 --> 00:17:02.760] I was in Sardinia and Korea, and you see more of those people who are, you know, fit and thin and healthy and happy.
[00:17:02.760 --> 00:17:03.640] I mean, yeah, it's true.
[00:17:03.640 --> 00:17:07.240] I think optimists live longer, even if they're wrong.
[00:17:08.920 --> 00:17:09.480] That's a good news.
[00:17:09.880 --> 00:17:10.440] I do that.
[00:17:10.440 --> 00:17:12.440] You know, the mental health.
[00:17:12.520 --> 00:17:12.920] Yeah.
[00:17:12.920 --> 00:17:14.840] I call myself a pathological optimist.
[00:17:14.840 --> 00:17:19.000] I don't know why, but I go to see the life of Brian.
[00:17:19.000 --> 00:17:20.440] You'll look on the bright side of life.
[00:17:20.440 --> 00:17:23.320] You know, it's kind of a funny thing, Monty Python skip.
[00:17:23.320 --> 00:17:25.400] But I think that mindset plays a big role.
[00:17:25.400 --> 00:17:36.600] And I think we underestimate the role of our beliefs and our mindset and our view of the world and our level of gratitude, our level of service or engagement, our connection to other people.
[00:17:36.600 --> 00:17:40.680] They seem like squishy things, but I think they are really consequential.
[00:17:40.680 --> 00:17:57.200] Yeah, no, I had a whole chapter on mental health because of its primacy here in the interactions with physical health and how stress, anxiety, depression, you know, is a key to these age-related diseases, how we deal with that.
[00:17:57.200 --> 00:18:05.120] And as you touched on earlier, this whole inflammation story is a common thread of the big three age-related diseases.
[00:18:05.120 --> 00:18:10.480] And, you know, we know that stress can induce that, anxiety.
[00:18:10.480 --> 00:18:22.080] So, any way that we can keep that inflammation low, and of course, that's going to be very much a factor of what we eat and our exercise and sleep health and all that.
[00:18:22.080 --> 00:18:23.760] So, there's so many things.
[00:18:23.760 --> 00:18:33.600] It could be environmental toxins burden that have that effect on inflammation, but we never should underestimate our mental health for that factor.
[00:18:33.600 --> 00:18:41.040] I was reading a lot about sociogenomics years ago and this whole idea that how our social relationships and connections affect our gene expression.
[00:18:41.040 --> 00:18:45.200] And I remember seeing these studies where they looked at people who were in relationship.
[00:18:45.200 --> 00:18:50.320] If they had a conflictual relationship, they were turning on inflammatory genes and gene expression.
[00:18:50.320 --> 00:18:56.560] If they had loving heart-centered connections, they would have anti-inflammatory genes turned on, you know.
[00:18:56.880 --> 00:19:09.680] And I think that's kind of worth noting that it may not be a hard science, but I think it's, although that was pretty good science, it was really just this idea that we should not neglect our relationships.
[00:19:09.680 --> 00:19:20.080] And often, I think what happens in people's lives is they work hard, they have their career, their family, they go and go, go, and they neglect their social relationships and their networks, and they end up like retiring or stopping.
[00:19:20.080 --> 00:19:24.480] And they have like, where are their friends and who are the people they can call up?
[00:19:24.480 --> 00:19:27.840] And the amount of loneliness and disconnection is a big factor.
[00:19:27.840 --> 00:19:28.560] No question.
[00:19:28.560 --> 00:19:36.600] And, you know, that was a graph that a lot of people have highlighted in the book about how, as we age, we tend to become reclusive.
[00:19:37.240 --> 00:19:47.800] And there's so much data to show that that social isolation is a risk factor for neurodegenerative and cardiovascular and even cancer.
[00:19:47.800 --> 00:19:49.720] So we want to avoid that.
[00:19:49.720 --> 00:19:53.720] And I think highlighting that, that social interaction.
[00:19:53.720 --> 00:19:57.880] I mean, we are really a social animal.
[00:19:57.880 --> 00:20:03.640] We have to use that ability to help us stay in the mix.
[00:20:03.640 --> 00:20:07.320] And so, you know, this is something I was impressed with that research.
[00:20:07.320 --> 00:20:13.000] I would have been one to discount it, but when I went through it all, it really was cogent.
[00:20:13.240 --> 00:20:20.200] You talked about the polygenic risk score and that it increases your risk, but it doesn't necessarily guarantee you're going to get a problem.
[00:20:20.280 --> 00:20:22.760] There's a lot we know about how to modify that risk.
[00:20:23.000 --> 00:20:39.560] I mean, I'm wondering, you know, the smoker you mentioned earlier who smoked two packs a day, you know, just as there's like the ApoE double four, which is the high-risk Alzheimer's and heart disease gene, the double two, I've heard some people refer to as the jackpot gene.
[00:20:39.640 --> 00:20:45.960] That's like you can smoke and drink and eat whatever you want, and you kind of won the genetic lottery and you don't have to worry as much.
[00:20:46.280 --> 00:20:47.400] Was there anything to that?
[00:20:47.400 --> 00:20:49.960] Was there any parts of that?
[00:20:50.120 --> 00:21:00.760] Well, if you want to pick ApoE2 homozygote, that's pretty good, but it doesn't give you the ability to withstand age-related diseases, it gives you longevity.
[00:21:00.760 --> 00:21:06.920] So that's the difference here that we're talking about: health span versus lifespan.
[00:21:06.920 --> 00:21:11.720] And so, Apolle 2 double is the one you want to get.
[00:21:11.720 --> 00:21:13.880] And of course, I got one copy.
[00:21:13.880 --> 00:21:14.480] I got one copy.
[00:21:14.360 --> 00:21:15.200] Oh, good for you.
[00:21:15.680 --> 00:21:25.120] And in fact, when I go through genome editing, there's a whole chapter in the book where people are editing turning Apolle 4 to Apolle 2 right now.
[00:21:25.120 --> 00:21:27.280] I mean, yeah, I mean, it's wild.
[00:21:27.280 --> 00:21:32.720] And in animals, and, you know, the idea to do this in people, that may happen someday, who knows?
[00:21:32.720 --> 00:21:48.240] But right now, Apo E2, no question that it does, unlike Apolle 4, it has a better associated lifespan, but it doesn't give you that age-related protection from these three diseases, really.
[00:21:48.240 --> 00:21:54.000] What also I think was important in your book is you do talk about the difference between this health span, lifespan distinction.
[00:21:54.000 --> 00:21:57.760] You know, we spend the last 20% of our lives in poor health.
[00:21:57.760 --> 00:22:01.520] That doesn't mean you can do what you want and you're engaged and you feel good, right?
[00:22:01.520 --> 00:22:06.080] And what's the point of living a long life if you feel like crap for the last 20% of your life?
[00:22:06.080 --> 00:22:06.480] Right.
[00:22:06.480 --> 00:22:08.160] Or you're taking a pile of pills.
[00:22:08.160 --> 00:22:12.800] How did they kind of make that almost the same in this welderly group?
[00:22:12.800 --> 00:22:15.120] How is their lifespan, health span the same?
[00:22:15.120 --> 00:22:16.400] There's a couple of things here.
[00:22:16.400 --> 00:22:21.680] We've got to do something about this elderly that you're framing because that's what we have now.
[00:22:22.080 --> 00:22:23.760] That's basically the story.
[00:22:23.760 --> 00:22:33.200] And most people, as they get into the 60s and 70s, they have at least one of these three, if not more, age-related major diseases.
[00:22:33.200 --> 00:22:39.760] That is compromising their health span, and it may indeed their lifespan as well.
[00:22:39.760 --> 00:22:58.160] But living with one of these major diseases, whether it's mild cognitive deficit, moving on to Alzheimer's or one of these cancers that you're trying to be a survivor, fighting it, or certainly all the cardiovascular disease issues that crop up, heart failure and arrhythmias and everything else.
[00:22:58.160 --> 00:22:59.040] This isn't easy.
[00:22:59.040 --> 00:22:59.920] This is not the life you want.
[00:23:00.760 --> 00:23:09.400] What I think is so extraordinary is we're at a time where we have the means of squashing these, preventing these diseases like we never had.
[00:23:09.400 --> 00:23:21.880] So, why accept this the way we've been all these years with this highest density of age-related disease people when we have the stack, the full stack?
[00:23:21.880 --> 00:23:26.520] Now, it isn't just polygenic risk score or sequencing, which we could get.
[00:23:26.520 --> 00:23:31.720] It's also become very inexpensive, but it's all these other layers of data that we've been talking about.
[00:23:31.720 --> 00:23:36.280] The point about that is: let's say the polygenic risk score is wrong or off a bit.
[00:23:36.280 --> 00:23:42.200] You've got all these other checkpoints of layers, and then you have multimodal AI to bring it all together.
[00:23:42.200 --> 00:23:51.160] And so, that's what gives us that pinpoint precision, both with respect to time, you know, when this is going to be cropping up way in advance.
[00:23:51.160 --> 00:23:56.200] And that's when we get all of these people to work with them to prevent the disease.
[00:23:56.200 --> 00:24:06.440] And, of course, that could be the lifestyle plus factors, or it could be drugs and other means, and even more high-tech ways to go into surveillance.
[00:24:06.440 --> 00:24:10.440] So, we have a path to do this for the big three diseases.
[00:24:10.440 --> 00:24:12.040] We just got to get moving on it.
[00:24:12.040 --> 00:24:14.280] I want to unpack that because there's a lot there you said.
[00:24:14.600 --> 00:24:20.280] I want to just ask you a question, though, before we dive into the big three, which is heart disease, cancer, and dementia.
[00:24:20.360 --> 00:24:21.560] You left out diabetes.
[00:24:21.720 --> 00:24:23.560] Yeah, I'm wondering why you left that out.
[00:24:23.560 --> 00:24:26.520] Yeah, because it's sort of the cause of all three of those things.
[00:24:26.680 --> 00:24:27.480] Well, that's right.
[00:24:27.480 --> 00:24:30.680] Diabetes by itself, you know, we can handle that.
[00:24:30.680 --> 00:24:34.040] But the problem with diabetes is it leads to the other three.
[00:24:34.040 --> 00:24:37.480] The other three are the big ones we have to work with.
[00:24:37.480 --> 00:24:41.160] And diabetes isn't necessarily age-related.
[00:24:41.160 --> 00:24:44.440] There's some of that, but it's not nearly like the other three.
[00:24:44.440 --> 00:24:47.280] And it doesn't have the 20-year lead time to work with.
[00:24:47.520 --> 00:24:56.880] So there's a lot of reasons why, although diabetes is considered a killer, certainly can compromise health span, it's mainly working through the other three.
[00:24:56.880 --> 00:25:07.200] You know, people are not dying of diabetes, but they're dying of the heart-related kidney, you know, other sequela, certainly more dementia and more cancer, too.
[00:25:07.200 --> 00:25:09.120] That's why I don't lump it in there.
[00:25:09.120 --> 00:25:12.320] But I think the prototype is Alzheimer's.
[00:25:12.320 --> 00:25:15.440] You saw, I wrote in the book and then also a substack.
[00:25:15.440 --> 00:25:18.720] There's this breakthrough test, the PTAU217.
[00:25:19.200 --> 00:25:35.760] And if you are APOE4, I mean, if you're a carrier, that's 25% of us are carriers, or you have a family history of Alzheimer's, or both, you probably want to get a PTAU217 because it's as good as a cerebral spinal fluid.
[00:25:35.760 --> 00:25:41.680] It's as good as a pet cow scan, you know, which is a lot of radiation and hard to get.
[00:25:42.080 --> 00:25:46.160] And CT scan in the brain, but it's expensive and radiation and hard to get.
[00:25:46.160 --> 00:25:49.920] Yeah, and here you've got a blood test, which is not that expensive.
[00:25:49.920 --> 00:25:52.560] It's available in this country for the past two years.
[00:25:52.560 --> 00:25:55.120] And you know, Mark, most people never heard of it.
[00:25:55.120 --> 00:25:57.760] I think it's part of your function tests that you do.
[00:25:57.920 --> 00:25:58.320] It is.
[00:25:58.320 --> 00:25:58.720] It is.
[00:25:59.040 --> 00:26:00.320] I added that.
[00:26:00.640 --> 00:26:05.120] Yeah, I don't know all the tests that you do in that, but that one is a good one.
[00:26:05.120 --> 00:26:18.880] So then you know you have, if you have, I don't recommend everybody getting this, but if you have APOE4 and you have family history, now you know with the P-TAU test, and you can get a brain clock, okay?
[00:26:19.200 --> 00:26:20.800] You can even get a methylation clock.
[00:26:20.800 --> 00:26:22.800] You've got these layers of data now, right?
[00:26:22.800 --> 00:26:27.200] And you also know about your lifestyle and what's good and what's not so good about it.
[00:26:27.200 --> 00:26:33.240] Now you find, oh, P-Tau-217 is elevated substantially, let's say.
[00:26:33.560 --> 00:26:36.600] Well, this is like an LDL cholesterol, right?
[00:26:36.600 --> 00:26:41.800] Because if you exercise and you go into a healthy lifestyle, you can bring it down.
[00:26:41.800 --> 00:26:52.920] And we've seen a randomized study presented here in San Diego at the Academy of Neurology annual meeting where they had these, the people who had PTAU217 elevated.
[00:26:53.160 --> 00:26:57.480] They were randomly assigned to intervention with lifestyle.
[00:26:57.480 --> 00:27:06.600] And it came way down, you know, P217, PTAW 181, all these markers, 75, up to 75% reduction.
[00:27:06.600 --> 00:27:14.280] That should reduce or, you know, the chances of ever developing Alzheimer's, particularly if it started early.
[00:27:14.280 --> 00:27:20.600] And then, of course, if the person started late, it should put it off, should defer it.
[00:27:20.600 --> 00:27:22.040] So this is exciting.
[00:27:22.040 --> 00:27:25.800] And I'm just amazed that most people don't know about this test.
[00:27:25.800 --> 00:27:26.440] No, I agree.
[00:27:26.760 --> 00:27:30.520] I want to just double down on that because what you're saying is so revolutionary.
[00:27:30.520 --> 00:27:39.480] You know, up till now, basically, if you had a family history of Alzheimer's, you had to cross your fingers and, you know, wait around and hope to not get it.
[00:27:39.480 --> 00:27:46.440] And there wasn't anything we offered for medicine that was going to prevent it or even treat it once you got it.
[00:27:46.440 --> 00:27:47.880] So it was kind of a scary thing.
[00:27:47.880 --> 00:27:51.640] And nobody wanted to know their APOE status because it's like, well, why should I know?
[00:27:51.640 --> 00:27:53.720] Because what am I going to do about it?
[00:27:53.720 --> 00:27:54.280] Yeah.
[00:27:54.280 --> 00:28:05.000] And I think, you know, what we've learned is that now with early biomarker testing, and like you said, these developed 20, 30, 40 years before you ever forget something, right?
[00:28:05.000 --> 00:28:07.640] You forget your keys or you start having memory loss.
[00:28:07.640 --> 00:28:16.240] You can start to see these early clues in your blood and you layer on top of that proteomics, layer on top of that AI to interpret it all.
[00:28:16.240 --> 00:28:21.520] And all of a sudden you have a window into where you might be headed that you can do something about.
[00:28:14.920 --> 00:28:21.760] Yeah.
[00:28:22.000 --> 00:28:38.080] And I think trials like the finger trial and the pointer trial are these large clinical trials that show while all the drugs we have for Alzheimer's have failed, the lifestyle interventions can slow, prevent, slow, and even reverse sometimes the changes that we see.
[00:28:38.080 --> 00:28:49.760] And I think Richard Isaac's work is very exciting about PTAW217 because it's like you can actually start to see how we can actually even reverse it once you start to have it, which is a pretty good idea.
[00:28:49.760 --> 00:29:04.160] That's what's the difference where we were a few years ago to where we are now is that we know that these markers are so accurate and we can use them to see if we're making progress.
[00:29:04.160 --> 00:29:15.680] Okay, so you have the, let's say, the brain organ clock and the p-tau 217 and someone who clearly has a high risk of Alzheimer's and you go six months with this new lifestyle, right?
[00:29:15.680 --> 00:29:22.480] And you see, oh, wow, the brain pace of aging is slowing down and the p-tau 217 has come down 50%.
[00:29:22.480 --> 00:29:24.080] You say, this is working.
[00:29:24.080 --> 00:29:26.320] And if you want, you can do imaging, of course.
[00:29:26.320 --> 00:29:39.200] But this is extraordinary because now we have the GLP-1 drugs like Ozempic, Munjaro, that are being tested in big Alzheimer's trial in thin people.
[00:29:39.600 --> 00:29:41.600] These are not obese or overweight.
[00:29:41.840 --> 00:29:42.640] These are thin people.
[00:29:43.200 --> 00:29:48.320] And because they have such potency of reducing brain inflammation.
[00:29:48.320 --> 00:29:56.320] So, we're not talking about the drugs that are being used for Alzheimer's, which don't work very well and are very risky and can cause hemorrhage in the brain.
[00:29:56.320 --> 00:30:00.360] These are drugs that have been out there, you know, 20-some years.
[00:29:59.920 --> 00:30:02.920] You know, I have a whole chapter in the book is how we blew it.
[00:30:03.160 --> 00:30:14.680] We thought they were only good for diabetes, you know, and it took this scientist in Denmark, Lata Knudsen, who kept pushing, we have to try it, we have to try it in obesity.
[00:30:14.680 --> 00:30:21.400] And they kept saying to her, Well, Lata, it's not going to work because the diabetics only lose three or four pounds.
[00:30:21.400 --> 00:30:28.120] Well, now we see we can get people to lose, you know, 40, 50, 60, 80 pounds.
[00:30:28.440 --> 00:30:30.200] These drugs are so potent.
[00:30:30.200 --> 00:30:39.720] And the reason it was blown was because the diabetics don't lose that weight, and we don't know why still today, which is such a mystery, right?
[00:30:40.040 --> 00:30:42.600] But what if it works in Alzheimer's?
[00:30:42.600 --> 00:30:54.680] Because it's working in so many other ways in terms of addiction, in terms of all these other cardiovascular, many conditions that we did not expect.
[00:30:54.680 --> 00:31:03.400] So, even if it doesn't work, there's other drugs, many other drugs that get well into the brain that knock down brain inflammation like GLP-1.
[00:31:03.400 --> 00:31:08.920] And so, we're going to have drugs for people who are at high risk for Alzheimer's to add to the lifestyle factors.
[00:31:08.920 --> 00:31:16.600] But of course, you want to press on the lifestyle stuff first before you ever really start with the drug.
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[00:33:04.080 --> 00:33:12.240] So, so you're someone who's listening, you go get this test, you're in your 40s, shows up as something that's a little bit elevated.
[00:33:12.240 --> 00:33:13.040] What do you do?
[00:33:13.040 --> 00:33:17.040] Yeah, well, first, don't get the test unless you have the risk factors, right?
[00:33:17.040 --> 00:33:24.560] I mean, you don't really want to get this without ApoE4 status or at least Alzheimer's in your family, right?
[00:33:24.560 --> 00:33:40.600] Because, or a polygenic risk score, even that says you're high-risk for Alzheimer's, something like that, because if you get tests that are not, you don't have a high test pre probability, as you know, you're going to get potentially false positives.
[00:33:40.600 --> 00:33:51.880] And the American Alzheimer's Association, which I think has some problems, they're labeling people with peak tau 217 as stage one Alzheimer's if it's elevated.
[00:33:51.880 --> 00:33:54.120] That's not good because it could be wrong.
[00:33:54.120 --> 00:33:57.960] Any test could be wrong, especially if it's done on the wrong people.
[00:33:57.960 --> 00:34:07.400] So, as long as I'm admonishing that get the test only if you have increased risk, and if it's elevated, then you're going to go on a campaign to bring it down.
[00:34:07.400 --> 00:34:15.080] And no, since you're saying a person's young in their 40s or 50s, they got lots of time to really get on it.
[00:34:15.080 --> 00:34:20.120] And, you know, within a few years, we're going to have a lot more additional ways to bring that down.
[00:34:20.120 --> 00:34:30.520] But just, I mean, the lifestyle story, it's hard to get people to adopt all these healthy behaviors, particularly get isn't just a behavior.
[00:34:30.520 --> 00:34:36.680] How do you get a lot more deep sleep, for example, a lot more sleep regularity, which has big impact?
[00:34:36.680 --> 00:34:37.880] That's not even a behavior.
[00:34:37.880 --> 00:34:41.480] That's just something that people have to learn how to improve.
[00:34:41.480 --> 00:34:51.800] The fact when you get into this aggressive prevention mode, it's more likely that people are going to take it seriously if they have this marker aligned with their risk.
[00:34:51.800 --> 00:35:03.800] So, in terms of the lifestyle, that's sort of a generic term, but let's kind of break it down to diet, exercise, sleep, stress, relationships, I mean, toxins, you call it lifestyle plus.
[00:35:03.800 --> 00:35:04.360] Yeah.
[00:35:04.680 --> 00:35:06.600] What are the biggest levers to pull?
[00:35:06.600 --> 00:35:15.920] Well, if we start with a diet, you know, I think you've been on this, but the ultra-processed foods are just horrendous, right?
[00:35:14.920 --> 00:35:21.680] They are the vectors of inflammation in our body, and they are propagating.
[00:35:21.840 --> 00:35:28.640] They are, I think, we're talking about cause and effect of these three age-related diseases.
[00:35:28.640 --> 00:35:29.440] And the U.S.
[00:35:29.440 --> 00:35:33.920] has the highest consumption in the world, 70% plus.
[00:35:34.240 --> 00:35:38.240] And of course, a lot of people are 80% or more.
[00:35:38.240 --> 00:35:39.840] And in the book, you know, I review.
[00:35:39.840 --> 00:35:40.640] Yeah, that's average.
[00:35:40.640 --> 00:35:41.200] That's average.
[00:35:41.520 --> 00:35:42.160] Yeah, yeah.
[00:35:42.160 --> 00:35:44.160] Children high, very high.
[00:35:44.480 --> 00:35:50.080] And I review in the book of my friend Chris Vontullikin, who wrote the book, Ultra Processed People.
[00:35:50.080 --> 00:35:56.880] And, you know, he went on like a 30-day, and he's a really great physician scientist in the UK.
[00:35:56.880 --> 00:35:59.200] And it told the whole story.
[00:35:59.200 --> 00:36:01.120] He had a brain scan beforehand.
[00:36:01.120 --> 00:36:04.400] He had all these inflammation markers beforehand.
[00:36:04.400 --> 00:36:10.160] And in 30 days, kind of like supersize me, he tried to go as high as he could on ultra-processed food.
[00:36:10.160 --> 00:36:14.640] By the time the 30 days was up, his brain was all inflamed.
[00:36:14.880 --> 00:36:19.280] Every biomarker had gone through the ceiling of abnormality for inflammation.
[00:36:19.280 --> 00:36:21.600] I mean, it was just 30 days of this bad diet.
[00:36:21.600 --> 00:36:23.120] He gained 20 pounds.
[00:36:23.440 --> 00:36:27.920] You know, this is something we have to work on.
[00:36:28.400 --> 00:36:31.680] It's just, we've done nothing in this country to bring it down.
[00:36:31.680 --> 00:36:34.000] Other countries are taking it more seriously.
[00:36:34.000 --> 00:36:38.960] The second thing about the diet, which I think is vital, is the protein craze.
[00:36:38.960 --> 00:36:43.280] We have people out there that are advocating ridiculous amounts of protein.
[00:36:43.280 --> 00:37:00.520] And I reviewed that in the book, that there's danger with that, not only for the kidneys, but also we've seen studies after study that show too high a protein diet, particularly animal protein, can induce, promote atherosclerosis.
[00:37:00.520 --> 00:37:02.440] That's the last thing we want, right?
[00:37:00.000 --> 00:37:03.720] It's pro-inflammatory.
[00:37:03.960 --> 00:37:17.560] So that's why, although it's probably wise if we keep up a decent amount of protein, maybe amp it up a bit as we get older, you know, maybe 1.2, 1.4, or so per kilogram, not per pound.
[00:37:17.560 --> 00:37:19.400] And that's what some people are advocating.
[00:37:19.400 --> 00:37:20.600] And that's just wrong.
[00:37:21.080 --> 00:37:21.880] It's dangerous.
[00:37:21.880 --> 00:37:23.640] There's no data to support it.
[00:37:23.640 --> 00:37:34.680] You know, I talk to people who are on this protein craze, and I try to get them onto the data and the evidence, which is, you know, really a danger sign if they go too high on a daily.
[00:37:34.680 --> 00:37:41.240] And it's not going to increase their muscle mass when you go past good studies, 1.5, 1.6 per kilogram.
[00:37:41.240 --> 00:37:43.400] So those are a couple of the main things.
[00:37:43.400 --> 00:37:48.840] I don't know what you think about that, but a couple of main things about the diet that we need to get out there.
[00:37:48.840 --> 00:37:52.920] And the sugar, the sugar and the starch, too, is just a component of the ultra-processed food.
[00:37:52.920 --> 00:37:56.120] But I think that's part of the driver of what's causing a lot of the problem.
[00:37:56.120 --> 00:37:59.640] And it is, you know, they're calling Alzheimer's type 3 diabetes, right?
[00:37:59.640 --> 00:38:01.160] Diabetes of the brain.
[00:38:01.160 --> 00:38:04.920] And I think that's a big factor for people, the amount of sugar and starch.
[00:38:04.920 --> 00:38:07.240] And it's obviously hidden in the ultra-processed food.
[00:38:07.240 --> 00:38:07.320] Yeah.
[00:38:07.480 --> 00:38:08.760] I think the protein thing is interesting.
[00:38:08.760 --> 00:38:11.880] I mean, I think, what were we going to say something about the sugar thing?
[00:38:12.280 --> 00:38:13.240] I think I agree with you.
[00:38:13.400 --> 00:38:17.400] I reviewed the sugar story, salt, caffeine, alcohol.
[00:38:17.400 --> 00:38:19.240] I mean, we went through every one of these things.
[00:38:19.240 --> 00:38:22.760] Everything you eat, fats and plant-based diets and red meat.
[00:38:22.760 --> 00:38:24.440] And I went through the whole thing.
[00:38:24.440 --> 00:38:30.840] And you're familiar with this recent study of 105,000 people followed 30 years.
[00:38:30.840 --> 00:38:38.040] And only 9% of them, only 9% got to the welderly state past age seven.
[00:38:38.040 --> 00:38:40.120] And the 9%, what do they eat?
[00:38:40.120 --> 00:38:46.640] They mainly play at plant-based foods, Mediterranean diet, some, but small amounts of red meat.
[00:38:44.840 --> 00:38:51.920] The kinds of things you would anticipate, where the data evidence is backing it up.
[00:38:52.240 --> 00:38:54.640] So, yeah, the diet is really important.
[00:38:54.640 --> 00:38:57.920] And we keep seeing study after study reinforcing that.
[00:38:57.920 --> 00:39:00.960] I think one of the things that's important, AJ, those, is being functional.
[00:39:00.960 --> 00:39:02.960] Frailty is the killer.
[00:39:02.960 --> 00:39:07.680] I mean, hip fracture is a bigger risk for death than getting a diagnosis of cancer.
[00:39:08.000 --> 00:39:09.680] That muscle mass is a big deal.
[00:39:10.000 --> 00:39:30.160] And the question is, that's the problem as you get older because when you lose it and it's hard to build it, and there's something called anabolic resistance, meaning when you're older, it takes a lot more work and a lot more protein to do the same thing you did when you had these trophic or growth hormone-like things when you were younger, anabolic hormones that were floating around your blood.
[00:39:30.480 --> 00:39:36.480] And the Protege group, which is a group of protein scientists led by Don Lehman and others, and I've had him on the podcast.
[00:39:36.480 --> 00:39:43.360] He talks about even higher amounts being eaten, like, you know, one up to one and a half to two grams per kilo.
[00:39:43.680 --> 00:40:01.200] And this was like a, I'm not a protein expert, but it was interesting to read their data showing that there was this, to overcome this resistance and the need to maintain muscle mass, that their data was like the kind of global think tank on, I don't know, protein experts together and they came up with.
[00:40:01.520 --> 00:40:09.280] I reviewed all that data and I would just say, you know, if you're going to go past 1.5, 1.6 per kilogram, you're starting to get to a fuzzy zone.
[00:40:09.520 --> 00:40:18.560] But Mark, you can increase your muscle mass not by just, you know, having adequate protein, by doing strength training.
[00:40:18.560 --> 00:40:28.240] And I gotta do that heavy over the last year because after all the research, you know, I always advocated aerobic exercise as a cardiologist.
[00:40:28.720 --> 00:40:29.560] Cardiologists, right?
[00:40:29.440 --> 00:40:34.520] And these people, patients would come in and they were really cut and buffed.
[00:40:34.520 --> 00:40:36.840] And I'd say, well, what are you doing lifting all these weights?
[00:40:29.760 --> 00:40:37.000] Right.
[00:40:37.320 --> 00:40:52.920] Well, now I'm doing that, not maybe as trying to be any like the Terminator, but I've been on a big kick on, you know, resistance and strength training, balance, posture, you know, but also I've never been this strong in my life.
[00:40:52.920 --> 00:40:55.720] And I don't need crazy amounts of protein.
[00:40:55.720 --> 00:40:58.920] The point being is it's part of the exercise.
[00:40:58.920 --> 00:41:02.280] It isn't like you just change your diet and you build up muscles, right?
[00:41:02.280 --> 00:41:04.360] It's the exercise that's so essential.
[00:41:04.360 --> 00:41:15.400] And by the way, the data for resistance training, as I review in the book with various graphs, it's extraordinary for preventing age-related, the big three.
[00:41:15.400 --> 00:41:17.160] So we should be doing that.
[00:41:17.160 --> 00:41:18.360] I learned from that.
[00:41:18.360 --> 00:41:21.400] I didn't realize how impressive that body of data was.
[00:41:21.400 --> 00:41:22.520] Yeah, you and me both.
[00:41:22.520 --> 00:41:25.080] When I was 15 on, I'm like, yeah, I better start strength training.
[00:41:25.080 --> 00:41:26.600] And it's changed my life.
[00:41:26.600 --> 00:41:29.160] And my body, I picture with me when I'm 40, and I was a runner.
[00:41:29.240 --> 00:41:30.120] I was into yoga.
[00:41:30.120 --> 00:41:31.320] I wasn't overweight.
[00:41:31.320 --> 00:41:35.720] But like, my body looked like I was like a skinny little rail compared to now.
[00:41:35.720 --> 00:41:44.840] I'm not like, you know, the Terminator or the rock, but I'm like, you know, at 65, beefier than I've ever been in my whole life.
[00:41:45.160 --> 00:41:49.880] And I was like, wow, this is for me, it's the same crazy as possible.
[00:41:50.120 --> 00:41:52.840] I think this is a really important step.
[00:41:52.840 --> 00:41:58.360] And then the other biggie is, of course, the deep sleep story and regularity.
[00:41:58.360 --> 00:41:59.880] I mentioned it earlier.
[00:41:59.880 --> 00:42:09.960] We need to get, as we get older and going along, as you said, with the inflammaging, is that we don't get enough sleep as we get older, particularly the slow wave deep sleep.
[00:42:09.960 --> 00:42:11.560] And we've got to get that up.
[00:42:11.560 --> 00:42:17.200] When I started looking at that data, I was horrified because I'm not a very good sleep, I had not been a good sleeper.
[00:42:14.760 --> 00:42:20.800] And I started tracking it with a ring and a smartwatch.
[00:42:20.960 --> 00:42:29.360] I'm saying, wow, I'm getting less than 15 minutes of deep sleep a night, you know, and terrible overall scores in my sleep because of that.
[00:42:29.360 --> 00:42:33.200] And so I started finding out what is causing all this problem, right?
[00:42:33.200 --> 00:42:39.920] And because I had very, you know, irregular times of going to sleep, you know, erratic.
[00:42:39.920 --> 00:42:48.320] And what I ate, what I drank, when I exercised, you know, when I ate, all these factors were playing such a big role.
[00:42:48.400 --> 00:42:53.520] Now I've been able to get, it's rare that I wouldn't get over 45 minutes a night, even up to an hour.
[00:42:53.520 --> 00:42:55.040] So it's been a big difference.
[00:42:55.040 --> 00:42:55.840] So I know that.
[00:42:56.240 --> 00:42:57.200] What did you do?
[00:42:57.200 --> 00:42:59.360] Oh, what were the things that made a difference?
[00:42:59.360 --> 00:43:09.760] Yeah, so all these things cumulatively by tracking, learning, like, for example, not exercising too late in the day, not eating too late in the day, you know, in the evening.
[00:43:09.760 --> 00:43:17.440] Interestingly, alcohol affects many people with respect to deep sleep, but that one didn't seem to have too much of an effect on me.
[00:43:17.440 --> 00:43:29.200] Avoiding drinking too much of fluids and then avoiding having to get up, interrupted sleep, made a big difference during the night because I always be hydrating, you know, in the evenings.
[00:43:29.360 --> 00:43:32.720] No, don't hydrate all day long, but don't hydrate in the evening.
[00:43:32.720 --> 00:43:46.080] So lots of things that I did, but you know, the timing and also certain foods, you know, I was basically, I wasn't aware of it, but you know, the indigestion was interrupting sleep somehow.
[00:43:46.400 --> 00:43:54.880] So certain foods, and also, I think there's these interactions, you know, stress and things that we all deal with.
[00:43:54.880 --> 00:43:59.040] I learned about better coping mechanisms to get sleep.
[00:43:59.040 --> 00:44:06.360] And I still like to amp it up more because that data that I review in super ages, it's very impressive.
[00:44:06.600 --> 00:44:15.000] The link between the deep sleep, which is when we get rid of the toxic waste metabolites in our brain.
[00:44:15.000 --> 00:44:15.880] That's the time.
[00:44:15.880 --> 00:44:22.120] And by the way, I know we both see patients that take ambien and other sleep medicines.
[00:44:22.120 --> 00:44:26.040] And what's interesting is that they backfire.
[00:44:26.040 --> 00:44:34.680] Not only do they not get rid of the waste, but they actually increase ambiences, especially been noted to increase the waste that stays in the brain.
[00:44:34.680 --> 00:44:38.280] So the person may feel like they're getting more sleep, but they're not.
[00:44:38.280 --> 00:44:46.600] And of course, along the way, I didn't have it, but certainly one of the concerns I had with that low amount of deep sleep was: did I have sleep apnea?
[00:44:46.600 --> 00:44:47.880] Was that the issue?
[00:44:47.880 --> 00:44:49.640] And that fortunately wasn't the case.
[00:44:49.640 --> 00:44:53.080] But as you know, that's a common problem that doesn't get diagnosed.
[00:44:53.080 --> 00:44:56.920] So it sounds like writing the book helped you live longer because you learn all these things.
[00:44:57.080 --> 00:44:57.400] I don't know.
[00:44:57.640 --> 00:44:59.160] Like you hadn't known before.
[00:45:00.120 --> 00:45:01.160] But those are powerful drugs.
[00:45:01.160 --> 00:45:01.720] Time will be.
[00:45:02.200 --> 00:45:06.120] I mean, strength training is a powerful drug, and sleep is a powerful drug.
[00:45:06.440 --> 00:45:06.760] Yes.
[00:45:07.000 --> 00:45:09.240] They're better than most of the drugs we have, actually.
[00:45:09.240 --> 00:45:09.640] It did.
[00:45:09.640 --> 00:45:18.920] It helped me, but of course, I wasn't going to, once I reviewed all the evidence and I felt compelling, that led me to change my ways.
[00:45:18.920 --> 00:45:21.720] And I'm hoping that's going to help a lot of other people too.
[00:45:21.720 --> 00:45:25.640] But I don't know if it's going to make me into the welderly.
[00:45:25.880 --> 00:45:33.400] With my family history, it's always in my mind, despite our welderly trial study, that, you know, I may not get into the.
[00:45:33.400 --> 00:45:37.080] So far, I fit, I don't have any age-related chronic disease.
[00:45:37.080 --> 00:45:39.960] And I hope I can go another, you know, 10, 20 years.
[00:45:39.960 --> 00:45:40.520] We'll see.
[00:45:40.520 --> 00:45:41.960] Well, I think you're a few years older than me.
[00:45:41.960 --> 00:45:45.440] And if you've escaped those diseases by now, you're probably kind of dodged the bullet.
[00:45:46.080 --> 00:45:46.960] I hope so.
[00:45:44.920 --> 00:45:51.600] I mean, but the main thing is, I wanted to get the hard evidence out there.
[00:45:51.920 --> 00:46:17.040] I wanted to get so people know that there is a huge body of evidence that is not Brian Johnson, don't die, or other longevity clinics that charge $250,000 that do hyperbaric chambers, plasmapheresis, all these putative anti-aging supplements, none of which have any data, you know, all this kind of reckless use of things.
[00:46:17.040 --> 00:46:22.160] I wanted to just put it out there that, hey, this is what we know, and it can make a world of difference.
[00:46:22.160 --> 00:46:25.600] And a lot of this stuff is not very expensive either, you know.
[00:46:25.840 --> 00:46:28.000] So that was the real purpose of doing the book.
[00:46:28.000 --> 00:46:32.720] And I just, as a, as an outgrowth, it helped me too.
[00:46:32.720 --> 00:46:35.280] Yeah, I think the things that work the best cost the least.
[00:46:35.520 --> 00:46:35.840] Yeah.
[00:46:35.840 --> 00:46:36.240] Yeah.
[00:46:36.240 --> 00:46:38.000] Eating well doesn't have to be very expensive.
[00:46:38.320 --> 00:46:40.480] Exercising is basically free.
[00:46:40.480 --> 00:46:43.920] You know, getting sleep and optimizing sleep is basically free.
[00:46:43.920 --> 00:46:44.320] Yeah.
[00:46:44.320 --> 00:46:47.600] Building relationships, connections, pretty much free.
[00:46:47.600 --> 00:47:01.200] You know, and yes, there may be things around the margin where we're going to learn in the future that maybe plasma phoresis helps, or maybe, you know, stem cells might help, or maybe some of these things that are under investigation now, like rapamycin may help.
[00:47:01.760 --> 00:47:08.160] But right now, they're edges, not the core of what people should be doing.
[00:47:08.160 --> 00:47:08.320] Yeah.
[00:47:09.760 --> 00:47:14.000] Majoring in the minors and minoring in the majors, you know, and I think that's a very good way to think about it.
[00:47:14.320 --> 00:47:19.200] We can do live a crappy lifestyle and take those drugs and things and actually think you're going to do much.
[00:47:19.200 --> 00:47:27.760] No, and all these things that people are, you know, trying to advance, like the rapamycin story, they have a danger too.
[00:47:27.760 --> 00:47:30.000] We can't measure the immune system, you know, routinely.
[00:47:30.360 --> 00:47:35.320] So, why are we taking an immunosuppressant drug, which in some people could be a big deal?
[00:47:35.320 --> 00:47:43.800] And if you look at this leaderboard of all the longevity researchers or influencers, they're all taking different doses.
[00:47:44.120 --> 00:47:47.560] It's like once a week, different dose once a day.
[00:47:47.560 --> 00:47:52.680] Nobody knows, but it's never been shown to have any benefit in people.
[00:47:52.680 --> 00:47:54.440] It's all in, you know, rodents.
[00:47:54.680 --> 00:48:07.560] Yeah, there was one trial I saw that was on elderly, and they found that if it was given intermittently, it actually improved their response to vaccines and actually helped their immune system function better, whereas continuous dosing didn't.
[00:48:07.560 --> 00:48:11.640] And I think there's mTOR1 and MTOR2, which have different roles in immunity.
[00:48:11.640 --> 00:48:15.160] And so, I mean, that story is still getting unpacked, but I find it interesting.
[00:48:15.720 --> 00:48:19.720] But again, it's like if you don't do the basics right, that still doesn't matter.
[00:48:19.720 --> 00:48:20.120] Right.
[00:48:20.120 --> 00:48:23.640] We don't know of any studies, you know, that are real.
[00:48:23.880 --> 00:48:29.000] Those are these small studies that in a limited number of people, they're not major endpoints.
[00:48:29.000 --> 00:48:37.000] But, you know, one thing that's interesting, Mark, is, you know, Steve Horovath, who had came up with the Horovath clock we were talking about, that epigenetic.
[00:48:37.000 --> 00:48:48.280] The only two things so far that have decreased biologic aging from that clock are exercise and then more recently, the GLP-1 drugs.
[00:48:48.280 --> 00:48:49.880] I mean, that's kind of interesting.
[00:48:49.880 --> 00:48:53.000] That's body-wide biologic aging.
[00:48:53.160 --> 00:48:59.320] What we haven't seen any studies that that's been accomplished through these other things like rapamycin.
[00:48:59.320 --> 00:49:13.080] So I welcome, I mean, if rapamycin works or metformin or whatever, I want these things to succeed, but I don't want people to jump to that unless we have the evidence because all these carry some risk.
[00:49:13.080 --> 00:49:23.040] I mean, metformin carries less risk than rapamycin because it doesn't cause immunosuppression, but it isn't something that we know is going to promote healthy aging.
[00:49:23.040 --> 00:49:39.680] But it does, but it does inhibit mitochondrial complex one, which worries me because with progressive resistance training compared to placebo with and without metformin, if you did a strength training with metformin, you didn't get the same response to building muscle, which really got like, I was like, oh boy.
[00:49:39.680 --> 00:49:41.200] Yeah, that's not a good thing.
[00:49:41.200 --> 00:49:43.680] I think, yeah, there may be like you're making a good point.
[00:49:43.680 --> 00:49:44.320] You really are.
[00:49:44.480 --> 00:49:45.200] This is really exciting.
[00:49:45.200 --> 00:49:58.240] So basically, Alzheimer's and dementia, the take-home is there's biomarkers now that we can detect early, both genetic risks combined with blood tests that give us an early indication that we should get on it.
[00:49:58.240 --> 00:50:05.120] And then the getting on it part, there's a lot of things we can do, lifestyle plus all the things we talked about.
[00:50:05.440 --> 00:50:07.440] And there's more for sure that we could unpack.
[00:50:07.440 --> 00:50:09.120] So I want to kind of get to the other ones.
[00:50:09.360 --> 00:50:10.160] Heart disease.
[00:50:10.160 --> 00:50:12.000] And this is your area of specialty.
[00:50:12.000 --> 00:50:15.440] Yes, but I just want to mention one thing.
[00:50:15.440 --> 00:50:28.560] You know, it's kind of chasing our tails, but the environment in terms of air pollution, in terms of microplastics, nanoplastics, and also, of course, forever chemicals.
[00:50:28.560 --> 00:50:41.840] These things are, you know, all three are inflammation inducers that are increasing our toll of age-related diseases, the big three, and diabetes too, for that matter.
[00:50:41.840 --> 00:50:44.160] So, you know, we're not doing enough about these.
[00:50:44.160 --> 00:50:49.360] And I think this is something that you've been working on for quite some time.
[00:50:49.360 --> 00:50:55.520] We got to get serious about this because any advances that we're going to make, we're going to talk about cardiovascular in a moment here.
[00:50:55.520 --> 00:51:00.600] We got to, these are the things that are taking a big toll on us.
[00:51:00.600 --> 00:51:06.120] Because, for example, the plastic story, let's just talk about that for a second in the heart.
[00:51:06.120 --> 00:51:20.760] The big study from Italy, multiple centers, where they took the carotid artery plaque at the time of surgery and they looked to see if there was plastics, microplastics, nanoplastics in the artery plaque.
[00:51:20.760 --> 00:51:23.800] And they found it in over 60% of people.
[00:51:24.120 --> 00:51:30.440] And that artery under the microscope was grossly inflamed right around where the plastics were.
[00:51:30.440 --> 00:51:31.400] During follow-up.
[00:51:31.560 --> 00:51:32.680] Was it a dose response?
[00:51:32.920 --> 00:51:34.200] Like, in other words, the more plastics?
[00:51:34.280 --> 00:51:36.920] The more plastics, the more vicious inflammation.
[00:51:37.240 --> 00:51:58.760] And what was even worse is the people who had the plastics followed versus those who didn't have plastics in their plaque had a four to five-fold increase of heart attacks, strokes, and death compared to those without the plastic that was basically establishing residence in their arteries.
[00:51:58.760 --> 00:52:08.680] And so, as we talk about cardiovascular now, preventing heart disease, you know, we got to factor in that particular thing because the plastics are everywhere.
[00:52:08.920 --> 00:52:10.840] They're not degradable.
[00:52:10.840 --> 00:52:13.240] And there were just, you know, more and more of them.
[00:52:13.240 --> 00:52:14.360] We got to do something about it.
[00:52:14.360 --> 00:52:15.640] But for the heart, this is where.
[00:52:16.040 --> 00:52:18.120] I want to just double down before you get in the heart.
[00:52:18.120 --> 00:52:33.240] I want to just double-click on this because, you know, what you're saying, people go, yeah, toxins, but to have a traditional physician who's got the credentials that you have saying that toxins are something we should pay attention to is near heresy when it comes to traditional medicine.
[00:52:33.400 --> 00:52:36.680] It's something I've been talking about for decades because I've seen it.
[00:52:37.080 --> 00:52:38.680] And when you look for it, you see it.
[00:52:38.680 --> 00:52:40.760] Even when you look at the literature, it's been there.
[00:52:41.160 --> 00:52:43.880] It's just been ignored because doctors don't know what to do about it.
[00:52:43.880 --> 00:52:47.200] Because they go, okay, well, you do your exposure by doing this and that and the other thing.
[00:52:47.200 --> 00:52:51.040] But this is something that I think is going to be an important thing to be investigated.
[00:52:51.280 --> 00:52:53.680] How do we measure our toxic load?
[00:52:53.680 --> 00:53:06.480] How do we start to help the body detoxify by supporting its both internal detoxification systems like the liver and the kidneys and the colon and the skin and sweat and all the things?
[00:53:06.640 --> 00:53:08.880] How do we actually help the body detoxify?
[00:53:08.880 --> 00:53:13.840] And what are novel methods of detoxification that we might want to think about when it comes to these compounds?
[00:53:13.840 --> 00:53:16.320] Because they're everywhere and we're all polluted.
[00:53:16.800 --> 00:53:17.920] Well, I think you're right.
[00:53:17.920 --> 00:53:20.960] They do play a huge role in all these diseases of aging.
[00:53:20.960 --> 00:53:21.520] You're right.
[00:53:21.520 --> 00:53:26.160] I mean, the dirty air and the dirty water, the things we drink.
[00:53:26.160 --> 00:53:28.960] So the plastics, of course, are pervasive.
[00:53:28.960 --> 00:53:36.240] And we can do some things at an individual family level, you know, in terms of not having things stored in the plastics.
[00:53:36.240 --> 00:53:42.480] And like the worst case scenario is you take something, food that you have in plastic and you put it in a microwave.
[00:53:42.480 --> 00:53:49.280] It's like microplastics you're going to eat at, you know, to the fourth power, right?
[00:53:49.280 --> 00:53:50.800] So there are some things we can do.
[00:53:50.800 --> 00:53:55.760] And, you know, just to everything we can to avoid the use of plastics.
[00:53:56.400 --> 00:54:00.240] But, you know, this is something we're not addressing.
[00:54:00.240 --> 00:54:03.920] And that's where the data are so incredibly strong.
[00:54:04.240 --> 00:54:05.360] And air pollution.
[00:54:05.360 --> 00:54:07.680] What are we doing about air quality?
[00:54:07.680 --> 00:54:16.880] Because the air quality, these fine particulate matter, 2.5 and smaller, they are the real incriminated.
[00:54:16.880 --> 00:54:22.640] They're the culprits for inflammation, big time increasing inflammation.
[00:54:22.640 --> 00:54:28.240] And, you know, for example, we have now young people, and we're going to get to cancer.
[00:54:28.240 --> 00:54:31.560] I don't mean to divert it from cardiovascular because that's my true love.
[00:54:31.720 --> 00:54:43.720] But the young people with cancer, why are people in their 20s and 30s presenting with colon cancer, breast cancer, and other cancers like we've never seen before?
[00:54:43.720 --> 00:54:48.680] Who, you know, what is the, could it be the ultra-processed food that they eat high amounts?
[00:54:48.680 --> 00:54:51.080] Could it be these environmental toxins?
[00:54:51.080 --> 00:54:53.720] Could it be, you know, the cumulative of all these things?
[00:54:53.720 --> 00:54:59.000] But something has got to give there because we're not, you know, we're not protecting our young people.
[00:54:59.000 --> 00:55:03.560] And we're seeing much more, a real spike in cancer.
[00:55:03.800 --> 00:55:08.120] These are age-related diseases we're actually seeing in young people, which is just horrible.
[00:55:08.120 --> 00:55:27.160] You know, there's literature around toxins that's been around, and even in heart disease, I remember reading a paper, I think it was the American Journal of Cardiology years ago, where they looked at anybody who had lead levels over two, which is considered normal because the level in the reference range is one to 10, but the normal level of lead is zero in the human body.
[00:55:27.160 --> 00:55:29.240] It's not like it required mineral.
[00:55:29.800 --> 00:55:38.440] That their risk of having a heart attack was higher or as high as those who had elevated cholesterol and an increased risk of strokes.
[00:55:38.440 --> 00:55:39.960] And it was a big risk factor.
[00:55:39.960 --> 00:55:50.280] And it was 39% of the population that had a lead level over two because we live in a world where there's coal burning and lead levels in the soil and stuff from historical exposure.
[00:55:50.280 --> 00:55:51.000] So you're right.
[00:55:51.000 --> 00:55:54.680] I mean, this toxin story is a big rabbit hole, and I've written a lot about that.
[00:55:54.760 --> 00:56:00.520] I talk a lot about it, but I think there's a lot of ways people can reduce their risks and reduce their exposures and not be crazy.
[00:56:00.520 --> 00:56:04.360] But there's ways to mitigate it and to help your body eliminate the toxins.
[00:56:04.360 --> 00:56:05.640] So I agree.
[00:56:05.640 --> 00:56:09.560] So let's talk about the heart disease prevention because people say, well, that story's been told.
[00:56:09.560 --> 00:56:13.160] You know, we've got statins, we've got this PC SK9 inhibitors.
[00:56:13.160 --> 00:56:13.800] We're all good.
[00:56:13.800 --> 00:56:14.800] Like, what's the big deal?
[00:56:14.800 --> 00:56:15.840] What should we worry about?
[00:56:15.840 --> 00:56:18.240] It's just all about LDL cholesterol.
[00:56:18.240 --> 00:56:19.200] What's new?
[00:56:14.520 --> 00:56:21.440] What should we be looking at?
[00:56:21.760 --> 00:56:23.360] What should we be thinking about?
[00:56:23.360 --> 00:56:27.840] And why are we still seeing so many people with heart disease?
[00:56:27.840 --> 00:56:31.280] Yeah, it's still the number one killer around the world, not just here.
[00:56:31.280 --> 00:56:35.280] And it's still the number one killer in women who, you know, they think that it's breast cancer.
[00:56:35.280 --> 00:56:37.120] No, no, it's this is it.
[00:56:37.120 --> 00:56:47.360] This is exciting because we do know the things that we've been reviewing for risk factors, but we have a way to now establish the risk.
[00:56:47.360 --> 00:56:52.160] Are they really high risk without before they ever have heart disease, 20 years plus?
[00:56:52.400 --> 00:57:02.080] And the way we do that is we can get a simple lipid panel, add the LP-little A, APO-B.
[00:57:02.400 --> 00:57:05.680] So a little more than what is the standard lipid panel.
[00:57:05.680 --> 00:57:09.360] The LP-little A will be part of a lipid panel in the next year or two.
[00:57:09.360 --> 00:57:17.200] But anyway, when we get that lipid panel, which is again very inexpensive, and we can also get a polygenic risk score, very inexpensive.
[00:57:17.200 --> 00:57:19.040] We can also get a heart clock, right?
[00:57:19.040 --> 00:57:21.040] And we can get inflammation markers.
[00:57:21.040 --> 00:57:29.840] Anyway, now you have the full stack with your records and you have somebody who is well before they've ever manifest heart disease.
[00:57:29.840 --> 00:57:33.200] And you say, oh, wow, this person is really high risk for heart disease.
[00:57:33.200 --> 00:57:34.240] What do we do?
[00:57:34.240 --> 00:57:39.600] Well, you get their LDL down, not just to below 70.
[00:57:39.600 --> 00:57:43.120] We go down to 20 or less than 30, right?
[00:57:43.120 --> 00:57:45.680] We have so many ways to do that now.
[00:57:45.920 --> 00:57:50.160] We have these injectables that are against this PCSK9.
[00:57:50.160 --> 00:57:56.720] We've got new drugs, five new LP-little A drugs that are going to be out within the next year or so that are really potent.
[00:57:56.800 --> 00:57:58.000] And we've had none of them.
[00:57:58.000 --> 00:57:58.960] None until now.
[00:57:58.960 --> 00:57:59.800] Yeah, we never had one.
[00:57:59.800 --> 00:58:02.920] We always tell, oh, too bad your LP-little A is over 100.
[00:58:02.920 --> 00:58:04.120] You know, nothing we can do.
[00:57:59.600 --> 00:58:06.760] We're going to be able to change that, and that's going to have a big impact.
[00:58:07.080 --> 00:58:11.160] We can get all the inflammation, get all over it, right?
[00:58:11.160 --> 00:58:18.280] In terms of bringing the inflammation down, we've already seen how GLP-1 drugs do that before any weight loss.
[00:58:18.280 --> 00:58:21.480] So that should work well in people who aren't even obese.
[00:58:21.480 --> 00:58:28.600] And we've seen how that can prevent heart, preserve ejection fraction, heart failure, which is half of all heart failure, right?
[00

Prompt 2: Key Takeaways

Now please extract the key takeaways from the transcript content I provided.

Extract the most important key takeaways from this part of the conversation. Use a single sentence statement (the key takeaway) rather than milquetoast descriptions like "the hosts discuss...". 

Limit the key takeaways to a maximum of 3. The key takeaways should be insightful and knowledge-additive. 

IMPORTANT: Return ONLY valid JSON, no explanations or markdown. Ensure:
- All strings are properly quoted and escaped
- No trailing commas
- All braces and brackets are balanced
Format: {"key_takeaways": ["takeaway 1", "takeaway 2"]}

Prompt 3: Segments

Now identify 2-4 distinct topical segments from this part of the conversation.

For each segment, identify:
- Descriptive title (3-6 words)  
- START timestamp when this topic begins (HH:MM:SS format)
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Most important Key takeaway from that segment. Key takeaway must be specific and knowledge-additive.
- Brief summary of the discussion

IMPORTANT: The timestamp should mark when the topic/segment STARTS, not a range. Look for topic transitions and conversation shifts.

Return ONLY valid JSON. Ensure all strings are properly quoted, no trailing commas:
{
  "segments": [
    {
      "segment_title": "Topic Discussion", 
      "timestamp": "01:15:30",
      "key_takeaway": "main point from this segment",
      "segment_summary": "brief description of what was discussed"
    }
  ]
}

Timestamp format: HH:MM:SS (e.g., 00:05:30, 01:22:45) marking the START of each segment.

Prompt 4: Media Mentions

Now scan the transcript content I provided for ACTUAL mentions of specific media titles:

Find explicit mentions of:
- Books (with specific titles)
- Movies (with specific titles)  
- TV Shows (with specific titles)
- Music/Songs (with specific titles)

DO NOT include:
- Websites, URLs, or web services
- Other podcasts or podcast names

IMPORTANT: 
- Only include items explicitly mentioned by name. Do not invent titles.
- Valid categories are: "Book", "Movie", "TV Show", "Music"
- Include the exact phrase where each item was mentioned
- Find the nearest proximate timestamp where it appears in the conversation
- THE TIMESTAMP OF THE MEDIA MENTION IS IMPORTANT - DO NOT INVENT TIMESTAMPS AND DO NOT MISATTRIBUTE TIMESTAMPS
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Timestamps are given as ranges, e.g. 01:13:42.520 --> 01:13:46.720. Use the EARLIER of the 2 timestamps in the range.

Return ONLY valid JSON. Ensure all strings are properly quoted and escaped, no trailing commas:
{
  "media_mentions": [
    {
      "title": "Exact Title as Mentioned",
      "category": "Book",
      "author_artist": "N/A",
      "context": "Brief context of why it was mentioned",
      "context_phrase": "The exact sentence or phrase where it was mentioned",
      "timestamp": "estimated time like 01:15:30"
    }
  ]
}

If no media is mentioned, return: {"media_mentions": []}

Prompt 5: Context Setup

You are an expert data extractor tasked with analyzing a podcast transcript. 
I will provide you with part 2 of 2 from a podcast transcript. 
I will then ask you to extract different types of information from this content in subsequent messages. Please confirm you have received and understood the transcript content.

Transcript section:
57:09.360 --> 00:57:17.200] But anyway, when we get that lipid panel, which is again very inexpensive, and we can also get a polygenic risk score, very inexpensive.
[00:57:17.200 --> 00:57:19.040] We can also get a heart clock, right?
[00:57:19.040 --> 00:57:21.040] And we can get inflammation markers.
[00:57:21.040 --> 00:57:29.840] Anyway, now you have the full stack with your records and you have somebody who is well before they've ever manifest heart disease.
[00:57:29.840 --> 00:57:33.200] And you say, oh, wow, this person is really high risk for heart disease.
[00:57:33.200 --> 00:57:34.240] What do we do?
[00:57:34.240 --> 00:57:39.600] Well, you get their LDL down, not just to below 70.
[00:57:39.600 --> 00:57:43.120] We go down to 20 or less than 30, right?
[00:57:43.120 --> 00:57:45.680] We have so many ways to do that now.
[00:57:45.920 --> 00:57:50.160] We have these injectables that are against this PCSK9.
[00:57:50.160 --> 00:57:56.720] We've got new drugs, five new LP-little A drugs that are going to be out within the next year or so that are really potent.
[00:57:56.800 --> 00:57:58.000] And we've had none of them.
[00:57:58.000 --> 00:57:58.960] None until now.
[00:57:58.960 --> 00:57:59.800] Yeah, we never had one.
[00:57:59.800 --> 00:58:02.920] We always tell, oh, too bad your LP-little A is over 100.
[00:58:02.920 --> 00:58:04.120] You know, nothing we can do.
[00:57:59.600 --> 00:58:06.760] We're going to be able to change that, and that's going to have a big impact.
[00:58:07.080 --> 00:58:11.160] We can get all the inflammation, get all over it, right?
[00:58:11.160 --> 00:58:18.280] In terms of bringing the inflammation down, we've already seen how GLP-1 drugs do that before any weight loss.
[00:58:18.280 --> 00:58:21.480] So that should work well in people who aren't even obese.
[00:58:21.480 --> 00:58:28.600] And we've seen how that can prevent heart, preserve ejection fraction, heart failure, which is half of all heart failure, right?
[00:58:28.600 --> 00:58:30.840] GLP-1s prevent that.
[00:58:30.840 --> 00:58:40.520] So for heart disease, we're seeing some really breakthroughs for the treatment, particularly the new target of LDL, that we have five different drug classes.
[00:58:40.520 --> 00:58:46.440] Statins, you've mentioned, but the PCSK9, we have three different ways to do that now.
[00:58:46.440 --> 00:58:48.840] We got other new drugs that are coming.
[00:58:49.080 --> 00:58:53.800] Just recently, the CETP inhibitor worked really well on top of.
[00:58:53.800 --> 00:58:57.400] So we can stamp out inflammation.
[00:58:57.400 --> 00:59:01.960] The other thing is, we have a metric we never had before, which is AI.
[00:59:01.960 --> 00:59:04.360] And by the way, that also goes with Alzheimer's.
[00:59:04.440 --> 00:59:07.080] You can do a retina AI exam.
[00:59:07.080 --> 00:59:15.800] So I have a picture of the retina, and you do AI on it, and it tells you when you're going to have Alzheimer's, if you're going to have Alzheimer's, five to seven years in advance.
[00:59:15.800 --> 00:59:20.760] The retina also tells if you're going to have heart disease or a stroke in advance.
[00:59:20.760 --> 00:59:27.800] It will even tell if you're going to, you know, your calcium score of your heart arteries through your retina.
[00:59:28.040 --> 00:59:29.800] It's remarkable.
[00:59:29.800 --> 00:59:32.040] And we should, that should be widely available.
[00:59:32.040 --> 00:59:33.720] It isn't yet, but it will be.
[00:59:33.720 --> 00:59:36.920] We'll be doing smartphone retina checks someday, right?
[00:59:37.240 --> 00:59:57.520] But here's where we get a real kick on a jump on this because if you are concerned about high risk, and somebody, you know, say 40, 50, they have significant risk factors, you can do a CT angio, which is now becoming very inexpensive.
[00:59:57.760 --> 01:00:00.000] And you can look at inflammation in the artery.
[01:00:00.000 --> 01:00:01.360] I go through this in the book.
[01:00:01.360 --> 01:00:04.560] Inflammation in the artery without a narrowing.
[01:00:04.560 --> 01:00:10.720] Okay, so basically, it does AI of the fat around the artery.
[01:00:10.720 --> 01:00:16.160] And this is something that was developed in the UK and it's now getting ready for FDA approval.
[01:00:16.160 --> 01:00:18.480] This is a big jump because we always were.
[01:00:18.560 --> 01:00:20.080] Well, this isn't the Clearly scan.
[01:00:20.080 --> 01:00:20.960] This is something else.
[01:00:20.960 --> 01:00:21.760] No, no.
[01:00:22.000 --> 01:00:24.240] Clearly, and the other ones in the U.S.
[01:00:24.320 --> 01:00:25.360] don't do this.
[01:00:25.360 --> 01:00:30.000] But this is an Oxford, University of Oxford spin-out.
[01:00:30.000 --> 01:00:31.440] I think it's called Carista.
[01:00:31.760 --> 01:00:34.400] They're going to have that available soon.
[01:00:34.400 --> 01:00:36.480] And I went through the data in the book.
[01:00:36.480 --> 01:00:47.280] I mean, they've had multiple papers, but it's striking: if you have inflammation without a narrowing, it's, you know, you could have 15-fold risk of a heart attack.
[01:00:47.280 --> 01:00:52.720] So that's when you use that as a metric, just like we were talking about the PTAW 217 for Alzheimer's.
[01:00:53.520 --> 01:00:56.160] We've got all these new things for cardiovascular.
[01:00:56.160 --> 01:00:58.160] We are going to get a grip on this.
[01:00:58.160 --> 01:01:00.720] And we got to, you know, ideally start early.
[01:01:00.720 --> 01:01:03.360] But, you know, the lifestyle factors work really well.
[01:01:03.360 --> 01:01:09.120] This is the most preventable known of the three big age-related diseases through lifestyle.
[01:01:09.120 --> 01:01:12.240] Because even without a lot of the drugs, like the lifestyle plays a big role.
[01:01:12.240 --> 01:01:19.360] Like, you know, I've seen data up to 90% by healthy diet, exercise, stress mitigation, sleep, right?
[01:01:19.360 --> 01:01:21.520] Yeah, I mean, is that in the book?
[01:01:21.520 --> 01:01:40.760] I found all these studies that I was really struck by that are recent that showed that if we practice the lifestyle factors that we've been reviewing with the details that we just discussed, that gets us seven to ten years of healthy aging without one of these age-related diseases.
[01:01:40.760 --> 01:01:49.560] I mean, who wouldn't want seven to ten years of healthy aging just from the stuff we've been discussing without any magic potion or pill?
[01:01:49.880 --> 01:01:52.360] So that's, I think, people don't know about that.
[01:01:52.360 --> 01:01:53.400] I didn't know about that.
[01:01:53.400 --> 01:01:54.840] It's really impressive.
[01:01:55.000 --> 01:01:55.560] That's powerful.
[01:01:55.560 --> 01:02:09.160] So, but you're saying that some of the advances in cardiology are more pharmacological than you're thinking are coming, like the drugs that lower this genetically determined lipoprotein called LP-little A, which I've been checking for 30 years.
[01:02:09.160 --> 01:02:11.320] Apo B, which I've been checking for 30 years.
[01:02:11.320 --> 01:02:18.680] I read some article the other day that was like, there's this great new test that can be more predictive of your risk of heart attack than any other test is just discovered.
[01:02:18.680 --> 01:02:19.640] I'm like, what is that?
[01:02:19.640 --> 01:02:21.480] I'm like, look through the article.
[01:02:21.480 --> 01:02:22.520] It's like ApoB.
[01:02:22.520 --> 01:02:23.400] I'm like, oh, God.
[01:02:23.800 --> 01:02:29.960] I mean, you only need to get it once, and then you can tell that if you need to check it further.
[01:02:29.960 --> 01:02:40.120] But you're getting at a key point here: it isn't just that we have better, you know, more armamentarium of drugs, but we didn't know how to get the risk down.
[01:02:40.120 --> 01:02:49.240] You know, we didn't know how to say this person's really high risk for atherosclerosis because we didn't really have, we didn't use the polygenic risk score.
[01:02:49.240 --> 01:02:53.000] We didn't have, as we do now, we're going to have a heart clock.
[01:02:53.800 --> 01:02:58.760] So there's a big debate out there, as you probably know, how low should we go on LDL?
[01:02:58.760 --> 01:03:00.840] Should we pull out all the stops?
[01:03:00.840 --> 01:03:15.280] Well, if you look at all the data, the lower you go, the more protection, but you don't want to necessarily give people, you know, azetamide and statin and injectable and all these things unless they really are at high risk.
[01:03:14.840 --> 01:03:19.680] Then you go for Broke and you also get the LPA and you get the inflammation down.
[01:03:20.000 --> 01:03:23.520] We have ways that we can do that and we're going to keep having better ways.
[01:03:23.520 --> 01:03:32.320] So this is a striking, it's a combination of who's at risk, the partitioning the risk, and having better ways to work on that risk.
[01:03:32.320 --> 01:03:34.960] Just to play devil's advocate, because this conversation comes up all the time.
[01:03:34.960 --> 01:03:37.520] You're a cardiologist, so your favorite organ is the heart.
[01:03:37.520 --> 01:03:40.480] And so your idea is get the LDL as low as you can.
[01:03:41.120 --> 01:03:44.320] Your brain is made up of a lot of only in people who are at high risk.
[01:03:44.320 --> 01:03:45.280] In people who are at high risk.
[01:03:45.280 --> 01:03:50.080] Okay, so if you're really high risk, but like what about the effects, for example, on the brain and cognitive function?
[01:03:50.080 --> 01:03:57.840] Because the cholesterol is a big part of your brain and sex hormones, which is what your testosterone is made from, is cholesterol.
[01:03:57.840 --> 01:04:00.320] So how do you kind of navigate that?
[01:04:00.320 --> 01:04:01.200] And what's the truth?
[01:04:01.200 --> 01:04:02.240] And what do we know?
[01:04:02.240 --> 01:04:09.520] Yeah, I mean, the statins are probably the most studied drug class in history, really.
[01:04:09.520 --> 01:04:16.960] Some of the data that comes out of these big meta-analyses would say, oh, people don't get any leg cramps.
[01:04:16.960 --> 01:04:18.480] That's not true.
[01:04:18.880 --> 01:04:20.800] You and I know that's not true.
[01:04:20.800 --> 01:04:30.560] People do get severe leg cramps where they can't even sleep at night, you know, and all sorts of other, you know, leg and muscle-related symptoms.
[01:04:30.560 --> 01:04:39.920] Now, with respect to cognitive and sexual dysfunction, the data really don't show a hit there at all.
[01:04:39.920 --> 01:04:54.000] And in fact, you know, I think that we have some data to suggest the chances of having dementia in people, and Alzheimer's, as you know, accounts for 70% of dementia.
[01:04:54.000 --> 01:05:01.480] That if you don't have the LDL lowered to, let's say, less than 100, less than 70, you're going to be at higher risk for dementia.
[01:05:01.480 --> 01:05:05.160] So, if anything, the data support statins.
[01:05:05.720 --> 01:05:12.200] And, you know, the data for sexual dysfunction, it's again, some of that's vascular.
[01:05:12.200 --> 01:05:16.600] And if it's vascular, we're talking about atherosclerotic.
[01:05:16.920 --> 01:05:20.680] And that, again, is going to be ameliorated with.
[01:05:21.000 --> 01:05:23.640] And, of course, we don't have to just rely on statins.
[01:05:23.640 --> 01:05:33.240] A lot of people do have side effects from statins, no matter what the group at Oxford keeps saying that everyone can take a statin and it's just, you know, it's mental if they can't.
[01:05:35.320 --> 01:05:48.760] When I wrote an op-ed in the New York Times like a decade ago, and I called out the diabetes from statins, okay, because if you take a very potent statin, you have a higher risk of developing type 2 diabetes, right?
[01:05:49.160 --> 01:05:52.280] Oh, did I get slammed by my cardiology colleagues for that?
[01:05:52.280 --> 01:05:54.280] I said, well, wait a minute, that's the data, folks.
[01:05:54.280 --> 01:05:55.240] I'm sorry.
[01:05:55.240 --> 01:06:02.440] And over the years, we've seen many more reports about the potent statins, high doses where you get a higher risk.
[01:06:02.600 --> 01:06:03.560] And you know what?
[01:06:03.560 --> 01:06:06.120] Most physicians are not keeping up with this.
[01:06:06.120 --> 01:06:13.720] They're not watching their patients to see if their glucose, like oh hemoglobin, you know, A1C or fasting glucose.
[01:06:13.720 --> 01:06:19.800] And this is bothersome to me because that is a side effect of statins, particularly potent statins.
[01:06:19.800 --> 01:06:33.720] So again, this is important because if we're going to lower LDL and pull out all the stops and high doses of mersuvastatin, crestor or a torostatin, lipitor, that could also raise the risk of that person developing type 2 diabetes.
[01:06:33.720 --> 01:06:35.400] We don't want to do that.
[01:06:35.400 --> 01:06:45.680] And we have cardiologists, my colleagues, they are, you know, really sold on statins and they basically ignore this diabetes issue.
[01:06:45.920 --> 01:06:47.360] Did I ever take grief?
[01:06:44.920 --> 01:06:48.800] I agree with you.
[01:06:48.960 --> 01:06:54.320] And I think there's a concern I have around its effect on mitochondrial function.
[01:06:54.320 --> 01:07:04.240] And some of the data I've seen that even in people without muscle pain, even without elevated muscle enzymes, that there's mitochondrial damage on muscle biopsies.
[01:07:04.240 --> 01:07:13.680] And for me, mitochondria are so key to healthy aging in the brain, in everything from Parkinson's to heart disease, diabetes.
[01:07:13.680 --> 01:07:16.160] Diabetics have poor, poorly functioning mitochondria.
[01:07:16.160 --> 01:07:18.320] They may be part of why it causes it.
[01:07:18.320 --> 01:07:25.360] And so I'm wondering, you know, some of these other drugs that are coming down the pike, even though some of them are expensive, maybe a better solution.
[01:07:25.360 --> 01:07:37.200] Well, people that have clear-cut adverse effects, you know, the PCSK9 injectable drugs are a winner because they're potent.
[01:07:37.200 --> 01:07:40.800] And they have not been associated with diabetes, which is really interesting.
[01:07:40.800 --> 01:07:44.800] They have not been associated with cognitive or other side effects.
[01:07:44.800 --> 01:07:47.440] So most insurers cover that now.
[01:07:47.440 --> 01:07:52.560] We, you know, went through years where it was because they were so expensive, the cost has come down.
[01:07:52.560 --> 01:08:05.120] So as long as people have the right indication where they have significant side effects or they need to have their LDL substantially lowered, it's usually not a financial stress for most people.
[01:08:05.120 --> 01:08:11.600] So heart disease, still its lifestyle, but then there's a cocktail of other drugs in very high-risk patients that you can detect early to figure out.
[01:08:12.160 --> 01:08:19.200] And what about lipoprotein fractionation, which is a lab test that we include as part of function health, as well as APOB and LPA?
[01:08:19.200 --> 01:08:23.120] Something I've been testing for 30 years, but do you think that's as important?
[01:08:23.120 --> 01:08:33.640] Because to me, the particle number and particle size story is important, and it's sort of a clue that there's insulin resistance, which is one of the biggest drivers of heart disease and all the other age-related diseases.
[01:08:33.880 --> 01:08:39.880] Yeah, I mean, I think it's mild, potentially mild, incremental information.
[01:08:39.880 --> 01:08:47.480] I just don't see that it has nearly the impact of just zeroing in on LDL and LP-little A.
[01:08:47.480 --> 01:08:50.920] And I do recommend that everybody get an ApoB at least once.
[01:08:51.320 --> 01:08:54.520] And then you can figure out whether that needs to be further assessed.
[01:08:54.520 --> 01:08:58.360] These other things, you know, it's an additional expense.
[01:08:58.360 --> 01:09:01.000] I just haven't seen the value.
[01:09:01.000 --> 01:09:06.680] But, you know, I have colleagues that are lipidologists that test every known particle to mankind, right?
[01:09:06.680 --> 01:09:11.880] I just haven't, I haven't really seen the benefit because it doesn't change usually.
[01:09:11.880 --> 01:09:14.280] To me, I got to know the person's risk.
[01:09:14.280 --> 01:09:17.160] And then I'm going to go after inflammation.
[01:09:17.160 --> 01:09:19.080] I'm going to work on their lifestyle.
[01:09:19.080 --> 01:09:22.360] And if necessary, you know, get their LDL down as low as possible.
[01:09:22.360 --> 01:09:28.120] So the other things just don't have, for me, an added value.
[01:09:28.520 --> 01:09:36.680] But I do know there are people that are, you know, wild and crazy on every particle, small, large, dense, you know, you name it, out there.
[01:09:36.680 --> 01:09:37.160] Yeah.
[01:09:37.160 --> 01:09:38.280] Yeah, so I hear you on that.
[01:09:38.280 --> 01:09:42.920] I think, you know, sometimes more information isn't always better, but you know, what is the most important information?
[01:09:42.920 --> 01:09:43.960] I think you covered that in your book.
[01:09:43.960 --> 01:09:51.720] And I think, you know, we're going down the kind of the horseman of the apocalypse, you know, the heart disease, the cancer, the dementia.
[01:09:51.720 --> 01:09:54.440] I think diabetes is sort of all in there related.
[01:09:54.440 --> 01:10:13.960] But you're talking about how there's kind of a newer, with the advances in our diagnostics, whether it's imaging or retinal scans or new ways we can measure dementia biomarkers we never had before, cancer, we'll get into in a sec, that these diseases can become more optional.
[01:10:13.960 --> 01:10:16.000] Like they're not inevitable.
[01:10:14.600 --> 01:10:20.480] We have more agency than we ever had before, given what we know now.
[01:10:20.800 --> 01:10:30.960] And when you layer off what we're learning with AI and using multimodal treatments, we're really able to actually make a big dent if people really understood how to navigate this.
[01:10:30.960 --> 01:10:34.880] And the sad part is that, you know, you spend your time thinking about what's coming.
[01:10:34.880 --> 01:10:45.520] Most physicians are just trying to deal with the onslaught of what is and don't have the bandwidth to actually apply this stuff until it kind of is way often decades later.
[01:10:45.520 --> 01:10:56.480] And so I really appreciate your sort of paying attention to, you know, what's happening and keeping your nose to the scent of where things are emerging because otherwise people just don't know.
[01:10:56.480 --> 01:10:58.720] And doctors, like you said, don't know.
[01:10:58.720 --> 01:11:02.560] And the average person doesn't know, but this is such a hopeful message.
[01:11:02.800 --> 01:11:12.400] I want to kind of finish on cancer because I think this is one of those things that, you know, the C word, you know, nobody wants to get that diagnosis.
[01:11:12.400 --> 01:11:13.760] It's very scary.
[01:11:14.240 --> 01:11:24.480] Most cancers are picked up late stage when the five-year survival rates are very low in the 5% to 20%, if that.
[01:11:24.800 --> 01:11:32.160] And picking things up early and understanding your risk can lead to cures, essentially.
[01:11:33.040 --> 01:11:49.040] And I think what I'd like to hear is your sort of perspective on this with new liquid biopsy testing, with new technologies of imaging, with new, you know, maybe other proteomics that are coming.
[01:11:50.000 --> 01:11:51.680] What is out there that's emerging?
[01:11:51.680 --> 01:11:55.520] Because, you know, my sister died of cancer in 57.
[01:11:55.520 --> 01:11:56.880] My dad died of cancer.
[01:11:56.880 --> 01:11:58.240] He was otherwise really healthy.
[01:11:58.240 --> 01:12:02.360] He'd been a smoker when he was younger, but quit and ended up getting lung cancer.
[01:12:02.360 --> 01:12:07.400] Like, they could potentially even still be around if they hadn't died of cancer.
[01:12:07.400 --> 01:12:08.760] And I don't want to get cancer.
[01:12:09.320 --> 01:12:10.280] I'm with you.
[01:12:10.600 --> 01:12:17.800] Yeah, my mother died of cancer in her 50s, and most of my relatives on my father's side had colon cancer.
[01:12:17.800 --> 01:12:20.680] You know, I've had a lot of cancer in the family for sure.
[01:12:20.680 --> 01:12:22.920] And I agree, no one wants to go through this.
[01:12:22.920 --> 01:12:27.400] And I do believe we have a path to prevent cancer.
[01:12:27.800 --> 01:12:30.040] And certainly it's spread, right?
[01:12:30.280 --> 01:12:37.640] If you can find it microscopically, which we don't right now very well, long before it's ever shown on a scan.
[01:12:37.640 --> 01:12:41.880] And once it's on a scan, if it's really cancer, you're talking about billions of cells, right?
[01:12:42.200 --> 01:12:45.080] You want to find it if it does exist microscopically.
[01:12:45.080 --> 01:12:48.200] So why is this such an exciting area?
[01:12:48.200 --> 01:12:55.000] Again, we can find through the full stack who's at risk and for which cancer.
[01:12:55.000 --> 01:13:09.080] And so we have a way, you know, whether it's polygenic risk or genome sequence, we can do, for example, you know, just looking at the clocks, which is another way to get a window into a risk of cancer.
[01:13:09.080 --> 01:13:13.560] If a person has a significant risk, and you know, family history is part of that, right?
[01:13:13.880 --> 01:13:19.240] Then they also confirm through these other, I mean, a simple polygenic risk will tell us a lot.
[01:13:19.240 --> 01:13:27.960] This is now a different story, completely, Mark, than the way we screen for cancer today, which is as dumb as it could possibly be.
[01:13:27.960 --> 01:13:29.880] Age 50, you show up.
[01:13:30.040 --> 01:13:32.200] Women, mammogram, right?
[01:13:32.560 --> 01:13:37.720] All right, only 12% of women in their lifetime will ever have breast cancer.
[01:13:37.720 --> 01:13:47.280] 88% will never develop breast cancer, but they're all supposed to get mammography on a frequent periodic basis starting age 40, 45.
[01:13:47.280 --> 01:13:49.360] This is crazy.
[01:13:44.920 --> 01:13:51.760] We don't do anything to partition risk.
[01:13:52.400 --> 01:13:58.000] The same for prostate cancer, colon cancer, you name the cancer.
[01:13:58.000 --> 01:13:59.040] This is what we do.
[01:13:59.040 --> 01:14:01.920] We treat every human the same.
[01:14:01.920 --> 01:14:04.720] We waste all this money on mass screening, right?
[01:14:04.720 --> 01:14:08.000] Now, what I'm suggesting is let's partition people's risk.
[01:14:08.000 --> 01:14:10.640] If they're high risk, then they should have screening.
[01:14:10.640 --> 01:14:13.040] But that screening is different.
[01:14:13.040 --> 01:14:15.280] It's basically establishing the risk.
[01:14:15.280 --> 01:14:25.840] And then if we see a person, you know, it's a significant risk, you can then do a plasma tumor DNA assessment, right?
[01:14:26.160 --> 01:14:27.920] That right now is pretty expensive.
[01:14:27.920 --> 01:14:29.760] It's $800, $900.
[01:14:29.760 --> 01:14:33.520] The one that's used the most is Gallery of Grail.
[01:14:33.520 --> 01:14:36.320] And almost 400,000 people have had that test.
[01:14:36.320 --> 01:14:37.840] But guess what, Mark?
[01:14:37.840 --> 01:14:41.360] The people who've had the test is because they're age 50.
[01:14:41.360 --> 01:14:43.600] I mean, that's a plus.
[01:14:43.600 --> 01:14:46.000] That's not the reason they should get the test.
[01:14:46.000 --> 01:14:49.200] It should be because they have risk of cancer.
[01:14:49.200 --> 01:14:52.320] Anyway, the yield for that test is very low.
[01:14:52.480 --> 01:14:54.480] And most of it is already late stage.
[01:14:54.480 --> 01:14:58.560] Two out of thousand, you might pick up an early cancer.
[01:14:58.560 --> 01:15:01.360] So you got to use the test right in the right people.
[01:15:01.360 --> 01:15:03.200] This is something I can't emphasize.
[01:15:03.200 --> 01:15:09.440] Then that test and all the other liquid biopsies have a much better chance to be helpful.
[01:15:09.760 --> 01:15:20.560] So we have that, but also this is where our immune system kicks in because we don't have that immune metric, system metric, except for immune clock.
[01:15:20.560 --> 01:15:26.320] But if we did, you know, if our immune system was amped up, we wouldn't have cancer spread.
[01:15:26.320 --> 01:15:27.520] We wouldn't see metastasis.
[01:15:28.560 --> 01:15:32.200] You know, what we know is this: some people, this is really fascinating.
[01:15:32.200 --> 01:15:39.640] Some people will have a positive test for tumor DNA, and they're reassessed in a few months, and it goes away.
[01:15:39.640 --> 01:15:41.320] What do you think happened?
[01:15:41.320 --> 01:15:46.040] Was it a false positive or did that person's immune system kick in?
[01:15:46.040 --> 01:15:49.080] I think what we're learning is it's the immune system.
[01:15:49.080 --> 01:15:53.720] And what we have to get is: this is the missing piece right now, the immunome.
[01:15:53.720 --> 01:16:12.680] If we can get this and find people who are at risk for cancer and just make sure throughout their lifetime that their immune system has got good integrity and it can fight off the threat of a cancer, of a foreign protein that would be on the antigen, on the surface of cancer cell.
[01:16:12.680 --> 01:16:20.120] So I am really gung-ho because if you look at the treatment of cancer, we're now seeing things we've never seen.
[01:16:20.120 --> 01:16:30.360] Personalized neo antigen vaccines to cure pancreatic cancer, to cure renal cell carcinoma, intractable, that is, people that failed, everything else.
[01:16:30.360 --> 01:16:33.560] The other thing, just to mention, here again is AI.
[01:16:33.880 --> 01:16:53.160] We are seeing AI used for the electronic health record using the unstructured nodes and the regular nodes and set points, that is the lab values, but even when they're in their normal range, AI analyzes, whoa, it's even in the normal range, and we look at it and say there's no asterisk, so it's okay.
[01:16:53.160 --> 01:16:58.040] Well, no, the AI says, uh-uh, this is flagging a risk of pancreatic cancer.
[01:16:58.040 --> 01:17:00.600] This is flagging a risk of ovarian cancer.
[01:17:00.600 --> 01:17:09.400] The hardest diagnosis of cancer we're seeing that can be brought much earlier through AI of all of a person's data.
[01:17:09.400 --> 01:17:14.800] We saw it from the study that was done in Denmark in the VA for pancreatic cancer.
[01:17:14.800 --> 01:17:17.600] We're going to see Storm Kettering has what were they looking at?
[01:17:17.600 --> 01:17:20.000] Because they were looking at tumor markers, were they?
[01:17:14.520 --> 01:17:21.440] We were looking at just regular blood tests.
[01:17:21.680 --> 01:17:28.480] Yeah, so they looked at a person's nonspecific symptoms, like abdominal symptoms for pancreatic cancer.
[01:17:28.480 --> 01:17:36.320] And they saw ranges of liver function tests in the normal range, but trending in the wrong direction, right?
[01:17:36.320 --> 01:17:44.240] So the AI picked up the higher risk of people that we might not, we might discount these are nonspecific symptoms.
[01:17:44.240 --> 01:17:46.160] These tests are lab tests.
[01:17:46.160 --> 01:17:51.120] They look normal, but they're not normal when you are looking at this in serial assessment.
[01:17:51.120 --> 01:18:03.360] So I'm also lots of different ways that AI is helping us to gauge a person's risk and help us to pick up these occult, difficult to diagnose cancer.
[01:18:03.360 --> 01:18:05.120] I mean, this is so important what you're saying.
[01:18:05.120 --> 01:18:10.640] That there was a paper in Nature Medicine recently on personalized lab data.
[01:18:10.640 --> 01:18:25.200] And the idea was that exactly what you're saying, that even though it's quote normal, it may not be normal for you because if you were like 20 and it goes up to 35, which is still in the normal range, that might not be good.
[01:18:25.200 --> 01:18:25.920] That's right.
[01:18:25.920 --> 01:18:31.680] And we need to start getting a baseline of what our data is and tracking it over time and having AI help us learn from it.
[01:18:31.680 --> 01:18:38.640] Because, you know, as a doctor, you see thousands of patients that come in and, you know, they've had their lab panel every year.
[01:18:38.640 --> 01:18:47.280] You can't keep in your mind what their liver function tests were last year, five years ago, or 10 years ago, and how that differs and how that, what's the variation from their normal or baseline tests.
[01:18:47.680 --> 01:18:49.840] You can't do that as a human being, right?
[01:18:50.160 --> 01:18:56.160] And I mean, I have certain patients who are OCD and they bring in spreadsheets with years and years of their data, and you can graph it all.
[01:18:56.320 --> 01:18:58.960] I'm like, wow, that's like, I never saw that before.
[01:18:58.960 --> 01:19:02.920] But without that, you really don't know what's going on.
[01:18:59.760 --> 01:19:06.840] That's the paper I was talking about on set points, exactly.
[01:19:08.600 --> 01:19:18.040] And we just don't look at that because if it's normal, we don't look at the last few years, how things are just inching up.
[01:19:18.040 --> 01:19:21.240] And that's the way AI can help us.
[01:19:21.240 --> 01:19:22.040] And it is helping.
[01:19:22.040 --> 01:19:23.560] We've already seen proof of it.
[01:19:23.560 --> 01:19:33.000] So for a variety of conditions, but especially these three age-related disease and especially cancer, because we are not doing well with cancer.
[01:19:33.240 --> 01:19:34.200] You said it.
[01:19:34.200 --> 01:19:37.720] We're only diagnosing cancer when it's way too late.
[01:19:37.720 --> 01:19:47.960] And that's got to change because when it's picked up, first picking up that the person has risk and picking up when it's microscopic well before you ever catch it on a scan.
[01:19:47.960 --> 01:19:57.480] That's why, you know, I'm not keen on these total body MRIs because they're being used to pick up already a cancer that's got a mass, right?
[01:19:57.480 --> 01:19:59.560] And of course, a lot of times it's not even cancer.
[01:19:59.560 --> 01:20:02.680] It's benign and people go through unnecessary biopsies.
[01:20:02.680 --> 01:20:11.720] But I do think if a person's high risk, and certainly if they have a positive liquid biopsy, you know, tumor DNA, then it's a very reasonable thing to pursue.
[01:20:11.720 --> 01:20:13.240] We're going to do much better.
[01:20:13.240 --> 01:20:22.360] And all these years of trying to treat cancer and cure it, you know, what do people have to go through to get there when you could prevent it?
[01:20:22.360 --> 01:20:26.040] And, you know, I think this is where we have a brilliant future.
[01:20:26.040 --> 01:20:30.440] It may take a while to get it implemented, but it's ready to go in many respects.
[01:20:30.440 --> 01:20:34.440] Just to go a layer deeper, so just you talk about polygenic risk for cancer.
[01:20:34.440 --> 01:20:42.200] And we've heard about the BRCAGENE or familial polyp disease, increased risk of cancer disease.
[01:20:42.200 --> 01:20:46.800] Those are unusual, although they're things you can measure and track if you have a family history.
[01:20:47.280 --> 01:20:55.040] You're talking about a different set of genetic biomarkers that are being discovered that help us segment people in terms of their risk.
[01:20:55.040 --> 01:20:55.200] Right.
[01:20:55.520 --> 01:20:56.800] Related to different cancers.
[01:20:56.800 --> 01:21:00.240] Yeah, so you're bringing up the rare mutations.
[01:21:00.240 --> 01:21:07.600] But, for example, they can all be had in a sequence, which costs a couple hundred dollars, a full whole genome sequence.
[01:21:07.600 --> 01:21:19.440] And BRCA2, we as men, you know, we're a lot of us carrying a BRCA gene, and just because we don't have breast cancer, you know, that means we have a higher risk of prostate cancer ourselves and other forms of cancer.
[01:21:19.440 --> 01:21:35.600] So, you know, these are pathogenic genes, which, and I go through that BRCA2 story in some depth because of the Icelandic data where it made a difference of up to seven years of healthy aging, mainly because of cancer.
[01:21:35.920 --> 01:21:45.360] Now, so you get these rare, so-called pathogenic genes that have a high risk of cancer, but you also can get a whole bunch of susceptibility genes.
[01:21:45.360 --> 01:21:56.560] So they're not that's high deterministic, you know, very, like we were talking about, ApoE4, two copies, but they are increasing the risk.
[01:21:56.560 --> 01:22:00.080] So what you have are three different types of gene markers.
[01:22:00.080 --> 01:22:10.240] One is the rare variants like BRCA2, BRCA, BRCA2, and as you said, Lynch syndrome and these other familial polyposis.
[01:22:10.240 --> 01:22:12.560] The next is the common variant.
[01:22:12.560 --> 01:22:20.880] The common variants, which is what you pick up in a, these are like, say, 200, 300 gene variants that would give you the high risk for breast cancer.
[01:22:20.880 --> 01:22:22.000] They're not BRCA.
[01:22:22.000 --> 01:22:26.640] These are just common variants that you got to add mixture from your mother and father, right?
[01:22:26.960 --> 01:22:34.280] And then the third group are these other susceptibility genes that can be gleaned from a genome sequence.
[01:22:34.520 --> 01:22:44.200] When you have all that data, which is again not expensive and processed properly, then you know what type of cancer you're at risk for, if you're at risk for a cancer.
[01:22:44.200 --> 01:22:46.120] It doesn't tell you when.
[01:22:46.120 --> 01:22:48.360] It just says yes, no, right?
[01:22:48.360 --> 01:23:02.760] That's the when is when we have to you know get early, get on this early and not treat everybody who's 50 and older as if they were a cattle, that we're all the same.
[01:23:02.760 --> 01:23:05.000] We have to be much smarter about this.
[01:23:05.240 --> 01:23:08.280] And this is what we call precision medicine or personalized medicine.
[01:23:09.320 --> 01:23:10.920] And then we're finally entering the year.
[01:23:10.920 --> 01:23:13.320] I think AI is going to help us get smarter about that.
[01:23:13.320 --> 01:23:23.480] The other thing you sort of mentioned was sort of liquid biopsies and you kind of touched on this a little bit, but proteomic kind of testing.
[01:23:23.480 --> 01:23:31.480] The liquid biopsy, from what you're, I hear you saying, you don't think it's a good screening tool because it picks the things late.
[01:23:31.480 --> 01:23:34.600] But if everybody got it, it would pick up things earlier, right?
[01:23:34.600 --> 01:23:47.160] If it was sort of cost was down and scale was up for blood tests every year with your checkup, you could potentially be picking up stuff much more frequently and much earlier, right?
[01:23:47.160 --> 01:23:53.560] Well, potentially, but you see, it's not being, it's just being done, you know, for on the age criteria.
[01:23:53.560 --> 01:24:00.760] And the yield of picking up an early cancer is two per thousand people, which is really, really low, right?
[01:24:00.760 --> 01:24:01.720] That doesn't make it a better test.
[01:24:01.880 --> 01:24:03.160] Unless you're one of those two.
[01:24:03.160 --> 01:24:03.440] Yeah, yeah.
[01:24:03.480 --> 01:24:12.120] I mean, and also, you know, if you had the test and it's negative, that doesn't put you in, you know, in the safe group.
[01:24:12.080 --> 01:24:14.880] Yeah, it's only if it's positive where it's really helpful.
[01:24:14.880 --> 01:24:16.720] I do think these tests are going to get better.
[01:24:14.440 --> 01:24:21.520] There's lots of ways, you know, this is a very minimal amount of tumor DNA in the plasma.
[01:24:21.840 --> 01:24:25.360] And there's ways to jack that up to make the test better.
[01:24:25.360 --> 01:24:28.080] And as you got to, it's got to be cheaper.
[01:24:28.640 --> 01:24:39.360] But yeah, again, this whole Bayes theorem of don't do tests that are not in people who are healthy of no risk.
[01:24:39.360 --> 01:24:46.400] But when you do it in people, like the two per thousand I cited is in healthy people age 50 plus.
[01:24:46.400 --> 01:24:52.640] But if it was done in people who were, you know, clearly had increased risk, that yield of picking up then it's a better test.
[01:24:52.640 --> 01:24:53.120] Oh, yeah.
[01:24:53.760 --> 01:24:58.720] And also when you're paying $900, that's substantial.
[01:24:58.720 --> 01:25:08.880] If we get that test down to $100 or something like that, and it's more sensitive, more accurate in the right people, it's going to become very commonly used.
[01:25:08.880 --> 01:25:12.240] So you're heading down the right path with that point.
[01:25:12.240 --> 01:25:12.720] Yeah.
[01:25:12.720 --> 01:25:37.280] And then the other thing I've been hearing about is proteomic tests where common protein, some of the common proteins we look at for cancer, like CA125 or CA99 for colon cancer, like they're combining that with multiple other proteins and they're able to kind of using AI to predict that you'll be able to pick up these cancers much earlier with these proteomic signatures that they have in the blood, which are really inexpensive to do.
[01:25:37.280 --> 01:25:37.600] Right.
[01:25:37.600 --> 01:25:42.320] So that's a Johns Hopkins Burt Vogelstein effort.
[01:25:42.320 --> 01:25:43.040] And that's right.
[01:25:43.040 --> 01:25:52.800] As you said, they combine some key proteins that have been established as markers with some gene variants and made it a relatively inexpensive test.
[01:25:52.800 --> 01:25:55.760] And that's one that certainly has a potential as well.
[01:25:56.000 --> 01:26:06.920] We're going to be able to do so much better with the screening using the blood because once it shows up in the blood in a microscopic, that's when we get all over it.
[01:26:07.080 --> 01:26:11.960] Because this is, I think, a new era of early diagnosis.
[01:26:11.960 --> 01:26:13.080] It's essential.
[01:26:13.080 --> 01:26:17.960] And we just, you know, again, you get it on a mammogram, it's already got a problem.
[01:26:17.960 --> 01:26:23.320] You know, and we're not even using AI in this country for mammograms routinely.
[01:26:23.320 --> 01:26:23.880] And we should.
[01:26:23.880 --> 01:26:26.760] That's the best AI case that exists today.
[01:26:26.760 --> 01:26:29.080] 100,000 plus women in Sweden.
[01:26:29.080 --> 01:26:35.320] The AI picked up 25% more cancers compared to radiologists alone.
[01:26:35.960 --> 01:26:40.440] You know, significant cancers and no increase in false positives.
[01:26:40.440 --> 01:26:41.880] Why aren't we using that?
[01:26:41.880 --> 01:26:50.120] So we're not doing a good job here for cancer screening or partitioning risk, no less preventing it.
[01:26:50.120 --> 01:27:06.040] I mean, you mentioned imaging a little bit, but my understanding is that with new AI advanced sort of interpretation and stuff, that with these more high-resolution scans, you can pick up cancers down to two millimeters, which is pretty small, like basically the side of a ballpoint pen.
[01:27:06.040 --> 01:27:06.600] Yeah.
[01:27:06.600 --> 01:27:10.920] And at that point, they're not likely to have spread or metastasized.
[01:27:10.920 --> 01:27:15.720] And then, you know, you can see changes over time if you do serial imaging.
[01:27:15.880 --> 01:27:18.440] Seems to me that's a kind of a useful tool.
[01:27:18.520 --> 01:27:19.000] Might be.
[01:27:19.000 --> 01:27:24.200] And it may make up things that are more sensitive than the gallery, which is not as sensitive.
[01:27:24.200 --> 01:27:25.320] Yeah, it might be.
[01:27:25.320 --> 01:27:41.000] I think what we've seen, at least unequivocal, you know, a huge trial, is that AI of a regular mammogram, not like you're talking about, not ultra-high resolution, it can really make a difference.
[01:27:41.240 --> 01:27:46.880] And so, that I think is, you know, we should be implementing that, and we're not.
[01:27:44.840 --> 01:27:48.880] And it's just a you know, we're missed opportunity.
[01:27:49.200 --> 01:28:00.240] There's a big study that showed that if you have AI analysis of a regular mammogram, you can predict cancer from that in that woman five years ahead if they're going to develop cancer.
[01:28:00.240 --> 01:28:07.120] So, the AI of scans continues to see things that we humans can't see.
[01:28:07.120 --> 01:28:21.920] And the fact that you can look at a mammogram with an AI not only make the diagnosis of cancer more better than radiologists alone, but also see some patterns that indicate the person's much higher likelihood of cancer in the next five years.
[01:28:21.920 --> 01:28:28.160] So, it's just like what we're talking about with the ability to predict the other age-related diseases.
[01:28:28.160 --> 01:28:36.960] Yeah, so the fourth thing you said was really around finding ways to enhance our own body's immune function and natural killer cell function.
[01:28:36.960 --> 01:29:00.960] I know Patrick Sun Shang is working a lot on this, and I don't know, I'm not deep enough into it to know whether there's a lot there to it, but it seems like an interesting theory that if we can see a decrease in our own tumor surveillance with lower natural killer cells, which is part of our immune system, the white blood cells that kill cancer and infections, that we could amplify that effect, that could be a powerful therapy.
[01:29:00.960 --> 01:29:08.160] Yeah, so this whole chapter on the immune system, and you know, after the brain, this is the most complex system there is.
[01:29:08.160 --> 01:29:13.360] There's so many different cells and interferons and antibodies.
[01:29:13.360 --> 01:29:22.560] But the big thing here is we have ability to control our immune system like never before, up or down, like a rheostat, right?
[01:29:22.560 --> 01:29:32.280] And with that capability, that gives the confidence that we can amp it up for people at high risk for cancer or at the earliest possible diagnosis.
[01:29:32.600 --> 01:29:38.920] So we're no longer going to give these, you know, toxic drugs, but we're going to just get their immune system in high gear.
[01:29:39.320 --> 01:29:59.800] And also, of course, what we've never seen before, Mark, is by taking people with autoimmune diseases like lupus, systemic sclerosis, even multiple sclerosis, by giving them T cell, engineered T cells, CAR T, directed towards depleting their B cells.
[01:29:59.800 --> 01:30:05.480] That when the B cells come back, they forgot that the person has an autoimmune disease.
[01:30:05.480 --> 01:30:07.400] They have a control alt delete.
[01:30:07.400 --> 01:30:09.080] I mean, this is incredible, right?
[01:30:09.400 --> 01:30:16.920] That they no longer, and for now, three, seven years of follow-up, they're cured of an autoimmune disease.
[01:30:16.920 --> 01:30:19.240] We had never seen anything like that before.
[01:30:19.240 --> 01:30:30.360] And of course, you know, we're seeing more and more reports of this ability to cure, you know, really vicious autoimmune diseases that can, you know, killers and no less really severe morbidity.
[01:30:30.360 --> 01:30:36.200] So that is another, besides the cancer immunotherapy to worry, which is huge.
[01:30:36.200 --> 01:30:47.640] Oh, I mean, you, the fact that we can, the more you give an immunotherapy, higher gear, high, the more chances you are going to be able to treat successfully a person with an intractable cancer.
[01:30:47.640 --> 01:31:00.280] So, between all these things, we're learning about the immune system, no less the missing metric, the ability to test a person's immune system at any point during, let's say, their annual checkup or whatever.
[01:31:00.280 --> 01:31:03.480] Once we get that, then that's the missing link right now.
[01:31:03.480 --> 01:31:04.520] And then we're also.
[01:31:04.680 --> 01:31:07.400] That's the protein clocks, that's the immune age protein clock.
[01:31:07.560 --> 01:31:17.360] Yeah, yeah, we have an immune clock, but we want more than that because that, as you got to early on in our conversation, that's a piece of it.
[01:31:14.920 --> 01:31:22.640] But we want to know about the T cell story, the B cells, the NK, all these different cells.
[01:31:22.640 --> 01:31:41.360] We want to know about, I do present in the book a kind of first-tier immunome that I had of Johns Hopkins startup called Infinity Bio, where I had all my autoantibodies, every virus I've ever been exposed to in my life.
[01:31:41.520 --> 01:31:47.520] Interestingly, you know, I never had been exposed to CMV and all sorts of things that are going to help.
[01:31:47.840 --> 01:31:50.000] And this could be done inexpensively.
[01:31:50.000 --> 01:31:51.200] It will be common.
[01:31:51.200 --> 01:31:55.280] It's all part of this immunome that we don't have right now that we need.
[01:31:55.280 --> 01:31:59.360] To loop back on the cancer thing, but before I go with that, you mentioned T cells and B cells.
[01:31:59.360 --> 01:32:02.000] People probably don't know about, you know, B cells are the ones that create antibodies.
[01:32:02.000 --> 01:32:05.120] And autoimmune diseases are where you make antibodies against your own body's tissues.
[01:32:05.120 --> 01:32:06.400] So that's why it's so important.
[01:32:06.400 --> 01:32:09.440] And T cells are more of an ancient part of your immune system.
[01:32:09.440 --> 01:32:16.080] They're more general and are we call cell mediated, which is different than antibody mediated.
[01:32:16.080 --> 01:32:20.240] And those will basically turn off the B cells so that you don't make antibodies.
[01:32:20.240 --> 01:32:21.360] That's kind of cool.
[01:32:21.360 --> 01:32:22.400] I didn't know about that.
[01:32:22.400 --> 01:32:31.200] Yeah, you know, these T regs that are the key T cells that you can get to tone down your whole immune system.
[01:32:31.200 --> 01:32:42.320] And then, you know, and then killing these cells that have the foreign, the alien antigen, the cytotoxic CD8 T cells.
[01:32:42.320 --> 01:32:44.960] I mean, so the immune system we have is rich.
[01:32:44.960 --> 01:32:49.440] The problem is, as we get older, you know, it lets down.
[01:32:49.440 --> 01:32:51.360] And in some people, more than others.
[01:32:51.360 --> 01:32:52.800] And we have to be on top of that.
[01:32:52.800 --> 01:32:58.320] That's the one thing that if you had to go back and say the welderly, how did they get there?
[01:32:58.320 --> 01:33:01.800] Maybe some of them are just, you know, random stochastic luck.
[01:33:02.120 --> 01:33:09.160] But for the most part, these people are, you know, they got a great immune system that just carried them through.
[01:33:09.160 --> 01:33:11.880] And we want everybody to have a great immune system someday.
[01:33:11.880 --> 01:33:12.120] Good.
[01:33:12.120 --> 01:33:14.040] And I think we're going to learn more about how to do that.
[01:33:14.040 --> 01:33:45.080] Just to kind of go back to the cancer story, I just want to finish summarizing it because as I think about all these new technologies, whether it's collections of genes that put you at higher risk that aren't a cancer gene, but that collectively increase your risk, combining with the liquid biopsies to get more and more accurate at less of a cost, combined with protein signatures of different cancers that can be picked up way before you'll see anything in any other test, combined with better resolution AI imaging done serial over time.
[01:33:45.080 --> 01:33:57.640] It seems to me that you can't prevent us from getting cancer because we live in the toxic world and there's shit that happens, but we could make dying of cancer a historical footnote.
[01:33:57.640 --> 01:33:58.120] Oh, yeah.
[01:33:58.120 --> 01:33:58.360] Yeah.
[01:33:58.760 --> 01:33:59.640] Is that fair to say?
[01:33:59.640 --> 01:33:59.960] Yeah.
[01:33:59.960 --> 01:34:10.680] I mean, what we have to do, and I go through this in the cancer chapter in the book, we have to prevent metastasis because people don't die of the cancer per se.
[01:34:10.680 --> 01:34:13.080] They die of the spread of that cancer.
[01:34:13.080 --> 01:34:24.200] And if we can just get rid of metastasis, which we can, there's a way to do this now, then that's going to be our big dent in the cancer story.
[01:34:24.520 --> 01:34:29.400] And, you know, obviously we want to even catch it when it's before it gets to microscopic.
[01:34:29.400 --> 01:34:33.480] And we put people under surveillance, who once we determine they're at high risk.
[01:34:33.480 --> 01:34:39.880] But I think what is so exciting here is just prevent it ever getting legs.
[01:34:39.880 --> 01:34:43.880] Don't, if it doesn't spread, we got a winner strategy here.
[01:34:43.880 --> 01:34:45.760] You and I can geek out on this all day long.
[01:34:45.920 --> 01:35:15.760] I think we didn't get to a lot of things I did want to talk about, but we covered, I think, some of the most important things, which is the advances in medicine are happening so rapidly that we're learning about ways to detect early, very early, far earlier than we used to, and to be proactive with what we learn about through lifestyle and other novel therapies that we can make these three horsemen of the apocalypse kind of not so scary anymore: heart disease, cancer, and dementia.
[01:35:15.760 --> 01:35:18.560] Yeah, I mean, that's the nuts of it.
[01:35:18.560 --> 01:35:26.320] I think what's so exciting, and you know, why I'm so optimistic, is for millennia, we talk about preventing these diseases.
[01:35:26.320 --> 01:35:27.920] And we never did it.
[01:35:27.920 --> 01:35:29.360] And now we can do it.
[01:35:29.600 --> 01:35:30.480] We can do it.
[01:35:30.480 --> 01:35:40.640] It wouldn't happen if we didn't have the science of aging metrics we've been discussing, these new ways to track a person, you know, really accurately and temporally.
[01:35:40.640 --> 01:35:47.200] And it wouldn't happen without the multimodal AI to assemble, integrate all the data at the individual level.
[01:35:47.200 --> 01:35:50.560] So it's these two things coming together that's made this possible.
[01:35:50.560 --> 01:35:53.280] It's a unique, you know, really momentous time.
[01:35:53.280 --> 01:35:59.200] And that's why, you know, I'm so optimistic that we can make a difference.
[01:35:59.200 --> 01:36:07.280] This will be the chance in medicine to finally fulfill that fantasy of primary prevention.
[01:36:07.280 --> 01:36:12.640] And really, at the end of the day, it comes down to creating large data sets on each individual.
[01:36:12.640 --> 01:36:38.360] So learning about all your biomarkers and data from genetics to proteins to lab testing to be able to understand the root causes and the risks, and then using AI and big data analytics to actually make sense of it all through the lens of our new understandings of human biology and like systems biology.
[01:36:38.360 --> 01:36:44.920] And to me, that's to me so exciting because we've been sort of just playing reactive medicine for so long.
[01:36:44.920 --> 01:36:49.720] And this is a time when we can move towards more proactive medicine.
[01:36:49.720 --> 01:36:52.120] And I think doctors would be happy about that.
[01:36:52.600 --> 01:37:04.760] They can figure out if we can figure out a way to make them do their job in a more sort of streamlined, easy way that makes this accessible to them and to their patients, it's going to be a game changer.
[01:37:04.920 --> 01:37:10.680] Yeah, I mean, you know, we've been banking on cures, and that's much harder than prevention.
[01:37:10.680 --> 01:37:11.080] Yeah.
[01:37:11.080 --> 01:37:14.680] And, you know, a pound of winning plan.
[01:37:14.680 --> 01:37:17.320] If we get serious about it, we can really do something.
[01:37:17.320 --> 01:37:18.040] Well, that's exciting.
[01:37:18.280 --> 01:37:21.800] I think everybody needs to check out your book, Super Agers.
[01:37:22.600 --> 01:37:23.960] It's quite a story.
[01:37:23.960 --> 01:37:29.560] It's a little more sort of technical than maybe most people would like, but there's Chat GPT.
[01:37:29.560 --> 01:37:31.480] You can look up stuff you don't understand.
[01:37:32.120 --> 01:37:36.600] And I think that this book is the potential to really change our thinking in medicine.
[01:37:36.840 --> 01:37:42.200] I really enjoyed it and I'm really grateful for you being so curious.
[01:37:42.200 --> 01:37:44.440] You're like a curious George.
[01:37:45.080 --> 01:37:47.560] And I think, thank you for your curiosity.
[01:37:47.560 --> 01:37:50.200] Thank you for all the work you've done in medicine for so many years.
[01:37:50.200 --> 01:37:56.200] And hope we get to chat again soon and get you back on the podcast and we talk about some things we could talk about.
[01:37:56.200 --> 01:38:01.080] I just would add, I tried to get it as simple as I could for everyone to understand.
[01:38:01.080 --> 01:38:03.400] And there are some parts that get a little dense.
[01:38:03.720 --> 01:38:06.040] I apologize early in the book for that.
[01:38:06.040 --> 01:38:09.160] But I think there's a lot of things in there that hopefully everyone can understand.
[01:38:09.160 --> 01:38:14.960] And I did do the reading so that people don't have to, you know, read it.
[01:38:14.960 --> 01:38:19.360] They can just do the audio and hear the passion and all that.
[01:38:14.680 --> 01:38:22.160] And finally, there's 70-some graphs in there.
[01:38:22.480 --> 01:38:26.480] So a lot of times people can grasp the graphs.
[01:38:26.480 --> 01:38:32.560] And so hopefully your point is a good one because there's a lot of 1800 citations.
[01:38:32.560 --> 01:38:33.920] So there's a lot there.
[01:38:33.920 --> 01:38:37.280] Hopefully, the people will get something out of it.
[01:38:37.440 --> 01:38:40.640] I know I'm going to see you well over 100 years old.
[01:38:41.120 --> 01:38:42.240] I hope you're right.
[01:38:42.240 --> 01:38:43.280] And vice versa.
[01:38:43.280 --> 01:38:45.520] If you get to 100, invite me to your birthday.
[01:38:45.840 --> 01:38:58.240] I just want to get to whenever age and stay as long as I can to meet that kind of welderly criteria of plus 80 plus and no age-related major diseases that we've been discussing.
[01:38:58.240 --> 01:38:59.520] I think that's a take-home.
[01:38:59.520 --> 01:39:01.360] Don't end up being elderly.
[01:39:01.360 --> 01:39:04.080] You can be welderly by just following this advice.
[01:39:04.080 --> 01:39:05.040] We're going to get there.
[01:39:05.040 --> 01:39:06.800] A lot more welderly in the future.
[01:39:06.800 --> 01:39:08.080] That's what's in store.
[01:39:08.080 --> 01:39:08.560] Thank you.
[01:39:08.560 --> 01:39:08.880] All right.
[01:39:08.880 --> 01:39:10.000] Well, thanks so much, Eric.
[01:39:10.000 --> 01:39:10.720] Thank you.
[01:39:10.720 --> 01:39:14.800] If you love this podcast, please share it with someone else you think would also enjoy it.
[01:39:14.800 --> 01:39:17.120] You can find me on all social media channels at Dr.
[01:39:17.120 --> 01:39:17.920] Mark Hyman.
[01:39:17.920 --> 01:39:18.400] Please reach out.
[01:39:18.400 --> 01:39:20.400] I'd love to hear your comments and questions.
[01:39:20.400 --> 01:39:22.720] Don't forget to rate, review, and subscribe to the Dr.
[01:39:22.720 --> 01:39:24.960] Hyman Show wherever you get your podcasts.
[01:39:24.960 --> 01:39:27.120] And don't forget to check out my YouTube channel at Dr.
[01:39:27.120 --> 01:39:30.320] Mark Hyman for video versions of this podcast and more.
[01:39:30.320 --> 01:39:32.240] Thank you so much again for tuning in.
[01:39:32.240 --> 01:39:33.600] We'll see you next time on the Dr.
[01:39:33.600 --> 01:39:34.560] Hyman Show.
[01:39:34.560 --> 01:39:41.680] This podcast is separate from my clinical practice at the Ultra Wellness Center, my work at Cleveland Clinic, and Function Health, where I am chief medical officer.
[01:39:41.680 --> 01:39:44.480] This podcast represents my opinions and my guests' opinions.
[01:39:44.480 --> 01:39:48.400] Neither myself nor the podcast endorses the views or statements of my guests.
[01:39:48.400 --> 01:39:55.360] This podcast is for educational purposes only and is not a substitute for professional care by a doctor or other qualified medical professional.
[01:39:55.360 --> 01:40:01.640] This podcast is provided with the understanding that it does not constitute medical or other professional advice or services.
[01:39:59.760 --> 01:40:05.800] If you're looking for help in your journey, please seek out a qualified medical practitioner.
[01:40:06.040 --> 01:40:14.360] And if you're looking for a functional medicine practitioner, visit my clinic, the ultrawellnesscenter at ultrawellnesscenter.com, and request to become a patient.
[01:40:14.360 --> 01:40:22.360] It's important to have someone in your corner who is a trained, licensed healthcare practitioner and can help you make changes, especially when it comes to your health.
[01:40:22.360 --> 01:40:27.000] This podcast is free as part of my mission to bring practical ways of improving health to the public.
[01:40:27.000 --> 01:40:31.400] So I'd like to express gratitude to sponsors that made today's podcast possible.
[01:40:31.400 --> 01:40:33.400] Thanks so much again for listening.

Prompt 6: Key Takeaways

Now please extract the key takeaways from the transcript content I provided.

Extract the most important key takeaways from this part of the conversation. Use a single sentence statement (the key takeaway) rather than milquetoast descriptions like "the hosts discuss...". 

Limit the key takeaways to a maximum of 3. The key takeaways should be insightful and knowledge-additive. 

IMPORTANT: Return ONLY valid JSON, no explanations or markdown. Ensure:
- All strings are properly quoted and escaped
- No trailing commas
- All braces and brackets are balanced
Format: {"key_takeaways": ["takeaway 1", "takeaway 2"]}

Prompt 7: Segments

Now identify 2-4 distinct topical segments from this part of the conversation.

For each segment, identify:
- Descriptive title (3-6 words)  
- START timestamp when this topic begins (HH:MM:SS format)
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Most important Key takeaway from that segment. Key takeaway must be specific and knowledge-additive.
- Brief summary of the discussion

IMPORTANT: The timestamp should mark when the topic/segment STARTS, not a range. Look for topic transitions and conversation shifts.

Return ONLY valid JSON. Ensure all strings are properly quoted, no trailing commas:
{
  "segments": [
    {
      "segment_title": "Topic Discussion", 
      "timestamp": "01:15:30",
      "key_takeaway": "main point from this segment",
      "segment_summary": "brief description of what was discussed"
    }
  ]
}

Timestamp format: HH:MM:SS (e.g., 00:05:30, 01:22:45) marking the START of each segment.

Prompt 8: Media Mentions

Now scan the transcript content I provided for ACTUAL mentions of specific media titles:

Find explicit mentions of:
- Books (with specific titles)
- Movies (with specific titles)  
- TV Shows (with specific titles)
- Music/Songs (with specific titles)

DO NOT include:
- Websites, URLs, or web services
- Other podcasts or podcast names

IMPORTANT: 
- Only include items explicitly mentioned by name. Do not invent titles.
- Valid categories are: "Book", "Movie", "TV Show", "Music"
- Include the exact phrase where each item was mentioned
- Find the nearest proximate timestamp where it appears in the conversation
- THE TIMESTAMP OF THE MEDIA MENTION IS IMPORTANT - DO NOT INVENT TIMESTAMPS AND DO NOT MISATTRIBUTE TIMESTAMPS
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Timestamps are given as ranges, e.g. 01:13:42.520 --> 01:13:46.720. Use the EARLIER of the 2 timestamps in the range.

Return ONLY valid JSON. Ensure all strings are properly quoted and escaped, no trailing commas:
{
  "media_mentions": [
    {
      "title": "Exact Title as Mentioned",
      "category": "Book",
      "author_artist": "N/A",
      "context": "Brief context of why it was mentioned",
      "context_phrase": "The exact sentence or phrase where it was mentioned",
      "timestamp": "estimated time like 01:15:30"
    }
  ]
}

If no media is mentioned, return: {"media_mentions": []}

Full Transcript

[00:00:00.320 --> 00:00:02.000] Coming up on this episode of the Dr.
[00:00:02.000 --> 00:00:02.880] Hyman Show.
[00:00:02.880 --> 00:00:11.440] When you start talking about preventing Alzheimer's and picking it up early, how early can you start to see the PTAU changes?
[00:00:11.440 --> 00:00:18.800] PTAW217 is the very first one that goes up and it starts 20 years before mild cognitive impairment.
[00:00:18.800 --> 00:00:19.680] 20 years.
[00:00:19.680 --> 00:00:20.000] Dr.
[00:00:20.000 --> 00:00:30.400] Eric Topol is a world-renowned physician using data, tech, and deep insight to transform how we detect and prevent diseases like Alzheimer's before they even start.
[00:00:30.400 --> 00:00:38.640] There's so much data to show that that social isolation is a risk factor for neurodegenerative and cardiovascular and even cancer.
[00:00:38.640 --> 00:00:41.760] Strength training is a powerful drug and sleep is a powerful drug.
[00:00:41.760 --> 00:00:44.480] They're better than most of the drugs we have, actually.
[00:00:48.240 --> 00:00:50.800] In functional medicine, we always start with the gut.
[00:00:50.800 --> 00:00:56.000] It's at the core of nearly every aspect of health, from digestion and immune function to brain and skin health.
[00:00:56.000 --> 00:01:01.440] Your gut microbiome regulates inflammation, absorbs nutrients, and maintains the integrity of your gut barrier.
[00:01:01.440 --> 00:01:07.680] That's why I take and recommend SEAD's DSO1 Daily Symbiotic, a next-level probiotic designed to go beyond digestion.
[00:01:07.680 --> 00:01:17.840] With 24 clinically studied probiotic strains and a pomegranate-based prebiotic, DSO1 supports gut immune function, gut barrier integrity, and even heart health through the gut-liver axis.
[00:01:17.840 --> 00:01:19.600] But here's what's really exciting.
[00:01:19.600 --> 00:01:24.480] Research now shows that gut health directly impacts skin health through the gut-skin axis.
[00:01:24.480 --> 00:01:29.680] DSO1 contains targeted strains clinically validated to support clear, hydrated skin from within.
[00:01:29.680 --> 00:01:33.600] As a member of SEED's clinical board, I've seen the science behind their formulations.
[00:01:33.600 --> 00:01:40.960] And new research shows DSO1 supports short-chain fatty acid production, which is key for gut barrier function, immune health, and healthy aging.
[00:01:40.960 --> 00:01:45.840] If you're ready to optimize your gut health, SEED is offering my community 25% off your first month.
[00:01:45.840 --> 00:01:49.680] Just head to seed.com/slash hymen and use code 25-hyman at checkout.
[00:01:49.680 --> 00:01:53.840] That's seed.com hymen with code 25-hyman for 25% off your first month.
[00:01:53.840 --> 00:02:00.440] I'm incredibly intentional about how I feel my brain because whether I'm with patients, writing, or leading a team, focus and clarity matter.
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[00:03:28.760 --> 00:03:30.440] Welcome back to the podcast, Dr.
[00:03:30.440 --> 00:03:31.080] Topols.
[00:03:30.960 --> 00:03:32.040] It's good to have you again.
[00:03:32.040 --> 00:03:32.760] Thanks, Mark.
[00:03:32.760 --> 00:03:33.560] Good to be with you.
[00:03:33.560 --> 00:03:39.480] Well, last time, you know, we talked a lot about AI and health and medicine and gotten some pretty cool topics.
[00:03:39.480 --> 00:03:45.680] Since then, you've written a book called Super Agers, which I think is a great title.
[00:03:46.000 --> 00:03:56.880] When you start talking about preventing Alzheimer's and picking it up early, how early can you start to see the PTAU changes, for example, or the proteomic cocktail change?
[00:03:57.200 --> 00:03:57.520] Yeah.
[00:03:58.080 --> 00:03:59.840] Is it five years before they get symptoms?
[00:03:59.840 --> 00:04:00.800] Is it 10, 20 years?
[00:04:01.040 --> 00:04:01.840] Yeah, I'm so glad you guys.
[00:04:02.000 --> 00:04:03.040] What do we know about that?
[00:04:03.200 --> 00:04:12.080] PTAU217 is the very first one that goes up and it starts 20 years before mild cognitive impairment.
[00:04:12.080 --> 00:04:13.200] 20 years.
[00:04:13.200 --> 00:04:14.160] I mean, it's incredible.
[00:04:14.720 --> 00:04:15.520] That's pre-dementia.
[00:04:15.840 --> 00:04:16.080] Yeah.
[00:04:16.080 --> 00:04:16.320] Yeah.
[00:04:16.320 --> 00:04:21.440] I mean, you got another few years before when you go from MCI to actual Alzheimer's.
[00:04:21.600 --> 00:04:28.880] Yeah, it reminds me of this patient I had who had APOE double four, and that's the high-risk Alzheimer's gene.
[00:04:28.880 --> 00:04:32.800] It doesn't mean you're going to get it, but it really dramatically increases the rest.
[00:04:33.040 --> 00:04:37.920] She was a patient of mine at Canyon Ranch like 25 years ago, and she was in her 90s.
[00:04:37.920 --> 00:04:38.720] She was a dentist.
[00:04:38.720 --> 00:04:41.840] She was still working and she had been a health nut her whole life.
[00:04:41.840 --> 00:04:44.640] Here she was in her 90s, completely cognitively intact.
[00:04:44.640 --> 00:04:50.160] Not sure I'd want her to be my dentist at 95, but still she was all there.
[00:04:50.160 --> 00:04:55.920] And I was like, wow, it was a very, it was one of those memorable patients that, you know, teaches you a lesson about what's possible.
[00:04:55.920 --> 00:05:01.120] And I was like, wait, just because you have a genetic risk doesn't mean you're going to get the disease.
[00:05:01.120 --> 00:05:11.040] Like everybody in my mother's side of the family on her dad's side all had severe heart disease in their 50s, heart attacks, you know, bypasses and so forth.
[00:05:11.040 --> 00:05:13.360] And I thought, oh boy, I'm going to be in trouble.
[00:05:13.360 --> 00:05:17.280] But it turns out that they might have a predisposition, but they're not predestined.
[00:05:17.440 --> 00:05:30.440] You've kind of started, I think, and you can correct me if I'm wrong, down this road by doing this study of elderly people who you end up calling welderly, which were people that lived a long time.
[00:05:29.840 --> 00:05:34.040] And you dove into a lot of things, genetics, lifestyle.
[00:05:34.200 --> 00:05:38.440] And I would love you to sort of unpack some of the myths that got busted there.
[00:05:38.440 --> 00:05:48.440] Because I think everybody thinks that, you know, there's a longevity gene, or if you just, you know, had a good hand dealt you with your genetic cards that you're going to live a long time.
[00:05:48.760 --> 00:05:51.400] And if you don't, you're kind of stuck with whatever you got.
[00:05:51.400 --> 00:05:56.760] You know, oh, my father got heart disease, my mother had diabetes, and my grandma got Alzheimer's.
[00:05:56.920 --> 00:06:00.360] I'm just kind of destined to be getting some disease in the future.
[00:06:00.360 --> 00:06:03.560] But you kind of found some surprising things when you did this study.
[00:06:03.880 --> 00:06:07.080] Can you unpack that study a little bit, what you found and what was surprising about it?
[00:06:07.080 --> 00:06:09.240] So it was called the Welderly Study.
[00:06:09.240 --> 00:06:20.920] And it took seven years to find 1,400 people who were average age near 90 and up to 102 who had never had a chronic illness, age-related or otherwise.
[00:06:20.920 --> 00:06:29.640] So it was a very unique cohort that has not yet ever been replicated in terms of that type of demographic.
[00:06:29.640 --> 00:06:32.760] And we did whole genome sequencing on all of them.
[00:06:32.760 --> 00:06:37.160] And surprisingly, we thought we'd find, as you said, all these genetic underpinnings.
[00:06:37.160 --> 00:06:38.680] And we found almost nothing.
[00:06:38.680 --> 00:06:49.640] This is also consistent with so many of these people had relatives, like the patient I present in the book, Lee Rushall, who is 98.
[00:06:49.640 --> 00:06:52.840] And her parents died in their 50s and 60s.
[00:06:52.840 --> 00:06:54.600] Her brothers, the same.
[00:06:54.600 --> 00:06:56.600] And so it is a genetic story.
[00:06:56.600 --> 00:07:02.200] And for many people, like myself, with a terrible family history, it's quite liberating.
[00:07:02.520 --> 00:07:04.520] But of course, some of it's genetics.
[00:07:04.520 --> 00:07:08.040] But for the most part, it's much less than we thought.
[00:07:08.040 --> 00:07:09.640] It was a big surprise to us.
[00:07:09.640 --> 00:07:13.640] It was a disappointment because we thought we're going to find all these important things.
[00:07:13.960 --> 00:07:18.880] And it's really in contrast to the elderly, which is, as you know, the elderly.
[00:07:19.520 --> 00:07:20.640] Elderly, I like that.
[00:07:20.640 --> 00:07:21.280] I like that.
[00:07:14.840 --> 00:07:22.000] Yeah, elderly.
[00:07:22.400 --> 00:07:27.200] The elderly are the people over 60 that have all these chronic age-related diseases.
[00:07:27.200 --> 00:07:34.480] The contrast is striking, and the genetic story is much less important than I think we had forecasted.
[00:07:34.720 --> 00:07:39.680] And also, of course, if you talk to these people, they really did take care of themselves.
[00:07:39.680 --> 00:07:41.600] They really had good lifestyles.
[00:07:41.600 --> 00:07:43.200] I think we learned a lot from them.
[00:07:43.200 --> 00:07:44.320] Can you talk a little bit about that?
[00:07:44.320 --> 00:07:52.960] Because that's part of what your work is really focused on: the polygenic risk, which means what are the patterns of genes that put you at risk, but don't necessarily make you predestined?
[00:07:52.960 --> 00:08:03.280] Yeah, that's really important that you're bringing up because there are several studies I review in the book of polygenic risk and how that's neutralized by lifestyle factors.
[00:08:03.280 --> 00:08:13.280] That's another way to support what we found on the welderly, whatever genetic load there is or burden, that there's ways to titrate that by taking care of ourselves.
[00:08:13.280 --> 00:08:15.520] But there's another point that's really interesting.
[00:08:15.520 --> 00:08:19.200] Some of the people in that welderly group did not take care of themselves.
[00:08:19.200 --> 00:08:23.840] I remember one fellow 99 years old who was still smoking two packs a day.
[00:08:23.840 --> 00:08:24.400] Wow.
[00:08:24.400 --> 00:08:32.320] Nothing, of course, is 100%, but there's a lot to titration of risk with really good lifestyle behaviors.
[00:08:32.320 --> 00:08:42.560] But there's another factor here, whether it's random or whether I do think, as I get into it later in the book, our immune system is so critical.
[00:08:42.560 --> 00:08:48.240] And that is giving us that resilience to withstand the threat of age-related diseases.
[00:08:48.200 --> 00:08:56.080] And I think we're only scratching the surface right now because clinically, we don't have a way to get the metrics of our immune system.
[00:08:56.080 --> 00:09:04.360] We're just starting to do that now, and we need to really get something that would be part of our assessment, whether it's annual checkup or whatever, particularly as we get older.
[00:09:04.680 --> 00:09:12.440] As you well know, we have this problem with immunosenescence or immune system starting to really let our guard down as we get older.
[00:09:12.440 --> 00:09:14.120] And it's highly variable.
[00:09:14.120 --> 00:09:23.640] Some people, it's entirely intact all the way through their 90s, and other people, it's already starting to lose some of its integrity in their 50s and 60s.
[00:09:23.640 --> 00:09:31.640] Yeah, so a lot of what people think of as the normal age-related diseases, heart disease, cancer, diabetes, dementia, these are all inflammatory diseases.
[00:09:31.640 --> 00:09:34.600] And there's a term for this called inflammaging.
[00:09:34.600 --> 00:09:35.080] Yes.
[00:09:35.080 --> 00:09:36.840] And that we tend to get more inflamed as we get older.
[00:09:36.840 --> 00:09:43.160] So on one hand, our immune system works less well to fight against infections, but on the other hand, it's overactive and causing inflammation.
[00:09:43.160 --> 00:09:51.240] And I think, you know, one of the things you talked about in the book is your epigenetic clocks, biological clocks, and how do we look at organ clocks and overall clocks.
[00:09:51.240 --> 00:09:57.640] And, you know, I was thinking about the other day, it occurred to me that when we measure a lot of the biological clocks, we do it through a blood test.
[00:09:57.960 --> 00:10:06.600] And the cells we're looking at, because there's no cells except for white blood cells, because red cells have no nucleus or no DNA.
[00:10:06.600 --> 00:10:09.640] So white blood cells are the things we're actually measuring these clocks on.
[00:10:09.640 --> 00:10:12.600] So are we actually indirectly measuring our immune age?
[00:10:12.600 --> 00:10:26.040] Yeah, so this is really important: that the epigenetic methylation clock, that is a body-wide assessment of biological age, but it doesn't, as you say, it doesn't get to the crux of the matter.
[00:10:26.040 --> 00:10:38.280] And so that's why it's so exciting on these proteins or proteomic scores, where you take up to 11,000 plasma proteins and you get eight organ clocks, including the immune system.
[00:10:38.280 --> 00:10:41.000] So, brain, heart, liver, kidney.
[00:10:41.000 --> 00:10:44.760] This is really great because now this can be done very inexpensively.
[00:10:45.520 --> 00:10:54.000] We're doing it in our research these days, and the costs for us have come down from what was it, eight or nine hundred dollars to less than a hundred dollars.
[00:10:54.640 --> 00:11:00.000] And the biobank, UK Biobank, is doing it for $50 for in 500,000 people.
[00:11:00.000 --> 00:11:02.240] They've already done it in 50, some thousand.
[00:11:02.240 --> 00:11:15.120] And so, when you have those protein clocks, you know, with AI separates out what's tagged to each organ, that's getting at your point, Mark, because it's no longer relying on just some white cells.
[00:11:15.120 --> 00:11:20.240] It's actually getting to the crux of the proteins that are associated with each organ.
[00:11:20.240 --> 00:11:29.360] So, it's our first cut of a way to inexpensively get a readout on the aging of each organ and also our immune system.
[00:11:29.360 --> 00:11:31.440] And that's a, I think that's a breakthrough.
[00:11:31.440 --> 00:11:37.120] And it's going to be part of our routine assessment in patients going forward.
[00:11:37.120 --> 00:11:38.240] And it's critical.
[00:11:38.240 --> 00:12:01.280] To me, the science of aging has brought these things forward, not just these ideas of reversing aging with fancy things like partial epigenetic reprogramming or centolytics or telomeres lengthening and all kinds of stem cells, but rather the metrics that have come in these recent years, like organ clocks and other things we'll talk about.
[00:12:01.280 --> 00:12:09.200] That's what's so exciting, giving us this real opportunity to prevent age-related diseases like we've never done before.
[00:12:09.200 --> 00:12:11.200] Yeah, I just want to unpack that because it's so important.
[00:12:11.200 --> 00:12:12.640] I'm sure most people will get it.
[00:12:12.640 --> 00:12:28.320] So, normally, when we look at biological age, quote, biological age, and the way it's been measured in the past, it's been by looking at your your genes and the epigenome, which is basically the control mechanism over your genes that determines which genes get turned on or off or expressed.
[00:12:28.320 --> 00:14:05.120] And we're looking at the patterns in that epigenome that give us a sense of your biological age and that's kind of an expensive somewhat nonspecific way to check but you're talking about this new technology using the tens of thousands of proteins in our blood that can be measured very easily and cheaply that show patterns that can give you clues about the specific rate of aging of different organs in your body is that right yeah and that's the key because it's not just you know with polygenic risk score or genome sequencing or things like you know apo e4 that you mentioned that just said that just told us yes or no that just told us you are maybe at risk for this type of cancer or alzheimer's whatever now we're getting at the point of not just what organ but when so the three major age related diseases uh take more than 20 years uh cancer for almost all cancers uh cardiovascular and certainly alzheimer's uh neurodegenerative they take more than 20 years and we've never really been able to get on top of that with all this runway that we have to work with it's incredible and so yeah you're right you know now we have a way to be ahead of it uh and that these metrics uh these uh ways of seeing what in what person what organ if if one is uh aging too fast out of pace with that person um and also, what is the trajectory or arc of that?
[00:14:05.120 --> 00:14:10.480] So, this is, I think um an opportunity that we've never had before and it's a it's a really big advantage.
[00:14:10.480 --> 00:14:19.760] Yeah, I mean you you you're a cardiologist, so you you were taught in you know plumbing 101, basically, and waiting until things happen.
[00:14:19.760 --> 00:14:26.560] And yes, you could give a statin, but that's a very, you know, kind of, I would say, weak tool.
[00:14:26.560 --> 00:14:32.800] I mean, it's a tool, but you know, the benefits marginal, like it's not like a panacea or a magic pill.
[00:14:32.800 --> 00:14:37.440] Yeah, it works well, you know, someone's already had a heart attack, secondary prevention.
[00:14:37.440 --> 00:14:39.120] But we're not making big inroads.
[00:14:39.120 --> 00:14:43.760] There's still plenty of people having heart attacks and bypass surgery and stents and everything else.
[00:14:43.760 --> 00:14:45.680] So we have to do better.
[00:14:45.920 --> 00:14:52.800] And as you know, cardiovascular is the most preventable of these three diseases, 80-90%.
[00:14:53.040 --> 00:14:58.800] Our colleagues, former colleagues from Cleveland Clinic, came out with that's 90%, others 80%.
[00:14:58.800 --> 00:15:05.040] But then cancer and neurodegenerative are 40-50% preventable through lifestyle.
[00:15:05.440 --> 00:15:12.400] So we know some things, even without these new metrics and new capabilities, to be able to prevent these diseases.
[00:15:12.400 --> 00:15:13.440] We're just not doing it.
[00:15:13.440 --> 00:15:17.840] And did you find out in that study of the welderly, what were those things that you found?
[00:15:17.840 --> 00:15:18.800] What was surprising?
[00:15:18.960 --> 00:15:22.800] What did you sort of see that you were surprised at or unexpected?
[00:15:23.280 --> 00:15:32.640] Well, it was interesting, the disposition of these people, very almost all of them, remarkably upbeat people.
[00:15:32.960 --> 00:15:38.560] You did not see people that were complaining or misanthropes or anything like that.
[00:15:38.560 --> 00:15:46.880] You know, they had a relatively sunny disposition, like Lee Russol and the other fellow who I present in the book, two patients of mine.
[00:15:47.120 --> 00:15:48.960] They were kind of prototypic.
[00:15:48.960 --> 00:15:56.080] So that's one thing, you know, it's hard to, there's not hard science on personality and being optimistic.
[00:15:56.080 --> 00:16:01.240] Of course, they're very grateful for how well they've healthily aged, but it's more than that.
[00:16:01.240 --> 00:16:03.560] They've been that way, you know, throughout their lives.
[00:16:03.880 --> 00:16:05.320] They're physically active.
[00:16:05.320 --> 00:16:08.040] You know, they're not sitting around.
[00:16:08.760 --> 00:16:17.720] I remember when I was getting back in touch with my 98-year-old, she's so busy with her art gallery, oil paintings.
[00:16:18.040 --> 00:16:20.920] It was hard to get her, you know, an appointment to go visit her.
[00:16:21.880 --> 00:16:25.560] So these people, they stay busy, they stay active.
[00:16:26.040 --> 00:16:27.560] They're not socially isolated.
[00:16:27.560 --> 00:16:29.240] They don't live in a cave, you know.
[00:16:29.240 --> 00:16:31.240] And they're relatively thin.
[00:16:31.720 --> 00:16:40.360] You don't see much obesity in people who are well into their 90s who have staved off any major age-related disease.
[00:16:40.360 --> 00:16:44.600] So they have a profile that's pretty typical among this group.
[00:16:44.600 --> 00:16:46.200] And they're not common.
[00:16:46.200 --> 00:16:48.920] I mean, really, it took seven years to find this cohort.
[00:16:48.920 --> 00:16:54.680] So yeah, we're talking about well less than 1% of people in that age group.
[00:16:54.680 --> 00:16:56.120] Yeah, I mean, less common in America.
[00:16:56.680 --> 00:17:02.760] I was in Sardinia and Korea, and you see more of those people who are, you know, fit and thin and healthy and happy.
[00:17:02.760 --> 00:17:03.640] I mean, yeah, it's true.
[00:17:03.640 --> 00:17:07.240] I think optimists live longer, even if they're wrong.
[00:17:08.920 --> 00:17:09.480] That's a good news.
[00:17:09.880 --> 00:17:10.440] I do that.
[00:17:10.440 --> 00:17:12.440] You know, the mental health.
[00:17:12.520 --> 00:17:12.920] Yeah.
[00:17:12.920 --> 00:17:14.840] I call myself a pathological optimist.
[00:17:14.840 --> 00:17:19.000] I don't know why, but I go to see the life of Brian.
[00:17:19.000 --> 00:17:20.440] You'll look on the bright side of life.
[00:17:20.440 --> 00:17:23.320] You know, it's kind of a funny thing, Monty Python skip.
[00:17:23.320 --> 00:17:25.400] But I think that mindset plays a big role.
[00:17:25.400 --> 00:17:36.600] And I think we underestimate the role of our beliefs and our mindset and our view of the world and our level of gratitude, our level of service or engagement, our connection to other people.
[00:17:36.600 --> 00:17:40.680] They seem like squishy things, but I think they are really consequential.
[00:17:40.680 --> 00:17:57.200] Yeah, no, I had a whole chapter on mental health because of its primacy here in the interactions with physical health and how stress, anxiety, depression, you know, is a key to these age-related diseases, how we deal with that.
[00:17:57.200 --> 00:18:05.120] And as you touched on earlier, this whole inflammation story is a common thread of the big three age-related diseases.
[00:18:05.120 --> 00:18:10.480] And, you know, we know that stress can induce that, anxiety.
[00:18:10.480 --> 00:18:22.080] So, any way that we can keep that inflammation low, and of course, that's going to be very much a factor of what we eat and our exercise and sleep health and all that.
[00:18:22.080 --> 00:18:23.760] So, there's so many things.
[00:18:23.760 --> 00:18:33.600] It could be environmental toxins burden that have that effect on inflammation, but we never should underestimate our mental health for that factor.
[00:18:33.600 --> 00:18:41.040] I was reading a lot about sociogenomics years ago and this whole idea that how our social relationships and connections affect our gene expression.
[00:18:41.040 --> 00:18:45.200] And I remember seeing these studies where they looked at people who were in relationship.
[00:18:45.200 --> 00:18:50.320] If they had a conflictual relationship, they were turning on inflammatory genes and gene expression.
[00:18:50.320 --> 00:18:56.560] If they had loving heart-centered connections, they would have anti-inflammatory genes turned on, you know.
[00:18:56.880 --> 00:19:09.680] And I think that's kind of worth noting that it may not be a hard science, but I think it's, although that was pretty good science, it was really just this idea that we should not neglect our relationships.
[00:19:09.680 --> 00:19:20.080] And often, I think what happens in people's lives is they work hard, they have their career, their family, they go and go, go, and they neglect their social relationships and their networks, and they end up like retiring or stopping.
[00:19:20.080 --> 00:19:24.480] And they have like, where are their friends and who are the people they can call up?
[00:19:24.480 --> 00:19:27.840] And the amount of loneliness and disconnection is a big factor.
[00:19:27.840 --> 00:19:28.560] No question.
[00:19:28.560 --> 00:19:36.600] And, you know, that was a graph that a lot of people have highlighted in the book about how, as we age, we tend to become reclusive.
[00:19:37.240 --> 00:19:47.800] And there's so much data to show that that social isolation is a risk factor for neurodegenerative and cardiovascular and even cancer.
[00:19:47.800 --> 00:19:49.720] So we want to avoid that.
[00:19:49.720 --> 00:19:53.720] And I think highlighting that, that social interaction.
[00:19:53.720 --> 00:19:57.880] I mean, we are really a social animal.
[00:19:57.880 --> 00:20:03.640] We have to use that ability to help us stay in the mix.
[00:20:03.640 --> 00:20:07.320] And so, you know, this is something I was impressed with that research.
[00:20:07.320 --> 00:20:13.000] I would have been one to discount it, but when I went through it all, it really was cogent.
[00:20:13.240 --> 00:20:20.200] You talked about the polygenic risk score and that it increases your risk, but it doesn't necessarily guarantee you're going to get a problem.
[00:20:20.280 --> 00:20:22.760] There's a lot we know about how to modify that risk.
[00:20:23.000 --> 00:20:39.560] I mean, I'm wondering, you know, the smoker you mentioned earlier who smoked two packs a day, you know, just as there's like the ApoE double four, which is the high-risk Alzheimer's and heart disease gene, the double two, I've heard some people refer to as the jackpot gene.
[00:20:39.640 --> 00:20:45.960] That's like you can smoke and drink and eat whatever you want, and you kind of won the genetic lottery and you don't have to worry as much.
[00:20:46.280 --> 00:20:47.400] Was there anything to that?
[00:20:47.400 --> 00:20:49.960] Was there any parts of that?
[00:20:50.120 --> 00:21:00.760] Well, if you want to pick ApoE2 homozygote, that's pretty good, but it doesn't give you the ability to withstand age-related diseases, it gives you longevity.
[00:21:00.760 --> 00:21:06.920] So that's the difference here that we're talking about: health span versus lifespan.
[00:21:06.920 --> 00:21:11.720] And so, Apolle 2 double is the one you want to get.
[00:21:11.720 --> 00:21:13.880] And of course, I got one copy.
[00:21:13.880 --> 00:21:14.480] I got one copy.
[00:21:14.360 --> 00:21:15.200] Oh, good for you.
[00:21:15.680 --> 00:21:25.120] And in fact, when I go through genome editing, there's a whole chapter in the book where people are editing turning Apolle 4 to Apolle 2 right now.
[00:21:25.120 --> 00:21:27.280] I mean, yeah, I mean, it's wild.
[00:21:27.280 --> 00:21:32.720] And in animals, and, you know, the idea to do this in people, that may happen someday, who knows?
[00:21:32.720 --> 00:21:48.240] But right now, Apo E2, no question that it does, unlike Apolle 4, it has a better associated lifespan, but it doesn't give you that age-related protection from these three diseases, really.
[00:21:48.240 --> 00:21:54.000] What also I think was important in your book is you do talk about the difference between this health span, lifespan distinction.
[00:21:54.000 --> 00:21:57.760] You know, we spend the last 20% of our lives in poor health.
[00:21:57.760 --> 00:22:01.520] That doesn't mean you can do what you want and you're engaged and you feel good, right?
[00:22:01.520 --> 00:22:06.080] And what's the point of living a long life if you feel like crap for the last 20% of your life?
[00:22:06.080 --> 00:22:06.480] Right.
[00:22:06.480 --> 00:22:08.160] Or you're taking a pile of pills.
[00:22:08.160 --> 00:22:12.800] How did they kind of make that almost the same in this welderly group?
[00:22:12.800 --> 00:22:15.120] How is their lifespan, health span the same?
[00:22:15.120 --> 00:22:16.400] There's a couple of things here.
[00:22:16.400 --> 00:22:21.680] We've got to do something about this elderly that you're framing because that's what we have now.
[00:22:22.080 --> 00:22:23.760] That's basically the story.
[00:22:23.760 --> 00:22:33.200] And most people, as they get into the 60s and 70s, they have at least one of these three, if not more, age-related major diseases.
[00:22:33.200 --> 00:22:39.760] That is compromising their health span, and it may indeed their lifespan as well.
[00:22:39.760 --> 00:22:58.160] But living with one of these major diseases, whether it's mild cognitive deficit, moving on to Alzheimer's or one of these cancers that you're trying to be a survivor, fighting it, or certainly all the cardiovascular disease issues that crop up, heart failure and arrhythmias and everything else.
[00:22:58.160 --> 00:22:59.040] This isn't easy.
[00:22:59.040 --> 00:22:59.920] This is not the life you want.
[00:23:00.760 --> 00:23:09.400] What I think is so extraordinary is we're at a time where we have the means of squashing these, preventing these diseases like we never had.
[00:23:09.400 --> 00:23:21.880] So, why accept this the way we've been all these years with this highest density of age-related disease people when we have the stack, the full stack?
[00:23:21.880 --> 00:23:26.520] Now, it isn't just polygenic risk score or sequencing, which we could get.
[00:23:26.520 --> 00:23:31.720] It's also become very inexpensive, but it's all these other layers of data that we've been talking about.
[00:23:31.720 --> 00:23:36.280] The point about that is: let's say the polygenic risk score is wrong or off a bit.
[00:23:36.280 --> 00:23:42.200] You've got all these other checkpoints of layers, and then you have multimodal AI to bring it all together.
[00:23:42.200 --> 00:23:51.160] And so, that's what gives us that pinpoint precision, both with respect to time, you know, when this is going to be cropping up way in advance.
[00:23:51.160 --> 00:23:56.200] And that's when we get all of these people to work with them to prevent the disease.
[00:23:56.200 --> 00:24:06.440] And, of course, that could be the lifestyle plus factors, or it could be drugs and other means, and even more high-tech ways to go into surveillance.
[00:24:06.440 --> 00:24:10.440] So, we have a path to do this for the big three diseases.
[00:24:10.440 --> 00:24:12.040] We just got to get moving on it.
[00:24:12.040 --> 00:24:14.280] I want to unpack that because there's a lot there you said.
[00:24:14.600 --> 00:24:20.280] I want to just ask you a question, though, before we dive into the big three, which is heart disease, cancer, and dementia.
[00:24:20.360 --> 00:24:21.560] You left out diabetes.
[00:24:21.720 --> 00:24:23.560] Yeah, I'm wondering why you left that out.
[00:24:23.560 --> 00:24:26.520] Yeah, because it's sort of the cause of all three of those things.
[00:24:26.680 --> 00:24:27.480] Well, that's right.
[00:24:27.480 --> 00:24:30.680] Diabetes by itself, you know, we can handle that.
[00:24:30.680 --> 00:24:34.040] But the problem with diabetes is it leads to the other three.
[00:24:34.040 --> 00:24:37.480] The other three are the big ones we have to work with.
[00:24:37.480 --> 00:24:41.160] And diabetes isn't necessarily age-related.
[00:24:41.160 --> 00:24:44.440] There's some of that, but it's not nearly like the other three.
[00:24:44.440 --> 00:24:47.280] And it doesn't have the 20-year lead time to work with.
[00:24:47.520 --> 00:24:56.880] So there's a lot of reasons why, although diabetes is considered a killer, certainly can compromise health span, it's mainly working through the other three.
[00:24:56.880 --> 00:25:07.200] You know, people are not dying of diabetes, but they're dying of the heart-related kidney, you know, other sequela, certainly more dementia and more cancer, too.
[00:25:07.200 --> 00:25:09.120] That's why I don't lump it in there.
[00:25:09.120 --> 00:25:12.320] But I think the prototype is Alzheimer's.
[00:25:12.320 --> 00:25:15.440] You saw, I wrote in the book and then also a substack.
[00:25:15.440 --> 00:25:18.720] There's this breakthrough test, the PTAU217.
[00:25:19.200 --> 00:25:35.760] And if you are APOE4, I mean, if you're a carrier, that's 25% of us are carriers, or you have a family history of Alzheimer's, or both, you probably want to get a PTAU217 because it's as good as a cerebral spinal fluid.
[00:25:35.760 --> 00:25:41.680] It's as good as a pet cow scan, you know, which is a lot of radiation and hard to get.
[00:25:42.080 --> 00:25:46.160] And CT scan in the brain, but it's expensive and radiation and hard to get.
[00:25:46.160 --> 00:25:49.920] Yeah, and here you've got a blood test, which is not that expensive.
[00:25:49.920 --> 00:25:52.560] It's available in this country for the past two years.
[00:25:52.560 --> 00:25:55.120] And you know, Mark, most people never heard of it.
[00:25:55.120 --> 00:25:57.760] I think it's part of your function tests that you do.
[00:25:57.920 --> 00:25:58.320] It is.
[00:25:58.320 --> 00:25:58.720] It is.
[00:25:59.040 --> 00:26:00.320] I added that.
[00:26:00.640 --> 00:26:05.120] Yeah, I don't know all the tests that you do in that, but that one is a good one.
[00:26:05.120 --> 00:26:18.880] So then you know you have, if you have, I don't recommend everybody getting this, but if you have APOE4 and you have family history, now you know with the P-TAU test, and you can get a brain clock, okay?
[00:26:19.200 --> 00:26:20.800] You can even get a methylation clock.
[00:26:20.800 --> 00:26:22.800] You've got these layers of data now, right?
[00:26:22.800 --> 00:26:27.200] And you also know about your lifestyle and what's good and what's not so good about it.
[00:26:27.200 --> 00:26:33.240] Now you find, oh, P-Tau-217 is elevated substantially, let's say.
[00:26:33.560 --> 00:26:36.600] Well, this is like an LDL cholesterol, right?
[00:26:36.600 --> 00:26:41.800] Because if you exercise and you go into a healthy lifestyle, you can bring it down.
[00:26:41.800 --> 00:26:52.920] And we've seen a randomized study presented here in San Diego at the Academy of Neurology annual meeting where they had these, the people who had PTAU217 elevated.
[00:26:53.160 --> 00:26:57.480] They were randomly assigned to intervention with lifestyle.
[00:26:57.480 --> 00:27:06.600] And it came way down, you know, P217, PTAW 181, all these markers, 75, up to 75% reduction.
[00:27:06.600 --> 00:27:14.280] That should reduce or, you know, the chances of ever developing Alzheimer's, particularly if it started early.
[00:27:14.280 --> 00:27:20.600] And then, of course, if the person started late, it should put it off, should defer it.
[00:27:20.600 --> 00:27:22.040] So this is exciting.
[00:27:22.040 --> 00:27:25.800] And I'm just amazed that most people don't know about this test.
[00:27:25.800 --> 00:27:26.440] No, I agree.
[00:27:26.760 --> 00:27:30.520] I want to just double down on that because what you're saying is so revolutionary.
[00:27:30.520 --> 00:27:39.480] You know, up till now, basically, if you had a family history of Alzheimer's, you had to cross your fingers and, you know, wait around and hope to not get it.
[00:27:39.480 --> 00:27:46.440] And there wasn't anything we offered for medicine that was going to prevent it or even treat it once you got it.
[00:27:46.440 --> 00:27:47.880] So it was kind of a scary thing.
[00:27:47.880 --> 00:27:51.640] And nobody wanted to know their APOE status because it's like, well, why should I know?
[00:27:51.640 --> 00:27:53.720] Because what am I going to do about it?
[00:27:53.720 --> 00:27:54.280] Yeah.
[00:27:54.280 --> 00:28:05.000] And I think, you know, what we've learned is that now with early biomarker testing, and like you said, these developed 20, 30, 40 years before you ever forget something, right?
[00:28:05.000 --> 00:28:07.640] You forget your keys or you start having memory loss.
[00:28:07.640 --> 00:28:16.240] You can start to see these early clues in your blood and you layer on top of that proteomics, layer on top of that AI to interpret it all.
[00:28:16.240 --> 00:28:21.520] And all of a sudden you have a window into where you might be headed that you can do something about.
[00:28:14.920 --> 00:28:21.760] Yeah.
[00:28:22.000 --> 00:28:38.080] And I think trials like the finger trial and the pointer trial are these large clinical trials that show while all the drugs we have for Alzheimer's have failed, the lifestyle interventions can slow, prevent, slow, and even reverse sometimes the changes that we see.
[00:28:38.080 --> 00:28:49.760] And I think Richard Isaac's work is very exciting about PTAW217 because it's like you can actually start to see how we can actually even reverse it once you start to have it, which is a pretty good idea.
[00:28:49.760 --> 00:29:04.160] That's what's the difference where we were a few years ago to where we are now is that we know that these markers are so accurate and we can use them to see if we're making progress.
[00:29:04.160 --> 00:29:15.680] Okay, so you have the, let's say, the brain organ clock and the p-tau 217 and someone who clearly has a high risk of Alzheimer's and you go six months with this new lifestyle, right?
[00:29:15.680 --> 00:29:22.480] And you see, oh, wow, the brain pace of aging is slowing down and the p-tau 217 has come down 50%.
[00:29:22.480 --> 00:29:24.080] You say, this is working.
[00:29:24.080 --> 00:29:26.320] And if you want, you can do imaging, of course.
[00:29:26.320 --> 00:29:39.200] But this is extraordinary because now we have the GLP-1 drugs like Ozempic, Munjaro, that are being tested in big Alzheimer's trial in thin people.
[00:29:39.600 --> 00:29:41.600] These are not obese or overweight.
[00:29:41.840 --> 00:29:42.640] These are thin people.
[00:29:43.200 --> 00:29:48.320] And because they have such potency of reducing brain inflammation.
[00:29:48.320 --> 00:29:56.320] So, we're not talking about the drugs that are being used for Alzheimer's, which don't work very well and are very risky and can cause hemorrhage in the brain.
[00:29:56.320 --> 00:30:00.360] These are drugs that have been out there, you know, 20-some years.
[00:29:59.920 --> 00:30:02.920] You know, I have a whole chapter in the book is how we blew it.
[00:30:03.160 --> 00:30:14.680] We thought they were only good for diabetes, you know, and it took this scientist in Denmark, Lata Knudsen, who kept pushing, we have to try it, we have to try it in obesity.
[00:30:14.680 --> 00:30:21.400] And they kept saying to her, Well, Lata, it's not going to work because the diabetics only lose three or four pounds.
[00:30:21.400 --> 00:30:28.120] Well, now we see we can get people to lose, you know, 40, 50, 60, 80 pounds.
[00:30:28.440 --> 00:30:30.200] These drugs are so potent.
[00:30:30.200 --> 00:30:39.720] And the reason it was blown was because the diabetics don't lose that weight, and we don't know why still today, which is such a mystery, right?
[00:30:40.040 --> 00:30:42.600] But what if it works in Alzheimer's?
[00:30:42.600 --> 00:30:54.680] Because it's working in so many other ways in terms of addiction, in terms of all these other cardiovascular, many conditions that we did not expect.
[00:30:54.680 --> 00:31:03.400] So, even if it doesn't work, there's other drugs, many other drugs that get well into the brain that knock down brain inflammation like GLP-1.
[00:31:03.400 --> 00:31:08.920] And so, we're going to have drugs for people who are at high risk for Alzheimer's to add to the lifestyle factors.
[00:31:08.920 --> 00:31:16.600] But of course, you want to press on the lifestyle stuff first before you ever really start with the drug.
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[00:33:04.080 --> 00:33:12.240] So, so you're someone who's listening, you go get this test, you're in your 40s, shows up as something that's a little bit elevated.
[00:33:12.240 --> 00:33:13.040] What do you do?
[00:33:13.040 --> 00:33:17.040] Yeah, well, first, don't get the test unless you have the risk factors, right?
[00:33:17.040 --> 00:33:24.560] I mean, you don't really want to get this without ApoE4 status or at least Alzheimer's in your family, right?
[00:33:24.560 --> 00:33:40.600] Because, or a polygenic risk score, even that says you're high-risk for Alzheimer's, something like that, because if you get tests that are not, you don't have a high test pre probability, as you know, you're going to get potentially false positives.
[00:33:40.600 --> 00:33:51.880] And the American Alzheimer's Association, which I think has some problems, they're labeling people with peak tau 217 as stage one Alzheimer's if it's elevated.
[00:33:51.880 --> 00:33:54.120] That's not good because it could be wrong.
[00:33:54.120 --> 00:33:57.960] Any test could be wrong, especially if it's done on the wrong people.
[00:33:57.960 --> 00:34:07.400] So, as long as I'm admonishing that get the test only if you have increased risk, and if it's elevated, then you're going to go on a campaign to bring it down.
[00:34:07.400 --> 00:34:15.080] And no, since you're saying a person's young in their 40s or 50s, they got lots of time to really get on it.
[00:34:15.080 --> 00:34:20.120] And, you know, within a few years, we're going to have a lot more additional ways to bring that down.
[00:34:20.120 --> 00:34:30.520] But just, I mean, the lifestyle story, it's hard to get people to adopt all these healthy behaviors, particularly get isn't just a behavior.
[00:34:30.520 --> 00:34:36.680] How do you get a lot more deep sleep, for example, a lot more sleep regularity, which has big impact?
[00:34:36.680 --> 00:34:37.880] That's not even a behavior.
[00:34:37.880 --> 00:34:41.480] That's just something that people have to learn how to improve.
[00:34:41.480 --> 00:34:51.800] The fact when you get into this aggressive prevention mode, it's more likely that people are going to take it seriously if they have this marker aligned with their risk.
[00:34:51.800 --> 00:35:03.800] So, in terms of the lifestyle, that's sort of a generic term, but let's kind of break it down to diet, exercise, sleep, stress, relationships, I mean, toxins, you call it lifestyle plus.
[00:35:03.800 --> 00:35:04.360] Yeah.
[00:35:04.680 --> 00:35:06.600] What are the biggest levers to pull?
[00:35:06.600 --> 00:35:15.920] Well, if we start with a diet, you know, I think you've been on this, but the ultra-processed foods are just horrendous, right?
[00:35:14.920 --> 00:35:21.680] They are the vectors of inflammation in our body, and they are propagating.
[00:35:21.840 --> 00:35:28.640] They are, I think, we're talking about cause and effect of these three age-related diseases.
[00:35:28.640 --> 00:35:29.440] And the U.S.
[00:35:29.440 --> 00:35:33.920] has the highest consumption in the world, 70% plus.
[00:35:34.240 --> 00:35:38.240] And of course, a lot of people are 80% or more.
[00:35:38.240 --> 00:35:39.840] And in the book, you know, I review.
[00:35:39.840 --> 00:35:40.640] Yeah, that's average.
[00:35:40.640 --> 00:35:41.200] That's average.
[00:35:41.520 --> 00:35:42.160] Yeah, yeah.
[00:35:42.160 --> 00:35:44.160] Children high, very high.
[00:35:44.480 --> 00:35:50.080] And I review in the book of my friend Chris Vontullikin, who wrote the book, Ultra Processed People.
[00:35:50.080 --> 00:35:56.880] And, you know, he went on like a 30-day, and he's a really great physician scientist in the UK.
[00:35:56.880 --> 00:35:59.200] And it told the whole story.
[00:35:59.200 --> 00:36:01.120] He had a brain scan beforehand.
[00:36:01.120 --> 00:36:04.400] He had all these inflammation markers beforehand.
[00:36:04.400 --> 00:36:10.160] And in 30 days, kind of like supersize me, he tried to go as high as he could on ultra-processed food.
[00:36:10.160 --> 00:36:14.640] By the time the 30 days was up, his brain was all inflamed.
[00:36:14.880 --> 00:36:19.280] Every biomarker had gone through the ceiling of abnormality for inflammation.
[00:36:19.280 --> 00:36:21.600] I mean, it was just 30 days of this bad diet.
[00:36:21.600 --> 00:36:23.120] He gained 20 pounds.
[00:36:23.440 --> 00:36:27.920] You know, this is something we have to work on.
[00:36:28.400 --> 00:36:31.680] It's just, we've done nothing in this country to bring it down.
[00:36:31.680 --> 00:36:34.000] Other countries are taking it more seriously.
[00:36:34.000 --> 00:36:38.960] The second thing about the diet, which I think is vital, is the protein craze.
[00:36:38.960 --> 00:36:43.280] We have people out there that are advocating ridiculous amounts of protein.
[00:36:43.280 --> 00:37:00.520] And I reviewed that in the book, that there's danger with that, not only for the kidneys, but also we've seen studies after study that show too high a protein diet, particularly animal protein, can induce, promote atherosclerosis.
[00:37:00.520 --> 00:37:02.440] That's the last thing we want, right?
[00:37:00.000 --> 00:37:03.720] It's pro-inflammatory.
[00:37:03.960 --> 00:37:17.560] So that's why, although it's probably wise if we keep up a decent amount of protein, maybe amp it up a bit as we get older, you know, maybe 1.2, 1.4, or so per kilogram, not per pound.
[00:37:17.560 --> 00:37:19.400] And that's what some people are advocating.
[00:37:19.400 --> 00:37:20.600] And that's just wrong.
[00:37:21.080 --> 00:37:21.880] It's dangerous.
[00:37:21.880 --> 00:37:23.640] There's no data to support it.
[00:37:23.640 --> 00:37:34.680] You know, I talk to people who are on this protein craze, and I try to get them onto the data and the evidence, which is, you know, really a danger sign if they go too high on a daily.
[00:37:34.680 --> 00:37:41.240] And it's not going to increase their muscle mass when you go past good studies, 1.5, 1.6 per kilogram.
[00:37:41.240 --> 00:37:43.400] So those are a couple of the main things.
[00:37:43.400 --> 00:37:48.840] I don't know what you think about that, but a couple of main things about the diet that we need to get out there.
[00:37:48.840 --> 00:37:52.920] And the sugar, the sugar and the starch, too, is just a component of the ultra-processed food.
[00:37:52.920 --> 00:37:56.120] But I think that's part of the driver of what's causing a lot of the problem.
[00:37:56.120 --> 00:37:59.640] And it is, you know, they're calling Alzheimer's type 3 diabetes, right?
[00:37:59.640 --> 00:38:01.160] Diabetes of the brain.
[00:38:01.160 --> 00:38:04.920] And I think that's a big factor for people, the amount of sugar and starch.
[00:38:04.920 --> 00:38:07.240] And it's obviously hidden in the ultra-processed food.
[00:38:07.240 --> 00:38:07.320] Yeah.
[00:38:07.480 --> 00:38:08.760] I think the protein thing is interesting.
[00:38:08.760 --> 00:38:11.880] I mean, I think, what were we going to say something about the sugar thing?
[00:38:12.280 --> 00:38:13.240] I think I agree with you.
[00:38:13.400 --> 00:38:17.400] I reviewed the sugar story, salt, caffeine, alcohol.
[00:38:17.400 --> 00:38:19.240] I mean, we went through every one of these things.
[00:38:19.240 --> 00:38:22.760] Everything you eat, fats and plant-based diets and red meat.
[00:38:22.760 --> 00:38:24.440] And I went through the whole thing.
[00:38:24.440 --> 00:38:30.840] And you're familiar with this recent study of 105,000 people followed 30 years.
[00:38:30.840 --> 00:38:38.040] And only 9% of them, only 9% got to the welderly state past age seven.
[00:38:38.040 --> 00:38:40.120] And the 9%, what do they eat?
[00:38:40.120 --> 00:38:46.640] They mainly play at plant-based foods, Mediterranean diet, some, but small amounts of red meat.
[00:38:44.840 --> 00:38:51.920] The kinds of things you would anticipate, where the data evidence is backing it up.
[00:38:52.240 --> 00:38:54.640] So, yeah, the diet is really important.
[00:38:54.640 --> 00:38:57.920] And we keep seeing study after study reinforcing that.
[00:38:57.920 --> 00:39:00.960] I think one of the things that's important, AJ, those, is being functional.
[00:39:00.960 --> 00:39:02.960] Frailty is the killer.
[00:39:02.960 --> 00:39:07.680] I mean, hip fracture is a bigger risk for death than getting a diagnosis of cancer.
[00:39:08.000 --> 00:39:09.680] That muscle mass is a big deal.
[00:39:10.000 --> 00:39:30.160] And the question is, that's the problem as you get older because when you lose it and it's hard to build it, and there's something called anabolic resistance, meaning when you're older, it takes a lot more work and a lot more protein to do the same thing you did when you had these trophic or growth hormone-like things when you were younger, anabolic hormones that were floating around your blood.
[00:39:30.480 --> 00:39:36.480] And the Protege group, which is a group of protein scientists led by Don Lehman and others, and I've had him on the podcast.
[00:39:36.480 --> 00:39:43.360] He talks about even higher amounts being eaten, like, you know, one up to one and a half to two grams per kilo.
[00:39:43.680 --> 00:40:01.200] And this was like a, I'm not a protein expert, but it was interesting to read their data showing that there was this, to overcome this resistance and the need to maintain muscle mass, that their data was like the kind of global think tank on, I don't know, protein experts together and they came up with.
[00:40:01.520 --> 00:40:09.280] I reviewed all that data and I would just say, you know, if you're going to go past 1.5, 1.6 per kilogram, you're starting to get to a fuzzy zone.
[00:40:09.520 --> 00:40:18.560] But Mark, you can increase your muscle mass not by just, you know, having adequate protein, by doing strength training.
[00:40:18.560 --> 00:40:28.240] And I gotta do that heavy over the last year because after all the research, you know, I always advocated aerobic exercise as a cardiologist.
[00:40:28.720 --> 00:40:29.560] Cardiologists, right?
[00:40:29.440 --> 00:40:34.520] And these people, patients would come in and they were really cut and buffed.
[00:40:34.520 --> 00:40:36.840] And I'd say, well, what are you doing lifting all these weights?
[00:40:29.760 --> 00:40:37.000] Right.
[00:40:37.320 --> 00:40:52.920] Well, now I'm doing that, not maybe as trying to be any like the Terminator, but I've been on a big kick on, you know, resistance and strength training, balance, posture, you know, but also I've never been this strong in my life.
[00:40:52.920 --> 00:40:55.720] And I don't need crazy amounts of protein.
[00:40:55.720 --> 00:40:58.920] The point being is it's part of the exercise.
[00:40:58.920 --> 00:41:02.280] It isn't like you just change your diet and you build up muscles, right?
[00:41:02.280 --> 00:41:04.360] It's the exercise that's so essential.
[00:41:04.360 --> 00:41:15.400] And by the way, the data for resistance training, as I review in the book with various graphs, it's extraordinary for preventing age-related, the big three.
[00:41:15.400 --> 00:41:17.160] So we should be doing that.
[00:41:17.160 --> 00:41:18.360] I learned from that.
[00:41:18.360 --> 00:41:21.400] I didn't realize how impressive that body of data was.
[00:41:21.400 --> 00:41:22.520] Yeah, you and me both.
[00:41:22.520 --> 00:41:25.080] When I was 15 on, I'm like, yeah, I better start strength training.
[00:41:25.080 --> 00:41:26.600] And it's changed my life.
[00:41:26.600 --> 00:41:29.160] And my body, I picture with me when I'm 40, and I was a runner.
[00:41:29.240 --> 00:41:30.120] I was into yoga.
[00:41:30.120 --> 00:41:31.320] I wasn't overweight.
[00:41:31.320 --> 00:41:35.720] But like, my body looked like I was like a skinny little rail compared to now.
[00:41:35.720 --> 00:41:44.840] I'm not like, you know, the Terminator or the rock, but I'm like, you know, at 65, beefier than I've ever been in my whole life.
[00:41:45.160 --> 00:41:49.880] And I was like, wow, this is for me, it's the same crazy as possible.
[00:41:50.120 --> 00:41:52.840] I think this is a really important step.
[00:41:52.840 --> 00:41:58.360] And then the other biggie is, of course, the deep sleep story and regularity.
[00:41:58.360 --> 00:41:59.880] I mentioned it earlier.
[00:41:59.880 --> 00:42:09.960] We need to get, as we get older and going along, as you said, with the inflammaging, is that we don't get enough sleep as we get older, particularly the slow wave deep sleep.
[00:42:09.960 --> 00:42:11.560] And we've got to get that up.
[00:42:11.560 --> 00:42:17.200] When I started looking at that data, I was horrified because I'm not a very good sleep, I had not been a good sleeper.
[00:42:14.760 --> 00:42:20.800] And I started tracking it with a ring and a smartwatch.
[00:42:20.960 --> 00:42:29.360] I'm saying, wow, I'm getting less than 15 minutes of deep sleep a night, you know, and terrible overall scores in my sleep because of that.
[00:42:29.360 --> 00:42:33.200] And so I started finding out what is causing all this problem, right?
[00:42:33.200 --> 00:42:39.920] And because I had very, you know, irregular times of going to sleep, you know, erratic.
[00:42:39.920 --> 00:42:48.320] And what I ate, what I drank, when I exercised, you know, when I ate, all these factors were playing such a big role.
[00:42:48.400 --> 00:42:53.520] Now I've been able to get, it's rare that I wouldn't get over 45 minutes a night, even up to an hour.
[00:42:53.520 --> 00:42:55.040] So it's been a big difference.
[00:42:55.040 --> 00:42:55.840] So I know that.
[00:42:56.240 --> 00:42:57.200] What did you do?
[00:42:57.200 --> 00:42:59.360] Oh, what were the things that made a difference?
[00:42:59.360 --> 00:43:09.760] Yeah, so all these things cumulatively by tracking, learning, like, for example, not exercising too late in the day, not eating too late in the day, you know, in the evening.
[00:43:09.760 --> 00:43:17.440] Interestingly, alcohol affects many people with respect to deep sleep, but that one didn't seem to have too much of an effect on me.
[00:43:17.440 --> 00:43:29.200] Avoiding drinking too much of fluids and then avoiding having to get up, interrupted sleep, made a big difference during the night because I always be hydrating, you know, in the evenings.
[00:43:29.360 --> 00:43:32.720] No, don't hydrate all day long, but don't hydrate in the evening.
[00:43:32.720 --> 00:43:46.080] So lots of things that I did, but you know, the timing and also certain foods, you know, I was basically, I wasn't aware of it, but you know, the indigestion was interrupting sleep somehow.
[00:43:46.400 --> 00:43:54.880] So certain foods, and also, I think there's these interactions, you know, stress and things that we all deal with.
[00:43:54.880 --> 00:43:59.040] I learned about better coping mechanisms to get sleep.
[00:43:59.040 --> 00:44:06.360] And I still like to amp it up more because that data that I review in super ages, it's very impressive.
[00:44:06.600 --> 00:44:15.000] The link between the deep sleep, which is when we get rid of the toxic waste metabolites in our brain.
[00:44:15.000 --> 00:44:15.880] That's the time.
[00:44:15.880 --> 00:44:22.120] And by the way, I know we both see patients that take ambien and other sleep medicines.
[00:44:22.120 --> 00:44:26.040] And what's interesting is that they backfire.
[00:44:26.040 --> 00:44:34.680] Not only do they not get rid of the waste, but they actually increase ambiences, especially been noted to increase the waste that stays in the brain.
[00:44:34.680 --> 00:44:38.280] So the person may feel like they're getting more sleep, but they're not.
[00:44:38.280 --> 00:44:46.600] And of course, along the way, I didn't have it, but certainly one of the concerns I had with that low amount of deep sleep was: did I have sleep apnea?
[00:44:46.600 --> 00:44:47.880] Was that the issue?
[00:44:47.880 --> 00:44:49.640] And that fortunately wasn't the case.
[00:44:49.640 --> 00:44:53.080] But as you know, that's a common problem that doesn't get diagnosed.
[00:44:53.080 --> 00:44:56.920] So it sounds like writing the book helped you live longer because you learn all these things.
[00:44:57.080 --> 00:44:57.400] I don't know.
[00:44:57.640 --> 00:44:59.160] Like you hadn't known before.
[00:45:00.120 --> 00:45:01.160] But those are powerful drugs.
[00:45:01.160 --> 00:45:01.720] Time will be.
[00:45:02.200 --> 00:45:06.120] I mean, strength training is a powerful drug, and sleep is a powerful drug.
[00:45:06.440 --> 00:45:06.760] Yes.
[00:45:07.000 --> 00:45:09.240] They're better than most of the drugs we have, actually.
[00:45:09.240 --> 00:45:09.640] It did.
[00:45:09.640 --> 00:45:18.920] It helped me, but of course, I wasn't going to, once I reviewed all the evidence and I felt compelling, that led me to change my ways.
[00:45:18.920 --> 00:45:21.720] And I'm hoping that's going to help a lot of other people too.
[00:45:21.720 --> 00:45:25.640] But I don't know if it's going to make me into the welderly.
[00:45:25.880 --> 00:45:33.400] With my family history, it's always in my mind, despite our welderly trial study, that, you know, I may not get into the.
[00:45:33.400 --> 00:45:37.080] So far, I fit, I don't have any age-related chronic disease.
[00:45:37.080 --> 00:45:39.960] And I hope I can go another, you know, 10, 20 years.
[00:45:39.960 --> 00:45:40.520] We'll see.
[00:45:40.520 --> 00:45:41.960] Well, I think you're a few years older than me.
[00:45:41.960 --> 00:45:45.440] And if you've escaped those diseases by now, you're probably kind of dodged the bullet.
[00:45:46.080 --> 00:45:46.960] I hope so.
[00:45:44.920 --> 00:45:51.600] I mean, but the main thing is, I wanted to get the hard evidence out there.
[00:45:51.920 --> 00:46:17.040] I wanted to get so people know that there is a huge body of evidence that is not Brian Johnson, don't die, or other longevity clinics that charge $250,000 that do hyperbaric chambers, plasmapheresis, all these putative anti-aging supplements, none of which have any data, you know, all this kind of reckless use of things.
[00:46:17.040 --> 00:46:22.160] I wanted to just put it out there that, hey, this is what we know, and it can make a world of difference.
[00:46:22.160 --> 00:46:25.600] And a lot of this stuff is not very expensive either, you know.
[00:46:25.840 --> 00:46:28.000] So that was the real purpose of doing the book.
[00:46:28.000 --> 00:46:32.720] And I just, as a, as an outgrowth, it helped me too.
[00:46:32.720 --> 00:46:35.280] Yeah, I think the things that work the best cost the least.
[00:46:35.520 --> 00:46:35.840] Yeah.
[00:46:35.840 --> 00:46:36.240] Yeah.
[00:46:36.240 --> 00:46:38.000] Eating well doesn't have to be very expensive.
[00:46:38.320 --> 00:46:40.480] Exercising is basically free.
[00:46:40.480 --> 00:46:43.920] You know, getting sleep and optimizing sleep is basically free.
[00:46:43.920 --> 00:46:44.320] Yeah.
[00:46:44.320 --> 00:46:47.600] Building relationships, connections, pretty much free.
[00:46:47.600 --> 00:47:01.200] You know, and yes, there may be things around the margin where we're going to learn in the future that maybe plasma phoresis helps, or maybe, you know, stem cells might help, or maybe some of these things that are under investigation now, like rapamycin may help.
[00:47:01.760 --> 00:47:08.160] But right now, they're edges, not the core of what people should be doing.
[00:47:08.160 --> 00:47:08.320] Yeah.
[00:47:09.760 --> 00:47:14.000] Majoring in the minors and minoring in the majors, you know, and I think that's a very good way to think about it.
[00:47:14.320 --> 00:47:19.200] We can do live a crappy lifestyle and take those drugs and things and actually think you're going to do much.
[00:47:19.200 --> 00:47:27.760] No, and all these things that people are, you know, trying to advance, like the rapamycin story, they have a danger too.
[00:47:27.760 --> 00:47:30.000] We can't measure the immune system, you know, routinely.
[00:47:30.360 --> 00:47:35.320] So, why are we taking an immunosuppressant drug, which in some people could be a big deal?
[00:47:35.320 --> 00:47:43.800] And if you look at this leaderboard of all the longevity researchers or influencers, they're all taking different doses.
[00:47:44.120 --> 00:47:47.560] It's like once a week, different dose once a day.
[00:47:47.560 --> 00:47:52.680] Nobody knows, but it's never been shown to have any benefit in people.
[00:47:52.680 --> 00:47:54.440] It's all in, you know, rodents.
[00:47:54.680 --> 00:48:07.560] Yeah, there was one trial I saw that was on elderly, and they found that if it was given intermittently, it actually improved their response to vaccines and actually helped their immune system function better, whereas continuous dosing didn't.
[00:48:07.560 --> 00:48:11.640] And I think there's mTOR1 and MTOR2, which have different roles in immunity.
[00:48:11.640 --> 00:48:15.160] And so, I mean, that story is still getting unpacked, but I find it interesting.
[00:48:15.720 --> 00:48:19.720] But again, it's like if you don't do the basics right, that still doesn't matter.
[00:48:19.720 --> 00:48:20.120] Right.
[00:48:20.120 --> 00:48:23.640] We don't know of any studies, you know, that are real.
[00:48:23.880 --> 00:48:29.000] Those are these small studies that in a limited number of people, they're not major endpoints.
[00:48:29.000 --> 00:48:37.000] But, you know, one thing that's interesting, Mark, is, you know, Steve Horovath, who had came up with the Horovath clock we were talking about, that epigenetic.
[00:48:37.000 --> 00:48:48.280] The only two things so far that have decreased biologic aging from that clock are exercise and then more recently, the GLP-1 drugs.
[00:48:48.280 --> 00:48:49.880] I mean, that's kind of interesting.
[00:48:49.880 --> 00:48:53.000] That's body-wide biologic aging.
[00:48:53.160 --> 00:48:59.320] What we haven't seen any studies that that's been accomplished through these other things like rapamycin.
[00:48:59.320 --> 00:49:13.080] So I welcome, I mean, if rapamycin works or metformin or whatever, I want these things to succeed, but I don't want people to jump to that unless we have the evidence because all these carry some risk.
[00:49:13.080 --> 00:49:23.040] I mean, metformin carries less risk than rapamycin because it doesn't cause immunosuppression, but it isn't something that we know is going to promote healthy aging.
[00:49:23.040 --> 00:49:39.680] But it does, but it does inhibit mitochondrial complex one, which worries me because with progressive resistance training compared to placebo with and without metformin, if you did a strength training with metformin, you didn't get the same response to building muscle, which really got like, I was like, oh boy.
[00:49:39.680 --> 00:49:41.200] Yeah, that's not a good thing.
[00:49:41.200 --> 00:49:43.680] I think, yeah, there may be like you're making a good point.
[00:49:43.680 --> 00:49:44.320] You really are.
[00:49:44.480 --> 00:49:45.200] This is really exciting.
[00:49:45.200 --> 00:49:58.240] So basically, Alzheimer's and dementia, the take-home is there's biomarkers now that we can detect early, both genetic risks combined with blood tests that give us an early indication that we should get on it.
[00:49:58.240 --> 00:50:05.120] And then the getting on it part, there's a lot of things we can do, lifestyle plus all the things we talked about.
[00:50:05.440 --> 00:50:07.440] And there's more for sure that we could unpack.
[00:50:07.440 --> 00:50:09.120] So I want to kind of get to the other ones.
[00:50:09.360 --> 00:50:10.160] Heart disease.
[00:50:10.160 --> 00:50:12.000] And this is your area of specialty.
[00:50:12.000 --> 00:50:15.440] Yes, but I just want to mention one thing.
[00:50:15.440 --> 00:50:28.560] You know, it's kind of chasing our tails, but the environment in terms of air pollution, in terms of microplastics, nanoplastics, and also, of course, forever chemicals.
[00:50:28.560 --> 00:50:41.840] These things are, you know, all three are inflammation inducers that are increasing our toll of age-related diseases, the big three, and diabetes too, for that matter.
[00:50:41.840 --> 00:50:44.160] So, you know, we're not doing enough about these.
[00:50:44.160 --> 00:50:49.360] And I think this is something that you've been working on for quite some time.
[00:50:49.360 --> 00:50:55.520] We got to get serious about this because any advances that we're going to make, we're going to talk about cardiovascular in a moment here.
[00:50:55.520 --> 00:51:00.600] We got to, these are the things that are taking a big toll on us.
[00:51:00.600 --> 00:51:06.120] Because, for example, the plastic story, let's just talk about that for a second in the heart.
[00:51:06.120 --> 00:51:20.760] The big study from Italy, multiple centers, where they took the carotid artery plaque at the time of surgery and they looked to see if there was plastics, microplastics, nanoplastics in the artery plaque.
[00:51:20.760 --> 00:51:23.800] And they found it in over 60% of people.
[00:51:24.120 --> 00:51:30.440] And that artery under the microscope was grossly inflamed right around where the plastics were.
[00:51:30.440 --> 00:51:31.400] During follow-up.
[00:51:31.560 --> 00:51:32.680] Was it a dose response?
[00:51:32.920 --> 00:51:34.200] Like, in other words, the more plastics?
[00:51:34.280 --> 00:51:36.920] The more plastics, the more vicious inflammation.
[00:51:37.240 --> 00:51:58.760] And what was even worse is the people who had the plastics followed versus those who didn't have plastics in their plaque had a four to five-fold increase of heart attacks, strokes, and death compared to those without the plastic that was basically establishing residence in their arteries.
[00:51:58.760 --> 00:52:08.680] And so, as we talk about cardiovascular now, preventing heart disease, you know, we got to factor in that particular thing because the plastics are everywhere.
[00:52:08.920 --> 00:52:10.840] They're not degradable.
[00:52:10.840 --> 00:52:13.240] And there were just, you know, more and more of them.
[00:52:13.240 --> 00:52:14.360] We got to do something about it.
[00:52:14.360 --> 00:52:15.640] But for the heart, this is where.
[00:52:16.040 --> 00:52:18.120] I want to just double down before you get in the heart.
[00:52:18.120 --> 00:52:33.240] I want to just double-click on this because, you know, what you're saying, people go, yeah, toxins, but to have a traditional physician who's got the credentials that you have saying that toxins are something we should pay attention to is near heresy when it comes to traditional medicine.
[00:52:33.400 --> 00:52:36.680] It's something I've been talking about for decades because I've seen it.
[00:52:37.080 --> 00:52:38.680] And when you look for it, you see it.
[00:52:38.680 --> 00:52:40.760] Even when you look at the literature, it's been there.
[00:52:41.160 --> 00:52:43.880] It's just been ignored because doctors don't know what to do about it.
[00:52:43.880 --> 00:52:47.200] Because they go, okay, well, you do your exposure by doing this and that and the other thing.
[00:52:47.200 --> 00:52:51.040] But this is something that I think is going to be an important thing to be investigated.
[00:52:51.280 --> 00:52:53.680] How do we measure our toxic load?
[00:52:53.680 --> 00:53:06.480] How do we start to help the body detoxify by supporting its both internal detoxification systems like the liver and the kidneys and the colon and the skin and sweat and all the things?
[00:53:06.640 --> 00:53:08.880] How do we actually help the body detoxify?
[00:53:08.880 --> 00:53:13.840] And what are novel methods of detoxification that we might want to think about when it comes to these compounds?
[00:53:13.840 --> 00:53:16.320] Because they're everywhere and we're all polluted.
[00:53:16.800 --> 00:53:17.920] Well, I think you're right.
[00:53:17.920 --> 00:53:20.960] They do play a huge role in all these diseases of aging.
[00:53:20.960 --> 00:53:21.520] You're right.
[00:53:21.520 --> 00:53:26.160] I mean, the dirty air and the dirty water, the things we drink.
[00:53:26.160 --> 00:53:28.960] So the plastics, of course, are pervasive.
[00:53:28.960 --> 00:53:36.240] And we can do some things at an individual family level, you know, in terms of not having things stored in the plastics.
[00:53:36.240 --> 00:53:42.480] And like the worst case scenario is you take something, food that you have in plastic and you put it in a microwave.
[00:53:42.480 --> 00:53:49.280] It's like microplastics you're going to eat at, you know, to the fourth power, right?
[00:53:49.280 --> 00:53:50.800] So there are some things we can do.
[00:53:50.800 --> 00:53:55.760] And, you know, just to everything we can to avoid the use of plastics.
[00:53:56.400 --> 00:54:00.240] But, you know, this is something we're not addressing.
[00:54:00.240 --> 00:54:03.920] And that's where the data are so incredibly strong.
[00:54:04.240 --> 00:54:05.360] And air pollution.
[00:54:05.360 --> 00:54:07.680] What are we doing about air quality?
[00:54:07.680 --> 00:54:16.880] Because the air quality, these fine particulate matter, 2.5 and smaller, they are the real incriminated.
[00:54:16.880 --> 00:54:22.640] They're the culprits for inflammation, big time increasing inflammation.
[00:54:22.640 --> 00:54:28.240] And, you know, for example, we have now young people, and we're going to get to cancer.
[00:54:28.240 --> 00:54:31.560] I don't mean to divert it from cardiovascular because that's my true love.
[00:54:31.720 --> 00:54:43.720] But the young people with cancer, why are people in their 20s and 30s presenting with colon cancer, breast cancer, and other cancers like we've never seen before?
[00:54:43.720 --> 00:54:48.680] Who, you know, what is the, could it be the ultra-processed food that they eat high amounts?
[00:54:48.680 --> 00:54:51.080] Could it be these environmental toxins?
[00:54:51.080 --> 00:54:53.720] Could it be, you know, the cumulative of all these things?
[00:54:53.720 --> 00:54:59.000] But something has got to give there because we're not, you know, we're not protecting our young people.
[00:54:59.000 --> 00:55:03.560] And we're seeing much more, a real spike in cancer.
[00:55:03.800 --> 00:55:08.120] These are age-related diseases we're actually seeing in young people, which is just horrible.
[00:55:08.120 --> 00:55:27.160] You know, there's literature around toxins that's been around, and even in heart disease, I remember reading a paper, I think it was the American Journal of Cardiology years ago, where they looked at anybody who had lead levels over two, which is considered normal because the level in the reference range is one to 10, but the normal level of lead is zero in the human body.
[00:55:27.160 --> 00:55:29.240] It's not like it required mineral.
[00:55:29.800 --> 00:55:38.440] That their risk of having a heart attack was higher or as high as those who had elevated cholesterol and an increased risk of strokes.
[00:55:38.440 --> 00:55:39.960] And it was a big risk factor.
[00:55:39.960 --> 00:55:50.280] And it was 39% of the population that had a lead level over two because we live in a world where there's coal burning and lead levels in the soil and stuff from historical exposure.
[00:55:50.280 --> 00:55:51.000] So you're right.
[00:55:51.000 --> 00:55:54.680] I mean, this toxin story is a big rabbit hole, and I've written a lot about that.
[00:55:54.760 --> 00:56:00.520] I talk a lot about it, but I think there's a lot of ways people can reduce their risks and reduce their exposures and not be crazy.
[00:56:00.520 --> 00:56:04.360] But there's ways to mitigate it and to help your body eliminate the toxins.
[00:56:04.360 --> 00:56:05.640] So I agree.
[00:56:05.640 --> 00:56:09.560] So let's talk about the heart disease prevention because people say, well, that story's been told.
[00:56:09.560 --> 00:56:13.160] You know, we've got statins, we've got this PC SK9 inhibitors.
[00:56:13.160 --> 00:56:13.800] We're all good.
[00:56:13.800 --> 00:56:14.800] Like, what's the big deal?
[00:56:14.800 --> 00:56:15.840] What should we worry about?
[00:56:15.840 --> 00:56:18.240] It's just all about LDL cholesterol.
[00:56:18.240 --> 00:56:19.200] What's new?
[00:56:14.520 --> 00:56:21.440] What should we be looking at?
[00:56:21.760 --> 00:56:23.360] What should we be thinking about?
[00:56:23.360 --> 00:56:27.840] And why are we still seeing so many people with heart disease?
[00:56:27.840 --> 00:56:31.280] Yeah, it's still the number one killer around the world, not just here.
[00:56:31.280 --> 00:56:35.280] And it's still the number one killer in women who, you know, they think that it's breast cancer.
[00:56:35.280 --> 00:56:37.120] No, no, it's this is it.
[00:56:37.120 --> 00:56:47.360] This is exciting because we do know the things that we've been reviewing for risk factors, but we have a way to now establish the risk.
[00:56:47.360 --> 00:56:52.160] Are they really high risk without before they ever have heart disease, 20 years plus?
[00:56:52.400 --> 00:57:02.080] And the way we do that is we can get a simple lipid panel, add the LP-little A, APO-B.
[00:57:02.400 --> 00:57:05.680] So a little more than what is the standard lipid panel.
[00:57:05.680 --> 00:57:09.360] The LP-little A will be part of a lipid panel in the next year or two.
[00:57:09.360 --> 00:57:17.200] But anyway, when we get that lipid panel, which is again very inexpensive, and we can also get a polygenic risk score, very inexpensive.
[00:57:17.200 --> 00:57:19.040] We can also get a heart clock, right?
[00:57:19.040 --> 00:57:21.040] And we can get inflammation markers.
[00:57:21.040 --> 00:57:29.840] Anyway, now you have the full stack with your records and you have somebody who is well before they've ever manifest heart disease.
[00:57:29.840 --> 00:57:33.200] And you say, oh, wow, this person is really high risk for heart disease.
[00:57:33.200 --> 00:57:34.240] What do we do?
[00:57:34.240 --> 00:57:39.600] Well, you get their LDL down, not just to below 70.
[00:57:39.600 --> 00:57:43.120] We go down to 20 or less than 30, right?
[00:57:43.120 --> 00:57:45.680] We have so many ways to do that now.
[00:57:45.920 --> 00:57:50.160] We have these injectables that are against this PCSK9.
[00:57:50.160 --> 00:57:56.720] We've got new drugs, five new LP-little A drugs that are going to be out within the next year or so that are really potent.
[00:57:56.800 --> 00:57:58.000] And we've had none of them.
[00:57:58.000 --> 00:57:58.960] None until now.
[00:57:58.960 --> 00:57:59.800] Yeah, we never had one.
[00:57:59.800 --> 00:58:02.920] We always tell, oh, too bad your LP-little A is over 100.
[00:58:02.920 --> 00:58:04.120] You know, nothing we can do.
[00:57:59.600 --> 00:58:06.760] We're going to be able to change that, and that's going to have a big impact.
[00:58:07.080 --> 00:58:11.160] We can get all the inflammation, get all over it, right?
[00:58:11.160 --> 00:58:18.280] In terms of bringing the inflammation down, we've already seen how GLP-1 drugs do that before any weight loss.
[00:58:18.280 --> 00:58:21.480] So that should work well in people who aren't even obese.
[00:58:21.480 --> 00:58:28.600] And we've seen how that can prevent heart, preserve ejection fraction, heart failure, which is half of all heart failure, right?
[00:58:28.600 --> 00:58:30.840] GLP-1s prevent that.
[00:58:30.840 --> 00:58:40.520] So for heart disease, we're seeing some really breakthroughs for the treatment, particularly the new target of LDL, that we have five different drug classes.
[00:58:40.520 --> 00:58:46.440] Statins, you've mentioned, but the PCSK9, we have three different ways to do that now.
[00:58:46.440 --> 00:58:48.840] We got other new drugs that are coming.
[00:58:49.080 --> 00:58:53.800] Just recently, the CETP inhibitor worked really well on top of.
[00:58:53.800 --> 00:58:57.400] So we can stamp out inflammation.
[00:58:57.400 --> 00:59:01.960] The other thing is, we have a metric we never had before, which is AI.
[00:59:01.960 --> 00:59:04.360] And by the way, that also goes with Alzheimer's.
[00:59:04.440 --> 00:59:07.080] You can do a retina AI exam.
[00:59:07.080 --> 00:59:15.800] So I have a picture of the retina, and you do AI on it, and it tells you when you're going to have Alzheimer's, if you're going to have Alzheimer's, five to seven years in advance.
[00:59:15.800 --> 00:59:20.760] The retina also tells if you're going to have heart disease or a stroke in advance.
[00:59:20.760 --> 00:59:27.800] It will even tell if you're going to, you know, your calcium score of your heart arteries through your retina.
[00:59:28.040 --> 00:59:29.800] It's remarkable.
[00:59:29.800 --> 00:59:32.040] And we should, that should be widely available.
[00:59:32.040 --> 00:59:33.720] It isn't yet, but it will be.
[00:59:33.720 --> 00:59:36.920] We'll be doing smartphone retina checks someday, right?
[00:59:37.240 --> 00:59:57.520] But here's where we get a real kick on a jump on this because if you are concerned about high risk, and somebody, you know, say 40, 50, they have significant risk factors, you can do a CT angio, which is now becoming very inexpensive.
[00:59:57.760 --> 01:00:00.000] And you can look at inflammation in the artery.
[01:00:00.000 --> 01:00:01.360] I go through this in the book.
[01:00:01.360 --> 01:00:04.560] Inflammation in the artery without a narrowing.
[01:00:04.560 --> 01:00:10.720] Okay, so basically, it does AI of the fat around the artery.
[01:00:10.720 --> 01:00:16.160] And this is something that was developed in the UK and it's now getting ready for FDA approval.
[01:00:16.160 --> 01:00:18.480] This is a big jump because we always were.
[01:00:18.560 --> 01:00:20.080] Well, this isn't the Clearly scan.
[01:00:20.080 --> 01:00:20.960] This is something else.
[01:00:20.960 --> 01:00:21.760] No, no.
[01:00:22.000 --> 01:00:24.240] Clearly, and the other ones in the U.S.
[01:00:24.320 --> 01:00:25.360] don't do this.
[01:00:25.360 --> 01:00:30.000] But this is an Oxford, University of Oxford spin-out.
[01:00:30.000 --> 01:00:31.440] I think it's called Carista.
[01:00:31.760 --> 01:00:34.400] They're going to have that available soon.
[01:00:34.400 --> 01:00:36.480] And I went through the data in the book.
[01:00:36.480 --> 01:00:47.280] I mean, they've had multiple papers, but it's striking: if you have inflammation without a narrowing, it's, you know, you could have 15-fold risk of a heart attack.
[01:00:47.280 --> 01:00:52.720] So that's when you use that as a metric, just like we were talking about the PTAW 217 for Alzheimer's.
[01:00:53.520 --> 01:00:56.160] We've got all these new things for cardiovascular.
[01:00:56.160 --> 01:00:58.160] We are going to get a grip on this.
[01:00:58.160 --> 01:01:00.720] And we got to, you know, ideally start early.
[01:01:00.720 --> 01:01:03.360] But, you know, the lifestyle factors work really well.
[01:01:03.360 --> 01:01:09.120] This is the most preventable known of the three big age-related diseases through lifestyle.
[01:01:09.120 --> 01:01:12.240] Because even without a lot of the drugs, like the lifestyle plays a big role.
[01:01:12.240 --> 01:01:19.360] Like, you know, I've seen data up to 90% by healthy diet, exercise, stress mitigation, sleep, right?
[01:01:19.360 --> 01:01:21.520] Yeah, I mean, is that in the book?
[01:01:21.520 --> 01:01:40.760] I found all these studies that I was really struck by that are recent that showed that if we practice the lifestyle factors that we've been reviewing with the details that we just discussed, that gets us seven to ten years of healthy aging without one of these age-related diseases.
[01:01:40.760 --> 01:01:49.560] I mean, who wouldn't want seven to ten years of healthy aging just from the stuff we've been discussing without any magic potion or pill?
[01:01:49.880 --> 01:01:52.360] So that's, I think, people don't know about that.
[01:01:52.360 --> 01:01:53.400] I didn't know about that.
[01:01:53.400 --> 01:01:54.840] It's really impressive.
[01:01:55.000 --> 01:01:55.560] That's powerful.
[01:01:55.560 --> 01:02:09.160] So, but you're saying that some of the advances in cardiology are more pharmacological than you're thinking are coming, like the drugs that lower this genetically determined lipoprotein called LP-little A, which I've been checking for 30 years.
[01:02:09.160 --> 01:02:11.320] Apo B, which I've been checking for 30 years.
[01:02:11.320 --> 01:02:18.680] I read some article the other day that was like, there's this great new test that can be more predictive of your risk of heart attack than any other test is just discovered.
[01:02:18.680 --> 01:02:19.640] I'm like, what is that?
[01:02:19.640 --> 01:02:21.480] I'm like, look through the article.
[01:02:21.480 --> 01:02:22.520] It's like ApoB.
[01:02:22.520 --> 01:02:23.400] I'm like, oh, God.
[01:02:23.800 --> 01:02:29.960] I mean, you only need to get it once, and then you can tell that if you need to check it further.
[01:02:29.960 --> 01:02:40.120] But you're getting at a key point here: it isn't just that we have better, you know, more armamentarium of drugs, but we didn't know how to get the risk down.
[01:02:40.120 --> 01:02:49.240] You know, we didn't know how to say this person's really high risk for atherosclerosis because we didn't really have, we didn't use the polygenic risk score.
[01:02:49.240 --> 01:02:53.000] We didn't have, as we do now, we're going to have a heart clock.
[01:02:53.800 --> 01:02:58.760] So there's a big debate out there, as you probably know, how low should we go on LDL?
[01:02:58.760 --> 01:03:00.840] Should we pull out all the stops?
[01:03:00.840 --> 01:03:15.280] Well, if you look at all the data, the lower you go, the more protection, but you don't want to necessarily give people, you know, azetamide and statin and injectable and all these things unless they really are at high risk.
[01:03:14.840 --> 01:03:19.680] Then you go for Broke and you also get the LPA and you get the inflammation down.
[01:03:20.000 --> 01:03:23.520] We have ways that we can do that and we're going to keep having better ways.
[01:03:23.520 --> 01:03:32.320] So this is a striking, it's a combination of who's at risk, the partitioning the risk, and having better ways to work on that risk.
[01:03:32.320 --> 01:03:34.960] Just to play devil's advocate, because this conversation comes up all the time.
[01:03:34.960 --> 01:03:37.520] You're a cardiologist, so your favorite organ is the heart.
[01:03:37.520 --> 01:03:40.480] And so your idea is get the LDL as low as you can.
[01:03:41.120 --> 01:03:44.320] Your brain is made up of a lot of only in people who are at high risk.
[01:03:44.320 --> 01:03:45.280] In people who are at high risk.
[01:03:45.280 --> 01:03:50.080] Okay, so if you're really high risk, but like what about the effects, for example, on the brain and cognitive function?
[01:03:50.080 --> 01:03:57.840] Because the cholesterol is a big part of your brain and sex hormones, which is what your testosterone is made from, is cholesterol.
[01:03:57.840 --> 01:04:00.320] So how do you kind of navigate that?
[01:04:00.320 --> 01:04:01.200] And what's the truth?
[01:04:01.200 --> 01:04:02.240] And what do we know?
[01:04:02.240 --> 01:04:09.520] Yeah, I mean, the statins are probably the most studied drug class in history, really.
[01:04:09.520 --> 01:04:16.960] Some of the data that comes out of these big meta-analyses would say, oh, people don't get any leg cramps.
[01:04:16.960 --> 01:04:18.480] That's not true.
[01:04:18.880 --> 01:04:20.800] You and I know that's not true.
[01:04:20.800 --> 01:04:30.560] People do get severe leg cramps where they can't even sleep at night, you know, and all sorts of other, you know, leg and muscle-related symptoms.
[01:04:30.560 --> 01:04:39.920] Now, with respect to cognitive and sexual dysfunction, the data really don't show a hit there at all.
[01:04:39.920 --> 01:04:54.000] And in fact, you know, I think that we have some data to suggest the chances of having dementia in people, and Alzheimer's, as you know, accounts for 70% of dementia.
[01:04:54.000 --> 01:05:01.480] That if you don't have the LDL lowered to, let's say, less than 100, less than 70, you're going to be at higher risk for dementia.
[01:05:01.480 --> 01:05:05.160] So, if anything, the data support statins.
[01:05:05.720 --> 01:05:12.200] And, you know, the data for sexual dysfunction, it's again, some of that's vascular.
[01:05:12.200 --> 01:05:16.600] And if it's vascular, we're talking about atherosclerotic.
[01:05:16.920 --> 01:05:20.680] And that, again, is going to be ameliorated with.
[01:05:21.000 --> 01:05:23.640] And, of course, we don't have to just rely on statins.
[01:05:23.640 --> 01:05:33.240] A lot of people do have side effects from statins, no matter what the group at Oxford keeps saying that everyone can take a statin and it's just, you know, it's mental if they can't.
[01:05:35.320 --> 01:05:48.760] When I wrote an op-ed in the New York Times like a decade ago, and I called out the diabetes from statins, okay, because if you take a very potent statin, you have a higher risk of developing type 2 diabetes, right?
[01:05:49.160 --> 01:05:52.280] Oh, did I get slammed by my cardiology colleagues for that?
[01:05:52.280 --> 01:05:54.280] I said, well, wait a minute, that's the data, folks.
[01:05:54.280 --> 01:05:55.240] I'm sorry.
[01:05:55.240 --> 01:06:02.440] And over the years, we've seen many more reports about the potent statins, high doses where you get a higher risk.
[01:06:02.600 --> 01:06:03.560] And you know what?
[01:06:03.560 --> 01:06:06.120] Most physicians are not keeping up with this.
[01:06:06.120 --> 01:06:13.720] They're not watching their patients to see if their glucose, like oh hemoglobin, you know, A1C or fasting glucose.
[01:06:13.720 --> 01:06:19.800] And this is bothersome to me because that is a side effect of statins, particularly potent statins.
[01:06:19.800 --> 01:06:33.720] So again, this is important because if we're going to lower LDL and pull out all the stops and high doses of mersuvastatin, crestor or a torostatin, lipitor, that could also raise the risk of that person developing type 2 diabetes.
[01:06:33.720 --> 01:06:35.400] We don't want to do that.
[01:06:35.400 --> 01:06:45.680] And we have cardiologists, my colleagues, they are, you know, really sold on statins and they basically ignore this diabetes issue.
[01:06:45.920 --> 01:06:47.360] Did I ever take grief?
[01:06:44.920 --> 01:06:48.800] I agree with you.
[01:06:48.960 --> 01:06:54.320] And I think there's a concern I have around its effect on mitochondrial function.
[01:06:54.320 --> 01:07:04.240] And some of the data I've seen that even in people without muscle pain, even without elevated muscle enzymes, that there's mitochondrial damage on muscle biopsies.
[01:07:04.240 --> 01:07:13.680] And for me, mitochondria are so key to healthy aging in the brain, in everything from Parkinson's to heart disease, diabetes.
[01:07:13.680 --> 01:07:16.160] Diabetics have poor, poorly functioning mitochondria.
[01:07:16.160 --> 01:07:18.320] They may be part of why it causes it.
[01:07:18.320 --> 01:07:25.360] And so I'm wondering, you know, some of these other drugs that are coming down the pike, even though some of them are expensive, maybe a better solution.
[01:07:25.360 --> 01:07:37.200] Well, people that have clear-cut adverse effects, you know, the PCSK9 injectable drugs are a winner because they're potent.
[01:07:37.200 --> 01:07:40.800] And they have not been associated with diabetes, which is really interesting.
[01:07:40.800 --> 01:07:44.800] They have not been associated with cognitive or other side effects.
[01:07:44.800 --> 01:07:47.440] So most insurers cover that now.
[01:07:47.440 --> 01:07:52.560] We, you know, went through years where it was because they were so expensive, the cost has come down.
[01:07:52.560 --> 01:08:05.120] So as long as people have the right indication where they have significant side effects or they need to have their LDL substantially lowered, it's usually not a financial stress for most people.
[01:08:05.120 --> 01:08:11.600] So heart disease, still its lifestyle, but then there's a cocktail of other drugs in very high-risk patients that you can detect early to figure out.
[01:08:12.160 --> 01:08:19.200] And what about lipoprotein fractionation, which is a lab test that we include as part of function health, as well as APOB and LPA?
[01:08:19.200 --> 01:08:23.120] Something I've been testing for 30 years, but do you think that's as important?
[01:08:23.120 --> 01:08:33.640] Because to me, the particle number and particle size story is important, and it's sort of a clue that there's insulin resistance, which is one of the biggest drivers of heart disease and all the other age-related diseases.
[01:08:33.880 --> 01:08:39.880] Yeah, I mean, I think it's mild, potentially mild, incremental information.
[01:08:39.880 --> 01:08:47.480] I just don't see that it has nearly the impact of just zeroing in on LDL and LP-little A.
[01:08:47.480 --> 01:08:50.920] And I do recommend that everybody get an ApoB at least once.
[01:08:51.320 --> 01:08:54.520] And then you can figure out whether that needs to be further assessed.
[01:08:54.520 --> 01:08:58.360] These other things, you know, it's an additional expense.
[01:08:58.360 --> 01:09:01.000] I just haven't seen the value.
[01:09:01.000 --> 01:09:06.680] But, you know, I have colleagues that are lipidologists that test every known particle to mankind, right?
[01:09:06.680 --> 01:09:11.880] I just haven't, I haven't really seen the benefit because it doesn't change usually.
[01:09:11.880 --> 01:09:14.280] To me, I got to know the person's risk.
[01:09:14.280 --> 01:09:17.160] And then I'm going to go after inflammation.
[01:09:17.160 --> 01:09:19.080] I'm going to work on their lifestyle.
[01:09:19.080 --> 01:09:22.360] And if necessary, you know, get their LDL down as low as possible.
[01:09:22.360 --> 01:09:28.120] So the other things just don't have, for me, an added value.
[01:09:28.520 --> 01:09:36.680] But I do know there are people that are, you know, wild and crazy on every particle, small, large, dense, you know, you name it, out there.
[01:09:36.680 --> 01:09:37.160] Yeah.
[01:09:37.160 --> 01:09:38.280] Yeah, so I hear you on that.
[01:09:38.280 --> 01:09:42.920] I think, you know, sometimes more information isn't always better, but you know, what is the most important information?
[01:09:42.920 --> 01:09:43.960] I think you covered that in your book.
[01:09:43.960 --> 01:09:51.720] And I think, you know, we're going down the kind of the horseman of the apocalypse, you know, the heart disease, the cancer, the dementia.
[01:09:51.720 --> 01:09:54.440] I think diabetes is sort of all in there related.
[01:09:54.440 --> 01:10:13.960] But you're talking about how there's kind of a newer, with the advances in our diagnostics, whether it's imaging or retinal scans or new ways we can measure dementia biomarkers we never had before, cancer, we'll get into in a sec, that these diseases can become more optional.
[01:10:13.960 --> 01:10:16.000] Like they're not inevitable.
[01:10:14.600 --> 01:10:20.480] We have more agency than we ever had before, given what we know now.
[01:10:20.800 --> 01:10:30.960] And when you layer off what we're learning with AI and using multimodal treatments, we're really able to actually make a big dent if people really understood how to navigate this.
[01:10:30.960 --> 01:10:34.880] And the sad part is that, you know, you spend your time thinking about what's coming.
[01:10:34.880 --> 01:10:45.520] Most physicians are just trying to deal with the onslaught of what is and don't have the bandwidth to actually apply this stuff until it kind of is way often decades later.
[01:10:45.520 --> 01:10:56.480] And so I really appreciate your sort of paying attention to, you know, what's happening and keeping your nose to the scent of where things are emerging because otherwise people just don't know.
[01:10:56.480 --> 01:10:58.720] And doctors, like you said, don't know.
[01:10:58.720 --> 01:11:02.560] And the average person doesn't know, but this is such a hopeful message.
[01:11:02.800 --> 01:11:12.400] I want to kind of finish on cancer because I think this is one of those things that, you know, the C word, you know, nobody wants to get that diagnosis.
[01:11:12.400 --> 01:11:13.760] It's very scary.
[01:11:14.240 --> 01:11:24.480] Most cancers are picked up late stage when the five-year survival rates are very low in the 5% to 20%, if that.
[01:11:24.800 --> 01:11:32.160] And picking things up early and understanding your risk can lead to cures, essentially.
[01:11:33.040 --> 01:11:49.040] And I think what I'd like to hear is your sort of perspective on this with new liquid biopsy testing, with new technologies of imaging, with new, you know, maybe other proteomics that are coming.
[01:11:50.000 --> 01:11:51.680] What is out there that's emerging?
[01:11:51.680 --> 01:11:55.520] Because, you know, my sister died of cancer in 57.
[01:11:55.520 --> 01:11:56.880] My dad died of cancer.
[01:11:56.880 --> 01:11:58.240] He was otherwise really healthy.
[01:11:58.240 --> 01:12:02.360] He'd been a smoker when he was younger, but quit and ended up getting lung cancer.
[01:12:02.360 --> 01:12:07.400] Like, they could potentially even still be around if they hadn't died of cancer.
[01:12:07.400 --> 01:12:08.760] And I don't want to get cancer.
[01:12:09.320 --> 01:12:10.280] I'm with you.
[01:12:10.600 --> 01:12:17.800] Yeah, my mother died of cancer in her 50s, and most of my relatives on my father's side had colon cancer.
[01:12:17.800 --> 01:12:20.680] You know, I've had a lot of cancer in the family for sure.
[01:12:20.680 --> 01:12:22.920] And I agree, no one wants to go through this.
[01:12:22.920 --> 01:12:27.400] And I do believe we have a path to prevent cancer.
[01:12:27.800 --> 01:12:30.040] And certainly it's spread, right?
[01:12:30.280 --> 01:12:37.640] If you can find it microscopically, which we don't right now very well, long before it's ever shown on a scan.
[01:12:37.640 --> 01:12:41.880] And once it's on a scan, if it's really cancer, you're talking about billions of cells, right?
[01:12:42.200 --> 01:12:45.080] You want to find it if it does exist microscopically.
[01:12:45.080 --> 01:12:48.200] So why is this such an exciting area?
[01:12:48.200 --> 01:12:55.000] Again, we can find through the full stack who's at risk and for which cancer.
[01:12:55.000 --> 01:13:09.080] And so we have a way, you know, whether it's polygenic risk or genome sequence, we can do, for example, you know, just looking at the clocks, which is another way to get a window into a risk of cancer.
[01:13:09.080 --> 01:13:13.560] If a person has a significant risk, and you know, family history is part of that, right?
[01:13:13.880 --> 01:13:19.240] Then they also confirm through these other, I mean, a simple polygenic risk will tell us a lot.
[01:13:19.240 --> 01:13:27.960] This is now a different story, completely, Mark, than the way we screen for cancer today, which is as dumb as it could possibly be.
[01:13:27.960 --> 01:13:29.880] Age 50, you show up.
[01:13:30.040 --> 01:13:32.200] Women, mammogram, right?
[01:13:32.560 --> 01:13:37.720] All right, only 12% of women in their lifetime will ever have breast cancer.
[01:13:37.720 --> 01:13:47.280] 88% will never develop breast cancer, but they're all supposed to get mammography on a frequent periodic basis starting age 40, 45.
[01:13:47.280 --> 01:13:49.360] This is crazy.
[01:13:44.920 --> 01:13:51.760] We don't do anything to partition risk.
[01:13:52.400 --> 01:13:58.000] The same for prostate cancer, colon cancer, you name the cancer.
[01:13:58.000 --> 01:13:59.040] This is what we do.
[01:13:59.040 --> 01:14:01.920] We treat every human the same.
[01:14:01.920 --> 01:14:04.720] We waste all this money on mass screening, right?
[01:14:04.720 --> 01:14:08.000] Now, what I'm suggesting is let's partition people's risk.
[01:14:08.000 --> 01:14:10.640] If they're high risk, then they should have screening.
[01:14:10.640 --> 01:14:13.040] But that screening is different.
[01:14:13.040 --> 01:14:15.280] It's basically establishing the risk.
[01:14:15.280 --> 01:14:25.840] And then if we see a person, you know, it's a significant risk, you can then do a plasma tumor DNA assessment, right?
[01:14:26.160 --> 01:14:27.920] That right now is pretty expensive.
[01:14:27.920 --> 01:14:29.760] It's $800, $900.
[01:14:29.760 --> 01:14:33.520] The one that's used the most is Gallery of Grail.
[01:14:33.520 --> 01:14:36.320] And almost 400,000 people have had that test.
[01:14:36.320 --> 01:14:37.840] But guess what, Mark?
[01:14:37.840 --> 01:14:41.360] The people who've had the test is because they're age 50.
[01:14:41.360 --> 01:14:43.600] I mean, that's a plus.
[01:14:43.600 --> 01:14:46.000] That's not the reason they should get the test.
[01:14:46.000 --> 01:14:49.200] It should be because they have risk of cancer.
[01:14:49.200 --> 01:14:52.320] Anyway, the yield for that test is very low.
[01:14:52.480 --> 01:14:54.480] And most of it is already late stage.
[01:14:54.480 --> 01:14:58.560] Two out of thousand, you might pick up an early cancer.
[01:14:58.560 --> 01:15:01.360] So you got to use the test right in the right people.
[01:15:01.360 --> 01:15:03.200] This is something I can't emphasize.
[01:15:03.200 --> 01:15:09.440] Then that test and all the other liquid biopsies have a much better chance to be helpful.
[01:15:09.760 --> 01:15:20.560] So we have that, but also this is where our immune system kicks in because we don't have that immune metric, system metric, except for immune clock.
[01:15:20.560 --> 01:15:26.320] But if we did, you know, if our immune system was amped up, we wouldn't have cancer spread.
[01:15:26.320 --> 01:15:27.520] We wouldn't see metastasis.
[01:15:28.560 --> 01:15:32.200] You know, what we know is this: some people, this is really fascinating.
[01:15:32.200 --> 01:15:39.640] Some people will have a positive test for tumor DNA, and they're reassessed in a few months, and it goes away.
[01:15:39.640 --> 01:15:41.320] What do you think happened?
[01:15:41.320 --> 01:15:46.040] Was it a false positive or did that person's immune system kick in?
[01:15:46.040 --> 01:15:49.080] I think what we're learning is it's the immune system.
[01:15:49.080 --> 01:15:53.720] And what we have to get is: this is the missing piece right now, the immunome.
[01:15:53.720 --> 01:16:12.680] If we can get this and find people who are at risk for cancer and just make sure throughout their lifetime that their immune system has got good integrity and it can fight off the threat of a cancer, of a foreign protein that would be on the antigen, on the surface of cancer cell.
[01:16:12.680 --> 01:16:20.120] So I am really gung-ho because if you look at the treatment of cancer, we're now seeing things we've never seen.
[01:16:20.120 --> 01:16:30.360] Personalized neo antigen vaccines to cure pancreatic cancer, to cure renal cell carcinoma, intractable, that is, people that failed, everything else.
[01:16:30.360 --> 01:16:33.560] The other thing, just to mention, here again is AI.
[01:16:33.880 --> 01:16:53.160] We are seeing AI used for the electronic health record using the unstructured nodes and the regular nodes and set points, that is the lab values, but even when they're in their normal range, AI analyzes, whoa, it's even in the normal range, and we look at it and say there's no asterisk, so it's okay.
[01:16:53.160 --> 01:16:58.040] Well, no, the AI says, uh-uh, this is flagging a risk of pancreatic cancer.
[01:16:58.040 --> 01:17:00.600] This is flagging a risk of ovarian cancer.
[01:17:00.600 --> 01:17:09.400] The hardest diagnosis of cancer we're seeing that can be brought much earlier through AI of all of a person's data.
[01:17:09.400 --> 01:17:14.800] We saw it from the study that was done in Denmark in the VA for pancreatic cancer.
[01:17:14.800 --> 01:17:17.600] We're going to see Storm Kettering has what were they looking at?
[01:17:17.600 --> 01:17:20.000] Because they were looking at tumor markers, were they?
[01:17:14.520 --> 01:17:21.440] We were looking at just regular blood tests.
[01:17:21.680 --> 01:17:28.480] Yeah, so they looked at a person's nonspecific symptoms, like abdominal symptoms for pancreatic cancer.
[01:17:28.480 --> 01:17:36.320] And they saw ranges of liver function tests in the normal range, but trending in the wrong direction, right?
[01:17:36.320 --> 01:17:44.240] So the AI picked up the higher risk of people that we might not, we might discount these are nonspecific symptoms.
[01:17:44.240 --> 01:17:46.160] These tests are lab tests.
[01:17:46.160 --> 01:17:51.120] They look normal, but they're not normal when you are looking at this in serial assessment.
[01:17:51.120 --> 01:18:03.360] So I'm also lots of different ways that AI is helping us to gauge a person's risk and help us to pick up these occult, difficult to diagnose cancer.
[01:18:03.360 --> 01:18:05.120] I mean, this is so important what you're saying.
[01:18:05.120 --> 01:18:10.640] That there was a paper in Nature Medicine recently on personalized lab data.
[01:18:10.640 --> 01:18:25.200] And the idea was that exactly what you're saying, that even though it's quote normal, it may not be normal for you because if you were like 20 and it goes up to 35, which is still in the normal range, that might not be good.
[01:18:25.200 --> 01:18:25.920] That's right.
[01:18:25.920 --> 01:18:31.680] And we need to start getting a baseline of what our data is and tracking it over time and having AI help us learn from it.
[01:18:31.680 --> 01:18:38.640] Because, you know, as a doctor, you see thousands of patients that come in and, you know, they've had their lab panel every year.
[01:18:38.640 --> 01:18:47.280] You can't keep in your mind what their liver function tests were last year, five years ago, or 10 years ago, and how that differs and how that, what's the variation from their normal or baseline tests.
[01:18:47.680 --> 01:18:49.840] You can't do that as a human being, right?
[01:18:50.160 --> 01:18:56.160] And I mean, I have certain patients who are OCD and they bring in spreadsheets with years and years of their data, and you can graph it all.
[01:18:56.320 --> 01:18:58.960] I'm like, wow, that's like, I never saw that before.
[01:18:58.960 --> 01:19:02.920] But without that, you really don't know what's going on.
[01:18:59.760 --> 01:19:06.840] That's the paper I was talking about on set points, exactly.
[01:19:08.600 --> 01:19:18.040] And we just don't look at that because if it's normal, we don't look at the last few years, how things are just inching up.
[01:19:18.040 --> 01:19:21.240] And that's the way AI can help us.
[01:19:21.240 --> 01:19:22.040] And it is helping.
[01:19:22.040 --> 01:19:23.560] We've already seen proof of it.
[01:19:23.560 --> 01:19:33.000] So for a variety of conditions, but especially these three age-related disease and especially cancer, because we are not doing well with cancer.
[01:19:33.240 --> 01:19:34.200] You said it.
[01:19:34.200 --> 01:19:37.720] We're only diagnosing cancer when it's way too late.
[01:19:37.720 --> 01:19:47.960] And that's got to change because when it's picked up, first picking up that the person has risk and picking up when it's microscopic well before you ever catch it on a scan.
[01:19:47.960 --> 01:19:57.480] That's why, you know, I'm not keen on these total body MRIs because they're being used to pick up already a cancer that's got a mass, right?
[01:19:57.480 --> 01:19:59.560] And of course, a lot of times it's not even cancer.
[01:19:59.560 --> 01:20:02.680] It's benign and people go through unnecessary biopsies.
[01:20:02.680 --> 01:20:11.720] But I do think if a person's high risk, and certainly if they have a positive liquid biopsy, you know, tumor DNA, then it's a very reasonable thing to pursue.
[01:20:11.720 --> 01:20:13.240] We're going to do much better.
[01:20:13.240 --> 01:20:22.360] And all these years of trying to treat cancer and cure it, you know, what do people have to go through to get there when you could prevent it?
[01:20:22.360 --> 01:20:26.040] And, you know, I think this is where we have a brilliant future.
[01:20:26.040 --> 01:20:30.440] It may take a while to get it implemented, but it's ready to go in many respects.
[01:20:30.440 --> 01:20:34.440] Just to go a layer deeper, so just you talk about polygenic risk for cancer.
[01:20:34.440 --> 01:20:42.200] And we've heard about the BRCAGENE or familial polyp disease, increased risk of cancer disease.
[01:20:42.200 --> 01:20:46.800] Those are unusual, although they're things you can measure and track if you have a family history.
[01:20:47.280 --> 01:20:55.040] You're talking about a different set of genetic biomarkers that are being discovered that help us segment people in terms of their risk.
[01:20:55.040 --> 01:20:55.200] Right.
[01:20:55.520 --> 01:20:56.800] Related to different cancers.
[01:20:56.800 --> 01:21:00.240] Yeah, so you're bringing up the rare mutations.
[01:21:00.240 --> 01:21:07.600] But, for example, they can all be had in a sequence, which costs a couple hundred dollars, a full whole genome sequence.
[01:21:07.600 --> 01:21:19.440] And BRCA2, we as men, you know, we're a lot of us carrying a BRCA gene, and just because we don't have breast cancer, you know, that means we have a higher risk of prostate cancer ourselves and other forms of cancer.
[01:21:19.440 --> 01:21:35.600] So, you know, these are pathogenic genes, which, and I go through that BRCA2 story in some depth because of the Icelandic data where it made a difference of up to seven years of healthy aging, mainly because of cancer.
[01:21:35.920 --> 01:21:45.360] Now, so you get these rare, so-called pathogenic genes that have a high risk of cancer, but you also can get a whole bunch of susceptibility genes.
[01:21:45.360 --> 01:21:56.560] So they're not that's high deterministic, you know, very, like we were talking about, ApoE4, two copies, but they are increasing the risk.
[01:21:56.560 --> 01:22:00.080] So what you have are three different types of gene markers.
[01:22:00.080 --> 01:22:10.240] One is the rare variants like BRCA2, BRCA, BRCA2, and as you said, Lynch syndrome and these other familial polyposis.
[01:22:10.240 --> 01:22:12.560] The next is the common variant.
[01:22:12.560 --> 01:22:20.880] The common variants, which is what you pick up in a, these are like, say, 200, 300 gene variants that would give you the high risk for breast cancer.
[01:22:20.880 --> 01:22:22.000] They're not BRCA.
[01:22:22.000 --> 01:22:26.640] These are just common variants that you got to add mixture from your mother and father, right?
[01:22:26.960 --> 01:22:34.280] And then the third group are these other susceptibility genes that can be gleaned from a genome sequence.
[01:22:34.520 --> 01:22:44.200] When you have all that data, which is again not expensive and processed properly, then you know what type of cancer you're at risk for, if you're at risk for a cancer.
[01:22:44.200 --> 01:22:46.120] It doesn't tell you when.
[01:22:46.120 --> 01:22:48.360] It just says yes, no, right?
[01:22:48.360 --> 01:23:02.760] That's the when is when we have to you know get early, get on this early and not treat everybody who's 50 and older as if they were a cattle, that we're all the same.
[01:23:02.760 --> 01:23:05.000] We have to be much smarter about this.
[01:23:05.240 --> 01:23:08.280] And this is what we call precision medicine or personalized medicine.
[01:23:09.320 --> 01:23:10.920] And then we're finally entering the year.
[01:23:10.920 --> 01:23:13.320] I think AI is going to help us get smarter about that.
[01:23:13.320 --> 01:23:23.480] The other thing you sort of mentioned was sort of liquid biopsies and you kind of touched on this a little bit, but proteomic kind of testing.
[01:23:23.480 --> 01:23:31.480] The liquid biopsy, from what you're, I hear you saying, you don't think it's a good screening tool because it picks the things late.
[01:23:31.480 --> 01:23:34.600] But if everybody got it, it would pick up things earlier, right?
[01:23:34.600 --> 01:23:47.160] If it was sort of cost was down and scale was up for blood tests every year with your checkup, you could potentially be picking up stuff much more frequently and much earlier, right?
[01:23:47.160 --> 01:23:53.560] Well, potentially, but you see, it's not being, it's just being done, you know, for on the age criteria.
[01:23:53.560 --> 01:24:00.760] And the yield of picking up an early cancer is two per thousand people, which is really, really low, right?
[01:24:00.760 --> 01:24:01.720] That doesn't make it a better test.
[01:24:01.880 --> 01:24:03.160] Unless you're one of those two.
[01:24:03.160 --> 01:24:03.440] Yeah, yeah.
[01:24:03.480 --> 01:24:12.120] I mean, and also, you know, if you had the test and it's negative, that doesn't put you in, you know, in the safe group.
[01:24:12.080 --> 01:24:14.880] Yeah, it's only if it's positive where it's really helpful.
[01:24:14.880 --> 01:24:16.720] I do think these tests are going to get better.
[01:24:14.440 --> 01:24:21.520] There's lots of ways, you know, this is a very minimal amount of tumor DNA in the plasma.
[01:24:21.840 --> 01:24:25.360] And there's ways to jack that up to make the test better.
[01:24:25.360 --> 01:24:28.080] And as you got to, it's got to be cheaper.
[01:24:28.640 --> 01:24:39.360] But yeah, again, this whole Bayes theorem of don't do tests that are not in people who are healthy of no risk.
[01:24:39.360 --> 01:24:46.400] But when you do it in people, like the two per thousand I cited is in healthy people age 50 plus.
[01:24:46.400 --> 01:24:52.640] But if it was done in people who were, you know, clearly had increased risk, that yield of picking up then it's a better test.
[01:24:52.640 --> 01:24:53.120] Oh, yeah.
[01:24:53.760 --> 01:24:58.720] And also when you're paying $900, that's substantial.
[01:24:58.720 --> 01:25:08.880] If we get that test down to $100 or something like that, and it's more sensitive, more accurate in the right people, it's going to become very commonly used.
[01:25:08.880 --> 01:25:12.240] So you're heading down the right path with that point.
[01:25:12.240 --> 01:25:12.720] Yeah.
[01:25:12.720 --> 01:25:37.280] And then the other thing I've been hearing about is proteomic tests where common protein, some of the common proteins we look at for cancer, like CA125 or CA99 for colon cancer, like they're combining that with multiple other proteins and they're able to kind of using AI to predict that you'll be able to pick up these cancers much earlier with these proteomic signatures that they have in the blood, which are really inexpensive to do.
[01:25:37.280 --> 01:25:37.600] Right.
[01:25:37.600 --> 01:25:42.320] So that's a Johns Hopkins Burt Vogelstein effort.
[01:25:42.320 --> 01:25:43.040] And that's right.
[01:25:43.040 --> 01:25:52.800] As you said, they combine some key proteins that have been established as markers with some gene variants and made it a relatively inexpensive test.
[01:25:52.800 --> 01:25:55.760] And that's one that certainly has a potential as well.
[01:25:56.000 --> 01:26:06.920] We're going to be able to do so much better with the screening using the blood because once it shows up in the blood in a microscopic, that's when we get all over it.
[01:26:07.080 --> 01:26:11.960] Because this is, I think, a new era of early diagnosis.
[01:26:11.960 --> 01:26:13.080] It's essential.
[01:26:13.080 --> 01:26:17.960] And we just, you know, again, you get it on a mammogram, it's already got a problem.
[01:26:17.960 --> 01:26:23.320] You know, and we're not even using AI in this country for mammograms routinely.
[01:26:23.320 --> 01:26:23.880] And we should.
[01:26:23.880 --> 01:26:26.760] That's the best AI case that exists today.
[01:26:26.760 --> 01:26:29.080] 100,000 plus women in Sweden.
[01:26:29.080 --> 01:26:35.320] The AI picked up 25% more cancers compared to radiologists alone.
[01:26:35.960 --> 01:26:40.440] You know, significant cancers and no increase in false positives.
[01:26:40.440 --> 01:26:41.880] Why aren't we using that?
[01:26:41.880 --> 01:26:50.120] So we're not doing a good job here for cancer screening or partitioning risk, no less preventing it.
[01:26:50.120 --> 01:27:06.040] I mean, you mentioned imaging a little bit, but my understanding is that with new AI advanced sort of interpretation and stuff, that with these more high-resolution scans, you can pick up cancers down to two millimeters, which is pretty small, like basically the side of a ballpoint pen.
[01:27:06.040 --> 01:27:06.600] Yeah.
[01:27:06.600 --> 01:27:10.920] And at that point, they're not likely to have spread or metastasized.
[01:27:10.920 --> 01:27:15.720] And then, you know, you can see changes over time if you do serial imaging.
[01:27:15.880 --> 01:27:18.440] Seems to me that's a kind of a useful tool.
[01:27:18.520 --> 01:27:19.000] Might be.
[01:27:19.000 --> 01:27:24.200] And it may make up things that are more sensitive than the gallery, which is not as sensitive.
[01:27:24.200 --> 01:27:25.320] Yeah, it might be.
[01:27:25.320 --> 01:27:41.000] I think what we've seen, at least unequivocal, you know, a huge trial, is that AI of a regular mammogram, not like you're talking about, not ultra-high resolution, it can really make a difference.
[01:27:41.240 --> 01:27:46.880] And so, that I think is, you know, we should be implementing that, and we're not.
[01:27:44.840 --> 01:27:48.880] And it's just a you know, we're missed opportunity.
[01:27:49.200 --> 01:28:00.240] There's a big study that showed that if you have AI analysis of a regular mammogram, you can predict cancer from that in that woman five years ahead if they're going to develop cancer.
[01:28:00.240 --> 01:28:07.120] So, the AI of scans continues to see things that we humans can't see.
[01:28:07.120 --> 01:28:21.920] And the fact that you can look at a mammogram with an AI not only make the diagnosis of cancer more better than radiologists alone, but also see some patterns that indicate the person's much higher likelihood of cancer in the next five years.
[01:28:21.920 --> 01:28:28.160] So, it's just like what we're talking about with the ability to predict the other age-related diseases.
[01:28:28.160 --> 01:28:36.960] Yeah, so the fourth thing you said was really around finding ways to enhance our own body's immune function and natural killer cell function.
[01:28:36.960 --> 01:29:00.960] I know Patrick Sun Shang is working a lot on this, and I don't know, I'm not deep enough into it to know whether there's a lot there to it, but it seems like an interesting theory that if we can see a decrease in our own tumor surveillance with lower natural killer cells, which is part of our immune system, the white blood cells that kill cancer and infections, that we could amplify that effect, that could be a powerful therapy.
[01:29:00.960 --> 01:29:08.160] Yeah, so this whole chapter on the immune system, and you know, after the brain, this is the most complex system there is.
[01:29:08.160 --> 01:29:13.360] There's so many different cells and interferons and antibodies.
[01:29:13.360 --> 01:29:22.560] But the big thing here is we have ability to control our immune system like never before, up or down, like a rheostat, right?
[01:29:22.560 --> 01:29:32.280] And with that capability, that gives the confidence that we can amp it up for people at high risk for cancer or at the earliest possible diagnosis.
[01:29:32.600 --> 01:29:38.920] So we're no longer going to give these, you know, toxic drugs, but we're going to just get their immune system in high gear.
[01:29:39.320 --> 01:29:59.800] And also, of course, what we've never seen before, Mark, is by taking people with autoimmune diseases like lupus, systemic sclerosis, even multiple sclerosis, by giving them T cell, engineered T cells, CAR T, directed towards depleting their B cells.
[01:29:59.800 --> 01:30:05.480] That when the B cells come back, they forgot that the person has an autoimmune disease.
[01:30:05.480 --> 01:30:07.400] They have a control alt delete.
[01:30:07.400 --> 01:30:09.080] I mean, this is incredible, right?
[01:30:09.400 --> 01:30:16.920] That they no longer, and for now, three, seven years of follow-up, they're cured of an autoimmune disease.
[01:30:16.920 --> 01:30:19.240] We had never seen anything like that before.
[01:30:19.240 --> 01:30:30.360] And of course, you know, we're seeing more and more reports of this ability to cure, you know, really vicious autoimmune diseases that can, you know, killers and no less really severe morbidity.
[01:30:30.360 --> 01:30:36.200] So that is another, besides the cancer immunotherapy to worry, which is huge.
[01:30:36.200 --> 01:30:47.640] Oh, I mean, you, the fact that we can, the more you give an immunotherapy, higher gear, high, the more chances you are going to be able to treat successfully a person with an intractable cancer.
[01:30:47.640 --> 01:31:00.280] So, between all these things, we're learning about the immune system, no less the missing metric, the ability to test a person's immune system at any point during, let's say, their annual checkup or whatever.
[01:31:00.280 --> 01:31:03.480] Once we get that, then that's the missing link right now.
[01:31:03.480 --> 01:31:04.520] And then we're also.
[01:31:04.680 --> 01:31:07.400] That's the protein clocks, that's the immune age protein clock.
[01:31:07.560 --> 01:31:17.360] Yeah, yeah, we have an immune clock, but we want more than that because that, as you got to early on in our conversation, that's a piece of it.
[01:31:14.920 --> 01:31:22.640] But we want to know about the T cell story, the B cells, the NK, all these different cells.
[01:31:22.640 --> 01:31:41.360] We want to know about, I do present in the book a kind of first-tier immunome that I had of Johns Hopkins startup called Infinity Bio, where I had all my autoantibodies, every virus I've ever been exposed to in my life.
[01:31:41.520 --> 01:31:47.520] Interestingly, you know, I never had been exposed to CMV and all sorts of things that are going to help.
[01:31:47.840 --> 01:31:50.000] And this could be done inexpensively.
[01:31:50.000 --> 01:31:51.200] It will be common.
[01:31:51.200 --> 01:31:55.280] It's all part of this immunome that we don't have right now that we need.
[01:31:55.280 --> 01:31:59.360] To loop back on the cancer thing, but before I go with that, you mentioned T cells and B cells.
[01:31:59.360 --> 01:32:02.000] People probably don't know about, you know, B cells are the ones that create antibodies.
[01:32:02.000 --> 01:32:05.120] And autoimmune diseases are where you make antibodies against your own body's tissues.
[01:32:05.120 --> 01:32:06.400] So that's why it's so important.
[01:32:06.400 --> 01:32:09.440] And T cells are more of an ancient part of your immune system.
[01:32:09.440 --> 01:32:16.080] They're more general and are we call cell mediated, which is different than antibody mediated.
[01:32:16.080 --> 01:32:20.240] And those will basically turn off the B cells so that you don't make antibodies.
[01:32:20.240 --> 01:32:21.360] That's kind of cool.
[01:32:21.360 --> 01:32:22.400] I didn't know about that.
[01:32:22.400 --> 01:32:31.200] Yeah, you know, these T regs that are the key T cells that you can get to tone down your whole immune system.
[01:32:31.200 --> 01:32:42.320] And then, you know, and then killing these cells that have the foreign, the alien antigen, the cytotoxic CD8 T cells.
[01:32:42.320 --> 01:32:44.960] I mean, so the immune system we have is rich.
[01:32:44.960 --> 01:32:49.440] The problem is, as we get older, you know, it lets down.
[01:32:49.440 --> 01:32:51.360] And in some people, more than others.
[01:32:51.360 --> 01:32:52.800] And we have to be on top of that.
[01:32:52.800 --> 01:32:58.320] That's the one thing that if you had to go back and say the welderly, how did they get there?
[01:32:58.320 --> 01:33:01.800] Maybe some of them are just, you know, random stochastic luck.
[01:33:02.120 --> 01:33:09.160] But for the most part, these people are, you know, they got a great immune system that just carried them through.
[01:33:09.160 --> 01:33:11.880] And we want everybody to have a great immune system someday.
[01:33:11.880 --> 01:33:12.120] Good.
[01:33:12.120 --> 01:33:14.040] And I think we're going to learn more about how to do that.
[01:33:14.040 --> 01:33:45.080] Just to kind of go back to the cancer story, I just want to finish summarizing it because as I think about all these new technologies, whether it's collections of genes that put you at higher risk that aren't a cancer gene, but that collectively increase your risk, combining with the liquid biopsies to get more and more accurate at less of a cost, combined with protein signatures of different cancers that can be picked up way before you'll see anything in any other test, combined with better resolution AI imaging done serial over time.
[01:33:45.080 --> 01:33:57.640] It seems to me that you can't prevent us from getting cancer because we live in the toxic world and there's shit that happens, but we could make dying of cancer a historical footnote.
[01:33:57.640 --> 01:33:58.120] Oh, yeah.
[01:33:58.120 --> 01:33:58.360] Yeah.
[01:33:58.760 --> 01:33:59.640] Is that fair to say?
[01:33:59.640 --> 01:33:59.960] Yeah.
[01:33:59.960 --> 01:34:10.680] I mean, what we have to do, and I go through this in the cancer chapter in the book, we have to prevent metastasis because people don't die of the cancer per se.
[01:34:10.680 --> 01:34:13.080] They die of the spread of that cancer.
[01:34:13.080 --> 01:34:24.200] And if we can just get rid of metastasis, which we can, there's a way to do this now, then that's going to be our big dent in the cancer story.
[01:34:24.520 --> 01:34:29.400] And, you know, obviously we want to even catch it when it's before it gets to microscopic.
[01:34:29.400 --> 01:34:33.480] And we put people under surveillance, who once we determine they're at high risk.
[01:34:33.480 --> 01:34:39.880] But I think what is so exciting here is just prevent it ever getting legs.
[01:34:39.880 --> 01:34:43.880] Don't, if it doesn't spread, we got a winner strategy here.
[01:34:43.880 --> 01:34:45.760] You and I can geek out on this all day long.
[01:34:45.920 --> 01:35:15.760] I think we didn't get to a lot of things I did want to talk about, but we covered, I think, some of the most important things, which is the advances in medicine are happening so rapidly that we're learning about ways to detect early, very early, far earlier than we used to, and to be proactive with what we learn about through lifestyle and other novel therapies that we can make these three horsemen of the apocalypse kind of not so scary anymore: heart disease, cancer, and dementia.
[01:35:15.760 --> 01:35:18.560] Yeah, I mean, that's the nuts of it.
[01:35:18.560 --> 01:35:26.320] I think what's so exciting, and you know, why I'm so optimistic, is for millennia, we talk about preventing these diseases.
[01:35:26.320 --> 01:35:27.920] And we never did it.
[01:35:27.920 --> 01:35:29.360] And now we can do it.
[01:35:29.600 --> 01:35:30.480] We can do it.
[01:35:30.480 --> 01:35:40.640] It wouldn't happen if we didn't have the science of aging metrics we've been discussing, these new ways to track a person, you know, really accurately and temporally.
[01:35:40.640 --> 01:35:47.200] And it wouldn't happen without the multimodal AI to assemble, integrate all the data at the individual level.
[01:35:47.200 --> 01:35:50.560] So it's these two things coming together that's made this possible.
[01:35:50.560 --> 01:35:53.280] It's a unique, you know, really momentous time.
[01:35:53.280 --> 01:35:59.200] And that's why, you know, I'm so optimistic that we can make a difference.
[01:35:59.200 --> 01:36:07.280] This will be the chance in medicine to finally fulfill that fantasy of primary prevention.
[01:36:07.280 --> 01:36:12.640] And really, at the end of the day, it comes down to creating large data sets on each individual.
[01:36:12.640 --> 01:36:38.360] So learning about all your biomarkers and data from genetics to proteins to lab testing to be able to understand the root causes and the risks, and then using AI and big data analytics to actually make sense of it all through the lens of our new understandings of human biology and like systems biology.
[01:36:38.360 --> 01:36:44.920] And to me, that's to me so exciting because we've been sort of just playing reactive medicine for so long.
[01:36:44.920 --> 01:36:49.720] And this is a time when we can move towards more proactive medicine.
[01:36:49.720 --> 01:36:52.120] And I think doctors would be happy about that.
[01:36:52.600 --> 01:37:04.760] They can figure out if we can figure out a way to make them do their job in a more sort of streamlined, easy way that makes this accessible to them and to their patients, it's going to be a game changer.
[01:37:04.920 --> 01:37:10.680] Yeah, I mean, you know, we've been banking on cures, and that's much harder than prevention.
[01:37:10.680 --> 01:37:11.080] Yeah.
[01:37:11.080 --> 01:37:14.680] And, you know, a pound of winning plan.
[01:37:14.680 --> 01:37:17.320] If we get serious about it, we can really do something.
[01:37:17.320 --> 01:37:18.040] Well, that's exciting.
[01:37:18.280 --> 01:37:21.800] I think everybody needs to check out your book, Super Agers.
[01:37:22.600 --> 01:37:23.960] It's quite a story.
[01:37:23.960 --> 01:37:29.560] It's a little more sort of technical than maybe most people would like, but there's Chat GPT.
[01:37:29.560 --> 01:37:31.480] You can look up stuff you don't understand.
[01:37:32.120 --> 01:37:36.600] And I think that this book is the potential to really change our thinking in medicine.
[01:37:36.840 --> 01:37:42.200] I really enjoyed it and I'm really grateful for you being so curious.
[01:37:42.200 --> 01:37:44.440] You're like a curious George.
[01:37:45.080 --> 01:37:47.560] And I think, thank you for your curiosity.
[01:37:47.560 --> 01:37:50.200] Thank you for all the work you've done in medicine for so many years.
[01:37:50.200 --> 01:37:56.200] And hope we get to chat again soon and get you back on the podcast and we talk about some things we could talk about.
[01:37:56.200 --> 01:38:01.080] I just would add, I tried to get it as simple as I could for everyone to understand.
[01:38:01.080 --> 01:38:03.400] And there are some parts that get a little dense.
[01:38:03.720 --> 01:38:06.040] I apologize early in the book for that.
[01:38:06.040 --> 01:38:09.160] But I think there's a lot of things in there that hopefully everyone can understand.
[01:38:09.160 --> 01:38:14.960] And I did do the reading so that people don't have to, you know, read it.
[01:38:14.960 --> 01:38:19.360] They can just do the audio and hear the passion and all that.
[01:38:14.680 --> 01:38:22.160] And finally, there's 70-some graphs in there.
[01:38:22.480 --> 01:38:26.480] So a lot of times people can grasp the graphs.
[01:38:26.480 --> 01:38:32.560] And so hopefully your point is a good one because there's a lot of 1800 citations.
[01:38:32.560 --> 01:38:33.920] So there's a lot there.
[01:38:33.920 --> 01:38:37.280] Hopefully, the people will get something out of it.
[01:38:37.440 --> 01:38:40.640] I know I'm going to see you well over 100 years old.
[01:38:41.120 --> 01:38:42.240] I hope you're right.
[01:38:42.240 --> 01:38:43.280] And vice versa.
[01:38:43.280 --> 01:38:45.520] If you get to 100, invite me to your birthday.
[01:38:45.840 --> 01:38:58.240] I just want to get to whenever age and stay as long as I can to meet that kind of welderly criteria of plus 80 plus and no age-related major diseases that we've been discussing.
[01:38:58.240 --> 01:38:59.520] I think that's a take-home.
[01:38:59.520 --> 01:39:01.360] Don't end up being elderly.
[01:39:01.360 --> 01:39:04.080] You can be welderly by just following this advice.
[01:39:04.080 --> 01:39:05.040] We're going to get there.
[01:39:05.040 --> 01:39:06.800] A lot more welderly in the future.
[01:39:06.800 --> 01:39:08.080] That's what's in store.
[01:39:08.080 --> 01:39:08.560] Thank you.
[01:39:08.560 --> 01:39:08.880] All right.
[01:39:08.880 --> 01:39:10.000] Well, thanks so much, Eric.
[01:39:10.000 --> 01:39:10.720] Thank you.
[01:39:10.720 --> 01:39:14.800] If you love this podcast, please share it with someone else you think would also enjoy it.
[01:39:14.800 --> 01:39:17.120] You can find me on all social media channels at Dr.
[01:39:17.120 --> 01:39:17.920] Mark Hyman.
[01:39:17.920 --> 01:39:18.400] Please reach out.
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[01:39:22.720 --> 01:39:24.960] Hyman Show wherever you get your podcasts.
[01:39:24.960 --> 01:39:27.120] And don't forget to check out my YouTube channel at Dr.
[01:39:27.120 --> 01:39:30.320] Mark Hyman for video versions of this podcast and more.
[01:39:30.320 --> 01:39:32.240] Thank you so much again for tuning in.
[01:39:32.240 --> 01:39:33.600] We'll see you next time on the Dr.
[01:39:33.600 --> 01:39:34.560] Hyman Show.
[01:39:34.560 --> 01:39:41.680] This podcast is separate from my clinical practice at the Ultra Wellness Center, my work at Cleveland Clinic, and Function Health, where I am chief medical officer.
[01:39:41.680 --> 01:39:44.480] This podcast represents my opinions and my guests' opinions.
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