The Peter Attia Drive - #19 - Dave Feldman： stress testing the lipid energy model

00:00:00.000 Hey everyone, welcome to the Peter Atiyah Drive. I'm your host, Peter Atiyah.

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00:00:41.500 Hey everyone, before introducing today's guest, a couple of housekeeping issues. First,

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00:01:17.940 over my head in this area, or what were they talking about here? Pretty much anything that's

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00:01:27.380 If that's something that interests you, certainly today's podcast will provide an opportunity

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00:01:39.040 a review also, but I'm probably not going to ask you to spend as much time doing so. All right,

00:01:43.960 on to today's guest. Now, this is going to be a slightly longer introduction than normal.

00:01:49.420 Apologies in advance. If you positively absolutely don't want to hear it, just skip ahead. I don't

00:01:53.920 know, five minutes or so. If you're a low carb enthusiast, you've undoubtedly heard about Dave

00:01:58.880 Feldman and his cholesterol drop protocol and his take on what he calls lean mass hyper responders or

00:02:05.880 people who go on ketogenic or low carbohydrate diets see a very high LDL cholesterol and or LDL particle

00:02:12.600 number. You've probably also heard that Dave is somewhat skeptical of the LDL is causal paradigm or

00:02:18.600 thinking in atherosclerosis. So you're probably going to understand that out of the gate, Dave and

00:02:23.780 I don't really see eye to eye on the genesis of heart disease. We go right into the conversation,

00:02:30.080 assuming people know the background. And the reason for that is I knew that this was going to be a long

00:02:33.780 enough discussion anyway. And I'd already heard Dave on a number of other podcasts present his model

00:02:39.000 and his observations. So I thought rather than recapitulate those things here, we would link to

00:02:44.820 those previous shows of which there are at least two or three, including a couple of presentations

00:02:49.040 on YouTube so that you can kind of watch those. If you're not already familiar with Dave's hypotheses,

00:02:54.360 I do recommend that you familiarize yourself with these because as I said, I didn't really make the

00:03:00.900 time in this episode for Dave to go into the depth that he would normally go into. And again,

00:03:06.340 that wasn't out of any reason other than I knew that we were going to have enough to talk about

00:03:11.420 without that. And I didn't want to reproduce or recreate the wheel, so to speak. Now, I believe

00:03:16.220 Dave is putting up a companion blog post for this episode. So if you head on over to his site,

00:03:21.760 which is cholesterolcode.com, he will undoubtedly have his own links and show notes. And that will

00:03:28.060 probably on some level overlap with what we do, but also probably provide some new information.

00:03:33.400 Now we've got a kind of a special treat on this as well, which is Tom Dayspring, who,

00:03:38.060 if you don't know who Tom is, you certainly will by the next week or so, because Tom is kind of my

00:03:43.540 foremost lipid mentors. And I wanted him to make sure that anything that Dave and I said that wasn't

00:03:49.740 accurate was sort of corrected. So he's actually taken a look at the transcript of this, which we

00:03:55.720 usually pull together for episodes. And he's kind of weighed in with some commentary, mostly clarifying

00:04:01.140 and elaborating on some technical stuff. But even as I said, correcting any mistakes that we've made.

00:04:05.060 So hopefully Tom's clarifications to the transcript will be valuable to those who want to kind of get

00:04:11.120 on the next level of detail. The show notes will have lots of links to graphics that help conceptualize

00:04:16.760 some of these topics we get into. I mean, a lot of the time that Dave and I were talking,

00:04:19.740 we were looking at diagrams and pointing things out. And so we hope to reproduce that for you.

00:04:24.660 Now, before jumping into this episode, I do want to provide my summary and synthesis of where I've

00:04:30.920 landed in my own mind when all was said and done. I think I came into this with a point of view and I

00:04:36.780 think I left with a slightly different point of view. And I think that it's actually kind of hard

00:04:41.920 maybe to follow the logic in my mind as I go through the episode. So I thought in the days after

00:04:49.100 we recorded this, which was in July this year, 2018, that I would sort of just put my thoughts down

00:04:55.040 and sort of crystallize them. So again, kind of an unusual thing to do, but I do think that this is

00:05:00.160 a complicated enough topic that it's helpful. Ultimately, I am not convinced by Dave's model.

00:05:05.160 And again, truthfully, I came into this maybe 20% thinking that there was a chance I would find the

00:05:10.840 argument convincing, but I left with that number being a lot less. And I'll explain why. There were

00:05:15.780 basically three reasons. The first is Dave was unable to explain to me the mass balance, meaning how does

00:05:21.380 one account for the greater amount of cholesterol in, and the greater number of the LDL particles.

00:05:28.300 Now it's possible that at the time of this podcast being released, Dave has given more thought to

00:05:32.960 the questions I posed and has an answer for that. But no one, including Dave, is disputing that the

00:05:39.240 phenotype of interest has more LDL cholesterol and more LDL particles. So therefore there's only three

00:05:45.380 ways this can happen. And these three ways are collectively exhaustive, but not mutually exclusive.

00:05:49.400 First, you can make more cholesterol. Second, you can clear less cholesterol. And third, you can

00:05:56.160 transfer cholesterol from other pools that we didn't see previously, such as cell membranes into

00:06:02.460 pools that we now look at, such as the lipoprotein. I think the data makes the first of these cases

00:06:08.780 by far the most likely, but Dave seemed unable to address why that would be the case. And therefore,

00:06:15.820 what could possibly account for this increase in the LDL-P and the LDL-C. So on first principles,

00:06:22.320 my doubt of the model has gone up from where we started the discussion to where we are now,

00:06:27.900 because the person who developed the model wasn't able to really articulate to me one of the most

00:06:33.720 fundamental tenets of any physical model, which is it must respect mass balance. Now, to be clear,

00:06:40.260 even if this fundamental condition were met, it would not be sufficient to make the case

00:06:44.980 that this phenotype is not at risk. It would be at best a necessary, but not sufficient criteria.

00:06:52.180 So in addition to not being able to really explain the mass balance of how these additional molecules

00:06:58.820 of cholesterol show up in the LDL particles, the second thing that I found difficult to reconcile

00:07:05.440 was that Dave argued that VLDL production was driving the LDL concentration. But the fact remains

00:07:12.840 that in insulin sensitive people, which presumably this phenotype that he's referring to are, it's

00:07:17.860 actually the opposite that is true. There were fewer, not more triglycerides being exported from the

00:07:23.500 liver. And there was less, not more APOC3 on the VLDL particles. This would actually reduce,

00:07:31.120 not increase their residence time. In other words, these so-called lean mass hyper responders would

00:07:36.740 actually have less VL to LDL conversion than say someone with type two diabetes. And I even point out

00:07:44.040 in this discussion that even the person with type two diabetes does not have nearly as much VLDL as we

00:07:48.540 might think they do. So I really see no evidence whatsoever from this energy model, which is, I believe

00:07:54.280 the terminology Dave uses, that we could explain this phenotype on the balance of triglyceride export

00:08:00.520 through VLDL to LDL. The third point that I still was not able to fully come to grips with was that

00:08:08.280 basically, even if you ignore the first two points I've made, which I would argue you can't, I'm still

00:08:13.960 unconvinced at this notion that we should exclude the roughly 2000 genetic mutations that are known to

00:08:19.940 produce a phenotype of high LDL, high HDL, and low triglyceride. These are called natural experiments.

00:08:27.760 And we have, as I said, about 2000 of such these natural experiments. And surely at least some of

00:08:33.280 these cases, for example, the PCSK9 gain of functions are excellent proxies for the key features

00:08:39.780 of these lean mass hyper responders. And yet to ignore them for reasons that are not at all based

00:08:45.780 in our understanding of the physiology of this disease. For example, the PCSK9 hyper functions somehow

00:08:51.440 having toxic endothelium reactions in response to this inability or impaired ability to take up

00:08:57.880 cholesterol, despite there being no evidence of that being true, because there's no evidence that

00:09:01.900 PCSK9 hyper functioning patients use an LDL receptor to take up cholesterol into their endothelial cells

00:09:09.140 is to basically say that one doesn't want to know the answer to this question. Now, I believe Dave is

00:09:13.780 about as intellectually honest as anybody is in this space. And I've made no secret of my general

00:09:19.980 disdain for the groups of folks that claim that LDL is not causal in atherosclerosis.

00:09:25.900 None of this is to suggest that I can be entirely certain that folks of this phenotype with very high

00:09:31.660 LDL are absolutely at increased risk for atherosclerosis, or to state that more technically,

00:09:37.680 that their risk for atherosclerosis is commensurate with their lipid profile.

00:09:41.720 I don't know that. And ultimately, I don't think we'll ever really know that. Nothing that Dave or

00:09:47.620 I discussed could ever definitively make that case for the reasons that make this study of lipids

00:09:53.020 challenging. Science is based on skepticism and certainty is forever elusive. So science gets

00:09:59.600 better and gets sharper through this type of discussion. But that said, a body of evidence

00:10:03.680 produces a probability of accuracy. And in the end, the probability of one idea here seems

00:10:09.760 disproportionately higher than the other. And as I said, coming into this discussion, I thought the

00:10:14.380 probability that Dave's ideas were correct was quite low. But following this discussion, I feel

00:10:19.480 I would say of a higher degree of confidence that his hypothesis is not correct. In other words,

00:10:26.740 my confidence in the probability of his hypothesis being correct has gone down based on these three

00:10:32.420 points I raise above. The idea of probability is the nuance that's sort of missing from this

00:10:37.880 discussion. And that's what troubles me, I guess, is that people think that we're dealing with a

00:10:43.340 disease that has one and only one risk factor. When in reality, we know that atherosclerosis is

00:10:48.740 incredibly complicated and is impacted by many things beyond the lipoproteins. But that doesn't

00:10:53.960 diminish their role in the causality of atherosclerosis. In the end, I would ask you to make up your own

00:11:00.920 mind because ultimately anyone who's listening to this, whose LDL is through the roof as a result

00:11:05.720 of going on a ketogenic or low carbohydrate diet, has to make a decision for themselves.

00:11:12.060 And so I hope that what Dave and I have discussed here allows you to make a slightly more informed

00:11:17.960 decision that you could have made before. And some of the other guests that I have already had on this

00:11:22.780 podcast, including Ron Krause, or those that will be on the podcast, including next week's guest,

00:11:27.300 Tom Dayspring, will allow you to further think through those issues.

00:11:30.920 So without further delay, and with apologies for how long this intro took,

00:11:34.800 welcome to this episode with Mr. Dave Feldman.

00:11:40.840 Hey Dave, welcome to San Diego.

00:11:42.880 Thanks for having me, Peter.

00:11:44.360 You're here for a conference, is that correct?

00:11:46.980 That's right, Low Carb USA.

00:11:48.960 Got it, that would explain all of the low carb folks that seem to be in town this weekend.

00:11:54.540 How many are going to end up showing up here?

00:11:56.320 None. I'm actually leaving very early tomorrow to go to New York, so I will be missing this.

00:12:04.240 I'm either deeply honored or very scared right now.

00:12:08.140 No, I actually was going to try to talk to one other person too, but they bailed on me and took

00:12:12.600 a better offer. This is going to be a bit of a different episode, Dave, in the sense that I think

00:12:18.520 this will be, even by the standards of this podcast, perhaps a bit more technical at times.

00:12:23.360 And I think this will probably be a podcast where you and I have already spoken offline.

00:12:28.340 I suspect a lot of what we discuss will need to be included in show notes because

00:12:32.380 there's just going to be so much visual stuff. There's so much data we're going to be talking

00:12:36.140 about. And some of it's just quite graphical in nature, which is not to be confused with graphic.

00:12:40.660 We will apologize in advance that this might be one of those shows when you're going to probably

00:12:45.680 get the most out of it sitting in front of your computer. But nevertheless, hopefully we can

00:12:51.440 certainly get some interesting stuff out of the way. I've been trying to think about how to set

00:12:54.440 the stage for this because I think it's safe to say many people listening to this don't know who

00:12:59.000 you are and don't know what we're going to be talking about or why we're even having this

00:13:02.600 discussion. So I'm going to take a small liberty of trying to synthesize some of what I've heard you

00:13:09.920 say in the past, but then turn it over to you to clarify it and kind of put it in context.

00:13:14.860 From my standpoint, I think you're one of the more thoughtful people on what I would call the

00:13:22.080 LDL is not necessarily causal and heart disease camp. And so certainly there's a number of people

00:13:28.680 out there for various different reasons who have argued that the causality of low density lipoprotein

00:13:35.020 and atherosclerosis is not a foregone conclusion. And in fact, there may be a subset of people in whom

00:13:40.660 it's not quite relevant. And what you and I have done over the years is had email exchanges and

00:13:47.220 things like that. And you've been very curious. You've done a lot of self-experimentation, which

00:13:52.540 you won't find a more sympathetic audience for self-experimentation than me. And I think in large

00:13:58.360 part, we want to kind of explore some of the deep lipidology around these ideas, but ultimately it

00:14:03.760 comes back to a question. And this is, I think, the question that at least if I'm going to be selfish

00:14:08.720 is the question I care about, which is today I have to make a decision. And I mean that literally.

00:14:14.880 So meaning at five o'clock this morning, I had a call with a patient. Luckily he was in a different

00:14:19.220 time zone, but we had to make a decision about his lipids. And I will have three more interactions

00:14:24.920 with patients today of which two will center around the same discussion. So ultimately decisions

00:14:30.780 have to be made about how to manage dyslipidemia. And most decisions have to be made with incomplete

00:14:37.120 information. So I certainly don't have any expectation that we will emerge from this discussion

00:14:42.700 knowing an answer, but nevertheless, hopefully we'll have clarified a few things. So

00:14:47.560 before I go any further, Dave, if someone were asking you, what are you known for with respect to

00:14:56.280 this? So you can probably juggle five tennis balls simultaneously or something else, but with respect

00:15:00.700 to this discussion, how does the low carb community kind of describe you?

00:15:04.760 Well, in many of them right now would describe me as a lipid expert. The irony is that I actually

00:15:10.680 push off that reputation to some degree. I'm not a formally trained biochemist. I'm not a medical

00:15:16.900 professional. I regularly feel like I need to emphasize that. In fact, I, I think that your series

00:15:24.740 straight dope on cholesterol was probably a way for a lot of people, myself included to kind of short

00:15:31.560 circuit a lot of the formal education that typically one would have to go through, through university to

00:15:36.720 get to really the general concepts of lipoproteins and how they work within the system. And so what got

00:15:43.920 me to this place going a little bit backward is that I went on a low carb diet. And now this story is

00:15:51.340 fairly ubiquitous. You hear it a lot. A number of people, myself included, saw their cholesterol rise

00:15:56.480 substantially. After that happened, yes, per what you just talked about, I started doing enormous

00:16:01.980 amounts of self-experimentation and I started elucidating a pattern. And part of what motivated

00:16:08.260 me to do that was that even though I had very little training on the medical side, I did have a lot on the

00:16:15.300 network side as a software engineer. And I saw a pattern that looked very familiar to me. And without

00:16:23.480 getting into a lot of geeky terminology, if there happens to be any software engineers listening,

00:16:28.720 you'll probably be familiar with this term. It's called dependency injection. And it's something that

00:16:33.740 gets involved with networks of distributed objects. And I saw that with lipoproteins, which you talk

00:16:40.100 about at length in the straight dope on cholesterol. And if I can, by the way, interject just this one

00:16:45.120 thing. Thank you for making that serious. I know I'm not the only person listening right now who would

00:16:50.700 say that it really was kind of a light during a very dark time. And so from that, kind of this whole

00:16:58.040 journey began. And weirdly, I went from being a fairly well-paid software engineer to kind of a poor

00:17:04.360 end of a one scientist, definitely tackling just exactly how far I could take moving around my

00:17:10.940 cholesterol. And I'm going to make an outrageous claim. I couldn't do it this week because I have

00:17:15.660 too many things going on. But I had always fantasized about the possibility of having a

00:17:19.660 conversation with you and given where I'm at on the research now saying, I would like you to write

00:17:23.420 down a number between 100 and 350. And then once you do, in about a week's time, I'm going to move

00:17:29.120 my LDL-C cholesterol to that number plus or minus 20 milligrams per deciliter. And I think that would

00:17:34.760 have been a lot of fun. And maybe we'll get a chance to do that in the future. But the bottom

00:17:38.760 line is, I feel as if I've come across enough with my own mapping of my own metabolism that I found how

00:17:44.940 I can move LDL cholesterol and LDL particle count up and down without medication or supplements by

00:17:51.940 finding what I believe to be the primary influencer, which is the energy metabolism,

00:17:58.060 especially that of fatty acid utilization for energy.

00:18:03.140 Okay. I think the other thing we'll want to make sure listeners have done by this point,

00:18:07.560 if they want to get really deep on the understanding of this, is probably go back and listen to

00:18:13.000 at least one, but potentially two or three of the other podcasts you've been on. You've been

00:18:19.480 interviewed a number of times. I've had the privilege of listening to several of them,

00:18:23.840 which is what helped me get more up to speed on some of your arguments. And I think rather than

00:18:31.520 just spend an hour going over those again here, I'd rather we sort of get to it more quickly,

00:18:36.740 which we will, and then let the listener go back and get that way of background.

00:18:40.820 So with that said, let's talk a little bit about your story. So before you went on a low carbohydrate

00:18:48.140 diet, you probably had a standard lipid panel. It probably showed what?

00:18:51.640 I believe the very last one that I had was typical of what I'd usually had gotten,

00:18:56.340 which is my total cholesterol. I believe it was 186. My LDL-C was 131. My HDL was 40.

00:19:08.360 And my triglycerides were 80.

00:19:10.540 Obviously people who have heard me talk about this before will know that that tells us

00:19:14.700 virtually nothing. Your total cholesterol is of no interest. Your LDL cholesterol of 131,

00:19:21.040 by the Framingham puts you a little over the 50th percentile. Your HDL cholesterol of 40 puts you

00:19:26.600 quite a bit below that actually. And your trigs of 80 in someone who's Caucasian doesn't give us a

00:19:32.660 great insight, gives us even less insight if you're African-American, but your trig to HDL ratio of about

00:19:38.640 two would be considered acceptable by most. Most people would even consider up to three acceptable.

00:19:44.900 So we would have no way of knowing from this what your LDL particle number would be,

00:19:51.260 or your APOB, which would be better predictors of your risk than any of these numbers here.

00:19:56.460 But nevertheless, this is what everybody gets, right? This is sort of the standard test.

00:20:00.400 Yes. And in fact, anybody who's ever considered going on a low carb diet,

00:20:03.500 it's one of the first things I jump on. As I say, do me a favor and take a particle count test

00:20:08.800 before you start the diet? Because I think a lot of us would be very interested to know what

00:20:13.280 particle counts are before people start the diets. It may actually hold keys to understanding what's

00:20:18.480 going on with what, I'm not sure if it was you or Tom Dayspring, I think one of the two of you

00:20:22.980 first started using the term hyper responder to elucidate those people who going on a low carb diet,

00:20:29.500 see their cholesterol go high, not just their LDL-C, but their particle count.

00:20:33.400 Yeah, I think Tom would deserve the credit for that. In fact, it'll probably come up many times

00:20:39.680 throughout this discussion and we'll certainly link to it. Tom wrote a really fantastic piece on

00:20:45.680 this in his Lipaholics series. I think it was in 2013, might've been 2014, but it was following

00:20:53.320 a number of cases that he and I had shared back and forth about this phenomenon. I would add something

00:20:59.540 else, Dave, if you're going to make a request that people draw the advanced lipid panels before,

00:21:06.040 the other thing that is essential is that they get a sterile panel. And that's not to be confused

00:21:11.060 with sterile like, you know, IL, it's sterile OL. And the reason for that is that there are basically

00:21:19.800 four things that are moving LDL particle number. And when I sit down with patients and talk about this,

00:21:26.060 we always start from this place, which is what moves the LDL-C? Well, three things that move it

00:21:32.360 are generally cargo related and one is generally clearance related. So the two things that move

00:21:39.480 at the macro level, the cargo is the amount of triglyceride it's carrying and the amount of

00:21:43.700 cholesterol it's carrying or to be more specific cholesterol ester. So to get a sense of what its

00:21:49.700 triglyceride burden is, you can get a crude sense from looking at the serum triglyceride level,

00:21:54.720 although there are no commercially available tests to my knowledge that actually measure the

00:21:59.380 triglyceride content of an LDL particle. At the research level that's been done, and I have some

00:22:04.400 data on a self-experiment I did in 2012, where we tracked the movement of cholesterol ester and

00:22:09.840 triglyceride through all of my lipoproteins, including chylomicrons. And if it becomes relevant,

00:22:14.540 we'll certainly go over that. I think you'll find it super interesting.

00:22:17.560 Yeah. And I think it's worth stratifying that just for a moment for the audience.

00:22:20.520 What you're referring to is if we do a blood test for triglycerides, that's inventory of all

00:22:26.560 lipoproteins. So we're not actually gathering it on a per-lipoprotein base. And this is what you're

00:22:30.980 saying is this test will help, or at least what we're trying to elucidate is exactly what it is

00:22:36.020 on total triglycerides. The blood test tells us nothing about the triglyceride burden within the

00:22:40.700 lipoprotein directly, but we know that that's one of the cargoes. And as a general rule, the more we see

00:22:45.820 the triglyceride go up, the more we know we need particles disproportionate to their cholesterol

00:22:51.080 content to traffic them. The next two things we look at that are also quote unquote cargo related

00:22:56.980 is the synthesis of cholesterol. It turns out we can measure that quite well. And we measure that by

00:23:02.580 using a number of molecules, but most commonly a molecule called desmosterol, which is the penultimate

00:23:09.660 molecule in one of the cholesterol synthetic pathways. So cholesterol synthesis begins,

00:23:15.620 as you know, with the creation of a molecule from two molecules of acetyl-CoA. And many,

00:23:21.600 many steps later, I believe it's north of 30. Yeah, it's 30. You'll have this pathway where you'll go

00:23:27.200 from desmosterol into cholesterol. So when we measure the desmosterol level, especially when we

00:23:33.460 measure changes in it, absent any other drugs, because there are some drugs that can interfere

00:23:38.240 with the conversion of desmosterol to cholesterol. But we get a sense of what the synthetic function

00:23:44.440 looks like. And so there are some people that are hypersynthesizers. There are some people that

00:23:48.240 have normal degrees of synthesis. And there are some people that actually synthesize a relatively low

00:23:52.500 amount. The third thing we look at are phytosterols. So these are plant-based sterols, which means we

00:23:58.840 can't make them. But by measuring them, we get a clever insight into how cholesterol may be

00:24:06.340 recirculated in the body. So again, I know you know all this stuff, Dave, but I think for the

00:24:11.380 listener, it's important for them to get a little brush up on this stuff. Most of the cholesterol in

00:24:16.160 our body is endogenous, meaning we made it and then we recirculate it. Maybe about 15% is

00:24:23.320 exogenous, maybe less. It would depend on a number of other factors. But the majority of the cholesterol

00:24:27.600 that you eat, and every once in a while you see a funny case study, and there was one this week about,

00:24:32.100 you know, guy eats 30 eggs a day and has low cholesterol. How is this possible? It's sort of

00:24:37.020 an idiotic discussion that I can't believe we're still having. Even Ancel Keys noted this a million

00:24:41.300 years ago. Dietary cholesterol plays a very trivial role in the circulating cholesterol pool because it

00:24:48.280 has esterified side chains that can't be absorbed. Nevertheless, you make all this cholesterol, we'll talk

00:24:52.800 about in detail, I'm sure, how it's trafficked. It comes back to the liver. A portion of that is

00:24:58.980 secreted through biliary means. And now that biliary cholesterol, along with phytosterols,

00:25:05.500 are brought in through this Neiman-PICC1-like1 transporter into the enterocyte where the LXR

00:25:10.700 gene basically tries to regulate how much of this stuff do you need. And if it's doing its job

00:25:17.140 correctly, it jettisons out anything excess through this ATP binding cassette, G5, G8. Of course,

00:25:23.840 there are people that have deficiencies in all of these things that can lead to hypercholesterolemia.

00:25:27.700 And in theory, the system should balance itself out. People who are very high synthesizers

00:25:34.420 tend to compensate by being low absorbers and vice versa. So the long-winded soliloquy was for a

00:25:41.360 reason. It's not only important to get the lipid and lipoprotein numbers, but it also helps to know

00:25:48.460 those three things at baseline, one of which you get for free. You're going to at least get a benchmark

00:25:52.480 of your triglyceride, but to also know your levels of desmosterol, which would be your proxy for

00:25:57.960 synthesis, your levels of cytosterol, cholinstanol, cytosterol. These things are phytosterols, meaning

00:26:04.480 we can't make them. So the higher they are, the more we know we're absorbing sterol.

00:26:09.020 The fourth thing that regulates LDLP. So again, it's triglyceride burden, cholesterol synthesis,

00:26:15.020 cholesterol reabsorption. The fourth thing is LDL clearance.

00:26:17.180 Now, that is not as static as people would like to believe. It's probably not even as static as I

00:26:25.080 used to believe. I used to believe that it was sort of genetically determined what your LDL

00:26:28.840 clearance would be. And obviously there's a great variability there. We see it all over,

00:26:34.240 but it turns out that that is highly regulated at the level of the liver. So even though we can use a

00:26:40.360 drug to demonstrate the variability of it, a statin being the most obvious example, statins are

00:26:46.400 specifically designed to increase LDL clearance from the liver by decreasing liver synthesis of

00:26:52.200 cholesterol. Other changes in cholesterol concentration throughout the body, probably

00:26:56.920 the burden of reverse cholesterol transport and other things will also impact that clearance. And

00:27:01.420 the majority of LDL of course is cleared hepatically. So we don't have an assay for that. So this is the

00:27:08.460 one where I always have to say to patients, the only way I can really figure out if your LDL piece

00:27:13.280 is skyrocketed because of defective clearance, which would, by the way, have to be a new onset

00:27:19.000 of defective clearance, is if the other three things don't change. Or if they get better, meaning

00:27:24.600 they all, I hate to use the term better or worse actually, because it's, this is really, they're

00:27:28.840 neither better nor worse. It's, they just are what they are, right? But if the synthesis goes down,

00:27:33.540 the absorption goes down, the trigs are largely unchanged and the LDL goes up, the LDL-P goes up,

00:27:38.500 then you know clearance has gone down. So most of the time you can't actually measure that unless

00:27:44.040 you get lucky. And by measure, I mean sort of impute. So anyway, this is helpful and I suspect

00:27:49.640 this will offer an alternative hypothesis to sort of what we're seeing. But anyway, I apologize. I'm

00:27:55.940 talking more than I should be. For what it's worth, what you just mentioned, I, I myself have not

00:27:59.960 gotten a sterile test. I haven't actually broken down these, but I've been particularly interested in

00:28:04.900 this. And for what it's worth, I've been looking forward to this because I think I may actually be

00:28:09.500 just the stealth interviewer in the room because I think it's just as possible. I may be asking you

00:28:13.640 more questions than you're asking me. I do want to add one thing to what you were just talking about

00:28:18.460 on a lot of people go on a low carb diet and they know they're bringing up their total amount of

00:28:23.620 dietary cholesterol who then see a likewise increase in their serum cholesterol, the cholesterol in the

00:28:30.140 blood naturally, because it's intuitive, come to the conclusion that must be because I am a

00:28:35.840 hyper absorber. I must be absorbing more cholesterol. And I think in the course of this conversation,

00:28:40.680 this will help illustrate another reason why that may be the case, because you may in fact be

00:28:45.300 trafficking more fat as energy and therefore it may be ride sharing with cholesterol in these lipoproteins.

00:28:51.760 Yeah, I think the terminology is going to be confusing. So when we talk about hyper absorbers,

00:28:58.640 we're referring very specifically to this mechanism about the, this Neiman peak C1 like one transporter

00:29:05.100 in the ATP binding cassette, which is called, it's usually referred to as ABC G5 G8. But as you said,

00:29:12.320 that person who says, Hey Dave, I just went on a low carb diet and I'm, you know, I'm eating more eggs

00:29:16.700 and more this and more that. And my cholesterol has gone up. Well, the problem with that is it's like

00:29:20.320 wrong on many levels, right? We should never be talking broadly or vaguely about cholesterol.

00:29:24.900 What went up specifically, right? Did LDL cholesterol go up? Did LDL particle number

00:29:29.640 go up? Did total cholesterol go up, et cetera. But it's quite likely that those two things are

00:29:35.280 not causal, meaning the person who's increasing their consumption of dietary or exogenous cholesterol

00:29:41.880 is also usually increasing their consumption of dietary fats. Absolutely. And as we'll talk about

00:29:48.200 later, I'm sure one of those subtypes of fats in a subset of susceptible individual seems to set off

00:29:55.240 a hypersynthetic pathway for cholesterol, which when we get to it, I want to share with you my data set on

00:30:03.240 hyper responders, meaning these patients, which is what is the pattern of hyper response?

00:30:08.620 Because not everyone has this experience where they go on a ketogenic diet and their LDL skyrockets.

00:30:13.420 I didn't have that experience, but I have the privilege of getting to see the blood of

00:30:18.040 tens, if not hundreds of people over the past few years. So I get to see, oh, sometimes this happens.

00:30:23.620 Sometimes it doesn't. What else is going on here? So what year did all this start for you?

00:30:28.860 In April of 2015 was where I got my second A1C of 6.1, which is a hemoglobin test, which suggests that

00:30:36.220 I'm pre-diabetic. And that was with a triglyceride of 80?

00:30:38.920 Yes, actually that's correct. That was the very last time. That was that same test.

00:30:42.260 So when I saw that, I then immediately felt compelled to go and learn everything I could

00:30:49.460 on how to change my blood glucose levels, because also I had a fasting glucose, if I want to say

00:30:56.660 like 103. And at the doctor's office, they said, well, yeah, this is the second year in the row,

00:31:02.200 but we'll keep monitoring it. And I said, well, no, thanks. I'm going to start trying to figure out

00:31:07.020 what it is I can do to dodge type two diabetes because it's rampant on my dad's side of the family.

00:31:11.700 And so I started to go to diabetic forums, diabetic forums. They were talking about this LCHF

00:31:19.400 diet, which I would then find out as a low carb, high fat diet. I would then look a little bit

00:31:24.760 further. I found out about the ketogenic diet and it all sounded very interesting. And I remember at

00:31:29.160 that time asking on the forum saying, okay, now wait a sec, how can I be sure my cholesterol won't go

00:31:35.980 up? And at the time the common answer was, well, it only happens for a few people. And even then it's

00:31:41.520 complicated, but it's really probably not a problem. And there wasn't really a very solid

00:31:46.240 answer to it, but I felt at least confident enough that it was unlikely to happen to me.

00:31:51.960 And therefore I would go ahead and take the shot because my cholesterol numbers were generally

00:31:56.100 pretty good. I did like hearing that it typically raised HDL. And that was the one thing my doctor

00:32:01.200 would occasionally ping me for. He'd say, I'd like it if your HDL was a little bit higher.

00:32:05.580 So after I started, both my dad and my sister got enticed to do it as well. My dad's type 2

00:32:12.160 diabetic. His last day once he was like 8.3. My sister's not diabetic, but was hypertensive.

00:32:19.420 They both get inspired. They end up going on the diet. To this day, now my dad's in the five nines,

00:32:24.980 something along those lines. And my sister's no longer hypertensive when she's staying on the diet

00:32:28.940 fairly well. The two of them get their cholesterol test before I do, after they started the diet

00:32:34.020 around the same time. And both of them, I warned them in advance that their LDL cholesterol might

00:32:38.740 bump a little. And sure enough, that is what happened to both of them, but it wasn't that

00:32:42.280 concerning. I get mine a little bit later, about seven and a half months later, and mine skyrockets.

00:32:47.520 So this is like late 2015?

00:32:49.400 Correct. So November 2015, I believe my total cholesterol was 329.

00:32:53.860 My LDL-C was 200 and I want to say 250. I can't remember. Somewhere around there.

00:33:01.920 And that was a very cathartic moment for me, at least as far as I'm looking at the lab work. I'm

00:33:07.560 going, what the heck happened? How did I get to this place? And for two very miserable weeks,

00:33:14.440 I found this guy, Peter Atiyah, who happened to already have a lot of data and a lot of a great

00:33:20.600 series. I engulfed your series, but I could hardly understand it at the time. And I started

00:33:25.280 reading up on Thomas Dayspring. I found Tara Dahl. I started looking at just anybody and everybody who

00:33:31.020 could say anything about lipids. And in the course of doing it, that's when I started seeing this

00:33:35.060 pattern, as I started tweaking a little bit into clinical lipidology, the book.

00:33:39.920 When you say the pattern, just to be clear, the increase in LDL cholesterol on the presence of a

00:33:45.300 low carbohydrate, high fat diet. No, I actually mean it being a network.

00:33:50.520 Okay. So say more about that. Lipoproteins are a boat. This is going to be one-on-one,

00:33:54.960 but let's kind of do that for the listener for a second. They're lipid carrying proteins. And so

00:34:00.180 your body makes them and they make them at numbers we can't even imagine. They're measured in

00:34:05.440 quintillions, which is like a million trillions. And it's doing this both in the gut and in the liver.

00:34:12.120 And when they make it, they're basically packing in lipids that the cells need. And in particular,

00:34:18.200 they pack just about every kind of lipid, not just triglycerides, which your body uses for energy,

00:34:23.780 but also cholesterol, which we're going to be talking about a lot, but also fat soluble vitamins

00:34:28.080 like A, D, E, and K. And it packs all of these, the same container. But what's neat about it

00:34:33.920 is this boat, in order for it to get to the cells that want to make use of it, need to have a complex

00:34:39.660 system in place so that they can kind of special order what it is that they want to take off of

00:34:44.820 these lipoproteins. And that's where it gets interesting because the lipoproteins have these

00:34:49.040 kind of snaky bumps on the top of them that are proteins that are the apolipoproteins.

00:34:55.220 And hopefully we don't have to get too technical for the audience on that, but of course I'll

00:34:58.700 appreciate it if we can.

00:35:00.320 I think we're going to have to.

00:35:01.560 Yeah, we're probably going to have to, but it's those apolipoproteins that you could relate

00:35:06.620 on a computer side to metadata, to headers, for example, as far as where it is that they're

00:35:12.820 going to go and why. And what excited me about, as I was learning about this, I was like, I

00:35:18.380 don't know how much of this I'm projecting my own experience as a software developer, but

00:35:22.840 this looks like a very complex series of distributed objects that clearly, if I'm looking at it from

00:35:31.040 a payload perspective, is primarily an energy distribution network. It appears as if it's

00:35:36.500 primary job, more than any other job, particularly chylomicrons and VLDLs, are to deliver this

00:35:43.640 fat-based energy to tissues. That's what they go out with, and that's what they come back

00:35:48.800 typically not with, coming back to the liver. And because almost everything ends up coming

00:35:54.700 back to the liver, this looks like it's a central regulator. And in that sense, this looks,

00:35:59.320 I mean, in many respects, it has many attributes common to what we would call in software as a

00:36:05.760 cloud network, something we use a lot. And it's very important to be able to do things

00:36:09.600 at scale, but particularly with the level of interaction that goes on with the lipoproteins

00:36:14.120 between each other. It's not like these boats go out autonomously and never have any interaction

00:36:19.100 beyond just going to dock and dropping off their different cargo. They actually constantly

00:36:25.100 connect with each other through things like cholesterol ester transfer protein, phospholipid

00:36:29.660 transfer protein, and so forth. These are different ways in which they, in the process of moving

00:36:34.500 through the bloodstream, actually have further interactions that move around the total pool

00:36:40.160 that's being used by the entire system. And hopefully I didn't get too technical there,

00:36:45.220 but you get the sense of it. In many ways, this has a lot of overlap with techniques that we use

00:36:49.860 right now and how we build networks out of servers.

00:36:52.560 So I think we do need to get pretty technical on this because I suspect that you and I will draw

00:37:00.160 different conclusions from the data. And in my experience, the easiest way to understand where

00:37:05.980 those differences lie is to sort of start to get into some of the things that we would view

00:37:11.620 differently. So I'll start with one thing that you said. So I like to be, I think, maybe clear on

00:37:17.960 where I believe the chylomicron, the VLDL, the IDL, and the LDL are coming from, going, and what

00:37:22.620 they're doing. Now, we can't actually know for certain any of these things. I've had some very

00:37:27.920 interesting discussions with people about this over the years. And I mean, I've had one of the

00:37:31.780 most brilliant lipidologists I've ever spoke to said, why do we have LDL? To which the answer is,

00:37:37.400 it's just God's cruel trick on our species because most other species don't have the LDL burden we

00:37:42.840 have. I think a more thoughtful answer though is the overwhelming burden of evidence is that the

00:37:48.080 purpose of LDL is to carry out reverse cholesterol transport. You alluded to this already. You basically

00:37:53.120 have these three different lineages. This is a bit of an oversimplification of lipoproteins.

00:37:57.200 You have these chylomicrons, which as you said, are primarily getting fat from the gut and very

00:38:05.040 rapidly undergoing a process of hydrolyzing themselves and releasing through an apolipoprotein

00:38:10.580 called ApoC2, all of their triglyceride through interaction with something called lipoprotein lipase.

00:38:17.120 So we have this rapid chemical reaction that very quickly gets rid of these incoming dietary

00:38:23.620 and sometimes non-dietary because I want to be clear that we can't really distinguish exogenous

00:38:29.380 and endogenous fat in that pool because you're going through that same recirculating process.

00:38:33.700 But at the risk of oversimplifying, fat comes in the body. If you're on a high fat diet,

00:38:38.780 you're eating fat, it's coming in the gut. The chylomicron, which is its own little lineage

00:38:43.420 because it has a different apolipoprotein. So it has this thing called ApoB48, as you know,

00:38:47.180 that comes in and then the ApoC2 interacting with the LPL is what's extracting that.

00:38:53.640 Oh yeah, great. Dave just whipped up a great picture. So we're going to link to all this

00:38:57.820 stuff. Yeah. So Dave, if you can make a note of this one and then that way when we're making the

00:39:01.580 show notes, we'll link all that stuff. Okay. Then you have another path we're not going to talk

00:39:07.440 about much today, which is the HDL path. Totally different. These particles last much longer.

00:39:11.940 They are primarily responsible for reverse cholesterol transport of which there are two

00:39:17.200 types. Reverse cholesterol transport means taking cholesterol from the periphery back to the liver

00:39:21.840 that can occur directly, which is when the HDL brings cholesterol itself back from another tissue

00:39:28.900 to the liver. And the most important place it does this is from the subendothelial space.

00:39:33.080 So if you have oxidized sterols waiting to cause atherosclerosis, the HDL can actually go and

00:39:39.440 through another one of those ATP binding cassettes. It can delipidate the HDL, the sterol, take it right

00:39:45.180 back to the liver. That's direct RCT. But there's also indirect RCT, which is the LDL can bring

00:39:52.940 cholesterol back, can give cholesterol to the HDL through CTEP as you alluded to. And that goes.

00:39:59.120 The other way, right? Like you mean HDL actually taking the cholesterol and giving it to the LDL to

00:40:03.600 take back to the liver? No, the, well, actually both. So LDL gives to HDL to go back to the liver.

00:40:08.580 Oh, I see what you're saying. Yeah, yeah, through CTEP. So that's indirect RCT. But it's that VLDL

00:40:14.500 to IDL to LDL path that is governed by these ApoB, like their lineage is described by ApoB 100,

00:40:21.360 which differentiates them. Now, one of the things I didn't learn until recently,

00:40:27.520 and I don't know if this is accounted for in the model, because the figure that we're going to link

00:40:31.600 to is not actually showing that, is that about 40% of LDL comes directly from the liver.

00:40:37.360 It's de novo created. Right. Tom Dave Spring linked me to the study that I'd since read on

00:40:43.060 this one. Really. Which one? Is this the Frank Sachs? I don't remember. I don't remember the

00:40:47.040 authors. They get into the different subspecies of ApoC3s and ApoE and how they counterbalance each

00:40:53.520 other as far as degree of affinity for clearance and so forth. Yeah, that's sort of, I mean, I wouldn't

00:40:58.920 say it's unrelated. This stuff's all related. So we'll park this topic because it's super interesting.

00:41:03.980 But when these lipoproteins have ApoE on them, which is pretty unusual, it's about two to five

00:41:10.720 percent if my memory serves me correctly. We'll fact check that. It might be different. But a very

00:41:14.880 small number of these ApoB 100s are carrying ApoE. And when they do, they actually have much

00:41:19.900 more rapid clearance. As in having ApoE only and not having ApoC3? Well, that's actually a good

00:41:25.440 question. ApoC3 is clearly the worst actor you could have here. There's nothing worse than having

00:41:29.660 an ApoC3 sitting on your ApoB 100 cell. In fact, some would argue that may be the single worst thing

00:41:36.740 you could ever have happen because it increases the residence time of them. So we're going to come

00:41:41.460 to this, I know, because you've written about remnants. I'm going to argue that we have no way

00:41:45.540 of knowing what a remnant is without being able to measure ApoC3. Because when we look at a VLDL

00:41:52.200 cholesterol, and I apologize to the listener, I swear we'll get back to our main point here.

00:41:56.040 Unless we actually know something more than just how much cholesterol is in VLDL, we have no way

00:42:02.100 of knowing whether it's an appropriate remnant, what we call a physiologic remnant, or a pathologic

00:42:06.520 remnant. And the pathologic remnants disproportionately carry ApoC3, which increases their residence

00:42:11.660 time. And the same is true on LDL. I do want to follow up on that point.

00:42:15.020 Yes, yes, yes. We absolutely will. Because it's such an important point. And to me, it's one of the two

00:42:20.140 most interesting clinical assays I'd like to see developed. I would love to see a clinical assay for ApoC3.

00:42:24.800 And for LDL triglyceride concentration, which goes back to a point we had a few minutes ago.

00:42:31.240 And for anybody listening who's developing that assay, please reach out to me. Because for all

00:42:35.880 the self-experimentation I do, I mean, one of the things I didn't mention is that I literally just

00:42:40.680 did my 100th blood draw last Tuesday. I've obviously done enormous amounts of self-testing to do this.

00:42:46.280 And that's exactly one of the things I want to check is how dynamic or not dynamic the distribution

00:42:52.540 of things like ApoC3 are based on, for example, existing illness or the energy distribution and

00:42:59.300 so forth. So anyway, I realize we're kind of getting in the weeds here.

00:43:02.340 Yeah, I mean, you should have a low level of C3 because your insulin levels are quite low. So C3 tends

00:43:09.440 to move with insulin. So this may be one of the things that explains why someone with type 2 diabetes

00:43:16.380 who is hyperinsulinemic will, on a particle-for-particle basis, maybe even have a greater

00:43:23.340 burden of the lipoprotein because the actual residence time of each of their particles,

00:43:27.560 both VLDL and LDL, is longer than someone with lower insulin.

00:43:31.480 So you have this de novo creation of VLDLs and you have this de novo creation of LDLs and they form

00:43:40.760 this circulating pool. But to my knowledge, we can't really differentiate those when we look at

00:43:45.360 that snapshot. I can't tell, is that an LDL that came from a VLDL or is that an LDL that came straight

00:43:52.060 from the liver in that form? And that was actually one of the questions I had for you, was how with a

00:43:57.900 kinetics study, can you actually determine if an ApoB100 lipoprotein that was secreted by the liver

00:44:05.620 ever has, say, an ApoC2 on it? I think you and I would probably be in agreement that we don't know.

00:44:12.600 We don't have any clinical way to measure that.

00:44:15.120 Right. And in that sense, I fully concede that I can't be sure, even with the energy model,

00:44:20.220 that the LDL particles that I'm seeing, the LDL-P, that I can say with any level of real confidence,

00:44:26.860 how many of the total proportion of those were truly for energy delivery?

00:44:32.400 So I would argue that depends, this is where we get into the semantics. I would argue none of them

00:44:38.160 are for energy delivery because that's not what LDL does. But I think what you mean is how many of

00:44:42.980 them came from VLDLs that were trying to deliver energy?

00:44:46.200 Right. Originated as VLDLs for the purpose of doing it. If the job of your, in the morning,

00:44:52.820 let's say that your job is to deliver pizzas.

00:44:54.660 Right. And that's your job. And you know what? It only takes you about an hour to do.

00:44:58.240 And then guess what? The rest of the next two to four days, you're actually going to be patrolling

00:45:03.600 the neighborhood. You're the neighborhood watch. And you're going around. You're also helping to

00:45:07.540 fix up people's houses or something along those lines. Somebody who comes into the neighborhood

00:45:12.120 and sees a whole bunch of these cars patrolling, they don't know how many of those people actually

00:45:16.900 delivered pizzas before they got started on that part of the shift. And that's basically what

00:45:20.780 we're both coming to, right? We don't actually know how many people left the liver, how many

00:45:25.340 VLDLs left the liver.

00:45:26.840 Well, we sort of know. I mean, we know that if, I mean, what Frank Sack's paper showed is if you

00:45:31.220 take patients with low triglycerides, and I believe he used a cutoff of 130 milligrams per deciliter,

00:45:36.480 38% were de novo secreted by the liver. 62% came from either IDL or VLDL, where you had de novo.

00:45:46.860 I don't think the paper differentiated between which ones went IDL to LDL versus VLDL to IDL to LDL.

00:45:53.460 So that's an important point. The second thing is the half-life, I actually had to go back and look

00:45:59.420 at these kinetics because I did a podcast with Ron Krauss, as you know. I mean, I don't remember when

00:46:05.100 we recorded it. I think it came out kind of recently. But he mentioned that LDL half-life

00:46:09.740 was a day. And I was like, I always thought it was longer than that.

00:46:12.600 The literature says two to four days.

00:46:14.060 No, actually, if you go back and look at the kinetics study, people are confusing half-life

00:46:17.240 with residence time. The half-life of an LDL particle is about a day. Now, it can be longer,

00:46:22.320 but that's a pathologic state, which gets back to this APOC3 thing.

00:46:26.080 That's interesting.

00:46:26.800 Yeah, you can have a pathologic state where LDLs will hang around longer. But if you look at the actual

00:46:31.780 kinetic studies, and Brown and Goldstein did this work, and this is part of the work,

00:46:36.080 I believe, that they won a Nobel Prize for, the kinetics of LDL are pretty well understood

00:46:40.240 using very elegant tracers. And we'll link to that paper because I actually had to go back and look

00:46:44.520 at it because I was surprised by Ron's answer when he said that the LDL particle half-life is really

00:46:49.300 only a day under non-pathologic states. But you're right. If I look at your LDL particles and I see

00:46:55.800 3,000 nanomole per liter, I do not know with absolute certainty how many of those your liver

00:47:01.620 made directly versus not. But again, assuming you're insulin sensitive, assuming you fit

00:47:06.120 Sachs' model of patient, that would suggest that roughly 40% of those were just de novo created.

00:47:13.420 And then of the remaining 60, some of those were from de novo IDL, and some came all the way through

00:47:18.200 the VLDL pathway.

00:47:19.860 So with that in mind, here's what I would speculate. And this is purely hypothetical,

00:47:24.400 but I would speculate if you were to grab a whole bunch of people who are, and we'll hopefully get

00:47:29.440 into this model that I'm talking about that I call lean mass hyper-responders. People are at the far

00:47:33.900 end of the spectrum. They are athletic, they are thin, and they are very, very low carb, and therefore

00:47:39.980 see very high levels of LDL-C and LDL-P, but they also have very high levels of HDL-C and low levels of

00:47:48.160 triglycerides. I suspect that they would show a very high rate proportionally of

00:47:54.360 VLDL secretion, that they actually are trafficking a lot more for their energy, triglycerides,

00:48:00.420 in VLDL particles, and therefore have succeeding LDL particles as to the explanation as to why

00:48:06.820 their LDL-C and LDL-P would be higher.

00:48:09.000 So let's use this as a moment, because I want to get into that in greater detail, but let's take

00:48:14.440 that step back and have you maybe just put a little bit more color on what you mean by

00:48:19.340 your lean mass hyper-responder phenotype.

00:48:22.600 For those people who go on a low-carb diet, some subset, and nobody seems to agree on this

00:48:27.720 because there's really not been any large study done on it. Some people will say it's 5%,

00:48:31.720 some will say it's 30%, will, like me, see that their LDL, their total cholesterol,

00:48:38.540 they will see both of those rise substantially.

00:48:39.800 Can I interrupt you for one sec?

00:48:40.840 Yeah.

00:48:41.220 Have the people at Virta Health released any of these data? Because they would probably have

00:48:45.720 the most rigorous database on this.

00:48:49.020 Here's a little bit of my qualification here. The problem that I have is, at least with what

00:48:54.500 we see at cholesterolcode.com, the blog that I have, we have lots and lots of hyper-responders

00:48:59.080 that send it in. There is seeming to be a higher proportionality of people who are lean and or fit,

00:49:05.600 who seem to be metabolically flexible. Virta, of course, its pool of participants, they had to

00:49:12.020 start out. I hope I don't get this wrong, but I believe that their BMI is at a much higher level

00:49:16.560 when they start.

00:49:17.440 Well, it's a company, obviously, that is dealing with patients with type 2 diabetes. So,

00:49:21.260 yes, they're not going to be disproportionately lean and fit to begin with.

00:49:25.240 Right.

00:49:25.440 So, you're saying that that basically wouldn't be the ideal pool to observe this phenomenon?

00:49:28.920 I would prefer a broader base.

00:49:30.640 Okay. All right. Sorry.

00:49:31.440 So, with that said, it's absolutely true. They've got some of the most pristine data. They

00:49:36.000 also have that data that I would be looking for where they get NMRs, for example, before

00:49:41.300 the participants start. So, that was nice, too. They're going to have so much great data

00:49:45.240 that comes out of that. But getting back to hyper-responders, per what you were talking

00:49:49.120 about before, this was what we called people, and this predates me, who would go on a low-carb

00:49:54.760 diet, would see their LDL cholesterol, their LDL particle count climb. And then there seemed

00:50:01.280 to be a subset, and I wrote about this about a year ago last month, of people who are on

00:50:07.320 the furthest end of the spectrum, actually tend to have the highest levels overall of

00:50:13.160 LDL cholesterol, but also have other things in common. This pattern is very distinctive.

00:50:19.260 They would have, say, an LDL of 200 or higher.

00:50:22.140 You mean LDL cholesterol?

00:50:23.320 Sorry. LDL cholesterol of 200 or higher. HDLC cholesterol of 80 or higher. And triglycerides

00:50:31.260 are 70 or lower. And this is so prominent to the extent to where I even did this kind

00:50:38.080 of recently at another conference. I called out another speaker to where I said, I'm very

00:50:42.160 interested in your lipid numbers because I think you might be a lean mass hyper-responder.

00:50:45.680 And she said, well, I hadn't actually taken it in years. And we tested it on the spot, and

00:50:50.680 it hit all of those points. Her LDL-C was 189, her HDL-C was 80, and her triglycerides

00:50:56.620 are 70. And this seems to, so far, span across all sorts of, for example, APOE types, APOE

00:51:04.380 3-3s and 2-3s, as well as the 3-4s and 4-4s. And we have not been able to identify any other

00:51:11.560 SNP or anything that's clearly associating this type.

00:51:15.080 Including the PPAR alpha and PPAR gamma?

00:51:18.440 That's one of the ones I wanted to follow up on, particularly since I heard your podcast

00:51:21.920 with Rhonda. And I had a bunch of people on Twitter just send me full body pictures for

00:51:26.640 me to use in this most recent speech I did on lean mass hyper-responders.

00:51:29.520 You have to be careful with that. You can get into trouble that way.

00:51:31.980 I did say, be sure to respond this tweet where I'm specifying exactly what I'd be using them

00:51:36.860 for. So anyway, generally speaking, they tend to be very fit. They tend to be very thin.

00:51:41.580 And oftentimes, and you kind of had a story of your own from before I even got into this,

00:51:47.160 they'll say, I really don't want to stop. I really love this way of life. I feel better

00:51:52.600 than I ever have in my life. And I give the same answer, not too far different from yours.

00:51:58.060 And then I say, okay, generally speaking, I feel like all of your markers look great,

00:52:04.720 low inflammation across the board. Of course, I give the standard, I'm not a medical doctor,

00:52:08.760 and this isn't medical advice, etc. But all that said, it's hard for me to come to the conclusion

00:52:14.120 that you're in trouble unless we can likewise see further markers such as expanding CIMT and CAC

00:52:20.140 and so forth. That's going to show that you actually are developing higher rates of atherosclerosis.

00:52:25.060 Now, I'll qualify in advance because I'm sure you'd want to say this as well. And I've mentioned

00:52:29.280 this to several people, things like atherosclerosis can develop without any sign for a fairly long

00:52:35.320 period of time. For example, I think it's what, 60% before you even see occlusion in the Lumina,

00:52:41.080 for example. Well, let's back up a little bit. So I always want to be careful that when people

00:52:45.620 are talking about CIMT and CAC, that we're never using those in the same terms as we would think

00:52:50.380 of biomarkers, right? So a biomarker, what you've described is, let's look at your LDL cholesterol or

00:52:55.480 better yet, your LDL particle number. But remember something, a CAC, which is a calcium score,

00:53:01.240 so it's a dry CT scan that very quickly scans over the heart and just picks up calcification,

00:53:05.200 no anatomic detail, or a CIMT, which is a type of ultrasound that looks at the intimal thickness.

00:53:11.240 So that's one of the walls of the artery's thickness in the carotid arteries in the neck.

00:53:16.120 These are both tests that are used to try to gauge advanced disease. So the real way to think about

00:53:22.640 this is to, and I think Ron and I talked about this at length in the podcast, is to look at a

00:53:27.640 pathology textbook. When you look at the autopsies, you'll get a sense of what's going on.

00:53:31.560 So long before you have luminal narrowing, which may or may not accompany a problem,

00:53:37.480 you have a very clear documented path of what this disease does. So again, I think you know this,

00:53:44.400 Dave, but I think for the listener, it is worth repeating this if they don't want to

00:53:47.600 go back and read some of the posts I've written on the progression of atherosclerosis.

00:53:53.200 When we're born, we have these beautiful arteries. The arteries have this endothelial lining. So this very

00:54:00.120 thin type of cell that coats the luminal, meaning the part that's closest to where the blood is

00:54:05.500 flowing. So there are spaces between these and via diffusion, lipoproteins get in there and out of

00:54:11.320 there all the time. This is relatively well understood to be a gradient phenomenon. So the

00:54:16.160 more of the lipoproteins you have, the more of them that are going to go in. But as we talked about

00:54:20.420 earlier, other things will influence it. The residence time, for example, which might be why this

00:54:24.900 APOC3 thing is such a pain in the butt, because if it allows these cells to stick around longer,

00:54:30.340 bad things happen. Now, what most people don't know, I think, is that an LDL particle is more

00:54:36.980 likely to come back out when it goes in there than it is to stay in there. That's good news. HDL

00:54:42.280 particles always come out of there. There are other types of particles. LP little a and pathologic

00:54:48.440 VLDL remnants can do the same thing as well. The problem occurs when proteoglycans bind to,

00:54:55.820 and let's just make math easy and not get into the LP little a's and the VLDLs at the moment. Let's

00:55:00.700 just talk about the LDL since that's the largest burden of this. But when these proteoglycans bind

00:55:05.960 to the LDL and it gets retained, all of a sudden now you have something that's where it's not supposed

00:55:12.300 to be. That's not where we want that thing. It's obviously in a high oxygen environment, so it's going

00:55:17.960 to undergo a chemical reaction called oxidation because it's carrying a cargo, a sterol, and by

00:55:24.720 the way, they can be carrying phytosterols and other things like that. But these things have

00:55:28.440 ample opportunity to undergo an oxidative reaction. It's that oxidative reaction that then kicks off

00:55:35.100 an inflammatory response in the endothelium. Now, the good news is today we at least have one

00:55:39.800 laboratory test that can measure that burden of oxidation. It's called the OXLDL assay. Now,

00:55:44.420 this has been around for a while, but clinically we've only been using it for a couple

00:55:47.840 of years because it turns out some very small percentage of those LDLs, once they are oxidized,

00:55:55.100 escape back into the circulation. So by sampling those, we can track indirectly, hey, what's

00:56:02.800 the likelihood that oxidative damage is happening? So for me, this is one of the most important

00:56:07.420 metrics I look at because I want to spend some time later on going over some clinical cases.

00:56:11.840 I want to see some of the data on yours. I want to show you some of the data that will explain

00:56:15.820 maybe how I'm thinking about this. But this oxidized LDL, which is well-documented and described

00:56:22.120 in different quintiles, right, is giving you a small sample of what's going on. But for the listener,

00:56:27.640 it's important to understand that when you get a blood test, that's not telling you what's happening

00:56:32.040 in your artery. It's giving you probabilities of things that are largely stochastically governed that

00:56:39.700 are going on in your artery. And the ox LDL is no exception. Even though it's a beautiful marker,

00:56:45.200 it's still dependent on the idea that a subset of those oxidized sterols are now escaping.

00:56:52.520 Can I actually ask a little more on that one? So we already know that LDL particles,

00:56:58.000 specifically ApoB100 at the LDL stage, have alpha-tocopherol, I think is how I'm saying.

00:57:05.560 Basically, it's vitamin E, right, as part of the antioxidant defense system. Part of the purpose

00:57:11.820 of an LDL particle is to actually provide that as a means to battle reactive oxygen species, right?

00:57:18.380 I don't know about that. And if it were solely true, it would make me wonder why people with LDL

00:57:25.360 deficiencies wouldn't have deficiencies of those processes as well, whereas to the best of our

00:57:29.920 knowledge, they don't.

00:57:30.880 Because I've actually been wanting to get into this a lot more recently. And correct me if I'm wrong,

00:57:34.860 basically, there's a certain degree with which you've got vitamin E on board. On top of that,

00:57:38.960 you've got the potential of the phospholipid shell to become oxidized. If you get oxidized

00:57:44.180 phospholipids, that also can bring about the role of LP little a that can cleave off the oxidized

00:57:51.960 phospholipids. That's ultimately what LPPLA2 is, right?

00:57:54.940 Correct.

00:57:55.200 It's the enzyme that's ultimately involved and helping to. And this is also, I don't know how much of this

00:58:00.620 is actually demonstrated, but as ultimately where a lot of the concept behind why it is,

00:58:05.600 you would have a higher detection of small lipoproteins, particularly small LDLs can come

00:58:11.940 around to is if you're getting them constantly oxidized and having to constantly cleave them

00:58:15.580 down to much smaller amounts, and then they constantly remodel.

00:58:18.400 Yeah, but we're getting off into two different things here. So let's come back to this. It's not

00:58:22.680 clear to me that there's sufficient evidence to suggest that part of the role of LDL is to combat the

00:58:28.100 oxidative stress.

00:58:29.440 Okay. Let's put that as homework that we'll catch up on after this. But this is relevant for whether

00:58:34.000 or not we're detecting oxidized LDLs that had never entered the intima, right?

00:58:39.200 No. The oxidized LDLs that we're detecting have escaped the intima.

00:58:44.220 Interesting.

00:58:44.560 There's a very small subset that are getting out.

00:58:46.840 Okay. That's definitely something I would like to follow up because I'm genuinely curious about

00:58:50.020 that myself as to whether or not they can be oxidized sufficiently that they'd get picked.

00:58:54.380 Because it also may be something that is part of the test or is no part of the test.

00:58:58.900 But I'd be curious as to how we can actually determine that.

00:59:01.700 Yeah. Meaning what you're basically asking is how do we know they weren't oxidized never inside

00:59:06.720 the subendothelial space? That's a fair question. I don't know the answer. I know very little about

00:59:11.180 this assay. I mean, I know the technical stuff of how the assay works. Like it's an ELISA assay.

00:59:15.160 I know what enzymes it's looking at. But the broader question is without a tracer,

00:59:20.720 do we know if that LDL has actually been in the subendothelial space where it was bound,

00:59:26.660 oxidized, and then escaped or liberated? So fair question.

00:59:30.460 It's certainly relevant to this larger question of the value of LDL particles as to whether they

00:59:35.420 play an important part of the immunological role.

00:59:38.360 Well, they do. Probably nowhere near as important as the HDL particle, which is probably why the HDL

00:59:43.460 particle has such a long residence time. And the HDL particle, as important as it is for

00:59:50.700 reverse cholesterol transport, both direct, where it's taking the lipid back to the liver directly,

00:59:57.000 or indirect, which we talked about, and you corrected me, thank you, where it takes it to

01:00:01.040 the LDL and the LDL takes it back to the liver. Certainly some have argued that an even more important

01:00:05.680 property of the HDL is the proteins that it carries. The immunoglobulins, all of the other things

01:00:10.760 that it carries that play this important role in immune function. So it really seems that the

01:00:15.860 overwhelming body of evidence is that the purpose of the LDL particle is to carry the cholesterol back

01:00:22.960 to the liver. Interesting. But this gets back to the multi-purpose value of a vehicle. Is it doing

01:00:29.400 things other than that that also turn out to be relevant? And I think this kind of gets to the

01:00:33.840 larger and more important question overall. Like the question that I started with going back to my

01:00:38.120 November 2015 days was, I thought, very naively, that in a few days I would learn all I would need

01:00:45.720 to about cholesterol and lipoproteins, find the landmark study that had a gajillion people,

01:00:50.740 and they would just show that if you had lower LDL cholesterol, you just died less. Like that was it.

01:00:57.220 End of story. And at first, I thought that I had found that because I had found plenty that pointed

01:01:03.860 to events and pointed to lower cardiovascular risk, but then wouldn't necessarily talk as much

01:01:09.380 about all-cause mortality. I then had to learn about all-cause mortality. And then more and more,

01:01:13.600 I felt like I couldn't get to something that really emphasized. I thought for sure, at least I would

01:01:19.200 see, for example, an elderly population, generally speaking, the lower your natural LDL, we can get into

01:01:26.080 SNPs, for example, on this, the more likely it is that you would just live longer, period.

01:01:29.680 But you have to remember how these studies are powered. So the challenge with ACM is I don't

01:01:35.920 think any study in the history of civilization is going to be powered to detect that. It's hard

01:01:39.900 enough to detect cardiac mortality in a study. I think we need to be more clear in what our concern

01:01:45.360 is. If the concern is if you are less likely to die of heart disease, you are more likely to die of

01:01:51.000 something else, then we should state that explicitly and say, hey, low LDL, while maybe protective of

01:01:57.420 cardiovascular disease, I will argue that is unambiguously clear and we can discuss that.

01:02:02.200 But the bigger question is, are you concerned that, well, it's increasing the risk of cancer

01:02:06.880 or neurodegenerative disease? A trade-off. Yes. So the question there is, that's a question of power.

01:02:12.200 And so it's not uncommon in cardiovascular studies to see a reduction in coronary mortality with no

01:02:18.540 change in all-cause mortality or a non-statistical change. Most of the time, you just don't see a change

01:02:24.020 or it's a change that's very slight. And then you have to ask yourself the question, even if it looks

01:02:28.580 like, hey, death went up or down of other causes, you have to go back and ask yourself,

01:02:33.760 was the study actually able to detect that? That's a very hard thing to detect.

01:02:38.040 Absolutely. And in fact, there's even a paper that I pointed to recently that says,

01:02:41.800 is this even worth chasing after? Because it takes so much expense and time in order to get to a level

01:02:47.100 in which it would be powered to detect for all-cause mortality, should we even make that part of the

01:02:52.120 criteria that's required? Well, there's a broader issue here, which is the lifetime exposure problem.

01:02:56.920 Exactly. And this is, of course, just the problem with atherosclerosis in general,

01:03:00.020 is you do a drug study that's two, three years, but atherosclerosis doesn't take two to three years

01:03:06.700 from zero to- Yeah. I try to not get into any wars on Twitter, but once in a while, I'm just,

01:03:12.440 I don't know, I've had one, two, few Topo Chicos and I'll let it rip. But if I have to see one more

01:03:17.240 person try to tell me why Fourier and Odyssey aren't interesting trials because they didn't

01:03:21.680 show a big enough benefit, I might scream. So just for the listener, Fourier and Odyssey were trials

01:03:27.580 that looked at two PCSK9 inhibitors. I want to also be clear before I get into my rant,

01:03:33.680 I am never having an economic discussion about this. I'm saying that because people often confuse

01:03:40.100 efficacy and effectiveness and cost and value and benefit. And I am not for a moment suggesting those

01:03:46.700 things don't matter. I am not going to argue one way or the other that the cost of a PCSK9 inhibitor

01:03:51.880 is worth it. That's an individual decision. Unfortunately, that decision is for most people

01:03:57.180 made by their insurance company, and that's totally reasonable. I'm only interested in this as a

01:04:02.720 conceptual tool, which is, does inhibiting PCSK9 make a difference? And if you had told me,

01:04:10.980 I remember knowing this, that Fourier and Odyssey had such short time horizons,

01:04:15.840 I thought there was no way they'd find a benefit. In particular, Fourier. So Fourier took patients

01:04:22.020 with an average LDL cholesterol of something like 90 or 92 milligrams per deciliter. These patients

01:04:29.140 were already on the maximum tolerated dose of a statin. Okay, so they're at the 10th percentile

01:04:34.900 in terms of their LDL-C. And in 2.2 years showed a reduction in events. The null hypothesis should be,

01:04:44.000 it should have never worked. You should have needed 20 years to show any benefit when you understand

01:04:50.180 Alan Snyderman's lifetime exposure model. So a lot of people are critical and say it didn't show a

01:04:55.640 mortality benefit. It just reduced revascularations and events in 2.2 years, to which I say, you're

01:05:01.900 looking at that incorrectly. The fact that it showed anything, to your point, Dave, lifetime exposure

01:05:07.600 is staggering. Also on patients who are already maximally statinized. So coming back to this thing

01:05:13.980 about lifetime exposure, this is where the Mendelian randomization becomes a very important tool in

01:05:20.680 understanding LDL's causality. What you alluded to at the outset, you are correct in noting is deficient.

01:05:28.120 There is no lifetime study where without a drug, you can prospectively manipulate LDL

01:05:36.120 and follow people for 100 years and determine outcomes. That would be the ideal study.

01:05:41.400 Yeah, that would be. You actually, you talked about this in the street dope.

01:05:44.980 No, I remember sort of going on. That's right, the magic wand test. Yeah.

01:05:48.420 And I think it's worth plugging in something important here. You've already said this on a prior

01:05:53.620 podcast, and I don't want anyone to misunderstand that you don't necessarily buy into the zero LDL

01:05:58.900 hypothesis. You don't know that you would have LDL at zero. So you do believe there's some kind of

01:06:03.240 trade-off. And you mentioned a few, for example, commonly known diseases for when your LDL actually

01:06:07.900 gets to such a low level, like cognitive diseases and so forth. The way I would say it is this.

01:06:11.720 So I'm glad you brought this up because it is a very important distinction. I absolutely believe

01:06:17.780 that the lower the LDL, the lower the risk of cardiovascular disease, all other things equal.

01:06:23.620 Why? Because LDL is necessary but not sufficient for atherosclerosis. And I say that full stop.

01:06:31.800 Now, it's important to understand what necessary but not sufficient means, because there's going

01:06:35.880 to be some people listening to this who are getting all phosphorylated now, and they're just getting

01:06:39.080 super pissed off. And my advice is sit down, shut up for a minute, and pay attention.

01:06:44.640 Extra points for the phosphorylated insert, by the way. That's for us lipid files.

01:06:48.280 Yeah, yeah. So necessary but not sufficient is the relationship between oxygen and fire.

01:06:54.400 Oxygen is necessary but not sufficient for fire. Can you have oxygen and not fire? Yes.

01:07:01.260 Can you have fire without oxygen? No. The lower the concentration of oxygen, the less likely you are

01:07:08.020 to spontaneously get a fire. So, and again, that's a bit of an oversimplification because there are so

01:07:13.660 many other factors. Endothelial health and oxidation and inflammation, of course, are so important

01:07:19.040 here. But the problem I have with the zero LDL model, which again, I think I don't want to speak

01:07:26.340 for people who, but I think what people are basically saying is there's a subset of people

01:07:29.980 in the medical community who are saying we should just be driving LDL to zero because, you know,

01:07:34.120 that's the best thing. Well, my view is, as you said, no, that's not necessarily the best thing.

01:07:37.940 That might be the best thing for the heart. In other words, it might be the best thing to lower

01:07:41.880 the risk of atherosclerosis, but it's irrelevant because it might come at other costs. And so it

01:07:47.680 depends on your point of view. I do from time to time get into arguments with other physicians

01:07:53.840 who take care of my patients as well, because I'm not a primary care physician. So I have to share my

01:07:59.420 responsibility with other physicians. And about twice or three times a year, I do have to sort of go

01:08:04.520 to war with one of these docs. And it's usually over one extreme or the other. And the most recent

01:08:10.040 example of this was a patient of mine who came to me on 80 milligrams of Lipitor, which is the maximum

01:08:18.000 dose of Lipitor. He had a very high calcium score and a very bad CTA, but he had not had an event

01:08:23.240 that we knew of. But for all intents and purposes, this is a secondary prevention patient, meaning we

01:08:29.920 define secondary as has he had an event or not? Well, he has had an event. His event is look at his

01:08:34.280 coronary arteries, right? But nevertheless, he came on 80 milligrams of Lipitor.

01:08:38.640 And his LDL cholesterol was very low, but his particle number was not quite at goal. The goal

01:08:45.480 for a patient like that would be 10th percentile or lower, given how aggressively you're managing.

01:08:50.000 He also had a slight elevation of LP little a. So I added Zetia, which because he had very high

01:08:56.460 levels of absorption, not uncommon given how much his cholesterol synthesis was being hit.

01:09:00.940 And that brought him into goal. So now he was totally at goal. His cardiologist was happy.

01:09:05.960 I was marginally happy. But what I didn't like was his desmostrol level was now unmeasurable.

01:09:14.040 Now it turned out it was unmeasurable before, but I was so fixated on just trying to get him in the

01:09:17.980 right zone. But now we had some breathing room and I said, you know, now that I'm thinking about it,

01:09:21.800 oh, and by the way, in the interim, Repatha and Pralulant had been approved. These are PCSK9 inhibitors.

01:09:26.740 And I thought, this guy has no measurable cholesterol in terms of synthetic function.

01:09:32.640 So it's very, very low. Now, a lot of people are right now going, aha, aha, that's the problem with

01:09:37.500 those statins. They inhibit cholesterol synthesis. Well, careful. That's true. But every cell makes

01:09:43.460 more than enough cholesterol for its own use with maybe a couple of exceptions. Gonadal tissues,

01:09:48.920 steroidal tissues during periods of high stress need to borrow cholesterol from other tissues.

01:09:53.360 But for the most part, every cell can sufficiently produce its own cholesterol.

01:09:58.360 I think you're right on the most part. I'm not sure if I'm convinced that every, I mean,

01:10:04.220 your body's running a buffet. That's the bloodstream. The bloodstream is this buffet

01:10:07.860 of things that the body anticipates it wants to make available on demand to cells.

01:10:13.540 And I believe, I mean, again, this is kind of just the engineering approach.

01:10:16.800 But we don't know that's true. That's a hypothesis with respect to the lipoproteins, at least.

01:10:20.640 Absolutely true. A hypothesis, but it's not been proven to the other

01:10:23.280 side as well, right? We can see that the synthesis can happen within most cells to be able to make

01:10:28.040 their own cholesterol. Do we have even in vitro studies where we can actually observe

01:10:32.100 that every amount of cholesterol that they would need would ultimately be synthesized,

01:10:35.860 even under periods of stress, like, for example, muscle repair and growth?

01:10:39.640 Well, we have natural experiments, right? We can look at the A-beta-hypolipoproteinemia patients

01:10:44.740 who can't traffic cholesterol. Therefore, they would be entirely dependent on their own

01:10:50.440 cellular endogenous production and they seem completely fine. So that's not proof because

01:10:56.060 we don't have proof to your point, but it's certainly evidence to suggest, I mean,

01:11:00.920 we also know when that's off, right? So like one of the first things we used to see in the ICU,

01:11:07.540 though at the time I didn't pay any attention to it, was anytime a patient came in and they were septic

01:11:11.860 or under great stress. So they had what's called systemic inflammatory response syndrome,

01:11:16.200 SIRS. So you could be in a car accident, you were shot, you have a, you know, a horrible infection.

01:11:21.880 Their HDL cholesterol would transiently take a huge bump. And I didn't think anything of it at the

01:11:27.880 time other than it was neat. It was like, wow, 2x bump in HDL cholesterol overnight. I think I could

01:11:32.780 now look back and interpret those data as huge reverse cholesterol transport. Now the HDL is going

01:11:38.460 out of its way to deliver cholesterol to probably the adrenal glands first and foremost, because the

01:11:44.260 enormous uptick of glucocorticoid, even epinephrine or epinephrine are needed. So clearly there are

01:11:49.860 examples of when this is not in a homeostatic balance. So, so I'll take your point that.

01:11:54.700 Because the A-beta lipoproteinemia patients, in theory, should be the ones who are outliving us all,

01:12:01.620 right? They can take out the whole component of heart disease, of atherosclerotic plaque, everything.

01:12:06.320 They should have massive longevity, relatively speaking, to everybody else.

01:12:11.460 So there's only about 12 genes that are well enough studied. We have enough patients that we

01:12:16.560 think we know something. And the most important of the longevity genes in cardiac is the hypo

01:12:23.940 functioning APOC3s. And that actually shows a net. A net longevity benefit. So work out of Albert

01:12:30.820 Einstein has identified these roughly a dozen genes and the hypo functioning APOC3s. I mean,

01:12:37.940 most of those genes are like GHR, IGF, APOE would be one, right? So APOE2 would carry with it

01:12:45.480 protective benefits in terms of longevity, both cardiac, but more of it is neurodegenerative.

01:12:50.700 But it's those C3s. In fact, as we have kind of alluded to a couple of times, I believe there's an

01:12:55.560 antisense oligonucleotide in clinical trials now trying to impair APOC3. So now that's becoming a

01:13:01.600 therapeutic target.

01:13:02.500 Dayspring alluded to that one.

01:13:03.800 Yeah. And again, this is one of those drugs that might not have much of a benefit in an insulin

01:13:07.140 sensitive person. They may have already captured that benefit by lowering insulin levels.

01:13:12.760 Well, and that's actually part of what this kind of energy model, and particularly that with

01:13:16.600 hyper-responders, specifically lean mass hyper-responders comes back to. I know you don't

01:13:21.040 necessarily hang out on Twitter too much, but you know that I have had...

01:13:24.000 More than I would like.

01:13:25.320 I have this pinned tweet. I've been pinging lots of lipid-lowering experts on this. I've said,

01:13:32.160 look, I'm looking for any studies that show people with high LDL will have high cardiovascular disease

01:13:39.160 if they likewise have high HDL and low triglycerides. But there's one qualification. It can't be a gene or

01:13:46.300 drug study.

01:13:47.060 That's two qualifications.

01:13:47.960 Oh, fair enough. Two qualifications.

01:13:49.260 I've seen that. Here's my concern with that, Dave. I have no doubt in my mind that you are

01:13:55.080 a truth seeker. I don't think that's true of necessarily some of your peers. I do think a number

01:13:59.340 of your peers are deluded and so filled with their own confirmation bias and so unwilling to

01:14:05.580 acknowledge that their precious low-carbohydrate diets could be hurting them that not with malicious

01:14:11.460 intent, but with blind carelessness, they are absolutely ambivalent to anything. I don't put you

01:14:17.060 in that category, so I will challenge you in the following way.

01:14:20.520 Great.

01:14:21.120 When you say, show me an example of something that is not a genetic study that can point to

01:14:27.920 that phenotype, the reason I would call issue with that is, why would you limit yourself from

01:14:33.160 genetic studies? It's sort of like me saying, show me, like, I want to know if there are people

01:14:39.060 who are six feet tall. I think they might be, but I've never seen one. So if you can go into

01:14:45.300 a kindergarten class and find me one, I'll believe it. But you must limit yourself to

01:14:49.520 the kindergarten class. I mean, that's an obscure example. What I'm basically saying is

01:14:52.880 you're excluding so much potential data by excluding all of the genetics. Because when

01:14:57.760 people talk about genetic studies, we have to remember something. Most of the genes, most

01:15:02.700 of the SNPs that lead to alterations in lipids and lipid metabolism are completely unidentified.

01:15:09.140 I mean, FH, for example, familial hypercholesterolemia, which would be the most obvious example to

01:15:13.620 counter that point, you're excluding because it's a genetic condition. But what the listener

01:15:18.820 might not know is that FH is a phenotypic diagnosis, not a genotypic diagnosis. FH is

01:15:25.720 arguably the most heterogeneous collection of genes you can imagine. So why would we exclude

01:15:31.640 looking at those people when that's, in many ways, one of the richest bodies of evidence

01:15:36.560 for a natural experiment in, to answer the question, can you have high LDL-C, high HDL-C,

01:15:43.860 low triglyceride, and still get atherosclerosis? That's the question you're asking, right?

01:15:47.880 Yes, yes. Well, so we'll double back to that in a sec, but basically you're taking us back

01:15:51.760 to genes. And this is why, like, this is another hypothesis, fully untested. I'm in the process

01:15:57.440 of trying to collect on it, but I call this loosely lipid, cellular lipid malabsorption,

01:16:01.900 or I just generally shorten it to lipid malabsorption. Basically, here's the issue that I have with

01:16:06.360 the existing Mendelian randomizations. For that matter, almost all of the gene-based studies

01:16:10.800 is what we're trying to get is, as much as we can, the isolation of just a higher gradient

01:16:17.040 of LDL particle count, right? That's what we all secretly, we want your wand that you're talking

01:16:22.360 about where we could wave it and then there's just magically more LDL particles in some people,

01:16:27.440 or for that matter, less LDL particles, without touching any other parts of the process.

01:16:34.160 The problem is that I believe of, I'm keeping a list of my own S&Ps of those genes that are either

01:16:42.240 resulting in higher or lower LDL-C. And unfortunately, of the ones that I find in the

01:16:47.740 Mendelian randomizations, they don't just result in the higher LDL-C and LDL-P. They also come to be

01:16:54.920 that way because there's a lack of lipids or lipoprotein uptake by the cells. Therefore,

01:17:02.600 particularly with endothelial cells, you've got to be concerned that that could cause dysfunction

01:17:06.040 and therefore could be a reason for why you would have higher levels of atherosclerosis.

01:17:10.920 And this is why, like I'm trying- Wait, wait, sorry, explain that part again,

01:17:13.560 the last part. Endothelial cells being dysfunctional.

01:17:16.500 Yes. Would that be potentially problematic for atherosclerosis?

01:17:18.920 Yes. Okay. Then why would we want to look at any SNP that would in any way impair or inhibit

01:17:27.280 them relative to a normal person's endothelial cell?

01:17:30.360 Why do we believe patients or a subset of patients with FH as a result of their FH have defective

01:17:35.860 endothelial cells? Well, if you've got defective LDL receptors-

01:17:39.300 There's no receptors on the endothelial cell. It's diffusion mediated.

01:17:43.040 Yes, but you've got the receptors with the adipocytes, right?

01:17:45.280 Yes, but at least 20, if not 40% of LDL uptake is not even receptor-bound in the body.

01:17:53.080 Okay. But what about that?

01:17:54.500 And not all cases of FH have receptor deficiencies. So there are at least 2,000

01:18:00.260 vaguely identified genetic causes of familial hypercholesterolemia. They have fewer receptors.

01:18:07.160 So the PCSK9s are a subset of FH, right? About 3% to 5% of patients with FH have-

01:18:12.800 Overexpression of PCSK9.

01:18:13.920 Overexpression of PCSK9.

01:18:15.540 Gotcha.

01:18:15.920 In fact, that's how PCSK9 was first discovered.

01:18:17.820 Okay. But in that case, you're impacting a cell's capability of uptake for lipids or

01:18:22.780 for lipoproteins, right?

01:18:23.900 Yes. You are in that situation. Those patients' livers will take up less LDL because PCSK9 is

01:18:31.420 a protein that does, among other things, degrades the LDL receptors because they have hyperfunctioning

01:18:37.180 PCSK9. They are more rapidly degrading their LDL receptors on the livers. So they're taking

01:18:43.560 up less LDL particles, which explains why they have higher LDL.

01:18:48.240 But this, again, introduces a dysfunction on the lipid metabolism itself.

01:18:51.580 But that has nothing to do with the endothelium. That has nothing to do where atherosclerosis

01:18:54.880 occurs. All that's doing is giving you more LDL in circulation.

01:18:57.980 Let me put it this way. Why not take anything that results in a higher level of LDL-C or LDL-P

01:19:04.240 that doesn't impact any lipid absorption from any tissue at all?

01:19:08.000 Right. But that might be a bit of an artificial constraint, right? I mean, as you pointed out

01:19:12.000 yourself, and I think anybody listening to this will appreciate, this is a complicated

01:19:16.400 dynamic system. So it is going to be difficult to have some perturbation in a system that will

01:19:23.100 lower or raise LDL that won't have some other effect. The question is, how do we, with some

01:19:29.120 reasonable degree of certainty, look at those other effects and ask whether or not they're germane to

01:19:34.060 the question of atherosclerosis and the causality of LDL to atherosclerosis? So I think the PCSK9

01:19:40.160 example is not an unreasonable one because we have a pretty clear understanding of what that gene does.

01:19:45.620 We have a very clear understanding of where that protein lives and what it's doing.

01:19:48.780 But if anything, that's resulting in the other direction, where if you have lower LDL-C

01:19:53.020 or LDL-P from an underexpression, a PCSK9, that actually results in a hyperabsorption of lipids,

01:20:01.100 for example. In the liver. Yeah. They have enhanced hepatic clearance. So both ends of

01:20:05.180 that though, right? So if you have hyperfunctioning and hypofunctioning PCSK9 patients out there,

01:20:10.760 both of whom exist, I believe the hyperfunctionings were discovered first, but the hypofunctionings

01:20:16.400 are kind of the ones that gave the drug companies the desire to go and, or not the desire, I guess

01:20:21.160 the idea to go and create a drug to mimic that phenotype. But these patients walk around with

01:20:26.900 LDL cholesterol of 10 to 20 milligrams per deciliter. And as far as anybody can tell,

01:20:31.600 there's no other side effect of that. Well, and this is the thing I want to zero in on is let's

01:20:35.720 say that we do that. Let's say that we go, okay, nevermind this side part of the lipid hypothesis end

01:20:40.840 of it, or I'm sorry, the lipid metabolism end of it. We should then be able to look back at these

01:20:46.140 people with the more novel versions of SNPs. And assuming that there's at least a large enough

01:20:50.640 population, we should see that longevity. Your mentioning of the APOC3 from earlier is the first

01:20:56.420 that I've been able to find of that one. I'm interested to see if we would see that across

01:21:00.440 the board with these people who have these SNPs. Yeah. I mean, I suspect it will have to do with

01:21:04.420 how many of them there are and how long they're being tracked. I sympathize with your concern as

01:21:10.260 it's absolutely the case in nutrition, nutrition, medicine. There's certainly a lot of personalities

01:21:16.020 that are out there, but I can understand, at least for me on, on my end, I like hard end points over

01:21:21.900 soft end points. Maybe it's just the engineer in me. I like ones and zeros. Death is pretty easy to

01:21:26.300 diagnose. Whereas soft end points, the downside is there can be arbitrary decision-making on the part

01:21:31.340 of the patient and the doctor is to, yeah, I, you know, I heard you mention that on one of the

01:21:35.140 podcasts. I got to tell you, I disagree with that. Having seen more patients in an ER when I was in

01:21:41.540 residency with MIs, I can honestly tell you, Dave, never once knew what their cholesterol levels were.

01:21:47.520 When someone comes in the ER with chest pain, I care about the advanced cardiac life support

01:21:52.320 algorithm, which involves oxygen, which involves an EKG, which involves troponin, which involves

01:21:57.520 morphine, aspirin, and potentially a trip to the cath lab. But we are in nowhere in that algorithm

01:22:04.420 are we asking what's their LDL and letting that help us think is this indigestion versus other

01:22:09.700 things. So I do take issue with calling MI a soft outcome. It's not so much whether it's a soft

01:22:15.340 outcome. It's whether or not there are things like say revascularizations that can be determined based

01:22:20.520 on a decision on the part of the doctor and the patient that may or may not have to do with their

01:22:24.960 knowledge of the lipids, right? Agree. I mean, these are all different things, but I also think we

01:22:29.200 should be careful not to take mortality as the only outcome. I will say this, and I hate putting on

01:22:34.360 the stupid doctor hat because it sounds ridiculous in this context. But unfortunately, I feel like I

01:22:38.560 have to go back into and out of that world here. I would say at least half the patients that come to

01:22:42.740 me do not actually find themselves asking for an extension in lifespan. My interest is longevity,

01:22:49.420 but longevity has two components. How do you increase lifespan? Meaning how do you delay death?

01:22:54.720 And how do you improve health span? Won't go into what that means. But the bottom line is there are many

01:22:59.820 people who say, I honestly have no interest in living one day longer than I might otherwise live,

01:23:05.280 but I want that quality to be much higher. So if we're going to say, and again, I don't necessarily

01:23:11.260 agree with that. I think the bigger issue is a statistical one with all cause mortality, but

01:23:14.480 nevertheless. But you're going to modality. Like if somebody has an MI and it actually impacts the

01:23:19.360 quality of life afterwards. Yeah. Right. What if your quality of life is decreasing as a result of a

01:23:25.020 procedure necessary or otherwise, or an MI or a decrease in ejection fraction? Because remember

01:23:30.740 about half the people who first present with atherosclerotic coronary disease present with

01:23:35.640 sudden death, but half the people don't, right? Half the people go through MI, stroke, God knows what

01:23:42.120 else that follows. So again, I see it as my chief responsibility to delay the onset of death. If a

01:23:48.040 patient decides that that comes at too great a cost, that's great. That's their decision. In the end,

01:23:52.480 the patients decide everything. But going back to what got us here, I am convinced that if patients

01:23:58.480 didn't have LDL, there would be little to no atherosclerosis. If you could give them no LDL over

01:24:04.640 the duration of their life, if a patient comes to you and they've already got disease and you lower LDL,

01:24:09.100 I don't think that that gets them out of the woods. I think that that's sort of just stochastically

01:24:14.100 moving them in the right direction. What we have to be careful of, and kind of going back to that

01:24:18.360 patient I was talking about, is we have to be able to identify the patients in whom the risk of LDL

01:24:24.760 lowering is starting to cause a problem elsewhere, meaning they're incurring an unacceptable risk

01:24:30.660 elsewhere. And in the case of this particular patient whose desmostrol levels had now become

01:24:35.880 unmeasurable, my concern was we have overdone it with him on the lipid side. There's a safer,

01:24:42.640 easier way we can lower his LDL without impairing his cholesterol synthesis because of the limited,

01:24:48.620 but to me, quite convincing data on the plausibility of Alzheimer's disease in patients with overly

01:24:54.140 suppressed cholesterol synthesis. So I want to be really clear when I repeat that. I am not suggesting

01:24:58.820 that statins cause Alzheimer's disease, which I know the blogosphere loves to talk about. If anything,

01:25:04.360 statins slightly increase the risk of diabetes in susceptible people over a great period of time.

01:25:08.920 But at the population level, there's actually no evidence that statins are causing Alzheimer's

01:25:13.080 disease. However, I think there are a subset of patients who are susceptible and you have to be

01:25:18.360 able to identify those patients. And that's the problem with population data, as you know, is you can

01:25:21.980 lose the nuance. The nuance is you, right? What matters to you, Dave? In the end, I don't really care

01:25:28.360 what your LDL is. I care about you not getting atherosclerosis. And if there is indeed someone walking

01:25:34.600 around out there with an LDL cholesterol of 300, who's not getting atherosclerosis, and there are

01:25:39.440 indeed examples of that, then that's great news. But we have to sort of use this heterogeneous

01:25:45.500 population-based data to then try to probabilistically figure out what do you want to do with somebody at

01:25:51.440 the individual level? So with this patient, in the end, after a lot of fighting, the decision was,

01:25:56.800 we're going to put him on Repatha, or we're going to start cutting down the Lipitor until we get that

01:26:00.940 desmostrol to bump. And so we're still in the process of doing that, actually. So that, to me,

01:26:06.060 is like kind of an example of what I would think of as hopefully where precision medicine would be

01:26:10.420 going, which is you're now well outside of a clinical trial, right? There's never going to

01:26:15.700 be a clinical trial that's going to ask the question, if you take a bunch of patients and

01:26:19.980 statinize them ad nauseum and you drive their cholesterol synthesis very low and follow them for 30

01:26:25.520 years, do a subset of those people get it? No. I mean, you have to be able to look at

01:26:29.700 retrospective data where those things were gathered. And we'll link to what I consider

01:26:33.600 one of the best papers on this topic. But getting back to the challenge,

01:26:37.400 in a sense, you're saying by ignoring the genetic data, that the genetic data basically answers the

01:26:43.020 question to your satisfaction, to where you don't need to look at non-genetic-

01:26:46.900 Not alone. I think of it as the genetic data coupled with the pharmacologic data,

01:26:51.760 coupled with the mechanistic data, give me a high enough degree of certainty that I am willing to act

01:26:57.420 in a certain direction. Remember, everybody, me, you, whoever's listening to this, they have to make

01:27:02.120 a decision. Indecision is a decision. So when you showed up with a hemoglobin A1c of 6.1, did you

01:27:09.180 have type 2 diabetes? Nope. Your doctor said, hey, I'm cool just waiting. But you said, no, indecision is

01:27:15.620 not a decision anymore. I'm going to do something about it. Because presumably you said, look, I have a

01:27:20.780 family history of this. I think I have a sense of what the progression of it is. And quite frankly,

01:27:25.440 I don't want to wait until I have this disease to do something about it. So you decided indecision

01:27:30.440 was not a viable decision. Sometimes indecision is a reasonable decision. But the point is people

01:27:34.560 have to understand they are making a decision, whatever they decide to do. Absolutely. Well,

01:27:38.840 and for what it's worth, as I say outside of here, and as I'll say on this podcast,

01:27:43.160 as I actually just said at the speech, I don't know if you saw the one that I did from last month,

01:27:47.340 I told people I prefer they not be echo chambering. I prefer they find everything that challenges

01:27:51.920 from every side. So with that said, going back to the lean mass hyper responder, you would say,

01:27:58.380 given what you know right now, given everything we've just talked about, that they are at high

01:28:02.000 risk of cardiovascular disease. Would that be correct? I'd want to know more data. But yes,

01:28:06.320 if I didn't know anything else other than... Let's say all cardiovascular risk markers save

01:28:11.640 LDL of 200 or higher, LDLP of typically 2000 or higher. Everything else is just pristine perfect,

01:28:19.160 like CRPs at the floor, their LPPLA, maybe... Let's look at this patient here. So we'll link

01:28:25.540 to these labs. I asked this patient, this is a patient I saw last week. So that's the only reason

01:28:28.940 I printed this up because I see this so often, but I'm like, let's just get the last one.

01:28:33.960 So this is a gentleman who's been on a low carb diet for a couple of years, is achieving

01:28:40.360 amazing success with it. He's a new patient to me, but he's been around the block on this stuff

01:28:46.700 before. And he's got an amazing history of his labs going back many years. So I've seen what he

01:28:52.000 looks like on and off all of these therapies, on and off drugs, et cetera. But he's one of these guys

01:28:57.480 where across the board looks fantastic, right? His glucose disposal is remarkable. His insulin levels

01:29:03.320 are very low. His C-reactive protein is 0.3. So everything looks good. So read off some of his

01:29:10.560 numbers just for the folks, Dave. He doesn't quite meet your lean mass because his trigs might be a bit

01:29:15.700 higher, but talk to me about this guy's numbers. So total cholesterol is 504. Is that high?

01:29:21.740 This is, I know what you're doing there. No, I'm just kidding. I get this all the time where

01:29:26.200 somebody sends me just that number. No, no, no. Okay, go ahead. But anyway, total cholesterol 504,

01:29:30.720 LDL-C direct. And it's worth emphasizing just real quick for the listener when they say direct,

01:29:35.200 it's very important to notice that because usually LDL-C on a typical lab is actually calculated

01:29:41.300 through the Friedwald equation. So when it's direct, that actually is a direct measurement. That

01:29:45.140 matters for remnant. Hope we'll get a chance to talk about remnant. We will talk remnants for

01:29:48.280 sure. So LDL-C at 362, HDL-C at 94, triglycerides at 125. The very first question I would ask if

01:29:57.340 somebody was sending this to me is whether it was faster or not. Yeah, this was, but I've gone back

01:30:01.360 and looked at all of his other trigs and he actually normally does reside below about 70. Oh,

01:30:06.180 he does. Okay. So he would be typical for lean mass. Yeah, he might've just eaten dinner a little

01:30:09.460 too late or something. You know, I'm not, I'm not sure what was going on. Do you want me to keep

01:30:12.440 going on the particles? Yeah. Go ahead. Hit the part. So APOB is 283. That actually is a little

01:30:17.600 higher than I'm used to seeing. LDL-P is above 3,500. Small LDL-P is at 1483. Small dense LDL-C

01:30:25.480 is at 47. All right, we'll stop there and come back to it. So I've told you that everything else on this

01:30:30.300 guy looks pretty good. Is this guy at risk? I'm actually looking ahead because I would have

01:30:34.740 cared about these other markers that could indicate inflammation. So for example, the fibrogen is,

01:30:39.040 is very high. LPPLA2 is above 600. I don't know. In fact, I think I actually just tweeted about this

01:30:45.740 recently. I don't know that I've seen an LPPLA2 above 300 or 400, I think of the labs that have

01:30:53.200 been sent to me. And I don't get a chance to interpret oxidized LDL, but you have the LDL

01:30:58.440 as above 135. So I would say by this lab, as it looks, I would be concerned about the triglycerides.

01:31:05.080 I would ideally want the triglycerides to go down. But is it your impression that if his trigs were

01:31:09.460 normal, he would be okay? I would be interested to see if the other inflammatory markers linked

01:31:13.880 back to the reason as to why the trigs would be a bit higher. That would be something I would be

01:31:18.520 very curious about. But yes, if you were to say, I think where you're trying to drive to is if I had

01:31:23.260 only the information of the lipid panel itself, and it did say not 125 on the triglycerides.

01:31:28.140 Let's make it even easier. Let's pretend that this patient had a zero calcium score.

01:31:32.780 Well, zero calcium score. I'm not entirely on calcium score, but I do care about calcium score.

01:31:38.640 The thing is, is I would say, if you were to give me the same numbers, let me make this easier. I

01:31:44.500 have Craig Moffitts, who's very close to this, except that his triglycerides are much lower.

01:31:49.620 If it was the same one, then I would wonder if there really was a risk. Yeah.

01:31:53.340 Okay. So again, that is a decision that every patient's going to have to make in that situation.

01:32:00.300 In the case of this patient, I feel very strongly that he is at increased risk,

01:32:04.260 though I think on many other metrics, I think his risk of cancer, he's actually an APOE23,

01:32:11.860 this patient, so his risk of dementia is going to be a bit lower. He's metabolically quite flexible.

01:32:16.360 But if his other inflammation markers were low, like the LPPLA, the OXLDL, all this stuff that was

01:32:21.480 below, would you feel he was at risk? If the only thing that was different was-

01:32:25.180 I would still feel he is at risk because, again, this is one of the three legs of the stool,

01:32:30.300 right? It's the burden of lipoprotein, it's the endothelial function or health,

01:32:34.600 and it's the inflammatory response to it. And I can't measure number two very well,

01:32:40.020 right? And even number three is pretty kludgy, meaning all of these things like fibrinogen and CRP

01:32:46.800 are not very specific. So you have to sort of, at the individual level, be very careful. You don't

01:32:52.100 draw too much of a false sense of confidence. But look, looking at him, he has among the lowest

01:32:58.700 asymmetric and symmetric dimethyl arginine levels I've ever seen. These are staggeringly low. I

01:33:04.480 would have expected those to be through the roof. So ADMA and SDMA are things that we use to look at

01:33:09.580 endothelial health. They inhibit nitric oxide synthase. So when ADMA and SDMA are elevated,

01:33:16.320 you're inhibiting nitric oxide synthase. You have less nitric oxide produced in the endothelium.

01:33:21.180 You're more prone, obviously, to constriction. I've never taken that test. I'd be interested

01:33:24.760 in trying. Again, just because I'm cheap and I didn't want to print up a bunch of paper,

01:33:27.780 I only printed two pages of this guy's labs because those are the two that are most relevant. But

01:33:31.440 you can take my word for it. The others were exceptional, right? Like this is a guy who looked

01:33:35.260 really good across the board. The question is, should anything be done? Now, if this patient had

01:33:40.240 a negative calcium score, which he did not, but if he did, I would have still recommended lipid

01:33:46.380 lowering therapy and or modification of diet. Why modification of diet? Because I've now seen

01:33:55.360 more of these patients than I can count. And there is a pattern that is emerging. And I think I wrote

01:34:00.660 about this in one of the cholesterol things, but the pattern that always occurs in these folks

01:34:05.040 and I say always with a relatively small N, maybe there's 30 of these cases I've seen

01:34:10.340 is this exact pattern. This one, he's like a perfect example of. So his desmosterol is very high.

01:34:18.180 Remember what we talked about at the outset? Yes. When a patient's LDL particle number is through the

01:34:23.240 roof, you go through the checklist. Are there triglycerides high? No, there's no way in hell a

01:34:28.320 trig of 120 accounts for someone being above the 99.9th percentile of LDL particle.

01:34:35.540 Does he have an LDL receptor defect? It turns out I don't think so because I've seen his,

01:34:40.900 even though I haven't seen his LDLP, I've seen his LDL-C off a ketogenic diet and it was 125.

01:34:47.980 Right. Is he lean and or fit?

01:34:50.020 He is. Okay.

01:34:50.760 Yeah. So his cholesterol synthesis is through the roof and his cholesterol absorption is quite high as well.

01:34:56.540 Are these affordable tests? Because I would definitely want to turn these around to

01:34:59.700 the existing group of lean mass.

01:35:01.600 I'm sure it's, yeah, I'm sure the cash cost on these is not onerous. But my point is,

01:35:05.940 I think that the explanation for this phenotype is the upregulation cholesterol synthesis

01:35:12.220 from the saturated fat. I don't think this is an energy issue per se. I think this is a sterile

01:35:19.660 regulated binding protein issue or some sort of regulatory path around what the body is doing with

01:35:26.440 ketones and or saturated fat. Tom Dayspring told me this a long time ago and I totally forgot about

01:35:32.820 it. And then the other day I went and looked up a case because I never paid attention to this.

01:35:36.600 We used to see patients all the time with diabetic ketoacidosis. So these are usually patients with type

01:35:41.540 one diabetes that come in the ER and usually it's precipitated by some acute illness. But basically

01:35:48.020 what happens is their glucose level becomes very high. They don't have enough insulin. Of course,

01:35:52.620 they get a bunch of electrolyte abnormalities, but they present with very high levels of ketones.

01:35:56.260 This actually is an emergency. So all the talk about ketosis being dangerous, this is the example

01:36:01.540 of where it is very dangerous. It's life-threatening. So what I didn't realize is I went back and looked,

01:36:06.800 it turns out a lot of these people have very elevated levels of LDL cholesterol, total cholesterol.

01:36:12.380 Now they also have elevated levels of triglyceride, but of course it's hard to know exactly what's

01:36:17.460 driving that. But once you correct this metabolic deficit, which is quite easy to correct, it's

01:36:24.220 basically potassium, IV fluids, glucose, and insulin, and you normalize their glucose levels

01:36:29.520 and their fluid balance and their electrolytes, the cholesterol returns to normal. So it might be that

01:36:36.840 the ketones themselves are a substrate to make more cholesterol. And again, we'll link to a great paper

01:36:42.200 that Tom wrote on Lipoholics several years ago where he goes through the biochemistry of how saturated

01:36:48.160 fats specifically and ketones could in a susceptible individual produce this phenotype. And so bringing

01:36:56.880 it back to this idea of genes, we might really be dealing with a subset of people, these hyper-responders,

01:37:05.700 whoever, whatever percentage of the population they are, who are the people that are susceptible to this

01:37:11.040 because you were not going to find a leaner person exercising harder than I was when I went on a

01:37:16.040 ketogenic diet. But I never had this response. But there is a distinction that I tend to find in

01:37:21.000 this is Occam's razor, again, more theory. And I'm actually going to be testing this myself in the

01:37:26.820 next series of experiments that I'm doing. There is a difference between those people who are doing

01:37:31.140 things like say endurance running and weightlifting or resistance training in that I think that there's a

01:37:37.020 greater overall gradient of receptor-mediated endocytosis for muscle repair and growth.

01:37:42.740 Now, I could be wrong about that, but I'll be very curious to see if that turns out to be the case

01:37:46.020 when I'm doing it myself.

01:37:47.060 Sorry, a greater amount of endocytosis of which lipoprotein and for which product?

01:37:51.480 Of LDL-P in particular.

01:37:52.840 Into muscles?

01:37:53.840 Yeah.

01:37:54.080 For what product?

01:37:55.020 For repair and growth.

01:37:56.020 So you're saying that in these people, they're relying on their LDL for cholesterol delivery to the

01:38:02.260 muscle?

01:38:02.500 Well, and phospholipids and just about anything else that would be inside of an LDL particle.

01:38:07.520 There's existing studies that are out there as far as like those people who do like a lot of

01:38:11.220 weight training will also see lower LDL-C. And this is why I'm saying it's completely theoretical.

01:38:15.860 I'll actually be testing this myself over the next few weeks because I'm actually going to be eating

01:38:19.880 to a very fixed diet, fixed sleep schedule, fixed everything, and then actually be introducing

01:38:24.740 basically any way in which I can get my muscles sore in a very fixed fashion that I can then turn

01:38:29.460 around as data. And if the hypothesis is true, I would expect that my LDL-C and my LDL-P might

01:38:35.620 change.

01:38:36.500 But I'm confused. Why is the runner's muscle more demanding than the weightlifter's muscle

01:38:42.480 or vice versa?

01:38:43.280 The other way around. That I doubt I would see the weightlifter actually seeing a difference.

01:38:47.640 Because I think there's more use of the product of LDL-P directly by the cells.

01:38:51.500 I may be wrong about that.

01:38:52.620 But what's the evidence that that's happening?

01:38:54.600 The evidence as far as the keto gains groups, I'm sure you've heard of them.

01:38:58.260 No.

01:38:58.680 There's a ketogenic group that's keto gains. There's not as many lean mass hypersponders that

01:39:03.880 come out of that group. They'll tend to see their LDL-C go up, but not as pronounced as those people

01:39:08.080 who are like, say, runner types or aerobic types, or even people who are doing yoga. There seems to be

01:39:13.820 actually a more pronounced difference of higher LDL-C depending on how much you're doing resistance

01:39:18.680 training or anaerobic training.

01:39:20.020 I'm not aware of any evidence to suggest that the muscle is relying on LDL for delivery of

01:39:26.120 anything, including energy.

01:39:28.980 Well, and I'm not so sure about it on energy. What I'm thinking about is in terms of just raw

01:39:32.780 material. As far as damage that can happen to, for example, the membrane of a cell. And I realize

01:39:39.560 this is kind of a key difference between us in that your sense is that effectively anything that

01:39:44.240 the cell is going to need, it can basically synthesize on its own, right?

01:39:47.060 No, I think my sense is that Occam's razor would at least have me start from a place of

01:39:52.680 plausibility. And I'm not aware of any data that suggests that LDL is functioning to do this.

01:39:59.620 What's the value of non-hepatic receptor-mediated endocytosis from your perspective?

01:40:04.840 So you're talking about very specifically the little bit of LDL that gets out of circulation

01:40:10.200 either with or without a receptor to non-hepatic tissue.

01:40:13.560 Yes.

01:40:14.420 Yeah. My sense is the most important value of that would be to tissues that need more

01:40:20.160 cholesterol to synthesize hormones.

01:40:21.840 But specifically cholesterol and not like the phospholipids or anything else that's on there?

01:40:25.920 You know, I think the phospholipids probably may be more delivered through others. I mean,

01:40:30.180 certainly the VLDL delivers far more phospholipid than LDL. But LDL is really a custom-built package

01:40:38.540 for cholesterol. Like if you look at how many cholesterol molecules fit inside an LDL particle versus

01:40:43.280 even an HDL particle. Remember, the HDL is the general of RCT. And yet it can still only carry

01:40:50.800 about 50 molecules of cholesterol. The LDL particle can carry 1,500 molecules of cholesterol.

01:40:57.840 That's staggering when you, again, consider the size of these things, right? Like it's tailor-made

01:41:02.220 for that. And that is largely conserved. I don't want to get us too far in the weeds, but I actually did a

01:41:08.080 very interesting kinetic experiment many years ago. So I did three blood tests every day for three days,

01:41:16.700 like the full NMR panel, but this is with kinetics. So this is not commercially available. So what

01:41:21.560 you're looking at is my ability to track, and you'll have to lay it down because I barely remember what

01:41:27.000 I did here, but this is pre-workout, immediately post-workout, four hours later, looking at my LDL

01:41:32.560 particles, my VLDL particles, my HDL particles, both in terms of their cholesterol and triglyceride

01:41:37.240 content. You see them going down yourself? I don't see any change in the cholesterol content. I mean,

01:41:41.440 it's minimal change in cholesterol content, right? What I think you see here is, yeah,

01:41:46.080 wow, under really periods of super high intense exercise, I actually did take some triglycerides out

01:41:51.720 of this. Minimal out of here. By the way, this backs up Garvey's data, which is there's virtually

01:41:57.100 no way to distinguish what's going on at the VLDL level. I mean, we can't tell what's a remnant

01:42:02.320 here or what's not a remnant. I apologize for the listener. We're looking at the chart,

01:42:05.340 but we're going to link to it so you'll see it. We're basically talking about this idea of

01:42:09.220 how much movement of cholesterol is going into and out of the LDL particle under these extreme

01:42:14.620 conditions. So I just did different types of workouts. So on this day, I did a crazy high

01:42:19.200 intensity interval training. On this day, I did a crazy intense swim. And I think on this day was the

01:42:24.880 hardest workout of them all was a crazy intense bike ride. And the listener can't see this,

01:42:28.860 but I'm smiling ear to ear. It's almost as if you knew I was going to...

01:42:31.780 I forgot I did this. I did this six, seven years ago.

01:42:35.460 And again, it's not commercially, you know, these are not assays that can be reproduced.

01:42:39.620 Right.

01:42:40.060 And again, I suspect you and I will look at these differently, right? I'm looking at these to say

01:42:43.900 the VLDL is definitely moving its triglyceride, the LDL a little bit, the cholesterol is barely

01:42:50.400 moving. Now this is different from a broader issue, which is how much did my cholesterol actually

01:42:57.280 change in those nine blood draws? Well, that was the variability of my LDL-P. So we'll link to a

01:43:03.980 graph that shows LDL-P versus LDL-C. These are nine points across three days.

01:43:10.540 I wish I could go back in time, find the U of... What is this? Like 2012, 2013, something like that?

01:43:17.220 Yeah, probably 2011 or 2012.

01:43:18.880 I'd be... Peter, this is day from the future. I need you to eat exactly the same thing you do on

01:43:24.040 all these days. Yeah, I pretty much did. Oh, you did? Yeah, yeah, yeah. I can hold for that.

01:43:27.520 Yeah. Okay, good. And I was timing exactly when I would eat it. This is back when I was very strictly

01:43:31.480 in ketosis. Fantastic. That's effectively what I'll be doing. So I'll actually have... I'll add

01:43:36.240 a two to your end, but I'm super excited to be seeing this now. Yeah, but you're not going to

01:43:40.860 have, unfortunately, this. I mean, this to me is the interesting part is, this is the part that

01:43:46.360 surprised me the most, was how little the cholesterol was actually moving out of the LDL.

01:43:52.040 Even when the particle was going down, and remember, the height of this bar is artificial.

01:43:57.400 It doesn't mean anything. This is not the LDL-P, right? This is milligrams per deciliter,

01:44:01.960 milligrams per deciliter of cholesterol of triglyceride. Maybe I'm getting a little confused

01:44:05.560 here. How do you know about the cholesterol moving out of the LDL-P? Because, well, what I can say is,

01:44:12.140 before the workout, there was 116 milligrams per deciliter of cholesterol in the LDL, and after the

01:44:17.600 workout, that's what was there. This is how much triglyceride was in the LDL. That's what was there.

01:44:21.720 Okay. So it's sort of a flux. Right. Because here's the thing. I mean,

01:44:25.880 in a sense, we're sort of, I know you can acknowledge this as well. We don't exactly

01:44:30.480 know what the true circulatory level of recycling is. You're just saying on a per-particle basis for

01:44:36.540 testing it afterwards. Like, for example, we're talking about the pool. Correct.

01:44:40.260 Not the individual particles in that sense. Yeah. It's basically saying, if you took four snapshots

01:44:46.960 in a room and how many people had blue shirts on and how many people had red shirts on and you saw

01:44:52.520 the deltas, you could not infer the actual numbers that went in and out, but just the net delta. So

01:44:58.720 there is either a net influx or efflux of people in blue shirts or red shirts. Right. That's the best

01:45:03.700 we can do. Now, there may be some kinetic studies that could do even one better, but that's, to me,

01:45:08.000 pretty interesting stuff. Let's circle back to remnants real quick. Okay. So this is why I kind of

01:45:13.340 pause a little bit on the case study that you showed me where you had the triglycerides a bit

01:45:16.840 higher. Now, as you know, it's what is the poor man's version of remnants is you basically can

01:45:23.560 just take your triglycerides divided by five. You probably actually... No, no, no, no. We got to

01:45:27.240 be very clear on this stuff. We're going to confuse the hell out of people. Okay. That's the poor man's

01:45:31.140 version for VLDL cholesterol. Correct. Very important distinction. So the poor man's version,

01:45:36.180 which should never be done because it is such an abomination, is to take the triglyceride level divided by

01:45:41.280 five. And that number would be an estimate of your VLDL cholesterol. What would you, Peter Atiyah,

01:45:47.800 recommend as the most effective means by which somebody could determine their remnant cholesterol?

01:45:52.360 We can't. It's impossible. We have no way of knowing remnant cholesterol. Well, let me be clear.

01:45:58.000 I think I know what you mean by remnant, which is why I'm asking that question.

01:46:01.740 You're asking pathologic remnant. You're asking VLDLs that have shed their triglyceride and are now

01:46:09.800 basically pathologic, small, started out as big, triglyceride rich, and now have shed that through

01:46:16.500 their APOC2 to LPL pathway and now have the potential for atherosclerosis. Is that what

01:46:22.340 you're meaning about remnant? No, I now think we may think of it differently. So straight up

01:46:27.440 Wikipedia right now would define remnant cholesterol as basically all cholesterol that's not in either

01:46:32.720 an LDL particle or in a HDL particle. So if you were to just subtract HDL cholesterol...

01:46:39.220 Yeah. So if you directly measure total cholesterol, which you can, and you can directly measure LDL

01:46:43.440 cholesterol and you can directly measure HDL cholesterol, you subtract those two and you

01:46:48.340 have the amount of cholesterol that is virtually all in a VLDL and presumably some IDL if it's...

01:46:54.540 Some IDL. Possibly chylomicron remnants if you ate recently, but you shouldn't have any

01:46:59.100 chylomicron remnants. Yeah, that's very easy to exclude. Right. But effectively, if you've had a

01:47:04.120 fasted cholesterol test, pretty much all your remnant cholesterol pretty much will be in VLDL,

01:47:10.260 has the longest residence time relative to the IDLs. That's correct. But that's sort of telling me

01:47:15.200 outside of very few pathologic states like Friedrichson type 3Bs, that's as interesting to

01:47:21.900 me as your eye color. The remnant cholesterol. Yeah. Really? Yeah. I mean, it's generally going to

01:47:26.960 be very low. It tracks quite well with triglycerides, though there are lots of examples where it's

01:47:32.760 been... Actually, I think I brought a copy of one of my other goofy experiments. I don't know. I

01:47:38.440 probably won't find it anytime soon. But there was an example of how mine was so far off. It was like

01:47:44.800 a 700% delta between actual versus predicted in one of these studies. But no, the point is like,

01:47:51.240 yeah, directionally speaking, I'd love to see a VLDL cholesterol below 15 milligrams per

01:47:56.060 deciliter, as calculated by taking non-HDL cholesterol, subtracting the LDL cholesterol,

01:48:02.360 which if you have a direct LDL cholesterol is your best measurement of that. But whether it's

01:48:08.040 10 milligrams per deciliter, 15 milligrams per deciliter, 20 milligrams per deciliter,

01:48:12.540 that just tells me the sum of cholesterol in all of my VLDL remnants. It tells me nothing about the

01:48:19.560 pathology of them. It tells me nothing about what they've done or where they're going.

01:48:22.960 But that said, the question then becomes, even for as much as what you just qualified,

01:48:29.320 does that become a more powerful predictor relative to something like, say, LDL cholesterol?

01:48:33.880 Maybe. But that's sort of like saying, is rubbing two stones together better than rubbing like two

01:48:39.440 logs together to start a fire? It's like, why not just use a Zippo lighter, right? It's sort of like,

01:48:44.260 we could split hairs on whether non-HDL cholesterol or remnant cholesterol is a better predictor of

01:48:49.900 cardiovascular disease than LDL cholesterol. But again, given that, you know, LDL cholesterol is

01:48:54.320 such a crappy predictor of cardiovascular disease, I prefer not to really even think about

01:48:59.240 that. That's, again, it's...

01:49:00.660 But we do have now a situation where this particular phenotype, where lean mass hyper responders will

01:49:06.100 have very low levels of VLDL cholesterol, have very high levels of LDL cholesterol, will have very

01:49:12.360 low levels of remnant lipoproteins.

01:49:14.180 Well, but we don't know that. There's no way you've measured that. I've never measured that.

01:49:19.180 That's not measurable in a commercial assay that's worth its salt. I think VAP does a

01:49:23.380 vague-ass version of that, but it's sort of bunk. But look at this. Look at Garvey's study. So we'll

01:49:28.440 link to this as well. So this is actually measuring the number of particles, right? So this is an insulin

01:49:34.340 sensitive person. Their total LDL-P is about 1,200. Their VLDL-P is about 80. You go to someone who's

01:49:44.680 insulin resistant but not diabetic, their LDL-P goes up to 1,435 on average. Their VLDL goes to 84.

01:49:54.000 Their IDL is counted. It's a rounding error though. And then you take the population with type 2 diabetes,

01:50:00.140 their LDL cholesterol is up to 1,600 nanomole per liter, and their VLDL goes up to 100. So

01:50:08.200 you're right. The VLDL is going up as you get more insulin resistant, but it doesn't appear to be very

01:50:15.240 clinically relevant, right? Because remember, it's all the burden of disease is from these

01:50:20.060 ApoB-bearing particles. And so the increase in VLDL particle number is not what's driving the risk

01:50:28.400 of the disease. You actually had a really nice graph in one of your figures that showed,

01:50:32.080 you titled it as remnant that was going up. Do you know the figure I'm talking about?

01:50:35.620 Yeah.

01:50:36.120 We'll link to that as well. But you had a graph that showed, I think, as people were becoming

01:50:39.300 more insulin sensitive, their pool of remnants was growing.

01:50:42.800 Well, and actually, I want to qualify something real quick. If I think it's the graph you're talking

01:50:46.080 about, it was the one downside to that is it was non-fasted remnants, which I've been trying to

01:50:52.360 find more fasted remnants, which I have a problem with.

01:50:55.000 It was in one of your talks.

01:50:56.420 It was in one of your talks.

01:50:57.860 But anyway, my point is what's missing from that analysis is ApoB or LDLP.

01:51:02.640 Right.

01:51:02.800 In other words, the expansion of that, see this study, which is, I mean, the most elegant study

01:51:06.760 of this ever done shows that if you only saw the top line, this to this to this, everyone would be

01:51:13.640 like, wow, the more insulin resistant you get, the more your total burden of ApoB goes up.

01:51:19.600 But what this is showing is where is that burden coming from?

01:51:22.260 The VLDL only increased by 20 nanomole per liter, but the LDLP increased by 400 nanomole

01:51:30.020 per liter.

01:51:30.940 Right.

01:51:31.100 And the point I'm coming to is this is where we're in uncharted territory is I don't believe

01:51:34.860 this will apply to people who are ketogenic fat adapted.

01:51:38.440 I don't believe this will apply to people who are very ketogenic fat adapted and particularly

01:51:42.260 who have this phenotype.

01:51:43.760 So let me see if I can come at it this way.

01:51:45.640 Right now, if I were to be able to get the data set for Framingham offspring, because that

01:51:50.080 is one of the studies that I was showing out from before.

01:51:52.640 And I could basically just do this basic calculation of remnant cholesterol the way that we were

01:51:58.300 talking about.

01:51:58.880 And conceding the point that you said earlier that there's no way to truly know, would I

01:52:04.580 still come up with a more valuable metric for subtracting HDLC and LDLC, particularly

01:52:10.640 when associating it to all-cause mortality?

01:52:12.980 Relative to like, say, LDLC.

01:52:14.780 Let me make sure I understand what you're saying.

01:52:16.080 You're saying if you could develop an assay to distinguish between the pathologic remnants

01:52:22.340 of VLDL versus the physiologic remnants.

01:52:25.300 I'm not even developing that.

01:52:26.240 Let's say I'm not even developing.

01:52:27.220 I'm just taking the existing HDLC and LDLC metrics as they're recorded right now.

01:52:31.380 Like I'm not even.

01:52:32.380 Oh, I see.

01:52:32.920 I'm just grabbing the data set as it is right now.

01:52:34.920 Yeah.

01:52:35.180 Will the remnant cholesterol that I get from that subtraction, will that actually be more

01:52:40.820 relevant to all-cause mortality than say LDLC?

01:52:43.360 I don't know, but it would certainly rival it.

01:52:47.060 Again, the data are probably more clear on non-HDL cholesterol versus LDL cholesterol.

01:52:52.400 That's typically what the literature talks about.

01:52:54.560 But as you can tell, the non-HDL cholesterol and LDL cholesterol are two of the three variables

01:52:59.620 you would need.

01:53:00.740 So there's a strong correlation between non-HDL cholesterol and remnant cholesterol.

01:53:04.660 And yes, I believe non-HDL cholesterol is more predictive than LDL cholesterol.

01:53:09.400 But there's one problem with non-HDL cholesterol that I definitely want to bring up for people

01:53:13.180 who are on a low-carb diet.

01:53:14.800 If you're going to be powered much more by triglycerides directly, literally triglycerides

01:53:20.160 being brought to you in VLDLs, then that is going to be relevant.

01:53:24.260 Now, again, conceding per what we talked about before, I can't know if I can stake my flag

01:53:29.220 on it just yet.

01:53:30.520 But I'd be willing to bet if I'm right on the energy model that in fact you are being

01:53:33.740 powered more by triglycerides found in VLDLs.

01:53:36.600 Then you could have a higher resulting LDL particles.

01:53:40.020 Effectively, the bigger question is, are particularly lean mass hyper-responders showcasing directly

01:53:46.120 that they are being powered much more by triglycerides brought on these VLDL boats, if you will, and

01:53:51.580 therefore having more subsequent LDL particles?

01:53:54.540 Okay, so my hypothesis is that that is not the case.

01:53:58.120 That it's the higher degree of synthesis, right?

01:54:00.140 Yes.

01:54:00.280 Going on with the cholesterol.

01:54:01.380 That's correct, that it is the higher degree of synthesis, which may or may not also be

01:54:07.040 matched by a higher degree of absorption.

01:54:10.280 If you're going to suggest a way that we could test this, how would you suggest that?

01:54:14.380 Before I do that, let me unpack where I think energy is moving from, right?

01:54:18.540 So I think we all agree that someone who is very insulin sensitive on a low-carbohydrate,

01:54:25.220 high-fat diet is utilizing a lot of triglyceride.

01:54:28.960 We agree on that.

01:54:30.020 Yes.

01:54:30.280 Okay, let's take an artificial construct and separate endogenous from exogenous triglyceride.

01:54:37.300 Meaning, someone on a low-carbohydrate diet is eating themselves and they're eating triglycerides

01:54:44.660 from the outside world.

01:54:45.860 Right.

01:54:46.280 Assuming they're in the phase of getting leaner, right?

01:54:49.020 So they're losing weight or even someone who's weight static, they're utilizing their

01:54:54.180 own internal stores of triglyceride that they're replenishing.

01:54:57.080 If they're staying weight stable.

01:54:58.160 100%.

01:54:58.720 Okay.

01:54:58.980 So the exogenous triglycerides enter the body through chylomicrons.

01:55:06.900 That's a pure lymphatic play through CTEP.

01:55:10.020 That's rapid hydrolysis.

01:55:11.260 I think we all get that.

01:55:12.260 I think it's this other endogenous pool that's interesting.

01:55:15.440 And if I could just interject this one thing, because this is one thing we're dancing around

01:55:18.200 that we both know that probably somebody who's not familiar with my work should be aware

01:55:21.760 of, chylomicrons, they drop off these triglycerides and they're just gone, almost like depending

01:55:27.380 on who you're reading within minutes to hours at the most.

01:55:29.760 So if you're taking a fast cholesterol test, per what we were talking about earlier, you

01:55:33.900 shouldn't see any chylomicrons or chylomicron remnants.

01:55:36.180 They should be gone.

01:55:36.880 And the cholesterol payload on those chylomicrons should be gone.

01:55:40.420 So with that in mind, go back to the endogenous triglycerides.

01:55:44.020 So endogenous means we're dealing with the pool of triglycerides that are coming out of

01:55:49.480 you as the person.

01:55:50.340 So you have adipocytes, adipocytes store triglycerides and those triglycerides are hydrolyzed such that

01:56:00.020 you have free fatty acids that will be transported.

01:56:03.880 So where do they go?

01:56:05.160 So when they come out of the adipocyte, who picks them up?

01:56:09.840 Albumin.

01:56:10.560 So albumin then does two things.

01:56:13.740 It can take it directly to the muscle so that the muscle can use it in the highly fat adapted

01:56:18.320 athlete, or it can take it back to the liver and it can be repackaged in VLDL, or it could

01:56:26.040 be turned into a ketone if we're getting into an extreme state of someone who's ketotic.

01:56:30.000 So let's talk about Craig Moffitt, who looks like a super fit dude who's running around,

01:56:35.320 has a total cholesterol of 457 milligrams per deciliter.

01:56:39.320 His LDL cholesterol is 335, his HDL cholesterol 109, and his trig is 67.

01:56:49.320 So you have, I'm assuming you did the math correctly, I'm not going to check it, but if

01:56:53.100 that's presumably the LDL is direct, his remnant cholesterol is 13 milligrams per deciliter.

01:56:57.940 And by the way, that's not terribly far off from what you would get by the trig by five formula.

01:57:03.300 He's not that far off.

01:57:04.460 Okay, fine.

01:57:05.760 So where is he getting his energy?

01:57:07.520 So let's say he's out for a run, right?

01:57:09.680 So he's not eating anything and he's fat adapted.

01:57:12.440 So he's, and he'll say he's fasted.

01:57:14.280 Let's make it even easier.

01:57:15.260 He's fasted going out for a run.

01:57:16.860 So his adipocytes are releasing free fatty acids to albumin.

01:57:20.500 The albumin is taking some fraction of that to the muscle directly, and they're undergoing

01:57:24.780 beta oxidation there.

01:57:26.740 The albumin is also going back to the liver.

01:57:29.020 And some amount of that is being converted into beta hydroxybutyrate, which goes down

01:57:33.240 its own metabolic pathway.

01:57:34.420 And some amount of that is being packaged in either a VLDL or an IDL.

01:57:38.940 Because remember, there's still de novo ILDL production in the liver, just as there's

01:57:43.920 de novo LDL production.

01:57:46.480 Those VLDLs and IDLs are leaving the liver and dropping off their payload of lipid to

01:57:52.840 that tissue.

01:57:53.860 So the tissue is basically getting ketones from the liver, triglyceride from albumin directly

01:58:00.700 to the muscle, and triglyceride through the VLDL and IDL directly to the muscle.

01:58:05.260 Do we agree on that?

01:58:06.260 We do, I'm just going to expand a little bit on what you just said.

01:58:09.240 So yes, it's full body lipolysis in that you're, he's releasing the free fatty acids

01:58:13.580 in the literature.

01:58:14.500 They're usually calling them NIFA is non-esterified fatty acids, but we'll just keep it to free

01:58:17.780 fatty acids.

01:58:18.880 It's getting released from all over.

01:58:20.060 And we usually measure them by the way, as one.

01:58:22.220 Yeah.

01:58:22.540 It's a little frustrating because a lot of this terminology gets interchanged, but the

01:58:26.040 free fatty acids that are ultimately making it back to its liver, getting packaged

01:58:29.580 into the VLDLs.

01:58:30.640 So while we're talking about the target sites of the muscles for which are making use of

01:58:35.600 triglycerides, I should emphasize that I believe that the primary purpose of the creation of

01:58:39.960 those is to replete everything.

01:58:41.740 So it's not just to fuel the muscles.

01:58:44.900 It's also to put it back into the adipocytes that just now released it as well.

01:58:49.800 In other words, Craig Moffitt, like many people who are lean mass hypersponders, if we could

01:58:55.420 install a little turnstile into their adipocytes, we would see that turnstile just spinning like

01:59:01.720 crazy.

01:59:02.340 They barely parked the triglycerides there before it's heading right back out.

01:59:06.100 And that's because there's less total adipose mass overall on Craig Moffitt compared to somebody

01:59:12.840 who's a lot heavier.

01:59:13.560 And therefore there needs to be more global supply of VLDLs relative to somebody else who

01:59:19.700 has a lot more fat mass.

01:59:21.320 But this depends on his energy requirement.

01:59:23.360 I mean, of course, while he's running, and I wrote a blog post on this a long time ago,

01:59:26.580 which I guess we ought to link to called, it's something about fat flux.

01:59:29.240 I don't remember the name of it exactly, but the gist of it was oversimplifying a fat cell

01:59:33.860 as having two input doors and one output door.

01:59:36.400 The two input doors being the de novo lipogenesis door, which is still an esterified entry door,

01:59:41.060 but I separate it as a different storage, meaning it's coming from a carbohydrate, not from

01:59:46.200 a fat.

01:59:46.640 And then you have the re-esterification door, which is the turnstile that allows fat to go

01:59:50.480 right back in.

01:59:51.380 And then you have the lipolysis door, which allows the fat to exit.

01:59:55.200 So a person who is in fat balance has a situation where L, lipolysis, equals the sum of the esterified

02:00:04.840 de novo lipogenesis plus the re-esterified fatty acids.

02:00:09.400 Agreed?

02:00:09.800 That's just straight up mass balance.

02:00:12.060 So when Craig's running, he's in negative fat flux.

02:00:16.040 Make no mistake about it.

02:00:17.360 His de novo lipogenesis is zero at that moment.

02:00:20.300 His esterification is something, and his lipolysis has to be something bigger.

02:00:24.820 Right.

02:00:25.240 If he's not depleting glycogen, which if he's highly fat adapted, he's not.

02:00:28.480 And maybe it's worth putting out a distinction.

02:00:30.300 I'm not talking about whether they were successfully, at the moment that he's running, successfully

02:00:34.860 re-esterifying these fatty acids back into the adipocytes.

02:00:37.860 And they might be, though.

02:00:38.880 And that's my point, is we don't know.

02:00:40.140 Right.

02:00:40.260 What we know is that in...

02:00:41.440 Which gets back to the question.

02:00:42.260 But do we know that it's the job of the liver to keep maintaining that buffet, to keep putting

02:00:46.520 that energy back out there?

02:00:48.320 And generally speaking, we do know that.

02:00:50.600 It's just to what degree.

02:00:51.740 My hypothesis is yes.

02:00:53.540 My hypothesis is, which is not, by the way, I don't think this is a commonly held view.

02:00:58.100 I think a lot of people would disagree with me, but my view is that the liver is the

02:01:01.860 n-ergostat of the body.

02:01:03.480 I borrow that term from Mark Friedman, who wrote an amazing chapter on this in 2008 that

02:01:08.860 has been one of the most influential things in my thinking on appetite.

02:01:13.180 But he described the liver as the n-ergostat.

02:01:15.620 So as an engineer, you'll appreciate the nomenclature, right?

02:01:18.420 It looks kludgy to someone who's not an engineer to say, why would he call it an n-ergostat?

02:01:23.120 But in engineering speak, that makes perfect sense.

02:01:26.220 But that the liver is probably most susceptible to detecting some currency of circulating energy

02:01:32.680 and circulating metabolites.

02:01:34.800 ATP would be the most logical thing for it to be sensing.

02:01:38.240 So probably ratio of ATP to ADP or ATP to AMP or ADP to AMP, something like that.

02:01:45.020 But yeah, I think the liver, I mean, I think most people don't appreciate how impressive

02:01:49.000 the liver is in general.

02:01:50.140 Like I was just talking to a patient this morning and I said, look, man, here's the

02:01:52.960 deal.

02:01:53.980 Anything that goes wrong with you can be supported extracorporeally, right?

02:01:58.280 You get into a coma, no problem.

02:02:00.320 You need to go on a left ventricular assist device.

02:02:03.020 Okay, it sucks, but like it's there.

02:02:04.960 You need dialysis.

02:02:06.120 You need a ventilator, all that stuff.

02:02:07.680 We do not have extracorporeal support for the liver.

02:02:10.020 It is too complicated.

02:02:11.900 Anybody who follows me knows just how much I'm loving this because you're the, you're

02:02:16.300 the preachers preaching to the choir by far.

02:02:18.520 I've often referred to the liver as like the straight laced partner who always puts up with

02:02:22.820 your crap.

02:02:23.900 He says, whatever you're giving it, it's having to parse out and figure out and balance the

02:02:27.820 ledgers and get everything in.

02:02:29.720 No, no, that's a great point.

02:02:30.820 And that was part of the other point I made to this patient who was not in any way opposing

02:02:34.300 that view.

02:02:34.780 He was just asking if the elevation we'd seen in his liver function tests, which was mild,

02:02:40.340 could explain a synthetic issue to which the answer was not a chance in hell under normal

02:02:44.660 circumstances because the liver has an enormous capacity to do its job under even the most

02:02:49.780 ridiculous stress.

02:02:50.700 So going back to Craig at the moment that he is running, which is the same as saying if

02:02:57.240 someone's losing weight while they're on a low carb diet, they are in negative energy

02:03:01.700 balance.

02:03:02.220 They are in negative fat flux.

02:03:04.020 And again, when I say losing weight, let's ignore the water weight and stuff like, like

02:03:07.160 I'm talking about legitimate weight loss.

02:03:09.460 Metabolism exceeds.

02:03:10.560 Yeah.

02:03:10.960 But that's what it means, right?

02:03:12.300 Like on a practical level, it means lipolysis, the amount of fat that is leaving the fat cell

02:03:17.300 has to exceed that which is reentering it.

02:03:19.400 And again, I don't know that this is entirely relevant, but you've alluded to it.

02:03:23.100 So it's worth reiterating.

02:03:24.480 Not all of that is oxidized, right?

02:03:26.640 Like some of that free fatty acid leaves, doesn't get oxidized.

02:03:29.920 And guess what?

02:03:30.420 Gets mopped back up, provided the hormonal milieu still permits it.

02:03:34.720 Yes.

02:03:35.160 So we agree on that completely.

02:03:37.700 I look at his remnant cholesterol of 13 milligrams per deciliter and say, okay, it doesn't tell

02:03:43.940 me anything.

02:03:45.080 So I apologize because I've sort of lost your question was looking at that, what could we

02:03:49.100 infer?

02:03:49.740 And this probably gets to just the larger problem that I feel like remnant cholesterol

02:03:54.400 is helping us to address.

02:03:55.620 Why is it that anybody would have high triglycerides at all?

02:04:01.700 Why aren't all triglycerides making their way to either the tissue that's using it immediately,

02:04:07.240 the skeletal muscle or the cardiac tissue, or to the adipocytes if the body means to not

02:04:12.260 have it sitting inside of lipoproteins parked in your bloodstream?

02:04:16.380 So that's a totally separate question.

02:04:17.760 I want to come back to this remnant cholesterol question though.

02:04:20.020 But that's where, look, this is why like the original graph that we talked to, this

02:04:24.880 is why I draw that dotted line.

02:04:26.280 I draw a lot of people's attention to it.

02:04:28.240 This is kind of the core emphasis.

02:04:30.000 So this is the energy delivery support diagram for the person who's going to be looking at

02:04:34.180 this later.

02:04:34.820 Right.

02:04:35.380 We see that the chylomicron, I mean, if I'm going to way oversimplify it, but not by too

02:04:39.740 much, chylomicron's job, deliver fat-based energy.

02:04:42.640 Yeah.

02:04:42.860 But it's so far gone that it's not really entering the discussion we're talking about outside

02:04:46.720 of very, very rare diseases.

02:04:49.220 HDL, not to deliver energy.

02:04:51.820 We'll just say things not related to delivering energy, but I just call it support, generally

02:04:56.260 speaking.

02:04:57.380 Operations not related to delivering energy.

02:04:59.760 I agree with that.

02:05:01.180 Okay.

02:05:01.800 Last line, liver.

02:05:03.300 This being the ApoB100 containing lipoprotein is the one lipoprotein that clearly is pulling

02:05:10.700 double duty.

02:05:11.500 No, no, no.

02:05:11.780 But hang on.

02:05:12.140 Remember now we're, this is where your diagram, which you acknowledge is oversimplified.

02:05:16.140 The oversimplification is hurting you, right?

02:05:17.940 So the liver has three purple arrows coming out of it.

02:05:21.780 VLDL, IDL, LDL.

02:05:24.660 Agreed.

02:05:25.100 Which is why earlier I was emphasizing that I believe there was a higher secretion of VLDLs

02:05:29.640 overall for those people who lean mass hyper responders, which is very relevant to our

02:05:34.060 discussion.

02:05:34.760 And how do we know that?

02:05:35.980 It's a theory.

02:05:36.640 I'm not saying that.

02:05:37.320 What I'm saying is, is if this arrow is fatter, if the VLDL secretion is at a greater degree,

02:05:42.600 it would make sense why there would be more remodeled final LDL particles remaining and

02:05:48.560 why we would see the inversion pattern in the first place, because it originated in order

02:05:52.760 to deliver more of those triglycerides, which was brought about.

02:05:56.360 So why the excess cholesterol?

02:05:58.520 If that were the case, Dave, wouldn't you hypothesize that the LDL particle would be

02:06:03.840 very high because you have more VLDL particles, but they're shedding all of their triglyceride

02:06:09.960 in an effort to deliver their energy payload, but you shouldn't have an increased LDL cholesterol.

02:06:15.580 You should actually have a reverse discordance from what we see in the insulin resistant patient,

02:06:21.120 where we typically see the LDL particle number being disproportionately higher than the LDL

02:06:26.160 cholesterol by percentiles, of course, in absolute numbers, that's always the case.

02:06:30.080 In other words, if I was buying your hypothesis, I would say the LDL cholesterol should be very

02:06:35.260 low.

02:06:35.920 You should have very cholesterol depleted skeleton particles that were mostly used to shed triglyceride

02:06:44.040 as VLDL.

02:06:44.740 Instead, we see the concordance.

02:06:46.400 We see the LDL-C and the LDL-P very concordant in people who don't appear to have other types

02:06:50.920 of diseases.

02:06:52.100 Well, at that point, they're so high, it's hard to know, but they're clearly not discordant

02:06:56.160 in the direction that would make sense, given your hypothesis.

02:06:59.180 In other words, what I'm getting at is, why is there so much cholesterol in those LDLs?

02:07:03.220 Correct me if I'm wrong, but as far as the actual drop-off rate, the LDL-C is still going

02:07:08.520 to be relatively standard on a per-particle basis in a healthy subject.

02:07:11.740 How much variability is there typically in LDL-C per LDL particle?

02:07:19.060 Because, and again, correct me if I'm wrong, I thought that the secretion level tends to

02:07:23.300 be fairly standard, kind of like a spare tire is standard per a car.

02:07:27.160 Yeah, it's-

02:07:28.080 The triglyceride levels can be very variable.

02:07:30.460 Yeah, but so can the cholesterol levels.

02:07:32.380 I mean, they have capacity to carry a lot, but think about it, like you have large and

02:07:35.940 small particles that even for the same amount of cholesterol, for the same amount of triglyceride

02:07:39.620 would have different amounts of cholesterol.

02:07:41.140 But the bigger point is, where is the cholesterol coming from?

02:07:44.660 So if we go back and look at my guy, or look at Moffitt, so Moffitt's LDL cholesterol was

02:07:49.100 335 milligrams per deciliter.

02:07:52.220 Right, but that's what's in circulation in the blood at that time.

02:07:55.060 So the larger question-

02:07:56.780 So hang on, just to be clear, Dave, is there any point during his 24-hour day when that

02:08:01.060 number is like 30 milligrams per deciliter of LDL cholesterol in his bloodstream?

02:08:05.780 I don't believe so.

02:08:06.720 So in other words, if you take the area under the curve, if we could get real-time LDL cholesterol

02:08:11.480 number on Moffitt and integrate him over 24 hours, we could argue, for argument's sake,

02:08:17.260 he's going to be always over 300 milligrams per deciliter.

02:08:21.120 His AUC would be very high.

02:08:22.840 Yes, for the LDL particle.

02:08:24.360 I mean, basically what we're talking about is what's, I almost want to say it in terms

02:08:28.460 of like birds in the air, right?

02:08:30.060 Like you have so many ships that have left the dock that are continuing in circulation.

02:08:34.120 I guess here's a different question that I'll pose back to you.

02:08:36.720 How much of that cholesterol-

02:08:37.560 But wait, I'm actually asking this because I'm trying to understand it.

02:08:39.720 How much of this cholesterol has already made a lap?

02:08:41.880 Are you thinking of this in terms of it's all getting synthesized and then reabsorbed and

02:08:45.180 then recreated again?

02:08:46.380 Let's go back and make sure we're agreeing on the same conditions here.

02:08:50.220 Notwithstanding the experiment where they eat a ton of fat and they go from having incredibly

02:08:56.400 high LDL to very high LDL.

02:08:58.440 But let's just take Moffitt.

02:09:01.060 Over the course of a week, assume you could do real-time LDL cholesterol sampling on him.

02:09:07.000 And specifically LDL cholesterol?

02:09:08.960 Yes.

02:09:09.340 Okay.

02:09:10.140 Or everything.

02:09:10.840 Everything that's on your page.

02:09:12.100 You could sample his total cholesterol, his HDL cholesterol, his LDL cholesterol, his VLDL

02:09:17.420 cholesterol, and his LDL particle number.

02:09:19.120 You could sample all of these things in every second for a week.

02:09:23.500 I think we're agreeing that he will always have a very high LDL-P and a very high LDL-C

02:09:28.420 and a low VLDL-C, correct?

02:09:30.960 Unless he eats a lot of fat.

02:09:32.320 We'll come back to that after, but yes.

02:09:33.700 Sure.

02:09:34.720 Okay.

02:09:35.100 So given that the half-life of his LDL is a day, where is that extra LDL cholesterol

02:09:40.640 coming from?

02:09:41.520 I believe it's being recycled.

02:09:43.100 Well, it's always being recycled.

02:09:44.620 Sure.

02:09:44.780 So where is his being recycled?

02:09:46.060 So where is he deficient in cholesterol that a person who has an LDL cholesterol of 100

02:09:52.200 is not?

02:09:53.120 I guess I don't understand the question.

02:09:54.440 Where is he deficient in cholesterol?

02:09:55.920 Yeah.

02:09:56.100 If he's got 335 milligrams per deciliter of cholesterol in his LDL particles, are you

02:10:01.620 telling me that he has less cholesterol in his cell membranes or less of it somewhere

02:10:07.080 else?

02:10:07.520 So he has more cholesterol in his body.

02:10:09.540 Correct.

02:10:10.440 Why?

02:10:10.680 For the same reason that we would have, say, life rafts on a boat, and once we have more

02:10:16.320 boats, we have more life rafts.

02:10:17.920 If we had a harbor just outside this window, right, and you had 100 boats, and on those

02:10:24.180 100 boats, their main job is to deliver something unrelated to life rafts.

02:10:27.500 They're delivering cargo to the other island, right?

02:10:31.380 And they deliver it.

02:10:32.280 100 of them go out.

02:10:33.500 100 of them come back.

02:10:34.360 And then demand on that island has changed.

02:10:37.280 Now they need to deliver five times as many things as they were delivering before.

02:10:41.420 The problem with that analogy is it assumes a completely fixed number of life rafts per

02:10:46.340 boat.

02:10:46.740 It definitely does.

02:10:47.700 But that's not how lipids work.

02:10:49.120 How does it work?

02:10:50.040 There's much more flux in the system.

02:10:51.740 And furthermore, you could ask the question in reverse.

02:10:54.160 Why isn't it higher?

02:10:55.360 Why wouldn't LDL-C be higher on a per boat?

02:10:57.900 Yeah.

02:10:58.100 Why wouldn't LDL-C be higher in that patient?

02:11:00.360 In other words, what's regulating it?

02:11:02.460 What's regulating how much LDL cholesterol he has?

02:11:06.480 The demand for the boats themselves, for LDL particles.

02:11:09.120 What's driving that demand?

02:11:10.300 This is, I think, where we differ, right?

02:11:11.760 The demand is for the cargo, the originating cargo that is clearly getting used.

02:11:15.340 Right.

02:11:15.680 But we agree that the VLDL vanishes very quickly.

02:11:18.560 The VLDL remodels to LDL very quickly.

02:11:21.980 Yes.

02:11:22.440 But if you go through the kinetics of this, I can't follow why he should still have that

02:11:28.540 much LDL cholesterol unless he is making more cholesterol.

02:11:33.140 In other words, I've tried to think of this 10 ways to Sunday.

02:11:36.500 The only way on a mass balance that I can explain this hypothesis is if he's making more cholesterol.

02:11:42.680 And not if he's recycling the same cholesterol?

02:11:45.300 Like, certainly he's making more relative to something he doesn't.

02:11:48.020 Only if he were depleting it in some other store.

02:11:51.540 So in other words, I'm making this up, but like, if you could say, well, all of us,

02:11:55.160 I'm like, I mean, you probably know this.

02:11:56.620 Everyone loves to quote this fact, right?

02:11:58.680 Like red blood cells have more cholesterol in them than LDL particles, right?

02:12:02.620 Right, right.

02:12:03.160 So the LDL denier loves to say, well, we don't think red blood cells are causing atherosclerosis

02:12:08.040 and yet they have more LDL, blah, blah, blah, blah, blah, whatever.

02:12:10.820 But my point is, unless you've depleted a pool of cholesterol elsewhere in his body,

02:12:17.940 just on mass balance, you had to make more of it.

02:12:20.620 As far as I understand, the liver can recycle cholesterol as many times as it wants to.

02:12:25.240 Again, that's true.

02:12:26.260 And the liver and the gut have a very clear pathway, which we described.

02:12:29.900 So correct me if I'm wrong.

02:12:30.760 The liver is the only organ that can actually degrade cholesterol, right?

02:12:34.020 Non-hepatic tissues can't degrade cholesterol.

02:12:36.320 Well, again, it depends what you mean by degrade.

02:12:38.780 You mean, remember, cholesterol has no caloric value.

02:12:41.320 It's something that we metabolize, right?

02:12:42.720 Right, but if you're synthesizing more, you're saying it's going to go somewhere if it needs

02:12:46.440 to be synthesized more.

02:12:47.740 Right.

02:12:47.980 If you're synthesizing more, presumably you have a higher growth of the organism.

02:12:52.960 You have more cells.

02:12:54.080 You need more cells because, obviously, probably the highest demand for cholesterol is for cell

02:12:58.240 membranes.

02:12:59.300 So that's what I'm trying to figure out.

02:13:00.240 It's like, where is all this extra cholesterol coming from if it's not being synthesized de

02:13:04.600 novo?

02:13:05.180 And that's my larger point.

02:13:06.500 The inversion pattern is part of what should bring this to light, is why then when I have

02:13:10.580 an enormous amount of fat, over three days I would see my LDL-C drop by 73?

02:13:15.140 Why would I see my LDL-P drop by 1,115 in three days from eating huge amounts of dietary

02:13:21.420 fat?

02:13:22.340 Why would that happen?

02:13:23.140 I mean, it's an interesting question.

02:13:24.480 I'm just not sure.

02:13:25.740 All it's basically saying is you have a way to perturb those levels.

02:13:30.000 I mean, I'll give you another just anecdote here.

02:13:33.700 You know, I did a one-week fast.

02:13:35.260 I went keto for a week and then ate nothing for a week.

02:13:37.860 And now I'm actually back on keto for a week.

02:13:39.620 And I'm checking my blood every seven days.

02:13:41.360 So that was my LDL-P before I, that's my normal LDL-P.

02:13:47.060 So I'm walking around at 920 nanomole per liter.

02:13:49.620 This is after, you know, months and months of time-restricted feeding with virtually no

02:13:53.360 carbohydrate restriction other than just, I don't eat crappy carbohydrates.

02:13:57.100 Right.

02:13:57.360 So then I went keto for a week.

02:13:59.180 And look, my LDL-P actually went up.

02:14:01.340 Now, I don't think I would meet criteria for being quote-unquote a hyper responder because

02:14:04.900 it went up to 1380, which is not that high.

02:14:07.380 But you know, that's still a significant jump for me, right?

02:14:09.960 Okay, what should it have done when I fasted for a week?

02:14:14.600 Shouldn't it have gone up according to this model?

02:14:17.000 Well, here's the catch.

02:14:18.420 The catch is I only know the three-day window.

02:14:21.260 I don't have a lot of data from people who have fasted for a week, as in just water fasted.

02:14:25.880 I do.

02:14:26.580 Okay, you do.

02:14:27.320 Good.

02:14:27.600 I've done this on multiple patients who have done three, five, and seven-day fasts.

02:14:31.400 Okay, who are fully ketogenic.

02:14:32.880 And you're saying it typically goes down?

02:14:34.220 Not always ketogenic, no.

02:14:35.060 Sometimes they're just, you know, fat adapted.

02:14:37.320 Sometimes they're not.

02:14:37.920 Sometimes they're actually insulin resistant, and we use the fast to kick them into a state

02:14:42.720 of ketosis to make it easier.

02:14:44.500 And again, I want to be very careful.

02:14:46.040 This is simply just anecdote because I've only done this on maybe 30 people.

02:14:50.540 But this is not uncommon.

02:14:52.420 I mean, look, my LDL cholesterol went from 64 to 37 after the fast.

02:14:56.800 I mean, it went way down.

02:14:58.260 Wow, fantastic.

02:14:59.180 And that's consistent with what I see.

02:15:01.000 Now, that's not the reason I'm fasting, to be clear.

02:15:02.740 I don't, I'm not using a fast to manipulate lipoproteins.

02:15:06.440 I'm doing it for a completely unrelated reason.

02:15:07.800 But my point is, I always see, and again, I can say always because it's a relatively small

02:15:12.420 N.

02:15:13.020 Obviously, at a large enough N, you're going to see counterexamples to anything and everything.

02:15:17.200 But the general principle seems to be, under caloric deprivation, LDL goes down.

02:15:22.060 And under fat deprivation, LDL goes down.

02:15:24.900 I've got to put in the one footnote.

02:15:26.540 And it's an annoying footnote that I keep putting in.

02:15:28.500 I really need to, and this is why I'm dying to get these parts of the exercise, I need

02:15:32.200 to look at a population that also is not getting any particularly weight training or resistance

02:15:36.580 training and so forth.

02:15:37.820 Whether it's my theory or not, that seems to impact overall lowering LDL-C numbers.

02:15:43.260 And I'm very curious about this.

02:15:44.360 I mean, I've got that in my patients.

02:15:45.780 Not every one of my patients lifts weights, despite my best efforts.

02:15:49.700 So I think the more common thing that we see is that when you put people on a high-fat

02:15:55.420 diet, the ones that go on to have this hyper-response, as you know, their trigs usually go down.

02:16:02.260 Their cholesterol goes through the roof, and it's driven by a doubling, tripling, or even

02:16:08.860 greater output of synthetic biomarkers, like desmostrol.

02:16:13.540 Now, for reasons I don't understand, you also tend to see at least two other three phytosterols

02:16:18.120 go up.

02:16:18.580 Now, one thing we didn't talk about, though I wrote about it, so I'm sure you know about

02:16:22.800 this, is this seems reversible if you eliminate the saturated fat.

02:16:27.900 It does seem to matter in this case, and you'll like this, at least in our own data with APOE4s.

02:16:33.320 Seems more likely if you're an APOE4, you will see a drop somewhat in saturated fats.

02:16:39.740 So I don't think I have a large enough sample size, because I've only put seven patients through

02:16:43.360 that protocol.

02:16:44.340 And I wrote about the very, very first one.

02:16:46.360 So that's probably the only one that you've seen that I've talked about.

02:16:49.460 But this was a young guy who went on a ketogenic diet, was crushing it, meaning like everything

02:16:56.360 was going well.

02:16:57.320 I mean, he'd, you know, he got through the adaption period.

02:16:59.280 I mean, his performance was exceptional.

02:17:01.200 All, you know, mentally never felt better.

02:17:03.220 He was not an overweight or metabolically ill guy to begin with.

02:17:05.960 He was just kind of a normal software guy who just decided he wanted to take it to the

02:17:09.640 next level.

02:17:10.900 But then he showed up with labs not unlike these.

02:17:13.820 He was the first guy I ever saw where there was a greater than sign on the LDL-P.

02:17:18.920 Right.

02:17:19.060 It maxes out at 3,500.

02:17:20.140 Yeah, I was like, oh, I didn't actually realize the assay stopped at 3,500.

02:17:23.980 This guy's my guy.

02:17:25.640 He looked better on some of the other metrics.

02:17:28.100 He didn't actually have a lot of the inflammatory stuff.

02:17:31.560 This was before the ox LDL assay was commercially available, so I didn't have that.

02:17:35.940 But, you know, his CRP and his LPPLA-2 were okay.

02:17:38.860 But we had the discussion, right, which is the discussion that at the end of the day,

02:17:42.000 I'm accountable for having, which is what are we going to do about it?

02:17:45.360 And he was young.

02:17:46.400 I mean, the guy was 30.

02:17:47.400 So it wasn't like we had to do something tomorrow, right?

02:17:50.620 This is not a guy who's going to have a heart attack in a week.

02:17:52.840 Because I think when you were originally writing about it, he actually pushed back a little

02:17:55.880 bit.

02:17:56.100 Like he wanted to come up with a...

02:17:57.720 Well, what he pushed back on was...

02:17:59.300 Because I basically said, look, man, I don't think the ketogenic diet's right for you.

02:18:02.400 Like, these numbers are crazy.

02:18:05.040 And he was like, yeah, I don't ever want to go back to what I was doing before.

02:18:08.100 I mean, he basically said in not so many words, like, I'd rather die of a heart attack and

02:18:11.420 feel this good than...

02:18:12.620 You know, and he's not saying like, I'm going to die of a heart attack tomorrow.

02:18:14.680 But he's like, look, I'd rather live to 60 and feel this way than live to 70 and not.

02:18:18.160 To which I say, totally fair, by the way.

02:18:20.360 Like, that's a very reasonable trade-off to make.

02:18:23.420 But let's also think about this a little more logically.

02:18:26.300 So that was actually probably the first case I ever discussed with Tom.

02:18:29.420 And this was, I think, back in 2011.

02:18:32.300 And it was actually this discussion, I think, that led Tom to go on to write the lipaholics

02:18:37.840 case, even though it wasn't the patient that he used in that case, because he then went

02:18:42.420 out and found others like them.

02:18:44.440 And what we just decided was on sort of biochemistry first principles, our hypothesis was it's the

02:18:50.580 saturated fat, more than the ketones.

02:18:53.200 Because that was the other thing.

02:18:53.960 This guy didn't want to leave ketosis.

02:18:55.500 Because my thought was, let's just dial this back, get you out of ketosis.

02:18:59.840 But so our hypothesis was both ketones and saturated fat can be readily converted into

02:19:06.300 cholesterol.

02:19:07.380 But if he's adamant on staying in ketosis, let's at least get his SFA down to 25 grams

02:19:12.720 per day, which was hard.

02:19:14.420 This is a guy that was eating about 100 grams of SFA a day, maybe 80 grams.

02:19:18.040 I mean, it was a lot.

02:19:19.160 And we basically just made most of it MUFA.

02:19:22.120 So I said to the patient, I said, look, the way we could do this.

02:19:24.720 Just for no other reason as the purpose of a thought experiment is, you're going to basically

02:19:29.580 have to become a nonstop olive oil macadamia nut eater.

02:19:34.420 Even the avocado you can't go hog wild on because eventually you'll get too much carbohydrate

02:19:38.480 out of it for this purpose.

02:19:40.360 And sure enough, I think he came back at like 1300, you know, after eight weeks or something

02:19:45.240 like that.

02:19:45.760 So six more patients have been so adamant about staying in ketosis and not taking any

02:19:52.500 medication, but wanting to go through this experiment.

02:19:56.280 And all of them have had the same response, which is if you can get them to mainline MUFA,

02:20:00.820 you fix the whole problem without reducing or increasing to any measurable effect, how

02:20:06.760 much fat they're consuming.

02:20:08.040 Have you been keeping track of their PUFA levels too?

02:20:10.380 Because it's hard to add a lot of MUFAs.

02:20:12.780 Their PUFA is going up.

02:20:13.820 And you know the issue with that, with adding more PUFAs.

02:20:16.500 The downside is, is there's the potential that you're actually adding more peroxidation

02:20:20.540 on the particle basis.

02:20:22.540 Yeah.

02:20:22.840 I mean, I think it depends.

02:20:24.400 This is one of those areas where I'm trying to get a lot smarter and I want to make sure

02:20:27.600 I'm not sitting in the echo chamber.

02:20:29.140 I've historically measured RBC levels of arachidonic acid and all of those things and tried to

02:20:34.280 keep track of the ratio of that to the EPA and the DHA and, but ultimately I don't, I

02:20:39.000 don't, I don't really think I know the answer to this yet.

02:20:40.680 And I also don't think, my guess is PUFAs are not as bad as I've historically thought

02:20:45.000 them to be, but they're probably not as good as MUFA.

02:20:47.580 So notwithstanding that, I just want to talk about this from the level of the thought experiment,

02:20:51.860 so to speak.

02:20:53.480 My sample size of those people is too small to know if there's a relationship to their

02:20:57.600 ApoE gene.

02:20:58.540 To your point, what I'm hearing you say is maybe that's more, that's something that you're

02:21:02.320 more likely to do in someone who's an ApoE4 carrier.

02:21:05.140 It's been a proportional kind of thing that we've sort of noticed.

02:21:07.940 I don't know.

02:21:08.460 But what I do know is it seems to point back to this idea that the hyper responders, that

02:21:13.820 the Occam's razor here is that they're making more cholesterol.

02:21:17.000 Because that makes sense from a mass balance standpoint.

02:21:19.540 Again, I'm still.

02:21:20.360 And I would have agreed with you were it not for this energy inversion that I see.

02:21:24.300 If it were not the very thing that I said from earlier, that I could move my LDL-C to

02:21:28.640 where I want to move it, that would be based on me basically arranging for a few days to

02:21:33.160 eat to a certain level.

02:21:35.280 And I'd be pushing down my LDL-C by eating up to a certain amount of saturation.

02:21:38.680 But notice you're pushing up and down on LDL-C within supraphysiologic levels.

02:21:43.500 Meaning, if I recall seeing your data, do you mind showing me that again?

02:21:46.960 Unfortunately, the computer died.

02:21:48.160 Oh, I'm sorry.

02:21:48.740 That's why I've had it closed.

02:21:49.900 But yes, what you'd see is an inversion graph.

02:21:52.020 No, and I'm very familiar with it.

02:21:53.320 And we'll obviously link to it.

02:21:54.520 But it was, as I describe it, you're showing that you can move your LDL between the ranges

02:21:59.940 of very high and stupidly high.

02:22:02.160 No.

02:22:03.440 What's the lowest you've ever got your LDL?

02:22:05.380 98.

02:22:06.200 And I suspect I could get my LDL down to 70 if I was willing to go through with it.

02:22:11.260 There's another part of this conversation we haven't had a chance to touch on, but that

02:22:15.280 you might find very interesting since we talked about the liver.

02:22:17.760 And again, more theory.

02:22:19.240 So about 80% of what I've talked about is an explanation that I'm trying to fit onto

02:22:25.320 what I know.

02:22:26.180 And this is definitely one of those.

02:22:28.280 But I suspect, given the data that I have for the whole second phase of my research, that

02:22:32.960 actually part of how I'm reducing my triglycerides in the blood through a certain series of experiments

02:22:39.380 I call carb swap experiments, is that I'm just trying to get a certain threshold of glycogen

02:22:45.300 stores up in my liver, which seem to be at a certain point, meaning that there will be

02:22:51.260 less VLDL secreted and therefore less LDL.

02:22:53.980 That's the theory.

02:22:55.220 I'm sorry to say again, by moving glycogen, you're doing what?

02:22:59.020 Again, I'm trying to think about it more like as an engineer, whether right or wrong.

02:23:02.860 I think, okay, if I were trying to engineer this body and I were caring a lot about the

02:23:08.840 long-term tank of storage, which is your adipocytes, but I was also to care about the short-term

02:23:13.420 tank, what is the reason why it would make sense from a mechanistic standpoint as to why

02:23:19.180 the body would want to be so adamant about mobilizing these triglycerides for fuel in

02:23:23.700 a low-carb, high-fat athlete, especially somebody who's very lean?

02:23:28.280 And the short Occam's razor, from my perspective, is it comes down to, well, there's very low glycogen

02:23:33.960 stores relative to somebody who's on a high-carb diet.

02:23:37.480 This isn't to say that they have bottomed-out glycogen stores.

02:23:40.080 But relatively speaking, there's less play.

02:23:43.540 And because of that, it makes sense as to why the body would activate more lipolysis,

02:23:47.480 have more of the free fatty acids moving through, keep making it more available, et cetera.

02:23:52.000 Okay, so then how could I tweak that?

02:23:54.980 But wouldn't that also just as easily be explained by the fact that when someone's walking around

02:23:59.880 with 60% of the glycogen in their muscle, there's, by definition, assuming they don't

02:24:06.400 have a sort of pathologic condition, there's not much circulating glucose.

02:24:11.280 And therefore, it's probably they're also in a low-insulin environment, which is fostering

02:24:15.840 lipolysis.

02:24:16.900 Right, but it's gradiated.

02:24:18.260 There's threshold points, which are part of what I'm trying to isolate out.

02:24:21.700 And there seems to be a threshold point with me.

02:24:23.700 For example, if I have around 90, it seems to be the last time I tested this, if I had around

02:24:29.220 90 carbs per day, net carbs per day, that seems to be the magic threshold.

02:24:33.540 If I do that for about three days, my LDL-C will just drop, like, substantially.

02:24:40.080 Now, let's say I did 70 net carbs for three days.

02:24:44.120 I've already done that.

02:24:45.160 It doesn't do it.

02:24:46.260 I have to get up to a certain threshold.

02:24:47.840 And once I get up to that certain threshold, which seems to be somewhere around 90, all

02:24:51.740 other things being equal, like I have to structure my life around this where I, like, sleep the

02:24:55.200 same amount and so forth, that seems to be the point at which there's an actual drop.

02:24:59.320 And I actually wrapped that around one of my presentations, is I actually had a fat shake,

02:25:05.680 a ketogenic shake for, I want to say, three days for a washout period.

02:25:09.640 And then for just two days, I added what I thought would be the calculation to demonstrate

02:25:14.720 what I was looking to do.

02:25:15.780 So I swapped out the fat for carbs, kept it isochloric for two days.

02:25:21.680 I had one that was a lower amount and one that was a higher amount.

02:25:25.340 I can't remember the numbers right offhand.

02:25:27.120 But then, to further emphasize this, I switched back to the high-fat diet for the next five

02:25:34.180 days.

02:25:35.380 And we saw my LDL-C drop almost immediately and continue to remain low for the next five

02:25:41.380 days.

02:25:42.320 And in fact, it got to the lowest point at the end.

02:25:44.840 So it seems to be at least as sensitive on your carbohydrate intake as your fat intake,

02:25:48.780 right?

02:25:49.120 Correct.

02:25:49.460 And this is very relevant because, again, I'm still thinking about this from the energy

02:25:53.920 model.

02:25:54.360 But hang on.

02:25:54.840 I'm not just saying this isn't interesting, but for this to be relevant, it has to be reproducing

02:25:59.480 something that's going to last over much longer than five days.

02:26:03.240 How do we know if these effects aren't transient?

02:26:06.340 And also, how do we know they're relevant if they require an extreme condition, such as,

02:26:12.360 you know, one of them I know you talked about how you just have to force feed yourself a

02:26:15.260 ton of fat.

02:26:16.080 Yeah, that was the very first presentation of my data, where I was having just a,

02:26:19.460 a very high protocol.

02:26:20.440 But that also dropped your LDL-C paradoxically, correct?

02:26:23.560 Correct.

02:26:23.920 But the point is, we have to back up for a moment.

02:26:26.580 Why does any of this stuff matter?

02:26:28.300 In the end, if you're listening to this podcast, or if you're sitting in front of me as a patient,

02:26:32.920 you have a very important question you have to ask yourself if your LDL-C is through the

02:26:37.140 roof as a result of what seems to be your diet.

02:26:40.200 Does it matter?

02:26:40.980 And do you want to do anything about it?

02:26:42.340 Right.

02:26:42.940 And this is why this is the most relevant question, is if you're right, and I'm not

02:26:46.980 saying that I know for sure either way, but let's say that you're right, you, Peter, to

02:26:50.740 you're right, that this, regardless of how we got here, if you have a high LDL-P because

02:26:56.760 of being on a ketogenic diet, then there's a lot of people who need to know that if they're

02:27:01.740 at higher risk.

02:27:02.480 And I definitely want to be one of the people that brings that to their attention.

02:27:05.100 I have emphasized this several times before, and I'll say it once more.

02:27:08.940 I am on a journey of science, not of advocacy.

02:27:12.020 I'm going to be quite a skeptic.

02:27:14.260 But all of that said, if I come to a point in which I can feel convinced that LDL-P is

02:27:18.260 in fact atherogenic, absent remnant lipoproteins, absent having high HDL, low triglycerides.

02:27:24.780 But we already know it's absent remnant lipoproteins.

02:27:27.240 I mean, there's a thousand studies, including this, to demonstrate that the atherogenicity between

02:27:32.100 these people and these people, I'm pointing to the Garvey study, has nothing to do with

02:27:37.040 what may or may not be remnants.

02:27:39.020 The LDL-P alone here.

02:27:41.380 So I think one thing that sort of—

02:27:42.980 I've not seen a study yet where remnant lipoprotein—I mean, I'll send you the ones

02:27:48.180 I have.

02:27:48.500 If you have some where LDL particle is more relevant than remnant lipoprotein, I would

02:27:55.160 be very curious.

02:27:55.700 Well, again, we have to be very careful what we mean by remnant.

02:27:58.220 So there are clearly going to be a subset of remnants that are potentially the most

02:28:03.460 pathologic on a per-particle basis.

02:28:06.440 But I think the body of evidence implicating the causal role of ApoB and LDL-P is so overwhelming.

02:28:13.460 Is it perfect?

02:28:14.080 Of course not.

02:28:15.200 But I think what concerns me with this culture—when I say this culture, I mean this sort of

02:28:19.880 low-carb culture of LDL doesn't matter—is if I had a dollar for every time I had to

02:28:26.680 see some low-carb enthusiast basically dismissing the idea that LDL is relevant and touting

02:28:32.880 the idea that statins are a big conspiracy theory, that's a really dangerous problem.

02:28:38.000 So look, just generally speaking, I think dismissiveness in general.

02:28:41.300 But we do have to care about the quality of evidence regardless.

02:28:43.480 Oh, we sure do.

02:28:44.000 Let me offer a very controversial viewpoint that I can't believe I'm about to voice publicly.

02:28:49.240 I think one of the challenges in the low-carb community is you have a group of people who

02:28:53.140 have become very used to rejecting mainstream information because they did so with nutrition,

02:28:59.420 right?

02:29:00.580 If you are on a low-carbohydrate diet, on some level, you have decided that the ADA, the AHA,

02:29:07.960 the USDA, the NIH, and the CDC are full of shit.

02:29:12.140 I think that's a fair point.

02:29:12.960 Okay.

02:29:13.740 Do you know what?

02:29:14.600 I think that when it comes to nutrition, that's largely true.

02:29:17.740 Now, I think they're coming around, but I think it's largely true.

02:29:21.100 And I think the body of evidence, the body of literature that pointed towards the food

02:29:26.600 pyramid was quite shoddy.

02:29:29.080 I don't think it was nefarious.

02:29:30.440 I don't think this was as much of a conspiracy as people want to make it out to be.

02:29:33.080 I don't think Ancel Keys was some evil dude who was like scheming away to like—I just

02:29:37.760 don't buy that.

02:29:38.320 I think there were strong personalities and lousy science.

02:29:41.580 Those are very different things.

02:29:42.960 And let me go on the record with saying, I basically agree.

02:29:45.220 I feel like there really is—

02:29:45.840 Well, this is the easy part to agree with.

02:29:46.940 Yeah.

02:29:47.380 This is the hard part that's coming up.

02:29:48.700 Okay, go ahead.

02:29:49.100 Okay, so what happens is a lot of people get into this mindset of, well, look, over here,

02:29:54.780 I saw an entire body of evidence that I was very easy to dismiss.

02:29:58.480 And by the way, look at the results.

02:29:59.880 Like, you don't have to be a rocket scientist.

02:30:01.760 If you're sitting there following the food pyramid, getting fatter and sicker, and you

02:30:04.980 abandon it and get better, there's the proof.

02:30:07.300 The real problem, and again, I apologize for getting on a soapbox.

02:30:12.700 The real problem is when people try to look at the last 50 years of lipid literature through

02:30:17.560 that same lens.

02:30:19.380 Nobel Prizes have been won in this field.

02:30:21.340 Now, I know that somebody's going to start screaming, oh, that's an appeal to authority.

02:30:24.620 That's a logical fallacy.

02:30:25.940 I got it to you, whoever said that, I acknowledge it.

02:30:29.940 But unless you're willing to go back and read every one of those papers, something even I

02:30:35.460 have not done, though I've probably read more of them than most, we're talking about apples

02:30:40.100 and oranges with respect to a body of literature here.

02:30:42.860 The body of literature implicating LDL as having a causal role, a necessary but not sufficient

02:30:49.460 role in the pathogenesis of atherosclerosis is on a different level from the body of the

02:30:55.940 literature that gave us the food pyramid.

02:30:58.900 And the real challenge, I think, in this low-carb community, this LDL-denying community, is they're

02:31:04.540 throwing the baby out with the bathwater.

02:31:06.660 Now, part of that is because I think there are too many doctors who are too lazy at the

02:31:12.040 other end of the spectrum.

02:31:13.440 They just assume, well, statins are what we give everybody.

02:31:16.820 Anybody whose LDL-C is above 100 gets to be on a statin.

02:31:19.460 And these doctors are equally guilty, in my mind, of being ignorant and not thoughtful and

02:31:23.720 not understanding the pathophysiology of the disease.

02:31:26.420 But somewhere between these is a measured space that requires a very careful consideration

02:31:32.400 of the literature.

02:31:33.580 So with that in mind, to kind of broad base this pretty well, this whole energy model

02:31:39.280 that we've been talking about, that I've been kind of walking you through and the audience

02:31:43.300 to some degree, it's the lens by which I came up with the challenge.

02:31:48.040 I didn't come up with the challenge because I was just like, today, I just want to tweet

02:31:51.940 out something that I think will get a lot of people annoyed.

02:31:54.860 I believed that I looked at those two sides of the dotted line.

02:31:58.940 And I said, it looks as if, if you are insulin resistant, we tend to see that there are high

02:32:03.600 levels of triglycerides.

02:32:04.700 We tend to see the high levels of VLDL, forget even remnant.

02:32:07.620 We can detect VLDL to a certain extent.

02:32:10.720 We can see that people who are down the range of metabolic derangement, they've got that.

02:32:15.100 And that tends to be highly associated with cardiovascular disease.

02:32:17.740 This is all on the energy delivery side.

02:32:19.520 On the other side of the LDL, we tend to see on the support side that there can be further

02:32:24.640 problems in the immunological role.

02:32:26.340 And oftentimes that can be induced by, likewise, lipolysis.

02:32:30.480 You'll see on the vitamin E studies, for example, this gets brought up quite a bit.

02:32:34.540 For example, if you inject lipopolysaccharides into a body, you'll actually have higher fatty

02:32:40.140 acid synthesis that's going on in the liver along with lipolysis in order to induce that

02:32:44.260 higher response.

02:32:45.620 So again, we see on that side, we see higher levels of triglycerides.

02:32:48.480 And I kept coming back to it.

02:32:50.120 I kept coming, you know.

02:32:50.960 But you're also, as we talked about, when you inject LPS in somebody, you're going to

02:32:53.760 see a higher HDL cholesterol too.

02:32:55.240 I mean, everything at that moment, LPS is a terrible toxin.

02:32:58.800 Like it's going to kick the body into a four alarm fire.

02:33:01.120 For sure.

02:33:01.560 Of course, it's going to want all of the energy substrate it can muster and all of the hormonal

02:33:06.600 precursors it can muster.

02:33:08.220 Agreed.

02:33:08.620 Agreed.

02:33:08.960 So when we're looking at an association between LDL particles and a bad outcome, we want to

02:33:16.480 absolutely confirm it was the cause and not the association, right?

02:33:20.820 But the same reason that if we were to say, I want to confirm ambulances aren't the cause

02:33:25.820 of death for people who are dying inside of ambulances.

02:33:28.360 Yeah.

02:33:28.760 I mean, we have to be a little careful with that analogy.

02:33:30.820 So let's be clear.

02:33:31.940 Can you get atherosclerosis without having an oxidized sterol taken up by a macrophage?

02:33:38.000 No.

02:33:38.700 Okay.

02:33:39.520 So if I could take all the LDL particles out of your body right now, I can feel totally

02:33:43.960 confident that you will not die of atherosclerosis.

02:33:46.120 Okay.

02:33:46.820 So does that not imply that LDL is necessary, but not sufficient for atherosclerosis?

02:33:52.240 I don't disagree with that.

02:33:54.140 Without question, LDL particles are-

02:33:57.100 It's important for some people to understand that because I do think, put it this way,

02:34:02.140 I've certainly heard people in this community argue the following, that the burden of

02:34:07.900 proof should be on the lipidology community to demonstrate that LDL is causal rather than

02:34:14.060 the reverse.

02:34:15.180 And I find that comical if it weren't for tragic.

02:34:18.820 Let's go back to the analogy for a second.

02:34:20.860 Are ambulances causal for ambulance-related deaths?

02:34:24.860 Absolutely.

02:34:26.680 They're a part of the-

02:34:27.760 If I took life-saving-

02:34:29.400 That's not the same thing.

02:34:29.920 I mean, because what you're basically saying is-

02:34:32.600 I'm emphasizing an association over a causation.

02:34:34.920 We both realize that, right?

02:34:37.040 So, okay.

02:34:38.320 It could be in this town, you actually are in worse shape if an ambulance picks you up.

02:34:42.480 There's very incompetent EMTs and their life-saving measures are poorly done.

02:34:46.640 And therefore, if you could ban all ambulances in this town, you'd find that actually-

02:34:50.360 But a Mendelian randomization of ambulances would ferret that out.

02:34:54.200 I would agree if there wasn't anything associated in the ambulance, in the Mendelian randomizations

02:34:59.540 with response by ambulances in the first place.

02:35:02.720 The only way I think you can discount the Mendelian randomization is if you believe that

02:35:08.640 the mutations that you are measuring, so you're looking at a series of mutations that are affecting

02:35:16.100 a phenotype, in this case cholesterol level, you'd have to convince yourself that each and

02:35:21.580 every one of those is also affecting something else that's driving the underlying cardiovascular

02:35:27.580 process.

02:35:28.660 Yes, yes.

02:35:29.560 But we've already went through this, right?

02:35:31.100 It can't be the LDL receptor because that's not even ubiquitous and there aren't LDL receptors

02:35:36.120 on individual cells.

02:35:37.180 I want this tested on a healthy vascular system, however that's occurring.

02:35:41.220 I want every cell to not have-

02:35:42.520 Why does a person with FH not have a healthy vascular system when they're born?

02:35:46.760 When they're born?

02:35:47.500 Yeah.

02:35:48.360 Meaning they inherit a clean slate, right?

02:35:50.160 Someone who's born with FH has a normal, beautiful vascular system that over time, in most of

02:35:56.200 them, becomes destroyed.

02:35:57.200 Just to answer this question, is there any cell in somebody who has FH that would function

02:36:02.920 like a normal cell in somebody who doesn't have FH in order to be able to acquire the

02:36:06.580 lipids or lipoproteins it wants to take?

02:36:08.920 There are plenty of patients with FH who do not have defective, completely defective LDL receptors

02:36:14.880 and therefore are not impeded.

02:36:16.860 Put it this way.

02:36:17.640 Their lipid metabolism is not impeded is what you're saying.

02:36:20.160 Not all of them.

02:36:21.000 Again, we have to be very careful when we talk about FH because there are at least 2,000

02:36:24.480 known versions of that disease.

02:36:26.000 It's very cumbersome.

02:36:27.240 So that's why I think it gets- FH gets talked about like it's one disease.

02:36:31.880 It's a phenotype that has all of these things that can cause it.

02:36:36.080 So the broader question is, is everyone with FH struggling to make steroid hormones?

02:36:44.260 I don't know the answer to that question.

02:36:45.360 No.

02:36:46.280 In fact, FH may be slightly protective in the case of an infection and in the case of diabetes.

02:36:52.600 And one argument for that, the diabetes one's a little hard to explain.

02:36:55.560 The infection one, FH has stuck around for a long time.

02:36:58.540 So there may have been a time when having the ability to mount an incredible immune response

02:37:03.960 would have proved to have a survival advantage.

02:37:06.740 And if you have four times the cholesterol of somebody else, that's one moment in when

02:37:12.780 that could come at a huge advantage.

02:37:14.480 Right.

02:37:14.580 Which gets back to the immunological response.

02:37:16.520 Sure.

02:37:17.000 But to get back to the larger point, I wouldn't blame somebody who has a poor digestive system

02:37:21.280 for being malnourished.

02:37:22.700 As long as we can count on everybody's tissues to be properly nourished and-

02:37:25.520 But I don't understand what you mean by blaming them.

02:37:27.180 Like, help me understand what you mean by that.

02:37:28.600 What I mean by that is if there was a problem with absorption of lipids or lipoproteins unrelated

02:37:34.240 to total quantity of LDL particles, that's what I'm going to care about.

02:37:38.540 And I hopefully will have an answer on this soon.

02:37:40.620 I'm actually working with a couple researchers who I'm trying to get an S&P list together

02:37:45.460 that doesn't include lipid metabolism issues.

02:37:48.860 So Ronald Krauss, who you had on from earlier, he was talking about this, that he-

02:37:52.040 They are looking right now on, for example, lots of the genetic studies, and he was explaining

02:37:57.260 the receptor issues associated with-

02:38:00.320 And this is how you end up with higher levels of LDL-C or LDL-P, right?

02:38:04.440 Is that you end up having less absorption, particularly on the liver side.

02:38:07.360 But I'm especially interested in non-hepatic tissues.

02:38:10.040 But there are.

02:38:10.560 There are people with Neiman-Pixi, one-like-one transporter deficiencies.

02:38:13.900 There are people with ATP-binding cassette deficiencies who have a huge increase in cholesterol.

02:38:19.420 It has nothing to do with an LDL receptor.

02:38:21.440 It's a transporter.

02:38:22.180 I'm not pointing just to the LDL receptor.

02:38:24.240 I'm pointing to just the health of the cell.

02:38:25.920 If the health of the cell is not compromised, then I'm interested.

02:38:29.820 If the lipid metabolism difference-

02:38:31.900 But why would someone who's ATP-binding cassette in their enterocyte that is not appropriately

02:38:39.000 excreting cholesterol, therefore driving up the recirculated cholesterol pool, why does

02:38:45.660 that mean that their endothelium is somehow defective?

02:38:48.920 I would have to follow what the path is that we're talking about.

02:38:51.740 I don't know that I could give an answer to that until I can actually see the study that

02:38:54.680 associates it.

02:38:55.620 If you can take a biopsy of anybody who's going to have this issue, and you can basically

02:39:00.580 effectively see that the cells for which they would be targeted, there is not going to be

02:39:04.200 any problems, I wouldn't have any problem with using it.

02:39:07.320 I mean, basically what we really want, what we really want is just the means of just an

02:39:11.760 overproduction on the part of the liver without it touching any other part of the lipid system.

02:39:15.600 And your point, I'll make your point for you.

02:39:18.180 It's hard to get an S&P that doesn't, in some way, touch other parts of the lipid system.

02:39:23.660 But that's also the point against it.

02:39:25.740 You see what I'm saying?

02:39:26.540 So let me ask you this.

02:39:27.780 You were saying, look, I want more evidence.

02:39:31.000 And I mean, I think science is based on skepticism.

02:39:33.980 I completely respect that.

02:39:36.660 But I think we also have to temper that with some modicum of understanding probability theory

02:39:42.120 and saying, look, at some point, the probability looks disproportionately one way versus the

02:39:46.920 other.

02:39:47.140 So right now, what would your confidence be in the idea that LDL is playing a causal role

02:39:54.240 in atherosclerosis, just as endothelial dysfunction and inflammation play a causal role in atherosclerosis?

02:40:00.800 Let's make a distinction.

02:40:01.740 The distinction is, if you're saying, is it part of the development of an atherosclerotic

02:40:07.260 plaque, it's nearly 100%.

02:40:09.160 If you're saying, is it the total quantity of LDL particles absent any inflammation or

02:40:16.620 anything else along those lines?

02:40:17.440 But nobody's saying that.

02:40:18.180 Nobody reasonable is saying that.

02:40:19.380 So again, listen to what I said, right?

02:40:20.840 So you've got three things that we can sort of use a metaphor and say they form the three

02:40:26.260 legs of the stool.

02:40:27.620 Three things have to happen for someone to get atherosclerosis.

02:40:30.660 Each of them is necessary.

02:40:32.740 None of them alone are sufficient.

02:40:34.780 That's just the nature of complicated biology.

02:40:37.240 Let me help you with the question.

02:40:38.360 I think this would be a better way of asking it.

02:40:40.580 If given the same quantity of oxidative stress, whether it's low or high, would you rather

02:40:46.880 have 1,000 nanomoles of LDL particles or would you rather have 2,000 nanomoles of LDL

02:40:52.840 particles?

02:40:53.580 Yeah.

02:40:53.880 We don't need to ask me that question.

02:40:55.400 I think the question is, what would you rather have?

02:40:57.080 I used to think that I would say the first, that I would rather have 1,000.

02:41:01.960 I would say last year was probably more like, could be about the same difference.

02:41:06.240 Learning what I've learned, especially with the antioxidative defense system and so forth,

02:41:10.700 and particularly given my own data, especially with the CIMT data that I presented recently.

02:41:14.860 I don't know if you've seen that one as well.

02:41:17.500 I was getting a carotid intermediate thickness test every six months.

02:41:23.680 And during those six months in the beginning of this diet and through the experimentation,

02:41:28.780 I was running at LDL-C levels of 200 or higher, LDL-P levels of 2,000 or higher.

02:41:35.280 For four tests in a row, you can actually see the regression that's happening on both the

02:41:39.900 left and right side of the carotid arteries.

02:41:41.820 Yeah.

02:41:42.300 I mean, again, I don't want to get started on CIMT, which is hopefully it's the same tech

02:41:46.700 doing it the exact same way.

02:41:48.360 I mean, I'm guessing your CIMT initially was pretty good and it may have gotten a little

02:41:52.440 bit better, but I don't know.

02:41:54.140 CIMT is even worse than calcium scoring, frankly.

02:41:57.040 Fair enough.

02:41:57.640 But again, Dave, we're putting a couple of N of how many's.

02:42:01.720 We're saying, look, these three little interesting anecdotes are basically calling us to suggest

02:42:08.420 that the null hypothesis around this topic should be what you're discussing rather than

02:42:14.020 what I think is a remarkable body of scientific literature that is not without its problems

02:42:20.120 and that is not absolute in its inference.

02:42:22.880 But it's not what I'm saying.

02:42:24.100 What I'm saying is it might not be what you're saying, but it's certainly what a lot of people

02:42:28.420 are using your words to say.

02:42:29.880 I have an energy model that a lot of people are utilizing probably overly simplistically.

02:42:34.540 But if my energy model is right, it would suggest as to why, the answer of why.

02:42:40.260 But Dave, you haven't even described it correctly to me today, right?

02:42:44.040 I mean, I guess it depends how liberal we want to be with the term model, right?

02:42:46.920 But there is no evidence that the LDL is there to carry cholesterol.

02:42:51.860 You have yet to explain to me where Moffitt got his cholesterol.

02:42:54.740 You're talking about to the quantity they has it at.

02:42:56.700 Yes.

02:42:57.380 The guy's got three times the amount of LDL cholesterol.

02:43:00.380 I think it typically tracks with the total particle count.

02:43:02.980 You have to give me the mass balance.

02:43:04.640 You're an engineer.

02:43:05.320 You know this stuff just as well as I do.

02:43:07.180 If you are a hyper responder coming to cholesterolcode.com right now and you turn over your lab, I can

02:43:12.720 look at your LDL scene before you get-

02:43:14.360 No, no, no, that's fine.

02:43:14.520 That's fine.

02:43:14.840 And look, that's just pattern recognition.

02:43:17.160 That's not the interesting thing to me.

02:43:18.260 I'm asking a very important physiologic question, which you have yet to provide an answer to.

02:43:22.120 And it seems to be the central tenant of your belief system.

02:43:25.780 Where did Moffitt get his cholesterol?

02:43:28.040 Why does he have three times more than he had before?

02:43:31.140 And the short answer to that is he's synthesized it and he's recycling it.

02:43:35.600 Now, there's some degree with which he's synthesizing-

02:43:37.340 Okay, so this is a totally different answer than before.

02:43:40.220 He has now increased his synthesis of cholesterol.

02:43:43.500 He doesn't have the same circulating pool.

02:43:46.120 This is not a shell game with boats, right?

02:43:48.340 No, I was talking about circulating before.

02:43:50.140 No, but what I certainly didn't hear you say before was that he has actually increased

02:43:54.580 his own endogenous production of cholesterol.

02:43:56.820 There's some amount where you're increasing it in order to meet that existing demand.

02:44:01.600 I don't know how much that is.

02:44:03.660 But this is different than what I understood you to say earlier, which is the reason he

02:44:07.160 has more cholesterol is it's just, it's along for the ride with the boats and he has to

02:44:11.740 have more boats, which defies-

02:44:13.780 No, that is correct.

02:44:14.640 But that defies the principle of mass balance.

02:44:16.500 You can't create matter out of nothing.

02:44:18.140 I'm not saying he's creating matter out of-

02:44:19.620 Okay.

02:44:20.020 So he had to make more cholesterol.

02:44:22.500 I don't see a way around that.

02:44:23.680 I'm not disagreeing with him making more cholesterol.

02:44:26.180 I think where we're disagreeing is, I think you're saying in total, he's making three times

02:44:30.940 more every day.

02:44:32.100 Am I wrong on that?

02:44:33.180 On average, he is making three times more or reabsorbing three times more, but just

02:44:38.520 based on what I'm seeing-

02:44:39.800 Reabsorbing at the liver or reabsorbing in non-hepatic tissues?

02:44:42.540 Probably in the gut.

02:44:43.720 That's where the majority of the reabsorption is taking place.

02:44:46.940 Okay.

02:44:47.220 In other words, he's sending it back out the other side.

02:44:49.300 Well, again, this is what we look at these sterile numbers for.

02:44:51.820 When the desmosterol goes through the roof, plus or minus the phytosterols, that tells

02:44:55.780 you these patients are making more cholesterol.

02:44:57.980 Okay.

02:44:58.500 But here's the question.

02:44:59.740 If this were purely about energy, he shouldn't be making any more cholesterol.

02:45:04.540 He should have more particles, perhaps, but they should be cholesterol depleted.

02:45:08.700 You answer this question for me.

02:45:11.080 When does somebody make more cholesterol depleted?

02:45:14.900 Because everything that I've read in clinical lipidology and so forth is it's like a standard

02:45:18.380 quantity on the non-triglyceride side of the ledger.

02:45:22.340 If you're making cholesterol on a per-particle basis, it can vary on a per-particle level,

02:45:27.140 but generally speaking, it tends to hit averages that are fairly consistent.

02:45:30.820 But this is an unusual circumstance you're describing, right?

02:45:33.200 This is the whole purpose of this experiment, is you're describing people whose demand you're

02:45:38.020 saying is so great for triglycerides that they're doing something-

02:45:41.180 That you make more boats.

02:45:42.160 But the boats, if they already have a standard composition, why would they change that standard

02:45:46.340 composition per boat?

02:45:48.300 So are you telling me that you're saying that the large LDL particle and the small LDL particle

02:45:53.640 in the insulin-resistant versus the insulin-sensitive patients have the same cholesterol composition?

02:45:58.940 No, that's my point.

02:46:00.080 My point is getting back to remnant cholesterol.

02:46:02.400 Why it is that I think there would be something that would happen on that dotted line, something

02:46:06.280 before and after, right?

02:46:07.980 Why would there be a problem with somebody who's metabolically deranged with their cholesterol

02:46:11.040 relative to one of these people that are theoretically metabolically flexible?

02:46:15.420 Why would there be a difference?

02:46:17.940 And the short answer to that, the short answer is, I don't know fully all of the aspects to

02:46:21.720 it.

02:46:22.800 I do know, though, there seems to be a longer residence time with VLDLs.

02:46:26.140 And we see that because that's the fastest blood test.

02:46:28.580 Yeah, no, we know that.

02:46:29.500 That's explained very clearly by APOC3, the residence time on VLDL for that matter as well

02:46:34.760 in pathologic states.

02:46:36.120 So if I became more insulin resistant and therefore ended up with higher VLDLs, I couldn't say two

02:46:42.640 years later have healed that and then have less VLDLs.

02:46:45.100 No, look back to the Garvey study.

02:46:46.780 There's a reason I printed this up because I knew we'd be talking about this over and

02:46:49.340 over again.

02:46:50.040 There's very little difference.

02:46:51.920 To try to impute or infer something about remnant cholesterol from VLDL is as complicated

02:46:59.440 as trying to assess LP little a by looking at LDL cholesterol.

02:47:05.080 Think about that for a moment.

02:47:06.340 When you look at LDL cholesterol, if it's directly measured, do you agree that it's the sum

02:47:10.060 total of LDL cholesterol plus LP little a cholesterol?

02:47:14.960 Yes, I believe that's how it's, I believe that's how the test works.

02:47:17.420 Yeah, it excludes VLDL cholesterol and IDL cholesterol because they contain APOE whereas

02:47:22.580 the LP little a and the LDL p do not.

02:47:24.600 So if you have a direct cholesterol measurement, the LDL C is technically LDL C plus LP little

02:47:30.900 a C. But there is no way on God's green earth you can look at that and infer what the LP

02:47:35.980 little a is.

02:47:37.080 Right, without testing directly.

02:47:38.220 Yeah, and similarly, we don't know what's going on with these VLDLs, but meaning in

02:47:44.680 Moffitt because we haven't measured it, but we've measured this in patients that span the

02:47:48.700 spectrum of insulin sensitive to diabetic and that doesn't appear to be the answer.

02:47:54.320 The difference in the atherogenicity, the difference in the residence time, and the

02:47:58.080 difference in the total APOE load appears all driven through the LDL particle, not the

02:48:04.020 VLDL particle.

02:48:05.360 So something else explains why they have more LDL.

02:48:09.100 That's what I want to find out.

02:48:10.500 Again, I'm very upfront about what it is that's theoretical and what isn't.

02:48:13.500 Well, we kind of already know the answer to that question.

02:48:15.180 It's the triglyceride content.

02:48:17.800 But until we can actually test it on people who are fat adapted or ketogenic, we can't

02:48:22.720 say that we do.

02:48:23.440 When we can do a kinetic study on VLDL secretion with people who are particularly like lean mass

02:48:27.640 hyper responders, then we'll have some idea.

02:48:29.700 But Dave, that will only offer you an explanation.

02:48:32.060 It will not change the question.

02:48:35.900 Of risk.

02:48:36.560 Yes.

02:48:36.960 Let's say you can do the kinetic study and hopefully somebody wants to fund this because

02:48:40.500 it is an interesting question.

02:48:41.760 Again, I've done the kinetic study on myself.

02:48:43.920 You've seen my data.

02:48:44.840 Right.

02:48:45.440 I lose triglyceride, not cholesterol.

02:48:47.740 Right.

02:48:48.080 Which I would expect, right?

02:48:50.020 I am seeing cholesterol basically stay the same in those cells during the periods of extensive

02:48:55.960 exercise and fasting.

02:48:57.260 We're seeing triglyceride movement within the cell.

02:48:59.400 But the point is, even if this theory turns out to be correct, it's an explanation, not

02:49:05.940 a reason.

02:49:06.820 It's an explanation for something, but it's not a reason to ignore it, is it?

02:49:10.960 This is where I think we're getting circular.

02:49:13.440 It's an explanation as to why it could be benign or even beneficial.

02:49:17.320 And that's where we're disagreeing ultimately, which I figured we would be, right?

02:49:21.180 Why would you have high LDL for a good reason?

02:49:25.120 And your answer would be, there wouldn't be one, right?

02:49:27.380 No, no, that's not true.

02:49:28.620 There wouldn't be a good reason with respect to cardiovascular disease.

02:49:32.020 There are plenty of good reasons to have high LDL.

02:49:34.240 We just talked about them.

02:49:35.260 The FH patients obviously get some benefit from their high LDL.

02:49:39.600 But from a cardiovascular standpoint, I don't think there is a single good reason to have

02:49:45.160 high LDL.

02:49:45.920 And I am not aware of a single card-carrying lipidologist or member of the community that

02:49:52.440 spends a lot of time in this literature that could come up with one.

02:49:54.500 And I've been asking.

02:49:55.800 I mean, it's something I've been very interested in.

02:49:57.520 Give me a teleologic reason to have high LDL from a cardioprotection standpoint.

02:50:02.420 I mean, I was asking this question seven or eight years ago.

02:50:04.680 I mean, there is no answer.

02:50:06.500 So again, it doesn't mean that having high LDL is always bad.

02:50:10.240 But it's really important to understand this distinction.

02:50:13.160 The other thing to keep in mind is lots of things in biology are not linear.

02:50:17.660 So look at Gilbert's syndrome.

02:50:20.240 Gilbert's syndrome is a very common condition.

02:50:23.380 You know, 2% or 3% of people listening to this have it, probably don't even know it.

02:50:26.340 But they have elevated unconjugated bilirubin, but very slightly elevated.

02:50:31.260 So if you've had a blood test done, you probably know down at the bottom it says, you know,

02:50:34.620 ALT, AST, bilirubin.

02:50:36.440 And normal bilirubin would be less than one.

02:50:38.720 But these patients with Gilbert typically get to about two.

02:50:41.540 Well, in half a dozen studies, these patients have an enormous risk reduction in cardiovascular disease.

02:50:48.540 Why?

02:50:49.620 Why would having a slight doubling of bilirubin, which by the way, at high levels is toxic.

02:50:54.780 So if you walk around with a bilirubin of 10, you're not going to be around very long.

02:50:58.980 And those patients present, they get sick, they have obvious symptoms, they're jaundiced, and they usually have some pathology that's leading to it.

02:51:05.000 But these patients can walk around with a bilirubin of 1.6 to 2, and they seem to be getting a benefit from it.

02:51:11.800 And they also seem to have lower LDL.

02:51:14.580 And even if they don't have lower LDL, because the literature is mixed on this, they always have lower ox LDL.

02:51:19.940 And it may be that the best explanation is that bilirubin has antioxidative properties.

02:51:28.080 So they get this protection from cardiovascular disease.

02:51:31.740 But it's a U-shaped curve, or an inverted U-shaped curve, rather.

02:51:35.660 Meaning, as that bilirubin gets higher and higher, they start to lose any of that benefit.

02:51:40.320 Right.

02:51:40.580 Meaning, whatever oxidative benefit they get, it's more than being outweighed by the damage that comes from that elevated bilirubin.

02:51:47.260 So, I guess my point here is, even if there's an explanation for why this is happening from an energy trafficking standpoint,

02:51:55.200 which, again, I really want to be clear, I do not think there is.

02:51:58.320 I do not think that energy trafficking explains this phenotype.

02:52:01.500 I think that is not the Occam's razor answer.

02:52:04.380 I think the Occam's razor answer is they're making a boatload more cholesterol.

02:52:07.480 Because I think we have pretty good data to suggest that.

02:52:09.920 Which I'm dying to test, by the way.

02:52:11.120 Yeah, yeah, I know.

02:52:11.660 I mean, we should make sure that you can, and that other people can do this.

02:52:14.400 But, of course, the point here is, it still won't actually answer the question, what should you do about it?

02:52:21.680 Just because there's a reason for something, doesn't mean that it's a benign condition, or that it should be ignored.

02:52:27.020 I agree, and not only that, it's separate subjects.

02:52:29.300 I'll even go a step further and say, it could be a U-shaped curve on this end as well.

02:52:33.760 It could be that you could have an LDL-P of, say, 1800.

02:52:37.220 And it turns out that's actually the bottom of the curve, and people at 1800 don't turn out to be as high a risk as people that are, like the one you just showed me, above 3500.

02:52:46.180 I not only grant that, I also further tell lean mass hyper-responders, I may turn out to be right on my cautious optimism as far as the risk in cardiovascular disease,

02:52:55.460 but it could turn out that there's something else we haven't yet determined.

02:52:58.340 That's a problem with this phenotype, which is another reason why we should be sharing all the symptoms that may be coming along with it as well.

02:53:04.060 But all of that said, all of that said, the larger question is, why then would I be able to identify a certain set of parameters that, when studied, seem to suggest that high levels of LDL-C, I want some with high LDL-P, doesn't prove to be problematic?

02:53:22.080 And that's why I want to get a hold of something.

02:53:23.540 I want to get a hold of a really large data set.

02:53:25.440 But how will you demonstrate that?

02:53:25.980 By stratifying.

02:53:27.260 Stratifying for HDL, high HDL, stratifying for low triglycerides.

02:53:31.560 No, no, no.

02:53:31.820 And stratifying for high LDL particle.

02:53:33.260 Know if they're not at increased risk for cardiovascular disease.

02:53:35.600 How long will you need to follow them to know that?

02:53:37.560 Well, that depends on the data set I can get a hold of.

02:53:39.900 I'm not in your space, so I have to work with other people who are researching it.

02:53:43.720 You're saying you want to do this with retrospective data?

02:53:46.120 Correct.

02:53:46.560 Okay, so meaning this is your challenge to say, don't give me genetic data, don't give me drug data.

02:53:50.640 I'd like just normal, non-drug, non-genetic stratified people, preferably.

02:53:56.800 And I'd like to stratify just on those three, just on HDL, LDL.

02:54:00.620 Even though your patients probably have some genetic SNPs that are explaining their phenotype.

02:54:06.180 Oh, I would definitely want to know that as well.

02:54:07.760 That's why I'm trying to actively get the 23 in me.

02:54:10.000 I would love to send it your way around us and so forth.

02:54:11.420 But the point is you're excluding anybody who has anything that could be called the genetic

02:54:14.760 alteration, even though the patient population you're trying to understand this in almost

02:54:18.500 assuredly has a genetic alteration that's rendering them susceptible.

02:54:22.120 I'm not trying to exclude that.

02:54:23.480 But you just said you don't want to consider any of the genetic drivers of FH.

02:54:29.500 Let me emphasize, if you're making a study that is gene-specific, then it's the gene that

02:54:34.840 drives the detection, the discovery of those people, right?

02:54:38.180 I don't want to do that.

02:54:39.240 I want to actually see if I can get a broad-based study of people who happen to already have

02:54:44.060 high HDL, low triglycerides, and high LDL, and see if they have high rates of not only

02:54:48.440 cardiovascular disease, but all cost mortality.

02:54:49.740 But again, I come back to the FH patients.

02:54:51.880 You can't find a more broader demographic of people in terms of variable genetic inputs

02:54:57.880 that produce a phenotype similar to what you're looking at.

02:55:00.760 I think we're just going to end up in one of these got to agree to disagree moments.

02:55:04.120 Until I can...

02:55:04.840 Which is fine.

02:55:05.560 I totally respect that.

02:55:06.560 But I just want you to understand what it sounds like from over here is you're looking

02:55:09.860 for a six-footer and you're not going to be happy until you see a six-footer.

02:55:12.480 And gosh, doggone, you're not going to leave the kindergarten classroom until you find one.

02:55:15.720 I would argue the opposite.

02:55:17.100 I would say, look, if I could right now just grab a million people in the United States,

02:55:22.000 just absolutely randomly determine, why would that not be significant data if I found that

02:55:26.620 people...

02:55:27.240 There was the stratification for which high LDL did not result in high levels of cardiovascular

02:55:31.740 disease or all-cause mortality.

02:55:33.240 Well, because if you're going to do that honestly, you're going to say, well, they can't have a

02:55:36.260 single genetic mutation.

02:55:37.380 They can't be taking a single drug and they can't be on any funky diet.

02:55:40.560 Let's say all of that turned out to be true.

02:55:42.680 What if they don't exist?

02:55:43.740 If I found that out, that would be definitely something I think would be very interesting

02:55:46.840 to my followers.

02:55:47.680 I would turn that back around.

02:55:48.660 But you'll never know if you found that out or not, Dave.

02:55:50.740 Well, I've already found two studies that do stratify for those three.

02:55:54.100 And of the two that do, high LDL does not result in high rates of cardiovascular disease.

02:55:58.500 Wait, wait.

02:55:58.800 You're talking about these glycogen storage disease cases?

02:56:01.700 No, no.

02:56:02.180 Framingham Offspring has one study where they stratified by three.

02:56:05.480 And I, unfortunately, my computer's data, I'd show you the other one.

02:56:08.120 There's another one that stratified discreetly between below 170 LDL-C and above 170 LDL-C.

02:56:14.980 And the high HDL, low triglyceride group, when compared to above and below, were nearly

02:56:20.040 identical, both on the high side and on the low side.

02:56:23.220 Yeah, but this study didn't stratify by ApoB.

02:56:25.540 Right.

02:56:25.900 I would love to have ApoB.

02:56:27.100 Okay, but that's the Quebec heart study for you right there.

02:56:29.560 The Quebec heart study has the stratification by all three of those metrics.

02:56:33.520 The Quebec heart study here, I printed it up here.

02:56:35.540 I mean, it basically is showing, it has nothing to do with the LDL-C once you know the ApoB.

02:56:40.900 Look at the risk.

02:56:41.760 Okay, I'm trying to get those three in conjunction.

02:56:44.800 I want to specifically stratify those three.

02:56:48.100 And in software, this is where I get a bit frustrated because I feel like there's such

02:56:52.100 a cultural difference between medicine and software.

02:56:55.500 We're used to having just loads and loads of free data, just like we're awash in free

02:56:59.020 data.

02:56:59.440 Google can't wait to give me everything that I want to see.

02:57:02.540 I requested, I've actually applied.

02:57:05.120 I know, I've heard you talk about it.

02:57:07.160 And are you being denied that or do they not have the data?

02:57:09.760 They just don't return my emails.

02:57:11.320 There's even people that I would think would be sympathetic inside the low carb community,

02:57:15.620 and I'm not going to try to call them out, who I've also tried to get this information

02:57:19.580 from.

02:57:20.420 And I just can't get it.

02:57:22.080 And I want just a nice, clean regression on three axes.

02:57:25.060 That's all I want.

02:57:26.680 That's nice and fat.

02:57:27.840 So the three axes being?

02:57:30.060 Triglycerides, HDL, and preferably LDL-P.

02:57:33.780 Now, there is an important distinction we've got to make with APO-B because APO-B can, in

02:57:37.640 theory, also include remnant lipoproteins.

02:57:40.900 Yeah.

02:57:41.140 LDL-P is more accurate than APO-B.

02:57:42.960 Right.

02:57:43.500 And LDL-P would be extremely fantastic.

02:57:46.000 If you could help me get in touch with that data set, I would be very interested.

02:57:49.080 Not with any major adjustments.

02:57:50.980 I mean, you know, whatever, Cox proportional, something like that might be fine.

02:57:53.760 But just generally speaking, if I could get a big fat data set and stratify on those three

02:57:58.560 axes, I think that would say a lot as to whether there's any validity to the energy

02:58:02.920 model overall.

02:58:03.860 So when you look at the MESA data, which stratify on a Kaplan-Meier curve, the difference between

02:58:09.840 LDL-C and LDL-P, you're saying that that's not relevant because it...

02:58:17.880 The thing we're dancing around here is obviously when you have high HDL-C and you have low triglycerides,

02:58:22.700 it suggests a number of different things.

02:58:25.560 But more broadly, it's suggesting a properly functioning lipid energy system and probably

02:58:30.080 not being in a state of a challenge of...

02:58:31.940 HDL-C tells us absolutely nothing.

02:58:35.160 If we've seen enough from Mendelian randomizations and another, how many more CTEP failures do

02:58:39.880 we need to see?

02:58:41.040 HDL-cholesterol tells us nothing about HDL function.

02:58:44.020 In fact, anytime you increase HDL-cholesterol pharmacologically, you seem to make patients worse.

02:58:49.700 I know, but these are modifications to the existing lipid system.

02:58:52.440 I get that, Dave, but boy, if you're going to hang your hat on, it's all about HDL-C triglyceride.

02:58:58.780 I mean, wow, we are so far beyond that in the lipid world at this point.

02:59:03.220 Like, if you're going to go through this brain damage, make it for something worthwhile.

02:59:06.860 But wouldn't you predict right now that if I did hang my hat on those two things, on those

02:59:11.980 two markers against LDL-C or ApoB or LDL-P, that it would fail?

02:59:18.720 That if I were to say, hey, I want to get a stratification just of high HDL-C and low triglycerides,

02:59:24.260 that you'd say, sure, Dave, I'll bet you $10,000.

02:59:27.260 I'll give you 100 to 1 odds.

02:59:29.240 Those people with high LDL, even if you stratify for those two, will still have high rates of

02:59:34.000 cardiovascular disease.

02:59:35.120 Again, I'd have to completely see the patient population before I could even hazard a guess.

02:59:38.480 But right now, you would assume that, right?

02:59:40.920 I am going to assume that LDL-P is going to be a stronger marker of prediction than HDL-C.

02:59:48.260 And that's not what I'm making the case on.

02:59:50.120 What I'm making the case on is whether or not there's a properly functioning lipid metabolism,

02:59:53.780 which would be indicated by all three of those.

02:59:55.300 No, you have absolutely no understanding of the lipid metabolism by looking at HDL-C and

03:00:00.140 triglyceride.

03:00:01.260 I mean, not even close.

03:00:02.880 No, no, no.

03:00:03.220 This isn't like we can disagree on things that are nebulous.

03:00:05.960 This is not nebulous, Dave.

03:00:07.080 This is, I mean, again, I hate that I'm saying this because I sound like a jerk and I don't

03:00:10.600 mean to.

03:00:11.120 You've got to spend more time with lipid people.

03:00:13.580 You really do.

03:00:14.460 You are not dealing with your peers at this.

03:00:16.560 You have to go and figure out like HDL-C is just categorically not a useful metric.

03:00:23.080 It is like a first order term on a, like, no, no, it's not even that.

03:00:28.040 Like in engineer speak, it's the fourth order term on a fifth order polynomial.

03:00:33.220 That hurts, Peter.

03:00:34.340 That hurts.

03:00:34.880 I mean, come on.

03:00:35.700 It's just not that interesting.

03:00:37.520 I'm just kidding.

03:00:38.360 I'm just kidding.

03:00:39.020 Look, it's super crude.

03:00:40.660 And don't confuse the ubiquity of it with its utility, right?

03:00:45.300 The ubiquity of it is, yeah, it's cheap.

03:00:47.080 It's easy.

03:00:47.860 Everybody's got it.

03:00:48.700 But like, let's not let people listen to this and get lulled into a false sense of,

03:00:53.860 hey, if my HDL is high and my trigs are low, who cares what my LDL is?

03:00:58.920 And unfortunately-

03:01:00.020 I want to prove that right or wrong.

03:01:01.560 Well, first of all, you'll never prove anything in science.

03:01:03.700 So let's be really clear on our lingo.

03:01:05.720 Okay.

03:01:06.160 No, no, no.

03:01:06.500 It's very important.

03:01:07.460 Fair enough.

03:01:07.840 No, no.

03:01:08.040 It's important for your listeners to understand that.

03:01:10.480 Fair enough.

03:01:11.120 Fair enough.

03:01:11.520 But likewise.

03:01:11.840 Nothing is proved.

03:01:12.680 It's about probability.

03:01:13.860 Sure.

03:01:14.360 But likewise.

03:01:15.180 Would you say the Lippin hypothesis is proved?

03:01:17.500 Absolutely not.

03:01:18.240 God, I just said there's nothing outside of mathematics that exists in a proof.

03:01:22.500 Right.

03:01:22.900 Nothing.

03:01:23.960 And I have the basis of the luxury of having been a mathematician once.

03:01:27.100 So I get it.

03:01:27.740 There's a luxury of being able to write QED at the bottom.

03:01:31.100 We will never do this here.

03:01:33.260 And if people are sitting there saying, well, I'm going to keep eating my bacon and eggs

03:01:38.380 like it's mainlining and ignoring my LDL-C because my HDL-C is high and my trigs are low

03:01:44.480 because, you know, I'm on a low-carb diet and somehow that makes me special because no

03:01:50.040 one's proved that this is wrong, wow, that's not the legacy I want.

03:01:55.440 So what if I continue to find more data sets that actually support that?

03:01:59.340 What do I do?

03:02:00.420 I don't know.

03:02:00.880 I don't know what that means.

03:02:01.840 What do you mean by more data sets?

03:02:03.440 Meaning more anecdotes?

03:02:04.880 No.

03:02:05.220 I'm talking like, let's say I do actually get a hold of Framingham Offspring.

03:02:08.840 Let's say I get a hold of, I forget what some of these larger data sets are and what

03:02:12.720 you have to go through.

03:02:13.900 Mesa.

03:02:14.360 Sure.

03:02:14.800 Let's say I can get Mesa and I can stratify for those three and it's showing the same

03:02:17.660 thing without doing a lot of adjustments or anything along those lines.

03:02:21.760 What would I tell my followers?

03:02:23.240 I would say, no, it looks as if still there's further evidence that showing high LDL-C in

03:02:27.520 this case is not problematic.

03:02:29.280 Or Mesa did actually stratify for LDL-P, didn't it?

03:02:32.400 Yes.

03:02:32.860 Yeah.

03:02:33.540 So that'd be a great example.

03:02:34.960 Mesa would be fantastic data to get a hold of.

03:02:36.880 Is that something you think I would ever actually be able to see or be able to run regressions

03:02:40.460 against?

03:02:41.040 I've never thought of it, but I agree with you.

03:02:43.340 That would be great.

03:02:44.280 I don't know who owns the data.

03:02:46.080 But would that be compelling to you?

03:02:47.920 If it turned out that we could run regressions, let's say that it was in the next room right

03:02:51.660 now and we worked it up on the computer and sure enough, I went by these stratifications

03:02:55.900 I was looking for that are like identical to somebody who would be, and they were typical

03:03:00.980 to somebody who was already a lean mass hyper responder and would show that they didn't have

03:03:05.400 high rates of cardiovascular disease.

03:03:07.660 Would that be compelling data to you?

03:03:09.500 I think compelling is the wrong word.

03:03:11.380 But the question is, how would it add to the existing body of literature that informs

03:03:15.960 a decision we have to make every day with a patient?

03:03:18.340 And the answer is, I'd have to see the strength of it and decide, how does this fit into the

03:03:22.740 existing body of literature?

03:03:24.300 I mean, that's the only way I can imagine thinking about this.

03:03:27.420 But everybody listening to this and you and I all have to put our heads on a pillow at night

03:03:32.680 with a null hypothesis against which we have to challenge existing data.

03:03:37.980 And I'm not convinced that the null hypothesis here should be anything other than the lipid

03:03:43.340 hypothesis.

03:03:44.320 Now, the lipid hypothesis gets bastardized all the time.

03:03:47.320 It gets misstated all the time.

03:03:49.120 It gets based on LDL-C and a whole bunch of other stuff.

03:03:52.780 But I'm talking about the real honest to goodness, no bullshit LDL hypothesis, which again, I've written

03:03:58.720 about eloquently and people have written about it far more eloquently.

03:04:01.980 I should say I've written about it in a kludgy way.

03:04:04.080 Others have written about it eloquently.

03:04:06.240 The lipoprotein, the endothelial damage, the inflammatory changes, all of these things

03:04:11.640 cascading, that's my null hypothesis.

03:04:14.880 And in the end, if there's data to counter that, I'm all for it.

03:04:18.580 For example, even when you look at the IL-1, IL-6 agonists, the low-dose mesotrexate studies

03:04:23.740 that showed you could delay or reduce cardiac events without changing lipoproteins, I don't

03:04:30.740 think I'm being delusional when I say that doesn't change the model.

03:04:35.620 It actually feeds into the model.

03:04:36.740 The model is there are three things that are driving this pathology.

03:04:39.880 If you reduce one of them, things get better.

03:04:42.360 All things equal if blood pressure goes down.

03:04:45.140 Do outcomes get better?

03:04:46.460 I believe they do.

03:04:47.200 Absolutely they do.

03:04:48.300 Yeah.

03:04:48.820 Very potent.

03:04:49.540 Why?

03:04:49.980 Endothelial function.

03:04:51.060 All things equal if you stop smoking.

03:04:52.860 Do outcomes get better?

03:04:54.220 Absolutely.

03:04:54.660 So when you start to look at all of these things, and again, with those-

03:04:58.740 But by outcomes get better, you're specifying-

03:05:00.260 Cardiac outcomes.

03:05:01.080 Right, cardiac outcomes.

03:05:01.900 The all-cause outcome is a much more complicated question that probably has a podcast in and of

03:05:06.520 itself.

03:05:07.120 To your question, yeah, Dave, of course.

03:05:09.540 I'd be incredibly curious to see this.

03:05:11.560 Who wouldn't be?

03:05:12.580 But don't think that one regression analysis on MESA is going to turn over 50 years of data,

03:05:18.480 regardless of what it shows.

03:05:20.020 The question is, how does it alter our understanding and thinking of the problem?

03:05:23.840 Look, the whole reason I'm even pursuing this particular strata is because of the model

03:05:28.600 in the first place.

03:05:29.440 I had to have something that I could conceive of that would inform the decision by which I

03:05:33.380 would be looking for what the data is that would disprove it.

03:05:36.660 That's why I'm in pursuit of disproving it.

03:05:38.580 At the end of the day, Peter, I can't emphasize this enough.

03:05:41.120 I'm not looking to talk to the echo chamber or looking to just maneuver around inside of a

03:05:45.840 number of people that are going to congratulate me.

03:05:47.760 I specifically-

03:05:48.760 But I think you're better off going to an NLA meeting than a low-carb meeting.

03:05:52.140 Sure, but they're freaking expensive.

03:05:54.020 I've looked at all of them.

03:05:55.300 I got the low-carb community to fund you.

03:05:58.100 If they want to know the answer, because I don't think they do, if I'm going to be brutally

03:06:01.920 honest, I think the worst of that crowd just want their confirmation bias.

03:06:06.760 They have seen these incredible benefits of low-carbohydrate diets, and their belief

03:06:11.240 is nothing can be wrong with this.

03:06:13.680 Like we somehow live in a monodimensional, monochromatic world where like it's that black

03:06:19.580 and white, and if the diet is good for this, it can't be bad for anything.

03:06:24.740 And they are so wed to that that they construct these crazy arguments.

03:06:29.360 But if they share your passion for truth, then they should happily fund you to go to an NLA

03:06:34.140 meeting and spend a week there and actually start hanging with these guys who are way smarter

03:06:40.040 than me.

03:06:40.780 Like I'm a knucklehead.

03:06:42.140 I mean, I know a lot about lipids for a knucklehead, but I'm talking about like the smartest

03:06:46.760 people in the world are the ones you need to be talking to on this topic.

03:06:50.980 And they're not at low-carb conferences.

03:06:53.100 I promise you that.

03:06:54.840 They're not on Twitter.

03:06:56.220 They're not playing patty cakes on their like high-carb or whatever low-carb blogs.

03:07:00.780 Like it's just not about that stuff, man.

03:07:03.000 And again, I mean, I think what you're doing is really interesting.

03:07:06.380 I don't agree with the model, but I'm glad that you're pursuing it.

03:07:10.340 I wish you the best in pursuing it with the right people.

03:07:13.440 Absolutely.

03:07:13.840 Well, and perhaps you'll be able to help me set up with the right people.

03:07:17.460 I would definitely be more interested in finding those voices that can help tear at

03:07:21.060 this model.

03:07:21.720 I would be more than happy to help in any way I can.

03:07:23.700 Great.

03:07:24.080 I can't emphasize enough, as I anticipated, I was going to ask you more questions than

03:07:27.500 you asked me.

03:07:28.500 I'm really appreciative that you took the time to chat with me about this.

03:07:31.480 No, my pleasure, Dave.

03:07:32.340 Thank you very much.

03:07:33.240 I apologize if this just took longer than we thought it might have.

03:07:36.940 And I know we went off on tangents all over the place.

03:07:40.340 I guess this will be one where the show notes are probably quite helpful.

03:07:44.020 But nevertheless, it was great meeting you in person.

03:07:46.320 I didn't realize it's only been three years since you've been at this.

03:07:49.520 It feels like a lot longer, actually.

03:07:52.200 It certainly does for me.

03:07:53.580 And my wife would say it's felt twice as long for her.

03:07:56.280 I mean, you have to realize something.

03:07:58.080 Almost nobody knew about me a year and a half ago.

03:08:00.620 And I knew almost nothing about cholesterol three years before that.

03:08:04.600 This has absolutely been a fresh journey.

03:08:07.040 And that's why I have to oftentimes emphasize that I'm not a formally trained biochemist.

03:08:11.500 I really have a lot of gaps, I'm sure, in my knowledge that I'm looking to fill and find

03:08:17.480 as fast as I can.

03:08:18.800 All right.

03:08:19.220 Well, it was great to meet you.

03:08:21.140 Enjoy your time in San Diego.

03:08:22.320 Oh, by the way, for the listener, this is being recorded on July 26th.

03:08:28.500 It will be a long time before this goes up, Dave.

03:08:30.820 So hopefully the listeners understand that whatever's transpired since then is just...

03:08:34.600 We pre-record these things many months in advance.

03:08:36.500 We may have to bump it up a little bit, depending on...

03:08:39.260 Maybe we can reshuffle it and get it out before the end of the year, which is probably right

03:08:43.340 now where it sits in the pipeline.

03:08:44.620 But you're going to subject me to quite a hell because I'm guaranteed every single

03:08:48.460 follower I have is going to be knocking on my door until this thing is opened up.

03:08:53.280 So that'll be pretty funny.

03:08:54.400 We'll do what we can.

03:08:55.300 Anyway, man.

03:08:55.840 All right.

03:08:56.180 Thanks so much.

03:08:57.100 Absolutely.

03:08:57.440 Awesome to finally meet you.

03:09:00.520 You can find all of this information and more at peteratiamd.com forward slash podcast.

03:09:05.780 There you'll find the show notes, readings, and links related to this episode.

03:09:09.960 You can also find my blog and the Nerd Safari at peteratiamd.com.

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03:09:16.080 Just click on the link at the top of the site to learn more.

03:09:18.920 Maybe the simplest thing to do is to sign up for my subjectively non-lame once a week

03:09:22.860 email where I'll update you on what I've been up to, the most interesting papers I've

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03:09:37.080 But usually Twitter is the best way to reach me to share your questions and comments.

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The Peter Attia Drive - October 08, 2018

#19 - Dave Feldman： stress testing the lipid energy model

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