#229 ‒ Understanding cardiovascular disease risk, cholesterol, and apoB
Episode Stats
Length
1 hour and 18 minutes
Words per Minute
156.12349
Summary
In this episode, we re-visit a topic covered in depth in previous episodes: Atherosclerotic cardiovascular disease. Why is it so important to care about this topic? And what are the tools we have to mitigate it?
Transcript
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Hey, everyone. Welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,
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my website, and my weekly newsletter all focus on the goal of translating the science of longevity
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into something accessible for everyone. Our goal is to provide the best content in health and
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wellness, full stop. And we've assembled a great team of analysts to make this happen.
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If you enjoy this podcast, we've created a membership program that brings you far more
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in-depth content. If you want to take your knowledge of the space to the next level at
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the end of this episode, I'll explain what those benefits are. Or if you want to learn more now,
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head over to peteratiyahmd.com forward slash subscribe. Now, without further delay,
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here's today's episode. Welcome to another special episode of the drive. As the podcast is now over
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four years old, we realize we've covered certain topics in a variety of ways across multiple
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episodes. We realize, of course, at times it can be hard to piece together this information,
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and it's also difficult for new listeners to be able to go back and keep track of information
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that's been covered in great depth in previous episodes. As a result, we wanted to release
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another episode that is kind of a compilation of clips from previous episodes. We did this before,
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and it was a huge success. So for this one, we want to focus on atherosclerotic cardiovascular
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disease, ASCVD, cholesterol, and ApoB. This episode includes clips on why it is so important
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to care about ASCVD, the role of cholesterol in ASCVD, and why I don't think anyone should refer to
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cholesterol as good or bad. And finally, we look at why ApoB is an important metric to track when
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looking at your lipids. We put these clips in the order of what we think is the best way to listen
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to them from top to bottom, and also provide some commentary in between clips to give you a little
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bit of context. Our hope is that not only will you understand this topic better, but you will also be
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able to identify some past episodes you may want to go back to and listen more deeply. Final thing
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is that some of these clips are taken from AMAs, so if you're not a subscriber, we hope this gives
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you a little bit of a sneak peek of what's covered in those episodes. This is still a fairly new concept.
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We've only done this once before. We got great feedback on that, which is why we're doing it again.
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So if you continue to like this, please tell us, and if you don't, tell us why.
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So without further delay, I hope you enjoy this special episode of The Drive.
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What we thought would be important is just answering the first question, which is why
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should someone care about this? It's such a complex topic. Why is it important for people
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to put the time in to really think through and understand it?
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It really starts with the ubiquity of this disease and its assault on human longevity. People have
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probably heard me say this before, but atherosclerosis is really the only inevitable disease of our
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species. Cancer, while prevalent with aging and dementia, while prevalent with aging, do not appear
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inevitable the way atherosclerosis does. So not everybody dies from atherosclerosis, but I think,
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to my knowledge, everybody dies with it, assuming they live long enough. So you have a condition
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that, as I said, is inevitable, is ubiquitous. Also, I think based on what you're going to hear
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me talk about today, we know a lot about this condition, and we really have tools to mitigate it.
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To me, that's the reason you want to really understand this. The impact is huge, and the tools
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that we have are also huge. So again, we talk about longevity. Longevity has two parts, health
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span, lifespan. The lifespan part comes down to delaying the onset of chronic disease, of which
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this is the most common chronic disease. So you can think of a couple of different paths to get there,
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but really the two biggest risk factors, I am putting smoking aside for a moment, which is
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a very straightforward behavioral risk factor. In terms of less clear behavioral risk factors,
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the two biggest are clearly hypertension, high blood pressure, and lipid abnormalities. And that's the
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one we're going to focus on here. So atherosclerotic cardiovascular disease, we'll just abbreviate
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ASCVD for short, is really what we're here to talk about. As we get started on this topic, Peter,
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I think we have people who listen to this podcast of all ages, young, old, everywhere in between.
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And I think it's a common thought for people under 30, 40, even some people under 50,
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where they're just like, this is something that only affects old people. I'll think about this
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when I'm older, but right now it doesn't really affect me. How would you answer the question in
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its basic form of, isn't this just a disease of old age? And why should those people who think that
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not just shut off the podcast at this point and instead continue to listen and continue to put in
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the effort? Probably have told this story before. And if not, or if folks haven't heard it,
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I think it's worth hearing again, right? I remember in sort of my first year pathology
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lecture in medical school, the pathologist said, what's the most common presentation for a first
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heart attack? So if a person is having their first heart attack, what is the most common thing that
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they will present with? That's the terminology we use in medicine. And of course, the hands shot up,
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chest pain being the obvious. Nope, that's not it. Nausea. Nope, that's not it. Left arm pain. No,
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that's not it. And it was a trick question. Of course, the answer was sudden death. The answer
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was that over 50% of people's first heart attack is fatal. Now, the good news is today, that number
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is a little bit less. It's probably slightly below 50%, but that's still a staggering number. Now,
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another way to think about this is through the lens of understanding the age distribution of people
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who have their first major adverse cardiac effect. So that is a heart attack, stroke, or sudden death
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due to one of those. If you don't mind, Nick, pull up figure one. This graph shows the age distribution
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for both male and female in the United States in terms of these incidents. I think the easiest graph
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for me to look at here is the one on the right, total annual events. And what you can focus on is the
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first two bars. That is the bars that are for people up to the age of 65. So if you look at the male
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bars, which are the darker bars, you can see that the sum total of those two bars, slightly below 25%,
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slightly above 25%. The implication of that is over 50% of men who are going to have a cardiac event in
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their life will have it before the age of 65. And for women, you do the same exercise. You can see
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that it's one third of women. So it's clear that there's a shift in time and that women, while subject
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to the exact same burden of disease, seem to experience it about a decade later, still fully
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one third of women are going to have their first cardiac event, which is going to be heart attack,
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stroke, or death as a result of those things before the age of 65. And a little over 50% of men will be
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in that camp. So as we're going to talk about in this episode, that's not the whole story. It's even
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more compelling to care about this when you're young, when you understand how long it takes for this
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disease to take hold and the implications therefore for prevention. The most sobering thing for me,
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when you look at this is it's not even the 50% under 65. It's almost the, especially for males,
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the almost 25% under 54. And especially when we get to what we get to later, which is for that to
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happen to someone who's 45, 50, it doesn't mean it started two years earlier. Right. And so I think
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it's pretty crazy when you see these type of stats laid out, how it creates that shift in your mind
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around why you should care about this. What we need to do is first almost step back and look at
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what exactly is ASCVD. I think people have to understand what it is to then really understand
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how it comes about, how to think about prevention. So what do you think the best way to walk people
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through in a relatively simple form, what this disease is? I'll explain it at a high level now.
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And I think we should go through it in some detail in a moment. But the pricey on this would be that
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ASCVD is a disease state characterized by the deposition or the buildup of cholesterol more clearly
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or more rigorously sterols, which include cholesterol and phytosterol in the artery
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wall. It initially starts as something called a fatty streak, which I'll explain in a little bit
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more detail later. And then it later consolidates into things called plaques. And these can ultimately
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lead to a reduction in blood flow. And of course, it's this reduction in blood flow that leads to
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what's called ischemia. Ischemia is the reduction in blood flow and therefore the resulting tissue
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damage that occurs to the heart is what results in a heart attack, which can be fatal depending on the
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amount of the cardiac tissue that is impeded from appropriate amount of oxygenation. To have this
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disease, you don't have to be obese. You don't have to have high blood pressure or things of that
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nature. It's really a question of the cholesterol in your blood. That's really what defines the disease.
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So the essential condition of atherosclerosis is the presence of cholesterol in the artery wall,
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which by the way, is not necessarily related to the measure of cholesterol in circulation,
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which we will talk about in great length. And although these often coexist, patients with
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cholesterol in their arteries do not necessarily have to have co-aggravating factors such as high
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blood pressure, diabetes, obesity, family history, smoking, all these things that exacerbate it.
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You mentioned cholesterol a few times, and obviously it's a topic that's been talked about on
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more podcasts than I can even count or recall right now. But for this conversation, can you define
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cholesterol just in its simplest form so everyone's aware of exactly what we're talking about as we're
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going to get into kind of the more nitty gritty? Cholesterol is an organic molecule that resides in
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the lipid family. So we typically characterize these molecules by their solubility in water,
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and this is a not soluble in water molecule. So it is a hydrophobic molecule. And I think the easiest
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way to sort of picture those things is to think about oils. So if you took an oil like olive oil
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and you poured some of it into a cup of water, you would immediately see what it means to have a
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hydrophobic substance in contact with something which is the ultimate hydrophilic substance, water,
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right? So they repel each other. Now, of course, cholesterol is about one of the most important
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molecules in the body. To be clear, if we didn't have the ability to make cholesterol, we would cease
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to exist. In fact, you couldn't be born without the ability to do this. There are rare genetic
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conditions that impair the ability to make cholesterol, and these are uniformly fatal. Why do we need
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cholesterol? There are broadly two things that cholesterol is essential for. The first is that
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they contribute heavily to the cell membrane of virtually every cell in the body. So cells are
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actually kind of fluid things, spherical things. And what allows them to have that fluidity and what
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allows them to have membrane channels that allow things in and out of them is the cholesterol layer
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that forms the membrane. And secondly, cholesterol is an essential substrate for the production of some
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of the most important hormones in the body, cortisol, estrogen, testosterone. It's also essential for the
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creation of bile acids, which are necessary to be able to digest food. So the mantra that I like to say
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is no cholesterol, no life, period. You should put that on a bumper sticker on your car. Just roll around
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Texas with that guy. No, I think that's great. Why don't we look at and discuss, Peter, how does
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AS CBD come about? So before I jump to the figures, I want to make one other point that I should have
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made a moment ago, and that is the necessity of the body to make cholesterol. So I think most people,
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when they think of cholesterol, will probably first think of what it is that's floating around in their
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bloodstream, but will very quickly turn to cholesterol within food. Because it turns out that when you eat
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certain foods, you can also eat cholesterol. So everybody knows, for example, eating eggs
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means eating cholesterol. And a natural question is, what is the relationship between the food that I eat
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that contains cholesterol and cholesterol you're measuring in my bloodstream? And the short answer is
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very little. And the reason for that is the cholesterol that we eat is in a form that the fancy term
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for it is called esterified. So it has a chemical bond that swings between an intermediary oxygen and
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then another side chain. From just a straight mechanical problem, that is too large for the
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receptors in our gut to absorb. So most of the cholesterol that we eat is in fact excreted out of
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our backside. We don't bring it into our body. And therefore, most of the cholesterol that we are going to
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talk about today is actually cholesterol that we have made. And it's transported between cells
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through these things called lipoproteins. One of the things I remembered from pathology A,
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so it's the first of the three major classes you take in pathology, was something that the professor
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said, which is he said, no doctor has more experience with what it is to have heart attacks than pathologists
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because 50% of the people who have a heart attack die on their first heart attack. So he said,
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I'm seeing 50% of the people who have a heart attack and their first presentation is death.
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So I kind of remembered that. And it's a very sobering fact to think that half the time. And
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again, I don't think that's true today, but I think 25 years ago, that was the case. The numbers are
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probably a bit better today. It might be a third of first events are fatal, but nevertheless, it was
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sobering. So you have this sort of weird factoid that's again, off in the recesses of my brain
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somewhere. And then you hand me this textbook and it actually made sense with what he said,
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because in addition to going through in great detail, the pathological staging of atherosclerosis,
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it was littered with autopsy sections of coronary arteries of people who had died for other reasons.
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And notably they were quite young. So here's a 26 year old male victim of a gunshot wound. Here's a
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27 year old female who died in a motor vehicle accident. Here's a so-and-so-and-so-and-so.
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And when you look at their coronary arteries, you realize they already have atherosclerosis.
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They already have oxidized ApoB bearing particles engulfed by macrophages and thickened intima. And
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while they may not have calcification in their arteries yet, or the types of plaque that would
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rupture within the ensuing weeks or days or months, they nevertheless had atherosclerosis and they were
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in their twenties and in their thirties. So all of a sudden, what this professor said 20 some odd
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years earlier made sense, which is this was now an explanation. This was a bridge to explain what
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otherwise seemed hard to understand. Atherosclerosis, it's a disease in the tissue and
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almost everything that lipid people talk about is in plasma. And if we don't understand the natural
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history of the disease, how can we construct a strategy to prevent it? And although much of my
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work has been on ApoB, the more important part I think has been on understanding how the natural
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history of atherosclerosis should direct our prevention strategy. What that leads to is that
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every major guideline in the world bases their selection of subjects for statin prevention
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prevention on the 10-year risk of disease. And that was a huge step forward in 1980 and 1990. But it
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totally, or not totally, but it very fundamentally makes prevention of premature disease almost
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impossible. When you plug in the numbers to calculate somebody's risk for any of the risk algorithms,
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the American College of Cardiology, 2019 AHA, Multisociety, you plug in numbers that belong to
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that particular patient. And what comes out is what you think is the risk for that particular patient.
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It actually isn't. But what drives that calculation is the age and the sex of that patient. Things like
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cholesterol, blood pressure, they contribute minimally to the actual calculation of 10-year risk.
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So what that means is if you're 35, well, there is even a risk calculator for you. But if you get to 40,
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almost everybody's risk is low at age 40. And it is until you get to about 55, 60, that risk gets you
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over the threshold for the American Prevention Guideline treatment. So prevention really starts
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at 55 to 60. But half, almost half of all infarcts and strokes occur before the age of 60.
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So how can that be? What Starry and his colleagues established was for the first three decades or so
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of life, the disease begins, gets a foothold in the artery. But it's only in the fourth decade that
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you start to develop the lesions that can actually precipitate a clinical event. But risk is low,
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and yet the event rate is high. How can that possibly be? Well, the answer is stunningly obvious.
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Which we've published. There are a ton more people under 60 than over 60. So the rate of events is
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low, but the absolute number of events is high. That's problem number one. Problem number two is, say you
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get to 60 and you didn't have an event. Well, the disease was developing and extending during your
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30s, 40s, and 50s. So by the time we start to try and prevent an event, the disease is well-advanced
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in the arteries. That, to me, are the two fatal flaws in the 10-year risk approach. And we published
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a paper pointing this out in JAMA Cardiology a few years ago. Borg Nordiskart and his colleagues have
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done exactly the same thing with the European guidelines. You can't beat these numbers.
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So rather than what Steri taught me, and it took some years before we could develop the methodology,
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of course risk is a good concept. Of course it is. But we should be selecting people also based on
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causes. I can measure your ApoB pretty precisely. I could measure your non-HDL cholesterol a little
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less precisely, but pretty well. And I know it's yours. When I calculate the risk, if I said, okay,
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Peter, you're my patient. You're a healthy guy. I calculate your risk is 4.1%. Now, what does that
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number mean? Is that your risk? Nope. It means that out of 100 people at 4.1%, 4.1% of them will
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have an infarct. But we know that within that category, there's a tremendous variance in real
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risk. Not everybody's at 4.1%. Some are higher, some are lower, some are dead on. So if I had two risk
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algorithms, the philosopher, A.J. Ayer, the English, the logical positive, he was actually
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darn good on probability. There's a real challenge predicting singular events. I'm either going to
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have an infarct in the next year or I'm not. It's not really a probability. So I either am or I'm not.
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If one algorithm said I had a 10% risk and another one said I had a 15% or 20%, whether I have an
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infarct or not, both of them were right because they said there was sort of a chance you could
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and there was a far larger chance you wouldn't. When we say people should be treated with a risk
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above 7.5%, that means 92.5% of the time, nothing will happen. Well, that's not a great incentive,
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I think, for helping people understand what's truly going to happen. So the way we can deal with
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this and what we've done is develop what's called a causal benefit model. We measure it, non-HDL or APOB,
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and we can project the risk over 20 or 30 years. If you're 30 years old, the period of time you should
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care about is up to age at least to 60. And so if you were in a group, let's say, and let's say I make
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you 35 again, and I say your chances of having an infarct or a stroke before you're 65 are 30%,
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now that's a number you can deal with. That's a number that has meaning. And we could also
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calculate how much the risk can be reduced by starting at age 35, or how much you lose by
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starting at age 45, or how much more you lose by starting at age 55.
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This next set of clips is a deeper dive into cholesterol, the limitations of the standard
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cholesterol blood panel, and an important segment on why I think no one should ever
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So I recently posted something on social media about my frustration with the way that the press,
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and frankly, even sometimes the medical establishment, writes about cholesterol,
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referring to good cholesterol and bad cholesterol. Now, if you've ever listened to me on podcasts,
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you understand that I talk about this in great detail. But a number of the comments suggested that
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there are a lot of people that are kind of new to this discussion. They haven't necessarily
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followed me. They certainly haven't heard the, I don't know, literally 25 hours worth of content on
00:23:50.880
cholesterol over the last four years on my podcast. And they were kind of looking for a little bit of,
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call it the TLDR version of cholesterol. And I thought this would be a great excuse to do it.
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So if you want to understand why I wail on people when they say bad cholesterol and good cholesterol,
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you have to really understand what cholesterol is and why that type of imprecise language is
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unhelpful, to put it mildly. Okay, so let's take a step back. What is cholesterol?
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So cholesterol is a lipid. It is synthesized by every cell in our body. That means every cell in
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our body makes cholesterol. Okay, so why do we make this stuff? Well, this stuff is super important
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where every cell in our body wouldn't make it. It's essential for the creation of a cell. So a cell,
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when you look at a picture of a cell in a book or online or something, they look like two-dimensional
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structures, right? They're sort of these flat things. But really, that's not what cells look
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like. That's kind of a cut open cell projected onto 2D. The reality of the cells are three-dimensional
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and they are fluid. They have to be able to be more than just perfectly open spheres.
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So what gives them that fluidity is their membranes. And it's the cholesterol within the
00:25:06.220
membrane that provides that fluidity. It's also what allows transporters to go across the surface of
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cells. These transporters are what allow various things like glucose, ions, hormones, etc. to traverse
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cell membranes. So it's important to understand that if we didn't have cholesterol, we wouldn't
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have cells. If we didn't have cells, I wouldn't be making this video and you wouldn't be here to
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watch this video. No cholesterol equals no life. Full stop. There are things that are almost equally
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essential for life that go beyond that. Cholesterol is the precursor to some of the most important
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hormones in our body, which ranges from things like vitamin D to cortisol, to estrogen, to
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testosterone, progesterone, etc. It's also essential for bile acids. We wouldn't be able to digest most
00:25:53.400
of our food without bile acids, especially fatty foods. So the list goes on and on as to why cholesterol
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is essential. So why does the story not end there? Why are we having this discussion? Well, when it comes
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to something as essential as cholesterol, not every cell in the body is capable of making enough
00:26:12.380
cholesterol to meet its individual needs. So the body has to be able to traffic cholesterol. So there
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are certain cells that tend to be net exporters of cholesterol, the liver, for example. As a general
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rule, the liver makes more cholesterol than it needs, whereas there are parts of the body that need
00:26:30.900
more cholesterol than they are typically capable of making, especially during periods of high stress.
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So those parts of the body need to receive cholesterol. And this poses a little bit of a
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problem because the main channel that we like to use in the body to transport things back and forth
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is, of course, the circulatory system. It is not the only system. We have a lymphatic system,
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but the circulatory system is the system that we tend to use most to transport things like this.
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Now, there are lots of things we transport in the circulatory system, and we do without any difficulty.
00:27:02.580
We transport glucose without any difficulty. We transport electrolytes without any difficulty.
00:27:09.460
We transport lactate without any difficulty. Why? Because all of those things that I just stated are
00:27:14.100
water-soluble. And of course, the circulatory system is made up of plasma and proteins. That's
00:27:19.800
what your blood is, the plasma being basically the water of the cell. And so things that are water-soluble,
00:27:25.240
like all of the proteins, hemoglobin, and things like that, things that I already stated,
00:27:28.920
glucose, electrolytes, they are soluble in water, and therefore they transport easily.
00:27:33.960
But as I said at the very outset, cholesterol is a lipid. And if you remember a little bit from a
00:27:40.180
chemistry class, you'll know that a lipid is not water-soluble. It is hydrophobic as opposed to what
00:27:45.640
we say is hydrophilic. So things that are hydrophobic can't move in water. Just as you would dump
00:27:52.280
olive oil into a glass of water, you would quickly realize how much they repel each other.
00:27:58.920
So we have this totally essential thing that we have to move around the circulatory system. Otherwise,
00:28:06.340
we would die. And we can't do it directly because the medium through which we need to
00:28:11.980
transport it repels the thing we're trying to transport. Aha, there's a solution. We need to
00:28:19.400
create a vehicle that we can transport this in. And that vehicle is called a lipoprotein.
00:28:26.840
And as its name suggests, lipo and protein, it's part lipid, part protein. And it's engineered in
00:28:34.880
a way that the lipid part is on the inside. The protein part is on the outside. Protein is water
00:28:40.380
soluble. So now you create this spherical molecule, which on the inside, you can package the cargo that
00:28:49.280
is hydrophobic, repels water. And on the outside, you have a coating that is hydrophilic, that is
00:28:56.460
attractive to water, and moves effortlessly through the water. And that's how we transport cholesterol.
00:29:04.000
Now, broadly speaking, these lipoproteins traffic in two types of families. A family that is defined by
00:29:12.920
ApoB, which is a lipoprotein that wraps around it, or an apolipoprotein that wraps around the
00:29:20.260
spherical larger lipoprotein. And ApoA, there's an ApoA family, there's an ApoB family. Technically,
00:29:27.140
there's two ApoB families. There's an ApoB 100 and an ApoB 48. I'm going to ignore the ApoB 48 right
00:29:34.640
now. That just exists on chylomicrons. And we could do another class on that at another day. But for now,
00:29:40.360
we're going to focus on ApoB 100, which defines the lineage of lipoproteins that are terms you've
00:29:48.160
probably heard of, VLDL, IDL, LDL, LP little a. And the ApoA lipoproteins define a totally different
00:29:55.560
class of these called HDLs. So what do those names mean anyway? VLDL, IDL, LDL, HDL. They all refer to
00:30:04.380
another feature of the lipoproteins that is distinct from the ApoLipoprotein that wraps around them,
00:30:10.360
which is their density. So if you think about the high school experiment where you take various
00:30:16.820
different substances and you put them into water, you might notice that you can separate how they
00:30:23.540
would float. Now, water is kind of a bad example of how that works because things are typically
00:30:28.980
binary behaving in water, either they're sink or they're going to float. But I think that gives you
00:30:33.360
a conceptual understanding of the difference in density. Density is mass over volume. And a higher
00:30:41.080
density object relative to a lower density object will sink versus float. So if you take all of those
00:30:48.760
lipoproteins that I mentioned, all of the ApoB ones, all of the ApoA ones, and you put them in a certain
00:30:54.440
type of gel in the lab, you can see a separation of them based on their density. And the highest density
00:31:01.420
ones of those, we just call the high density lipoproteins, the HDLs. You have more than one
00:31:08.120
ApoA on an HDL and you have different subclasses of HDLs. HDLs are really complicated and we don't
00:31:13.980
even come close to understanding all the ins and outs of them, which by the way is why I get really
00:31:18.880
annoyed when people say having a high good cholesterol is good. Again, what they really
00:31:23.740
mean to be saying is having a high HDL cholesterol is good. And while it's true that on average,
00:31:31.200
higher HDL cholesterol is associated with and traffics with metabolic health in a way that
00:31:39.000
low HDL cholesterol tends to traffic with bad metabolic health, you can absolutely not tell by
00:31:45.760
looking at an individual based on how high their HDL cholesterol is, if they're in good shape or not.
00:31:51.380
Because that single snapshot of how much cholesterol is in the HDL tells you nothing about the
00:31:57.740
functionality of the HDL and it's the functionality of the HDL that matters. I'm not going to talk any
00:32:02.800
more about that because I have an entire podcast coming out on HDL biology where we'll go into that
00:32:08.020
in great detail. But it should be stated that efforts to raise HDL cholesterol pharmacologically
00:32:15.120
have by and large, mostly not exclusively, but mostly failed in improving outcomes.
00:32:21.360
Okay. So over on the LDL ApoB side, the most abundant ApoB 100 or ApoB for short lipoprotein is
00:32:29.880
the low density lipoprotein. That's the one that gets called bad cholesterol. And again, on the ApoA
00:32:36.780
side, we have HDL, which gets called good cholesterol. So a couple of things I want to say on this.
00:32:41.840
One, if you're talking LDL, you are referring to the low density lipoprotein. If you say HDL,
00:32:49.180
you are referring to the high density lipoprotein. But if someone says, what is your HDL? What is your
00:32:56.160
LDL? They're asking for a laboratory metric. They are asking incorrectly. There is no laboratory metric
00:33:02.780
called LDL or HDL. There is HDL cholesterol, LDL cholesterol, abbreviated LDL-C and HDL-C.
00:33:12.440
There is LDL-P and HDL-P, which is the particle number of LDL, which can be counted via electrophoresis
00:33:19.700
or NMR. Of course, my preferred way to count the number of these particles is to look at ApoB.
00:33:25.580
The ApoB concentration to me is the most important number you want to understand to predict from a
00:33:32.480
biomarker standpoint, your cardiometabolic risk, ASCVD risk, because it captures all of the
00:33:38.300
atherogenic particles. So ApoB counts the total of the LDLs, inclusive of the LT little A's,
00:33:44.920
the IDLs, although they virtually never exist. They have such a short residence time and the VLDLs,
00:33:49.300
which can become problematic in people with metabolic syndrome and high triglycerides.
00:33:52.820
So ApoB gives you the total atherogenic burden of those lipoproteins. And therefore,
00:33:57.540
I think it's the preferred metric by which we want to assess risk. But if you want to look at LDL,
00:34:02.520
you have to look at LDL-C, LDL cholesterol. And HDL, you have to look at HDL cholesterol.
00:34:08.880
Now, is the cholesterol in the HDL any different from the cholesterol in the LDL? No, of course not.
00:34:15.360
Therefore, it is totally erroneous to say HDL is good cholesterol and LDL is bad cholesterol.
00:34:21.640
No, instead, what is true is that LDLs themselves as lipoproteins are bad actors because of what they
00:34:31.140
do. What they do is they go into artery walls where they get oxidized and they basically dump
00:34:39.180
their oxidized sterile contents into the subendipelial space, which elicits an immune
00:34:45.280
response and a whole bunch of other things that lead to atherosclerosis, which I'm not going to get
00:34:48.340
into now. But the point of this discussion that I want people to understand that LDLs and HDLs are
00:34:54.900
lipoproteins. If you want to talk about the cholesterol, you talk about LDL cholesterol and
00:34:59.060
HDL cholesterol, but the cholesterol in them is the exact same. And there is no such thing as good
00:35:03.800
cholesterol or bad cholesterol. And so you just have to be careful when you see things written
00:35:09.980
that are written through that lens, because what it tells you is the person writing this doesn't
00:35:15.040
understand the basics of lipids and lipoproteins. And if they don't understand the basics of lipids
00:35:20.960
and lipoproteins, because what I just told you guys is literally the 101 on this subject,
00:35:25.700
we didn't get to the senior level class, let alone the graduate level class. And this is complicated
00:35:31.920
stuff once you get into that level. So if someone writing to me is butchering the 101,
00:35:37.520
you can stop reading. Because whatever else they're saying, they're undoubtedly screwing
00:35:43.200
it up. So there it is. There's the TLDR on lipids.
00:35:48.180
If a doctor gets a report now, he gets total cholesterol, triglycerides, non-HDLC, LDL-C,
00:36:02.920
HDL-C. Five numbers. Do you think he actually looks at any of those numbers? He's trying to do a good
00:36:09.360
job. He does. But let's say the triglycerides are high. Can he do anything with that? Nope.
00:36:15.440
Because everything is based on LDL-C. So he's got, in reality, four numbers that are doing nothing.
00:36:23.300
Let's explain that to people, Alan, because you and I know the ins and outs of that very well. But
00:36:27.960
I think most people here don't understand the difference between the calculated and measured
00:36:33.100
LDL. So let's start with that. And then let's talk about how VLDL has been estimated. And let's
00:36:39.680
bring this all back in terms of some other work you've done, which is understanding the role of
00:36:44.680
triglyceride in ApoB. So let's start with the basic. You go to the doctor, you get a set of labs done,
00:36:51.060
and the LDL number comes back at 140 milligrams per deciliter. Is that actually what it is? Or is
00:36:57.120
that an estimation? That's an estimation. It's almost always a calculation. And there are at least
00:37:04.100
eight different methods to calculate LDL cholesterol. So if there are eight different methods, they don't all
00:37:09.840
give the same answer or you wouldn't have eight different methods. LDL cholesterol can also be
00:37:15.320
measured directly. That assay has never been validated in disease patients. And no one has
00:37:21.780
ever published a paper showing that it's more accurate in terms of disease identification than
00:37:28.920
calculated LDL cholesterol. And yet people have paid good money for that lab test. There's no question
00:37:37.160
that the number of LDL particles is a more accurate index of risk than the LDL cholesterol. The VLDL
00:37:45.960
cholesterol is a cholesterol that's in the very low density lipoprotein particles, the particles that
00:37:52.160
come out of the liver. That cholesterol is atherogenic. There's a lot of triglyceride in that particle.
00:37:59.440
So the people who measure triglyceride say, well, the triglycerides are high. That must be the
00:38:05.000
problem. And there's no question that people with high triglycerides are at increased risk of heart
00:38:10.360
disease. But the people with the high triglycerides who are at increased risk of heart disease have a
00:38:16.320
higher number of LDL particles and VLDL particles. It's the particle. And when you're measuring the
00:38:22.900
triglyceride, you're just measuring a blob of liquid in a bunch of particles and you need to know
00:38:29.600
the number of them. So it's an important number in the sense of if you're a lipoprotein guy trying
00:38:37.520
to figure things out. If it's extremely high, it increases the risk of pancreatitis. But I haven't
00:38:43.920
seen any solid evidence that triglyceride itself is pro-atherogenic. What's atherogenic is the
00:38:50.020
cholesterol inside the VLDL particles. It's the number of those particles that get into the wall. Now,
00:38:55.660
there's a complicating reality. Because in general, all I need to know is the ApoB. But there is a
00:39:03.180
disorder called remnant, type 3 dyslipoproteinemia. And that's a very specific, highly atherogenic
00:39:12.140
condition that manifests with high triglycerides, high cholesterol, but get this, you know, low ApoB.
00:39:21.360
So when I measure my lipids in ApoB, I can recognize that. But if you don't measure the ApoB,
00:39:28.720
and this applies to most of the people who are listening to this podcast,
00:39:32.900
if they go to see their doctors, that condition can't be diagnosed.
00:39:41.700
Our last out of clips will focus on why I think ApoB is a superior lipid metric
00:39:45.700
to LDL cholesterol or even non-HDL cholesterol when trying to predict risk.
00:39:51.360
Are you optimistic? I mean, is this just a question of time? I mean, in 10 years,
00:40:01.580
will kids in med school be learning about ApoB instead of LDL?
00:40:06.180
I'm pessimistic. Europe, the 2019 guidelines were very pro-ApoB. The evidence from Mendelian
00:40:13.340
randomization, like the newer technologies, Mendelian randomization, they've just been
00:40:17.880
slam dunk for ApoB. Let's explain that to folks, because I want to talk about the causality
00:40:23.220
of this, and this might be the perfect way to actually explain the causality of ApoB in the
00:40:29.660
context of this tool. So can you explain to folks what a Mendelian randomization is? People see this
00:40:36.640
all the time in studies, but I don't think it's entirely clear for the average person what it means.
00:40:41.040
I'll try, okay? It's not my expertise, but I'll try. The conventional ways of taking things apart
00:40:49.480
with prospective observational studies like Framingham, there's a limited amount of the
00:40:55.340
certainty of your conclusions because of confounding you can't deal with. You take measurements at age 20
00:41:02.400
and you follow someone for the next 30 years. Well, a lot of things change in the next 30 years that
00:41:08.420
you don't have a handle on. Your inferences are probable but not causal. What Mendelian randomization
00:41:17.040
allows you to do is to come a lot closer to causality because, for example, you can identify
00:41:26.280
groups of genes that are associated where changes in the gene are associated with a little lower
00:41:31.980
cholesterol or a little higher cholesterol. And when you lump together a bunch of those different
00:41:38.440
genes that can have different makeups because you can change the makeup of a gene pretty easily,
00:41:44.540
you can see fairly substantial differences in cholesterol. So what you've got is information on
00:41:52.400
somebody that's fixed at birth. And you see, is that associated with a difference in outcome?
00:42:00.260
You've gotten rid of a lot of stuff in the middle. And what a number of Mendelian randomizations have
00:42:07.640
shown is that ApoB includes all the information in triglycerides, LDL cholesterol, and even HDL
00:42:15.380
cholesterol. It sums them, which in the sense of VLDL and LDL makes perfect sense. So there are caveats
00:42:23.260
in Mendelian randomization. You can't just push a button and say, give me the answer. But George
00:42:30.920
Davies Smith, really arguably one of the founders of Mendelian randomization, or not arguably, he was,
00:42:37.660
he's the author of a number of the Mendelian randomizations saying ApoB incorporates and therefore
00:42:45.520
beats triglycerides and LDL cholesterol. So that's a huge level of information
00:42:53.800
that isn't even mentioned in almost any of the guidelines.
00:42:59.580
Yeah. So let's make sure people understand everything you just said, because you said a lot
00:43:02.880
of things in there. When you prospectively follow a cohort, the way the Framingham cohort was followed
00:43:09.760
or the Framingham offspring or the MESA cohort, or any of these cohorts have been followed. You can
00:43:15.100
take a bunch of people and you could measure their ApoB or their LDL-C or whatever metric it is that
00:43:20.760
you're trying to determine if it in fact has a causal relationship to the disease of interest.
00:43:25.520
You can follow them over decades and you would demonstrate as has been demonstrated that the
00:43:31.780
people with higher B, higher LDL-C, higher non-HDL-C and lower HDL-C all have a higher risk of developing
00:43:41.200
atherosclerosis over time. But it's hard to say that that's causal just based on that information,
00:43:47.520
because over the ensuing 20 years that you follow them, they are free to make other choices that may
00:43:54.960
impact those variables of interest and other variables. So the Mendelian randomization attempts
00:44:01.440
to get around that by saying, at the time of, I was going to say birth, but really at the time of
00:44:08.000
conception, we all get randomized to a set of genes. We get assigned a set of genes. I guess they're not
00:44:15.060
perfectly random because they come from our parents, but for the purpose of not changing,
00:44:19.780
they are indeed a random assignment that is fixed. If we can identify which genes map to which
00:44:29.400
phenotype and we can figure out the genes that map to the phenotype of our interest, namely driving up
00:44:37.500
or down a variable of interest such as APOB, then we don't really have to worry about the confounders
00:44:43.620
that occur in between because the genes can't change. Just to put a bow on that, basically,
00:44:50.560
now when you see a difference in outcome, it's much more likely to be causally related to the
00:44:58.720
phenotype of interest because the gene has not changed that underlies it. Now, what are some of
00:45:04.580
the ways that we can get tripped up with Mendelian randomization? I mean, there's some pretty big ones.
00:45:09.500
Yeah. Before we get there, HDL cholesterol was the rage, okay? The total rage because the epidemiological
00:45:18.980
evidence couldn't be clearer. In fact, it was four times more clear. My recollection
00:45:24.480
was that Framingham demonstrated low HDLC was four times more predictive of cardiac events than high
00:45:33.400
LDLC. Am I remembering that correctly? I'm not sure it's that multiple. Yeah, but it's multiples.
00:45:38.500
And it turns out, as we know now, at least from the CTP inhibitors, that you can't manipulate HDL
00:45:45.900
and change outcomes. And that's one of the elements of demonstrating an overall causal relationship.
00:45:53.040
And the Mendelian randomization show HDL is not causal, whereas they show APOB is. And cholesterol
00:45:59.760
is too, by the way. Those are two very important studies, Alan. I mean, and both of those have been
00:46:05.300
in the last 10 years. Yeah. It's an incredible technical advance in being able to examine questions
00:46:15.720
and look at numbers of people that would be unimaginable in conventional studies. The Mendelian
00:46:23.680
randomization, they're always talking hundreds of thousands of people because they've got these huge
00:46:27.480
data banks with genes. And those numbers get you around the confounding of things. You have huge
00:46:34.460
numbers. But it's like any methodology. No method is perfect. This one can mislead you too,
00:46:43.420
particularly when you've got a sequence of associated variables. For example, people show using MR that
00:46:50.720
triglycerides were, quote, causal or associated with increased risk. But when you took into account
00:46:57.300
the non-HDL cholesterol or the APOB, it disappears. So when you've got a linked metabolic chain,
00:47:03.680
you've got to be careful that you've gone to the end of it. You've got the real actor,
00:47:09.580
not act one leading to, that you've got the real persona dramatis. Which is why it's surprising that
00:47:16.460
HDL didn't, at least at the first order, demonstrate causality. Because there's no doubt that phenotypically,
00:47:24.700
the high triglyceride, low HDL phenotype is so associated with metabolic syndrome that it makes up two
00:47:33.040
of the five criteria. That's an incomplete description. That's like you describing yourself
00:47:40.720
as six feet tall, I wish, and not giving your weight and letting me guess your BMI. You cannot
00:47:49.820
characterize any phenotype without the APOB. It really drives me around the bend. When people
00:47:57.700
speak saying, I got somebody because I got their triglycerides and their HDL. Well, I say, okay,
00:48:03.760
what's their APOB? How can you pretend you've evaluated the system when you haven't counted the
00:48:10.640
number of atherogenic particles? Because they could be normal, they could be high, or you can have a type
00:48:17.040
three. They don't know. And it's not a phenotype. There is no phenotype without putting any APOB in
00:48:26.300
there. They're lipoprotein particles. They're disorders of lipoprotein particle metabolism. Of
00:48:35.860
course, the triglycerides and cholesterol are important. But my analogy, I didn't do a good
00:48:40.680
analogy there. But it's so fundamental that it drives me to distraction as to why you wouldn't
00:48:51.460
want to know a core element of knowledge. But it doesn't seem to bother many of my friends.
00:48:58.880
You walked through the pathophysiology of how the APOB-bearing particle wreaks havoc in the artery wall
00:49:05.340
many, many years before we see clinical events. And you also mentioned that there are other
00:49:10.640
factors that can amplify or exacerbate that. I can't remember exactly how you said it, but that
00:49:15.120
was the gist of it. Well, two of those things that are widely accepted to exacerbate risk are smoking
00:49:23.040
and hypertension. In fact, smoking and hypertension probably carry a greater risk for atherosclerosis
00:49:30.620
than APOB, or is that not the case? It all depends the way you think about it. Because if you just
00:49:37.400
say, what's the risk somebody with hypertension faces, they have high risk, no question. But then
00:49:42.440
you say, what is hypertension? The last 30 or 40 years, there have been almost an infinite number
00:49:50.480
of basic science studies on hypertension. And when you were in medical school, and even before that,
00:49:56.300
when I was in medical school, we talked about pathophysiology of hypertension. And what strikes me
00:50:02.560
is, we don't talk about the pathophysiology of hypertension anymore. But the basic science
00:50:09.780
goes on in rats, is healthier than ever. And there isn't anything I know of that's come out of that
00:50:17.100
basic science that's been clinically useful in the last 30 years. The drugs we use, we use them
00:50:23.680
because they work. So what is hypertension? It's a higher blood pressure than we should have.
00:50:31.480
And where is the disease that produces that higher blood pressure? Is it resistance? We don't have a
00:50:37.980
clue. Okay? We don't have a clue. And it strikes me it's the same thing as much of the debate in lipids
00:50:44.320
about APOB, or the drunk looking for the key under the light, because this is where the light is,
00:50:50.120
not where he lost it. Everybody who's anybody has the same viewpoint. My bet is it's in the proximal
00:50:57.120
aorta. My bet is that it isn't that complicated. We lose elastins in the proximal aorta. And that's
00:51:04.140
systolic hypertension. Thank you very much. What could accelerate that process?
00:51:12.520
When I read hypertension, I get lost because I get page after page after page of peripheral
00:51:18.820
arteriolar tone and very complex metabolic studies and very sophisticated animal models.
00:51:27.400
And there's some renal left. It's a miasma for me, an absolute miasma.
00:51:33.240
I hadn't heard about the proximal aorta. So say a bit more about that.
00:51:36.480
Well, this is me. The proximal aorta is elastic. And if you look at a flow curve,
00:51:42.320
a hydrostatic pressure curve, when we're young, it's rounded because as the left ventricle ejects
00:51:49.620
blood rapidly into the aorta, the aorta expands. So it absorbs some of that energy. You know that
00:51:56.440
wind kessel that they mentioned in school? That's not that big a deal, but the energy is partially
00:52:03.380
captured, partially regained. But the wall isn't battered. The wall can give way. Me, personally,
00:52:13.460
just in the middle of my brain, imagine that if those elastic fibers start to go, then the wall's
00:52:20.280
stiff. So now when the left ventricle ejects blood, the pressure goes up more rapidly and it falls more
00:52:27.360
rapidly and diastole. And that's why you get systolic hypertension with normal diastolic pressures.
00:52:33.440
So my bet would be, if I was not the age I am, I would be looking at factors like cardiac output
00:52:40.100
again, which used to be way back when, or factors that alter the behavior of the proximal aorta.
00:52:46.460
As much as something that's, to me, pathophysiologically, much more likely to be involved. So once I got
00:52:55.180
hypertension, okay, then I've got a driving force to push particles into the wall.
00:53:00.720
And so you think it's the actual increase in the pressure of the plasma?
00:53:06.780
And the response of the wall. I think there are responses to the wall. The wall thickens up. It
00:53:13.300
Does it also damage the endothelium? Do you think that plays a role?
00:53:16.360
That's right. I don't understand endothelial dysfunction. It's more a language thing to me
00:53:21.860
than it is a reality. I know the endothelium is critically important. It functions abnormally,
00:53:27.220
and that's endothelial dysfunction. How that fits into the overall thing, I don't know.
00:53:33.160
My bet is ApoB particles are part of the process of inducing endothelial dysfunction,
00:53:38.400
but I don't know that clearly experimentally. So going back then to the question at the top,
00:53:46.680
does it make sense to even compare hypertension to ApoB? They both seem to play a causal role.
00:53:53.020
Is one more causal than the other, or is that a silly question because they're not binary and static?
00:53:59.600
I think that's not the right question. I think our blood pressure goes up as we age.
00:54:04.060
I mean, hypertension involves so much of the population, it's not clear to me what the word
00:54:10.420
disease means. The prevalence as we age is so high that to me, it's becoming almost an aging process
00:54:19.480
because we're lasting a lot longer than we were probably designed to go. So you have this repetitive
00:54:25.000
injury to the proximal aorta. It gets a little progressively less able to deal with it. So in the
00:54:31.880
time we're 50, what percent? 60% have higher blood pressure. I mean, the figures are staggering.
00:54:39.140
I'm not sure. Don't quote me on that, but it's high, high, high.
00:54:45.640
It does rise with age, but not that much. When we look at people at age 35, we can pretty
00:54:53.600
accurately categorize the group they belong to at age 35. Not that they won't change somewhat. So
00:55:00.440
if you're high at age 35, you got about a 95% chance of staying high. 5% will go out of the high
00:55:08.800
zone. They won't go low, low. So if you're high at age 35, I wouldn't bet anything's going to move
00:55:16.780
you down. That's why I think it's such a good signal for when we should start thinking about
00:55:22.160
treating people. And if you're low, some people go from low towards high, but the majority don't,
00:55:29.100
and we keep following them. But if you're high, no, we've published a fair amount of this. If you're
00:55:36.060
high, it's not a hundred percent, but it's about 90% that you're going to be high.
00:55:41.780
Is there a gender difference? At least clinically, I seem to see women as they go through menopause
00:55:46.740
experience dyslipidemia that men wouldn't experience over that same decade or even five-year
00:55:52.600
I think there are changes and ApoB goes up with menopause. I'd like there to be more data. I think
00:55:59.520
part of the reason it's held ApoB back is that people didn't measure it. So they were sort of,
00:56:05.080
well, what I measured has to be important because I can't answer your question. Hopefully more data
00:56:10.320
will be coming. But I agree with you. People can change at the menopause. So I'm not saying we don't
00:56:15.300
keep looking at people. But when you have somebody at age 35 to 40 who's high, the odds are high that
00:56:24.100
Are we doing a better job treating hypertension than dyslipidemia?
00:56:28.040
I have no idea. The incidence of coronary disease is going up in the last five years. And that's
00:56:34.580
despite statin therapy. And that's the obesity diabetes. So I think we've been too quick to congratulate
00:56:43.460
ourselves at how well we're doing. There are many reasons that treatment is not succeeding as well
00:56:50.060
as it should. And I think the complexity of the lipid phenotype of the lipid model is part of the
00:56:57.100
answer. It's easy for me. I get the ApoB where I want it to go. Yeah. I mean, an explanation for your
00:57:03.600
observation would be if in the last five to 10 years, the incidence of atherosclerosis or major adverse
00:57:09.480
cardiac events is rising, despite the advances we have, you would argue or could argue that if
00:57:16.060
we're measuring LDL-C, and that's our proxy for treatment, but as dyslipidemia is growing in the
00:57:24.380
metabolic context, meaning if you have more medicine and more insulin resistance and more type 2 diabetes,
00:57:29.860
we know that those phenotypes are associated with greater discordance between ApoB and LDL-C,
00:57:34.600
suggesting that you'd have a greater and greater portion of the population that is being undiagnosed
00:57:40.520
or being underdiagnosed because you're treating their LDL-C and you believe that it's lower than
00:57:47.120
their risk actually is because their ApoB is higher. I know you know what I just said. I hope the listener
00:57:51.620
understands what I just said. Yeah. What you just said was important. It's another example,
00:57:58.360
an unfortunate, sad example. They're trying to quantify lipoproteins based just on lipids,
00:58:04.600
is not adequate. You're not capturing all the information that you should.
00:58:15.000
Let's go back to kind of the macro point here around ApoB, which is a greater coalescing around
00:58:22.060
the idea that ApoB concentration matters. So I think it's very well understood that two of the
00:58:30.640
biggest risk factors for cardiovascular disease are smoking and hypertension. I don't think there
00:58:36.440
is any ambiguity that cigarette smoking and high blood pressure increase the risk of cardiovascular
00:58:42.740
disease. And they both appear to do so through a mechanism that weakens the endothelium or creates
00:58:49.480
an injury to the endothelium. The question now becomes, as you put it, Tom,
00:58:56.020
how ironclad is the story that it's the ApoB bearing particle in the presence of injured
00:59:04.440
endothelium that is the Trojan horse that begins this destructive trajectory of taking that cholesterol
00:59:13.240
into the subendothelial space, becoming retained, undergoing this chemical oxidation process,
00:59:21.160
which then kicks off an inflammatory response that paradoxically, as an attempt to repair the
00:59:27.480
damage, results in what can be a fatal injury. There are other hypotheses. For example, there are
00:59:34.780
people who note, and we have, I mean, look, I have a patient in our practice, Tom, you've weighed in on
00:59:39.540
her case, walks around with a total cholesterol of 300 and something, an LDL cholesterol of 220 milligrams
00:59:47.580
per deciliter, an ApoB of 170 milligrams per deciliter. She's in her late 60s and her coronary
00:59:56.180
artery calcium score is zero. We have elected to not treat her with any lipid lowering therapy.
01:00:01.700
In other words, there are exceptions to this. How do we reconcile that?
01:00:08.800
Well, it's the human body in medicine. As you know, not all smokers are going to come down with
01:00:13.560
lung cancer or chronic obstructive lung disease. Why not? If that's such a horrible risk factor.
01:00:20.040
I try to explain this, and I've certainly seen cases like you say, where, oh my God,
01:00:25.160
if I was just going to say, give me your ApoB or whatever cholesterol metric, you're going on three
01:00:30.440
drugs right now. You've got no choice. And maybe in the old days, we approach people that way, but no
01:00:35.900
more. I think you have to individualize your whatever risk factors you discover that might wind up
01:00:42.160
causing atherogenesis and then figure it out. So particle number is certainly a major factor that
01:00:49.700
might force it in, but not always. Endothelial function, although you can certainly, if you
01:00:55.060
review the history of this and how do you really determine endothelial function, not everybody has
01:01:00.580
serious endothelial dysfunction who winds up with atherosclerosis. So particle number itself in some
01:01:06.020
people can just make the particles go in. I think if we take most adults, who's not going to have
01:01:12.120
a little bit of endothelial dysfunction. So I agree with you, it's a combination of something
01:01:18.520
about atherogenic particles, be it their number, endothelial dysfunction. But I'm talking more and
01:01:24.500
more now when I discuss any type of lipoprotein, I don't care which subgroup you want to talk about.
01:01:30.240
I think we certainly have to know its particle concentration, but I like to talk about particle
01:01:35.780
quality. So what are the other attributes of any lipoprotein that might contribute to its
01:01:42.540
atherogenicity or in some perhaps not understood, make it relatively, it's not going to generate
01:01:49.700
atherosclerosis. And there certainly have to be things like that going on. So as we're getting
01:01:54.460
smarter, we're looking at other components of the lipoproteins that could be other proteins that are on
01:02:00.480
them, that could be their complex lipidome. And trying to see, aha, can that help us discern
01:02:06.680
whether in you a given particle concentration is more worrisome than it is in the next person.
01:02:14.760
So there's a lot going on. And also from the gist of this conversation, listeners will know
01:02:20.560
atherosclerosis, atherogenesis is a multi-complex, multi-factorial disease.
01:02:26.660
And that's why even when Peter and I, if we consult on a case and we realize in this person,
01:02:33.000
we have to beat up ApoB and get their particle numbers to a more physiologic range, we don't
01:02:38.540
stop once we do that. We examine in great detail for other things that might be injuring the endothelium
01:02:44.680
or the arterial wall and see are any of those treatable or so. So we're getting a little bit
01:02:50.080
smarter on lipoproteins, but there certainly is more to it than just particle number.
01:02:54.080
Do we think that there's a limit to where the benefit of reduction becomes diminishing or even
01:03:01.860
J curves in the other direction? So we discussed it in the first episode significantly. We did so
01:03:08.920
again with Ron Krauss. It wouldn't be the worst idea in the world a couple of years from now to sit
01:03:15.000
down and do it again and re-examine the data. But again, I think the causal relationship between
01:03:19.960
ApoB and atherosclerosis is as strong as virtually anything we see in medicine for which you can't
01:03:28.200
do the perfect experiment where you have to rely on natural experiments. Nevertheless, maybe it's not
01:03:34.900
entirely clear what the dose response looks like. So if you have somebody whose ApoB is 160 milligrams
01:03:41.220
per deciliter, there's a risk reduction that comes to lowering it from 160 to 100 and lowering it from
01:03:48.180
100 to 80 and lowering it from 80 to 60. What do we know about the risk reduction in lowering it,
01:03:56.600
say, from 60 to 40 to 20? And I ask both what we could infer pharmacologically and non-pharmacologically.
01:04:04.920
In other words, from the Mendelian randomization versus the pharmacologic.
01:04:09.600
Well, even using pharmacologic trials and Mendelian randomization, the concept you're going to come
01:04:15.840
across with is lower is better. And with the pharmacologic thing, we're modulating things
01:04:21.820
that either have clinical trial proof that if you lower them, it's good, or the Mendelian
01:04:26.440
randomization, looking at genes where that drug might be doing something, it works. Now, you do need
01:04:33.560
a few ApoB-containing lipoproteins. They do traffic other lipids. They traffic fat-soluble lipoproteins.
01:04:40.100
But we must never confuse A-beta lipoproteinemia, where nobody or that person can't make them,
01:04:46.800
or hypo-beta lipoproteinemia, where they make a few enough to traffic those other things that
01:04:52.720
a lipoprotein might have to traffic. But even the guidelines where they examine people looking at
01:04:59.760
their baseline ApoB or LDL cholesterol, the first thing they suggest, at least in the higher risk
01:05:05.260
people, is try and get a 50% reduction. And that's where most of the bang for the buck is
01:05:10.500
going to be. Now, if you still have options that you can lower it further, yeah, the trials show,
01:05:17.300
yeah, there is incremental reduction events, but it's a much smaller absolute risk reduction and
01:05:23.280
dropping at the 50% or so. So I don't know if that answers your question. So most people don't have
01:05:31.140
the type of levels where with modern therapeutics, with modern lifestyle, we can more often than not
01:05:38.940
attain physiologic concentrations. And if I want to talk about ApoB, that's probably under 50 milligrams
01:05:45.540
per deciliter if we can get there. That's what the newborns have. That's when you go in clinical trials,
01:05:52.520
if you take it down that low, you see your most risk reduction. And so far, at least with pharmacologic
01:05:58.860
lowering of ApoB with the currently FDA-approved drugs, there is no signal of harm.
01:06:06.200
Yeah, again, it's funny because I was just about to say, with the current crop of drugs,
01:06:11.400
specifically the PCSK9 inhibitors, we are routinely seeing patients who easily can get an ApoB into the
01:06:20.740
20 to 40 milligram per deciliter range. You and I actually sat down a couple of months ago and did a
01:06:27.820
calculation to estimate how much cholesterol is actually contained in the circulating lipoproteins
01:06:36.520
versus that which is in cell membranes. Do you remember doing this with me?
01:06:41.500
Not per se, but we're developing equations. You're the master of that.
01:06:47.680
Well, it was one of these things, right? It was sort of like, look, when you look at a person's
01:06:51.840
plasma glucose level, you realize pretty quickly it represents a tiny fraction of total body glucose.
01:06:59.380
And similarly, there's such a concern about plasma cholesterol level, but given how essential
01:07:07.200
cholesterol is, it's understandable why people would be concerned that low cholesterol could be
01:07:12.200
problematic. But once you do the calculation and realize virtually all of the cholesterol in the
01:07:17.740
body is contained within the cell membrane or within the steroidal producing tissue, the circulating
01:07:25.620
amount is a very narrow window into the total amount of cholesterol and therefore a reduction of say
01:07:33.720
60 milligrams per deciliter to 50 milligrams per deciliter of ApoB or even something more extreme,
01:07:42.060
like a full 50% reduction of total cholesterol, 200 milligrams per deciliter to 100 milligrams per
01:07:49.380
deciliter does not represent a significant reduction in total body cholesterol. This is a very important
01:07:55.000
point, right? Let me repeat it. You have a total body cholesterol that you measure in the plasma that
01:08:01.500
says, oh, it's 200 milligrams per deciliter. That goes down to 100 milligrams per deciliter. Let's say
01:08:06.640
the LDL fraction reduced from, you know, 150 to 75 or something. Someone might say, God, you just cut
01:08:13.500
cholesterol in half. That can't be good for you given the importance of cholesterol. But my point is,
01:08:19.280
no, you simply cut the amount of cholesterol being carried by the lipoproteins in the plasma
01:08:24.120
in half. That doesn't capture the majority of the cholesterol.
01:08:28.680
Yes. Thanks for refreshing my memory. What you're talking about now, it's really pools of cholesterol
01:08:34.600
throughout the body. And I think I'm so glad you brought this up because this is just not even
01:08:40.220
understood. Even in the lipidology community, we have a total body cholesterol. There are basically
01:08:46.460
three pools. There's your brain and nothing we're talking about today has anything to do with brain
01:08:52.020
cholesterol. It's a separate system. It doesn't interact with the other cells in your body or
01:08:56.780
certainly with the cholesterol in your plasma. So if it's not in your brain, where is cholesterol in
01:09:02.480
your body? Well, it's either in all your peripheral cells, perhaps some more than others,
01:09:07.560
or it's circulating in your plasma. And if it's in the plasma, where is it? There's an
01:09:14.200
eatsy-weensy amount bound to albumin. There's more bound within all of the lipoproteins that are
01:09:20.920
trafficking in your body, meaning your ApoB and your ApoA1 particles. But believe it or not,
01:09:26.900
if I wanted to search down blood cholesterol for you, I would suck out your red blood cells and
01:09:32.480
extract cholesterol from them. Red blood cells carry far, far more cholesterol than do all of
01:09:38.900
your lipoproteins put together. And the other crucial point you made subtly, and I hope everybody
01:09:44.740
understood you, the amount of cholesterol within your lipoproteins has no correlation with your
01:09:51.020
cellular cholesterol or even your red blood cell cholesterol. So however you're modulating some
01:09:57.880
LDL, total cholesterol, HDL cholesterol metric, that tells you nothing about what might you be
01:10:04.780
doing to the cholesterol content of your cells. So don't have a panic attack if you're making LDL
01:10:11.760
cholesterol 30, because I can assure you virtually every cell in your body, even if that's your
01:10:17.300
plasma LDL cholesterol, has more than enough cholesterol because it can de novo synthesize
01:10:22.880
it. It can put it in its cell membranes or other organelles that require cholesterol. If it's a
01:10:28.100
steroidogenic tissue, it can produce a little more or perhaps delipidate some. So there's no cell that's
01:10:35.240
being deprived of cholesterol in the periphery when you are modulating lipids through lifestyle or drugs.
01:10:47.300
So on ASCVD, I've also become far more aggressive on the timing and magnitude of ApoB reduction.
01:10:59.280
So take a step back and ask, what are the leading causes or modifiable causes of ASCVD? The big three
01:11:08.600
are pretty unambiguously smoking, hypertension, and hyperbeta lipoproteinemia, which is just a really
01:11:16.840
fancy word for saying too many lipoproteins that have ApoB on them. So that's LDL, IDL, VLDL, LP little
01:11:25.960
a. By measuring ApoB, why I'm such a fan of measuring ApoB as opposed to just measuring LP, LDL particle
01:11:34.040
number or LDL cholesterol number is we have one single number that captures the total concentration
01:11:40.840
of ApoB. And while that's pretty well associated with non-HDL cholesterol, which is a far better
01:11:46.500
surrogate than LDL cholesterol, it's still better. And that's been demonstrated. And I think we even
01:11:52.220
covered that in a previous podcast where we went over the discordance between non-HDL cholesterol
01:11:58.380
and ApoB. So now the question becomes, well, when should you start ApoB reduction and how much
01:12:05.340
should you lower it? And I'll tell you, I used to take a point of view that if a 40-year-old
01:12:11.040
had an elevated ApoB, let's just put some numbers to this, right? So the 20th percentile of ApoB is
01:12:19.000
about 80 milligrams per deciliter. I used to say that, let's say somebody was at the 50th percentile,
01:12:26.260
they're 40 years old, their calcium score is zero, and they were ambivalent about lipid-lowering
01:12:31.940
therapy. And let's assume that they're not insulin resistant, and you've done all of the things that
01:12:36.460
you can do reasonably with nutrition. I wouldn't push that hard. I've now taken a very different
01:12:42.140
stand, which is I've basically taken the stand with others that I've taken with myself, which is
01:12:47.040
the evidence is overwhelming that infantile levels of ApoB are not deleterious in any way. Meaning
01:12:56.140
an ApoB of 30 to 40 milligrams per deciliter, which is the level that children would have,
01:13:01.940
poses not only no risk to children as evidenced by the fact that, I mean, that doesn't require
01:13:07.080
an explanation, but as evidenced by what we see in the literature on adults with levels that have
01:13:14.280
been pharmacologically reduced, tells me that we need to be lower. And the amount of time it takes
01:13:19.960
to see a benefit tells me we don't want to wait until there's an issue. In other words, if the reason
01:13:26.120
we begin therapy is because somebody has a positive calcium score, which again, we covered this in
01:13:31.640
great detail. So for people listening, we have a dedicated ASCVD AMA, which goes into heavy detail
01:13:39.480
for about 90 minutes on all this stuff, where if this is of interest, that's a great AMA that goes
01:13:45.980
super deep on basically all of the reasons why I think my point of view now is treat early and treat
01:13:53.440
aggressively. And I will now also make a very bold statement. Again, it's let's start with the thought
01:13:58.600
experiment, right? If the thought experiment for colon cancer was do a colonoscopy every day on a
01:14:05.240
person's life, starting at the age of 30, would you eliminate colon cancer deaths? I think the answer
01:14:11.220
is yes. And similarly, I would say pharmacologically lower ApoB to somewhere in the 20 to 30 milligram
01:14:20.440
per deciliter range for everybody in the population. While someone is in their 20s, can you eliminate
01:14:27.540
ASCVD? And I think the answer is probably yes. In other words, I think what you're basically going to
01:14:33.200
do is eliminate death from atherosclerotic causes. And that would need to be started in 20s?
01:14:40.960
I think so. Yeah. Very early on. Yeah. So again, how do you take that thought experiment and turn it
01:14:46.300
into a practical implication? Because I don't think it's practical to take every 20-year-old
01:14:51.600
and obliterate their ApoB. Although it's clearly something we do in the subset of patients who have
01:14:59.080
significant genetic abnormalities, such as the cluster of genetic abnormalities that coalesce
01:15:05.660
around a condition called familial hypercholesterolemia. We certainly do medicate those
01:15:10.060
patients, usually as teenagers. So this is not some completely crazy idea. But I think practically
01:15:16.300
what it means is basically by the time you're in your late 30s or early 40s, if you have any measure
01:15:22.140
of ApoB that's even north of the 20th percentile, that should be completely lowered. So in some ways,
01:15:29.880
I would view an ApoB ceiling of 60 as the limit. And that's probably at about the fifth percentile.
01:15:36.720
You'd sort of want everybody to be below the fifth percentile.
01:15:46.240
We hope you enjoyed this special episode of The Drive. This is one of the most talked about topics,
01:15:50.420
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01:15:55.080
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01:15:59.240
notes. However, we hope this provided you with a little more understanding of AFCVD,
01:16:02.440
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