WEBVTT - Decoding Longevity with Dr. Nir Barzilai 0:00:17.130 --> 0:00:25.690 Pushkin. On every episode of Decoding Women's Health, we talk 0:00:25.730 --> 0:00:28.970 about the science behind women's bodies and share stories from 0:00:29.050 --> 0:00:32.889 leading researchers and clinicians. But now I want to hear 0:00:33.089 --> 0:00:38.290 your stories and your questions. No question is too complex, awkward, 0:00:38.450 --> 0:00:41.970 or small. So tell me what kindacologic questions have been 0:00:42.010 --> 0:00:45.449 on your mind lately. We'll get into everything from entimetriosis 0:00:45.489 --> 0:00:50.569 to fibroids, pms, pcos, and more. We really want to 0:00:50.610 --> 0:00:54.010 hear from you, so please send your questions to us 0:00:54.050 --> 0:00:58.569 at Decoding Women's Health at Pushkin dot fm. That's Decoding 0:00:58.610 --> 0:01:02.090 Women's Health at Pushkin dot fm, or feel free to 0:01:02.130 --> 0:01:05.209 leave us a voicemail at four FI five two oh one, 0:01:05.610 --> 0:01:06.810 three three eight five. 0:01:17.370 --> 0:01:22.250 This show is not a substitute for professional medical advice, diagnosis, 0:01:22.410 --> 0:01:26.850 or treatment. It is for informational purposes. Please consult your 0:01:26.890 --> 0:01:31.850 healthcare professional with any medical questions. Also in this show, 0:01:31.970 --> 0:01:35.930 we use women as shorthand for people with XX chromosomes. 0:01:36.690 --> 0:01:40.650 We understand sex and gender are more complex and acknowledge 0:01:40.650 --> 0:01:44.330 the experiences we describe reach beyond that word. 0:01:47.450 --> 0:01:51.930 I think everybody knows that aging has a biology because 0:01:52.490 --> 0:01:55.290 we know who's young and who's old. But we know 0:01:55.410 --> 0:01:59.530 even more than that. We know that some people age 0:01:59.650 --> 0:02:03.410 faster than others, or some people are ages much slower 0:02:03.410 --> 0:02:07.810 than others. In other words, there's a chronological age that's 0:02:07.890 --> 0:02:13.130 your passport, birth certificate, and then there's your biological age. 0:02:12.930 --> 0:02:17.370 That's Doctor Neer Barzilai. He's a gyroscientist, which means he 0:02:17.490 --> 0:02:23.970 focuses on better understanding the biologic mechanisms of aging. For decades, 0:02:24.010 --> 0:02:26.730 he has been studying the aging process and looking for 0:02:26.810 --> 0:02:30.730 clues within our own bodies to help us all age better. 0:02:31.850 --> 0:02:34.970 He's the founding director of the Institute for Aging Research 0:02:35.010 --> 0:02:38.530 at Albert Einstein College of Medicine, and he's also the 0:02:38.570 --> 0:02:43.570 scientific director of the American Federation for Aging Research. Doctor 0:02:43.649 --> 0:02:47.889 Barzilai has been studying centenarians and their families to understand 0:02:47.929 --> 0:02:52.969 their genes, often referred to as longevity genes. He's hoping 0:02:53.010 --> 0:02:57.410 to identify interventions that could actually delay the process of aging. 0:02:58.530 --> 0:03:02.050 He's engaged in some really fascinating work looking at whether 0:03:02.209 --> 0:03:06.850 existing drugs such as met foreman and rapamycin can be 0:03:06.929 --> 0:03:11.530 repurposed to delay the hallmarks of aging. Is one that 0:03:11.570 --> 0:03:15.090 I have been following quite closely for some time. And 0:03:15.169 --> 0:03:17.970 I was excited to have doctor Barzilai on the show 0:03:18.450 --> 0:03:21.929 to hear more about his ongoing research, but I also 0:03:22.049 --> 0:03:24.969 wanted to get his honest thoughts on all the hype 0:03:25.090 --> 0:03:31.450 surrounding longevity medicine, because that word longevity is everywhere these days. 0:03:32.450 --> 0:03:36.330 So today we're breaking down what the latest science actually 0:03:36.490 --> 0:03:41.290 says about living longer and living better, starting with this 0:03:41.410 --> 0:03:46.450 concept of biologic age, as doctor Barzilai says, there's your 0:03:46.490 --> 0:03:50.130 chronologic age, how old you are, and then there's your 0:03:50.130 --> 0:03:54.290 biologic age how your body functions. He told me one 0:03:54.370 --> 0:03:57.689 of his missions is to be able to define biologic 0:03:57.770 --> 0:04:00.210 age in a test, just. 0:04:00.090 --> 0:04:02.890 Like you have cholesterol and you have glucos and you 0:04:02.930 --> 0:04:05.810 measure blood pressure. We know that there's a biology for aging, 0:04:05.850 --> 0:04:09.410 and we know that there's a hope because some people 0:04:09.970 --> 0:04:13.530 do better than others, which means there's flexibility. But there's 0:04:13.650 --> 0:04:18.370 one additional thing that we have to know, and this biology, 0:04:18.530 --> 0:04:23.890 this aging, is what drives diseases. Cardiovascar disease and cancer 0:04:24.050 --> 0:04:29.010 and diabetes and Alzheimer's and more are all driven by 0:04:29.050 --> 0:04:32.450 this biology of aging. So it's not that you're getting 0:04:32.490 --> 0:04:34.970 a disease and you're getting old. Okay, you're getting old 0:04:35.010 --> 0:04:39.090 and that drives disease. It means really that you have 0:04:39.210 --> 0:04:44.050 to target this aging before you have diseases. You have 0:04:44.089 --> 0:04:45.330 to think of prevention. 0:04:45.890 --> 0:04:48.650 What is the biology of aging? Can you take us 0:04:48.690 --> 0:04:52.330 through the biology of aging in a very big strokes 0:04:52.370 --> 0:04:53.529 kind of fashion. 0:04:53.529 --> 0:04:58.330 Yeah, very big strokes. We have something that we call 0:04:58.450 --> 0:05:03.130 the hallmarks of aging, and there are now twelve hallmarks 0:05:03.130 --> 0:05:06.650 of aging. For example, one of the hallmarks is the 0:05:06.969 --> 0:05:11.969 decline in the number and faction of mitochondria. Mitochondria is 0:05:12.010 --> 0:05:17.010 really important because that's the source of energy that we 0:05:17.170 --> 0:05:21.050 have and a lot of the complain of elderly that 0:05:21.089 --> 0:05:25.210 they feel that they're losing energy is because of decline 0:05:25.289 --> 0:05:29.850 in their mitochondrial function. One of our major companies in 0:05:30.330 --> 0:05:34.210 our Longevity Biotech Association, and actually company that is also 0:05:34.849 --> 0:05:39.450 using our facilities in Einstein, is a company that can 0:05:39.610 --> 0:05:44.489 actually take a sell and expand it and take a 0:05:44.529 --> 0:05:49.650 lot of mitochondria and then infuse it to your vein. 0:05:50.289 --> 0:05:53.770 So what happens when you infuse mitochondria to the vein, 0:05:54.210 --> 0:05:58.210 This mitochondria goes into the cells and get inside and 0:05:58.330 --> 0:06:01.609 replenish the mitochondria and the energy and everything that has 0:06:01.610 --> 0:06:04.010 to do with it, right, So that's one of the 0:06:04.050 --> 0:06:07.250 problems and one of the promises. Let me give you 0:06:07.289 --> 0:06:12.690 another one. There is a process that's called autophogy, and 0:06:12.810 --> 0:06:18.490 autophogy is a green energy garbage disposal. So, first of all, 0:06:18.490 --> 0:06:22.490 there's a lot of garbage that accumulates by mistakes in 0:06:22.529 --> 0:06:26.290 our cells all the time, okay, all the time, so 0:06:26.330 --> 0:06:29.770 we get garbage, and there is a garbage disposal that's 0:06:29.770 --> 0:06:34.530 called autophogy. It's a biological process that is quite well understood. 0:06:36.650 --> 0:06:42.250 This process declines with aging, so your cells are starting 0:06:42.289 --> 0:06:48.010 to accumulate more garbage. For example, what happens in Alzheimer's 0:06:48.050 --> 0:06:52.570 when we are accumulating those better amyloid or tao. This 0:06:52.730 --> 0:06:59.490 is all garbage that cannot be really disposed appropriately. So 0:06:59.810 --> 0:07:05.250 there's effort to produce a drug. There's actually a drug 0:07:05.370 --> 0:07:12.210 in biotech that is enhancing autophogy. And when you atophagy 0:07:12.250 --> 0:07:14.770 and you give it to animals, for example, they live 0:07:14.810 --> 0:07:18.369 healthier and they live much longer, and in particular models 0:07:18.370 --> 0:07:22.050 that have Alzheimer's disease. So I'm giving you two examples 0:07:22.050 --> 0:07:25.010 that are only two of those hallmarks of aging. There's 0:07:25.090 --> 0:07:27.730 telomeres by the way, people hear a lot about telomeres. 0:07:27.770 --> 0:07:29.210 That's a hallmark of aging too. 0:07:29.490 --> 0:07:32.170 One other hallmark of aging. Can you speak about inflammation? 0:07:32.330 --> 0:07:34.010 Can you drill down on that a little bit for 0:07:34.090 --> 0:07:35.090 us or is it relevant? 0:07:35.490 --> 0:07:40.450 Yeah, no, it is relevant. Inflammation or as we call it, inflammaging, 0:07:40.850 --> 0:07:44.570 is another one of the hallmarks of aging that we're 0:07:44.650 --> 0:07:48.450 trying to address. And you know, in the clinical setup, 0:07:48.570 --> 0:07:51.810 everybody talks about it because you kind of can measure 0:07:51.850 --> 0:07:56.050 it with highly sensitive tests. There are good markers for 0:07:56.970 --> 0:07:57.730 the breakdown. 0:07:57.770 --> 0:07:59.610 You know, when we go over the age of fifty, 0:07:59.650 --> 0:08:04.170 we're dealing with breakdown, and in response to this breakdown, 0:08:04.170 --> 0:08:07.970 there's an inflammation, and so inflammation is a response. 0:08:08.010 --> 0:08:09.929 So some of it is good, but then it goes 0:08:09.970 --> 0:08:14.650 bad because it's I'm trying to say that inflammation is 0:08:14.690 --> 0:08:18.330 not the cause of aging. I think it's a more 0:08:19.010 --> 0:08:25.130 secondary biomarker. But if we fix everything else with aging 0:08:25.250 --> 0:08:30.489 will probably decrease inflammation. Two. So inflammation is kind of 0:08:30.490 --> 0:08:33.929 of a center, but you have to understand that it's both. Okay, 0:08:34.370 --> 0:08:37.569 inflammation is bad also in the sense that it also 0:08:37.690 --> 0:08:41.250 drives things worse, but it's not what starts the process 0:08:41.250 --> 0:08:41.770 of aging. 0:08:42.050 --> 0:08:44.530 How do you measure aging? Are these biologic clocks that 0:08:44.569 --> 0:08:48.170 are marketed to us of any value? How do you 0:08:48.210 --> 0:08:49.969 look at aging? How do you measure it? 0:08:50.370 --> 0:08:53.650 So let me start by saying, I have ten measurements 0:08:53.730 --> 0:08:57.450 of my biological age, and I'm anywhere between twenty years 0:08:57.490 --> 0:09:00.010 younger than my age and four years older than my age, 0:09:00.050 --> 0:09:03.490 and it kind of tells you the problem, although I 0:09:03.490 --> 0:09:07.010 would also tell you that eight of those ten are 0:09:07.010 --> 0:09:12.530 pretty much in agreement. So those tools that were developed 0:09:13.370 --> 0:09:18.250 are kind of good to tell you what's your biological age. 0:09:18.490 --> 0:09:23.530 What they fail is to change if you do intervention. 0:09:23.929 --> 0:09:28.850 So what do we want. We want a biomarker that 0:09:29.210 --> 0:09:32.770 you will take and you will tell you you're two 0:09:32.850 --> 0:09:36.250 years older than your age, and the doctor will say, well, 0:09:36.770 --> 0:09:40.250 start exercising and take me for me. Okay, and you 0:09:40.290 --> 0:09:42.210 want to come in three months and see that you're 0:09:42.250 --> 0:09:45.290 now two years younger than when you started. Okay, that's 0:09:45.290 --> 0:09:48.890 what we want because we have to show success. You know. 0:09:49.130 --> 0:09:53.490 Let's say we stop aging and we ask you after 0:09:53.530 --> 0:09:56.730 two years, how you are. You said, you know, I'm 0:09:56.770 --> 0:09:59.610 the same, because you don't know how it would be 0:09:59.650 --> 0:10:03.090 if you're two years older. Right, it's a problem. So 0:10:03.130 --> 0:10:06.050 we need the market. It's like with blood pressure and glucose, 0:10:06.090 --> 0:10:10.210 you wouldn't know unless you're tested, So we need this. 0:10:10.450 --> 0:10:12.770 We also we need it for the development of drugs. 0:10:12.770 --> 0:10:14.650 We need in a phase two trial to see if 0:10:14.650 --> 0:10:17.490 it takes us to the right direction before we spend 0:10:17.569 --> 0:10:21.090 billion dollar in a phase three trial. My last grant 0:10:21.170 --> 0:10:26.410 that is with Dan Belsky from Columbia, we're looking at 0:10:26.450 --> 0:10:31.810 one hundred thousands biomarkers to see not only what's your 0:10:31.850 --> 0:10:39.729 biological age, but which of those biomarkers have changed in common, right, 0:10:39.890 --> 0:10:43.770 So we want to find those that are aging biomarkers. 0:10:43.809 --> 0:10:47.890 That also tells you that you're getting a respond I 0:10:47.929 --> 0:10:50.730 think once we have those biomarkers, we're going to learn 0:10:50.850 --> 0:10:54.250 so much for them and going to implement so fast 0:10:54.330 --> 0:10:58.050 that you can yourself see in your clinic what you're 0:10:58.050 --> 0:10:59.610 doing that is right or wrong. 0:11:00.410 --> 0:11:03.130 Sels in essence, can you just define what that is 0:11:03.170 --> 0:11:06.490 and how that segue is into inflammation because these are 0:11:06.490 --> 0:11:08.650 all words that are now like all over the internet 0:11:08.730 --> 0:11:10.970 and on social media, and so I think it's an 0:11:11.010 --> 0:11:13.130 important for our listeners to understand a little bit about 0:11:13.130 --> 0:11:13.690 what they are. 0:11:14.530 --> 0:11:18.609 So I have to tell you something that might frighten you. Initially, 0:11:19.210 --> 0:11:23.690 each one of our cells every day have thousands of 0:11:24.929 --> 0:11:29.730 basically mutations. Okay. The good thing is that we're pretty 0:11:29.730 --> 0:11:32.930 good at fixing everything. Okay, it's part of what we do. 0:11:33.770 --> 0:11:37.130 It was never meant to fix everything, because if we 0:11:37.290 --> 0:11:40.850 fix all the mutation will never have evolution, right. Evolution 0:11:41.010 --> 0:11:43.570 is based on the fact that, oh, there's mutation here 0:11:43.569 --> 0:11:45.290 and there. Some of them are bad, some of them 0:11:45.290 --> 0:11:47.570 are better. Let's take the better and let's, you know, 0:11:47.929 --> 0:11:52.010 reproduce with them. So in a way, mutation is why 0:11:52.050 --> 0:11:56.610 we have evolution. But of course sometimes will fail. So 0:11:56.650 --> 0:12:00.250 now we have a mutation, and sometimes also very rare, 0:12:00.330 --> 0:12:03.490 this mutation actually has an effect. It changed something in 0:12:03.530 --> 0:12:07.050 the cell. It could make this cell a cancer cell. 0:12:09.250 --> 0:12:16.290 It could make this cell say, you know, I'm committing suicide. Okay. 0:12:16.569 --> 0:12:20.730 But one of the options, and this option is very common, 0:12:21.090 --> 0:12:24.929 is that the cell sees that it's stress and it's 0:12:24.970 --> 0:12:29.010 become what is known as the senescen cell. It stops dividing. 0:12:29.970 --> 0:12:33.449 And that's fine, except that if you have a lot 0:12:33.490 --> 0:12:39.489 of those senescence cells, they secrete proteins that could be harmful, 0:12:40.130 --> 0:12:44.490 and particularly in the area that there's a lot of 0:12:44.530 --> 0:12:48.209 them when they accumulate, and that's what happened with aging. 0:12:48.330 --> 0:12:53.450 It accumulates. Then it is a risk actually of cancer 0:12:53.730 --> 0:12:57.770 and other diseases. And in animal models, when you remove 0:12:57.850 --> 0:13:01.290 those senescence cell they get healthier. I don't want to 0:13:01.330 --> 0:13:04.770 say they live longer, but they get healthier. So senesin 0:13:04.929 --> 0:13:07.849 is one of those hallmarks. It's one of those hallmarks 0:13:08.130 --> 0:13:10.970 that is out there to find. What are the drugs 0:13:11.530 --> 0:13:14.290 that you can take in order to remove a bunch 0:13:14.330 --> 0:13:16.770 senesence cells and improve your health. 0:13:17.370 --> 0:13:21.690 So are so called gerotherapeutics you mentioned, Matt Foreman, How 0:13:21.730 --> 0:13:25.170 are they different from other drugs? Like we know that statins, 0:13:25.170 --> 0:13:28.330 for example, are very effective at preventing heart attacks and stroke, 0:13:28.929 --> 0:13:31.250 both of which can kill you. How is this class 0:13:31.250 --> 0:13:34.090 of drugs, the ones that target aging itself? How are 0:13:34.130 --> 0:13:34.689 they different? 0:13:35.490 --> 0:13:40.010 Studings are such great drugs, they're so important, they're preventing 0:13:40.130 --> 0:13:46.050 so much cardiovascular events and cardiovascular mortality. But if you 0:13:46.130 --> 0:13:48.810 give them to animals, if you give them to cells, 0:13:48.850 --> 0:13:51.449 they don't change the hallmarks of aging. And if you 0:13:51.490 --> 0:13:54.729 give them to animals, they don't live longer. Okay, So 0:13:54.770 --> 0:13:57.730 they are drugs that are very important when you grow. 0:13:57.890 --> 0:14:01.249 But in my view, you don't call them gero therapeutics. 0:14:01.290 --> 0:14:05.850 They're not therapeutics for aging. What the statins have shown 0:14:05.970 --> 0:14:09.850 to do is taking care of cardiovasclar disease, so you 0:14:09.890 --> 0:14:13.449 can get now all shade or concert or another disease, 0:14:13.770 --> 0:14:16.010 which is not what we want to do. We want 0:14:16.050 --> 0:14:20.490 you to do something maybe one drug, and it will 0:14:20.490 --> 0:14:23.730 delay your aging, which means it will delay many diseases 0:14:23.730 --> 0:14:24.690 and not just one. 0:14:25.610 --> 0:14:27.729 The way I look at this and tell me if 0:14:27.730 --> 0:14:30.250 this is like kind of a basis. Aging is the 0:14:30.330 --> 0:14:34.729 root cause of cardiac disease or brain health issues or 0:14:34.970 --> 0:14:37.970 metabolic issues, and so if you target the aging process, 0:14:38.010 --> 0:14:40.370 then you target all these downstream effects. 0:14:40.090 --> 0:14:43.930 Of aging exactly. Aging drives the diseases. 0:14:44.130 --> 0:14:46.210 Right. Do you see a day where we have like 0:14:46.450 --> 0:14:50.610 one drug or one therapeutic or one intervention or is 0:14:50.610 --> 0:14:53.610 it going to be a combination of these things? And 0:14:53.930 --> 0:14:56.810 can you highlight some important ones that you're working on. 0:14:56.890 --> 0:14:59.770 For the first three questions, the answer is yes, I 0:14:59.770 --> 0:15:03.330 mean it's everything. What do we need to show to 0:15:03.370 --> 0:15:07.050 say that this drug is gerotherapeutic A. We want to 0:15:07.050 --> 0:15:09.810 put it in cells. We want to expose it to 0:15:09.930 --> 0:15:13.450 cells and show that the cells are getting younger, okay, 0:15:13.970 --> 0:15:18.290 which really means the hallmarks of aging are changing. Second, 0:15:18.610 --> 0:15:21.770 we want to give it to animals, all the animals. 0:15:22.370 --> 0:15:25.970 One of the problems we had in drug development is 0:15:26.010 --> 0:15:29.650 that people were doing age related disease, were working on 0:15:29.770 --> 0:15:34.170 young animals, and I just made a lot of effort 0:15:34.290 --> 0:15:37.810 to say it's different bodies. The young and old are 0:15:37.850 --> 0:15:41.970 totally different bodies. So you have to give a drug 0:15:42.010 --> 0:15:44.850 to an old animal and show that it becomes healthier 0:15:45.210 --> 0:15:49.050 and it lives longer. Okay, that's the pre clinical part. 0:15:49.330 --> 0:15:53.210 The clinical part is you want to show that the 0:15:53.330 --> 0:16:00.850 drug that was designated for a specific disease unexpectedly prevented 0:16:01.010 --> 0:16:05.490 other diseases. You want to show that this drug that 0:16:05.770 --> 0:16:12.290 was targeting one specific disease is actually changing overall mortality, 0:16:12.730 --> 0:16:17.570 not disease specific mortality. And if that's the strict definition 0:16:18.570 --> 0:16:23.330 for gerotherapeutics, we have already four drugs. Now what are 0:16:23.330 --> 0:16:27.250 the four drugs. One drug is met forming. Met forming 0:16:27.330 --> 0:16:30.890 it's an extract of the French lilac, but it's modulated, 0:16:30.930 --> 0:16:33.490 so it's not a nutraceutical. You need a prescription for that. 0:16:34.210 --> 0:16:37.650 But people notice that it also lowered glucose, and then 0:16:37.690 --> 0:16:42.370 it was used in diabetes, and in clinical trialing diabetes, 0:16:42.450 --> 0:16:46.530 it was shown that METFORMI decreased cardiovastri disease, and there's 0:16:46.610 --> 0:16:50.050 less cancer, and there's less alzheimer and there's less mortality 0:16:50.810 --> 0:16:54.410 when you take met forming. The latest paper was showing 0:16:54.490 --> 0:16:58.170 that you're something like twice as likely to get to 0:16:58.210 --> 0:17:00.170 the age of ninety if you're a diabetic and you're 0:17:00.210 --> 0:17:03.370 on met forming. So this is one drug. The second 0:17:03.410 --> 0:17:10.330 drug is the class that is called s GILT two inhibitors. 0:17:11.370 --> 0:17:16.689 The third classes the GLP one agonist, the ozempiic and manjaro, 0:17:17.410 --> 0:17:22.609 and the fourth is biphosphonates, which are anti ostroporotic drugs. 0:17:22.810 --> 0:17:25.050 So these are repurpose drugs, right, These are all drugs 0:17:25.090 --> 0:17:27.490 that are being used for other things. So I just 0:17:27.530 --> 0:17:29.490 want to back end into a couple of them that 0:17:29.570 --> 0:17:32.610 I'm really curious about because I've followed this field for 0:17:32.650 --> 0:17:37.410 a while. Met Foreman, right, mett Foreman was really out there. 0:17:37.570 --> 0:17:40.890 Then it lost a little favor. Where do you position 0:17:40.970 --> 0:17:43.090 it in terms of a longevity strategy. 0:17:44.090 --> 0:17:49.170 Losing a little favor is through podcasts of people who 0:17:51.330 --> 0:17:54.530 just are opinionated. Okay, in my mind. What happened to 0:17:54.570 --> 0:17:57.010 me for it gained favor, And let me explain to 0:17:57.050 --> 0:18:02.010 you why I'm claiming that those drugs affect more than 0:18:02.050 --> 0:18:05.730 one whole mark of aging. Right, met forman You can 0:18:05.810 --> 0:18:09.570 think it's only for diabetes and only for metabolism, but 0:18:09.850 --> 0:18:14.050 they're nine studies around the world during COVID that showed 0:18:14.050 --> 0:18:18.570 that people on metforming had less hospitalization, less mortality, which 0:18:18.690 --> 0:18:22.130 led to a clinical study. Okay, and that's what we need, 0:18:22.210 --> 0:18:26.610 clinical studies. And the clinical study was taking patients who 0:18:26.770 --> 0:18:30.250 just got COVID within the first three days, mostly within 0:18:30.530 --> 0:18:35.010 first day of COVID, and they gave them metforming and 0:18:35.090 --> 0:18:39.250 they had less hospitalization, less death, and less long COVID. 0:18:39.810 --> 0:18:43.969 And the point is metforming is not only metabolism, it's 0:18:44.010 --> 0:18:48.850 also immunity, it's also inflammation. It also makes the body 0:18:48.930 --> 0:18:53.730 more resilience to acute the salt. So this idea that 0:18:53.810 --> 0:19:00.170 metforming lost favor, I think is irresponsible. The second thing 0:19:00.330 --> 0:19:06.050 that happened that really made me crazy is not everything 0:19:06.129 --> 0:19:09.410 that's good for young is good for old. Okay. If 0:19:09.450 --> 0:19:13.250 you have high cholesterol metal when you're young, you're building 0:19:13.290 --> 0:19:15.850 your go nuts and brains, and it's great but if 0:19:15.890 --> 0:19:18.370 you have high cholesterol metabolism when you're old, you're clogging 0:19:18.369 --> 0:19:22.490 your arteries. Right. It's the same with drugs. Not every 0:19:22.570 --> 0:19:25.010 drug that is good for old people it's good for young. 0:19:25.530 --> 0:19:29.690 In fact, metformin has a lot of problems if you're 0:19:30.090 --> 0:19:33.530 let's say, less than fifty and don't have diabetes. There's 0:19:33.570 --> 0:19:36.050 a lot of things. It's decreasing growth from on the 0:19:36.050 --> 0:19:38.610 growthrom on igf one, and you don't want to decrease 0:19:39.369 --> 0:19:42.690 this igf one when you're young. It decreases testosterone in man. 0:19:43.090 --> 0:19:48.530 So there's a lot of confusion of what metformin is 0:19:48.570 --> 0:19:52.609 doing and the fact that young people are saying, you know, 0:19:52.730 --> 0:19:54.770 I noticed that it's not good for me. Well, you 0:19:54.810 --> 0:19:56.010 should have never been on them. 0:19:56.650 --> 0:19:59.609 Talk to me about the GLP ones and aging. 0:20:00.970 --> 0:20:03.330 If you look what GLP one is doing in cells, 0:20:03.690 --> 0:20:07.090 it's correcting a lot of the hallmarks of aging. If 0:20:07.129 --> 0:20:10.449 you give it to animals, even to animals that you 0:20:10.570 --> 0:20:13.570 make sure or that they are the same weight. Okay, 0:20:13.609 --> 0:20:17.129 you have to change the amount of the agonists. You 0:20:17.170 --> 0:20:19.770 have to feed the animals differently, but if you match 0:20:20.490 --> 0:20:25.369 the animals will still live twenty percent longer. Obesity drives aging, 0:20:25.609 --> 0:20:29.169 there's no doubt just treating obesity is good. But the 0:20:29.250 --> 0:20:32.649 point I'm making is that the GLP agonists are taking 0:20:32.690 --> 0:20:37.850 care of obesity, but that's not even their majority effect. 0:20:38.369 --> 0:20:42.929 They're affecting other cells directly, other organs and tissues directly. 0:20:43.369 --> 0:20:47.050 They're doing much more from aging than just the weight loss, 0:20:47.090 --> 0:20:50.810 which is important on its own. So those drugs were 0:20:50.850 --> 0:20:54.930 developed for diabetes, okay, because in diabetes they're doing something good. 0:20:54.930 --> 0:20:59.930 They're increasing insultin secretion, decreasing local goaues. But then they 0:20:59.930 --> 0:21:03.530 had a strong effect on weight loss also. And now 0:21:03.530 --> 0:21:06.649 when you give it, you notice that it prevents heart diseases, 0:21:07.210 --> 0:21:11.369 it prevents kidney diseases, it prevents some cognitive de client. 0:21:11.450 --> 0:21:15.369 It's not clear if it's pre alzheimer or Alzheimer's, but 0:21:15.930 --> 0:21:19.889 it's investigated now. In other words, it has effects on 0:21:20.050 --> 0:21:24.970 aging that are in part weight loss and in part independent. 0:21:26.369 --> 0:21:31.530 What is the mechanism of the best posphonates impacting aging processes? 0:21:32.650 --> 0:21:36.250 So some of it is senolytics, it takes care of 0:21:36.290 --> 0:21:39.810 the cells. Some other effects we are not sure. But 0:21:40.050 --> 0:21:43.210 one of our thoughts and their supporting elements is that 0:21:43.250 --> 0:21:46.290 the biphosphonates are in the bones, and a lot of 0:21:46.290 --> 0:21:49.130 our stem cells are in the bones, and that they 0:21:49.129 --> 0:21:53.930 are doing something to make the stem cell both youthful 0:21:54.330 --> 0:21:58.129 and also go into the periphery and through that improve 0:21:58.210 --> 0:21:58.810 our health. 0:21:59.129 --> 0:22:01.729 So interesting. So talk a little bit about rapamycin. 0:22:02.010 --> 0:22:07.889 Rapamycin is a drug that increased health span of almost 0:22:07.970 --> 0:22:13.210 every animal in the world. World and why is it important? 0:22:13.330 --> 0:22:18.209 Because all animals are aging similarly to us in the 0:22:18.250 --> 0:22:22.330 sense you know, their skin, their hair, they get diseases, 0:22:23.010 --> 0:22:29.170 their their muscular skeletal is fading away, not the same diseases, 0:22:29.250 --> 0:22:32.930 not exactly the same, but it's all aging, and that's 0:22:32.970 --> 0:22:38.970 why the animals are important. The longest living animal groups 0:22:39.010 --> 0:22:44.449 of animals has been the combination of rapamizing and metformin. 0:22:44.570 --> 0:22:49.969 They lived substantially longer, and that's why rapamicin is exciting. 0:22:50.450 --> 0:22:54.530 Rapamicin is also an FTY approved drugs, but it's approved 0:22:54.609 --> 0:23:00.050 in very high doses as an immune suppressor for people 0:23:00.090 --> 0:23:05.210 who got kidney or some transplant. Of course, we don't 0:23:05.250 --> 0:23:08.010 want to be immune suppressed when we're old or any 0:23:08.170 --> 0:23:11.530 any time of our life, so the stud these have 0:23:11.570 --> 0:23:16.010 been done only on those people and not on people 0:23:16.490 --> 0:23:20.050 who would get you know, tenth of the dose and 0:23:20.170 --> 0:23:24.570 see what's their effect on aging. There's some clinical, small 0:23:24.609 --> 0:23:28.290 clinical trials on that, but we just don't have enough 0:23:28.450 --> 0:23:33.010 evidence to suggest that this is something that we can take. 0:23:33.050 --> 0:23:36.210 And without clinical studies, we don't know the side effects, 0:23:36.290 --> 0:23:41.330 we don't know the safety, so we are not there yet. 0:23:41.609 --> 0:23:43.170 It didn't make it to the fore top. 0:23:46.490 --> 0:23:50.570 Coming up, doctor Barzilai walks us through a longitudinal study 0:23:50.970 --> 0:23:56.010 that he's co leading called the superager Study, what differentiates 0:23:56.090 --> 0:23:59.129 most people who live to one hundred from many of us. 0:23:59.890 --> 0:24:10.010 His answers might surprise you. Let's talk a little bit 0:24:10.010 --> 0:24:12.330 about the Superasier Family Study. Can you tell me about 0:24:12.330 --> 0:24:12.890 this study? 0:24:13.129 --> 0:24:17.449 The Superagor study started at Einstein, but now we have 0:24:17.490 --> 0:24:22.330 an initiative to recruit ten thousand centenarians and their families 0:24:22.450 --> 0:24:25.649 across the United States so we can find all the 0:24:25.730 --> 0:24:30.530 longevity genes and develop all drugs that we could to 0:24:30.730 --> 0:24:34.689 imitate them. And it's very important because we found a 0:24:34.770 --> 0:24:39.490 lot of genes variants that are different in them than 0:24:39.609 --> 0:24:43.930 others that had the functional consequences. And in fact, two 0:24:44.010 --> 0:24:47.970 drugs have been developed in part because of our discovery, 0:24:47.970 --> 0:24:50.770 and there are others that are on their way. Even 0:24:50.810 --> 0:24:55.290 more promising. But there's another study. We have a longitudal 0:24:55.369 --> 0:25:00.210 study on the offspring of centenarians and the people who 0:25:00.290 --> 0:25:02.770 they are married to. Pretty much if they don't have 0:25:02.850 --> 0:25:06.330 longevity in the family. And when we look at those 0:25:07.170 --> 0:25:10.810 people in a longitudal study, we have about fourteen hundred 0:25:11.090 --> 0:25:15.850 of them. The offspring of centenarians have pretty much half 0:25:15.890 --> 0:25:21.010 the cardiovascure disease, half the mortality, half the cognitive decline. 0:25:21.210 --> 0:25:26.530 So just this genetic is making a huge difference for them. 0:25:26.890 --> 0:25:29.610 What if we learn from superagers, what can we adopt? 0:25:29.650 --> 0:25:30.770 What can we learn from them? 0:25:31.090 --> 0:25:34.209 So listen carefully to what I tell you, because I 0:25:34.210 --> 0:25:38.090 mean you're asking me as if what was their diet 0:25:38.210 --> 0:25:42.449 and what was their exercise, and what was their social 0:25:42.490 --> 0:25:46.369 connectivity and all that, And I'll tell you we were 0:25:46.410 --> 0:25:50.650 in a way lucky, but that didn't matter to them. 0:25:50.890 --> 0:25:54.370 That's not what they were about. In other words, it's 0:25:54.410 --> 0:25:57.410 not that they did what the doctors tell us to do. 0:25:57.930 --> 0:26:01.409 Fifty percent of them were overweight, over obese, fifty percent 0:26:01.490 --> 0:26:06.170 of them did not move at all, even moderate exercising, 0:26:06.930 --> 0:26:10.850 very few vegetarians. So as a group, they're nothing. To 0:26:11.129 --> 0:26:14.130 tell you, There is this woman I always say, there's 0:26:14.170 --> 0:26:16.409 a woman who I met when she was one hundred 0:26:16.490 --> 0:26:20.689 years old and she was smoking, and I said, Helen, 0:26:20.730 --> 0:26:22.970 nobody told you to stop smoking. And she said, the 0:26:23.010 --> 0:26:26.330 four doctors who told me to stop smoking, they died, right, 0:26:27.490 --> 0:26:29.970 And she continued to smoke until she was one hundred 0:26:30.010 --> 0:26:32.929 and ten. And the argument was for me, is you know, 0:26:33.010 --> 0:26:35.609 who knows how long you would leave if you don't smoke. 0:26:35.690 --> 0:26:37.369 She got to one hundred and ten. I don't know 0:26:37.810 --> 0:26:41.969 what's the answer to that, really, So in this case 0:26:42.170 --> 0:26:45.050 we don't learn from them. What we learn is the 0:26:45.129 --> 0:26:49.610 genetic case. What are their longevity genes that slows their 0:26:49.650 --> 0:26:53.570 aging process and how can we make them a therapy? 0:26:54.010 --> 0:26:57.210 You know, our maximum lifespan as humans is somewhere like 0:26:57.250 --> 0:27:01.490