What actually lowers cardiovascular risk: an expert's guide

The Truth About Reducing Cardiovascular Risk | Dr. Kevin Maki & Mike Haney

Dr. Kevin Maki is a clinical research scientist with more than 35 years of experience designing and conducting studies on cardiometabolic risk. He is the founder and chief science officer of Midwest Biomedical Research and holds an academic appointment in the School of Public Health at Indiana University. A former president of the National Lipid Association, Maki has collaborated with the American Heart Association and contributed to research spanning pharmaceutical and nutrition interventions for cardiovascular disease and diabetes. His work has included clinical trials on red meat, seed oils, avocado, and a wide range of lipid-lowering therapies.

In this episode, Levels editorial director Mike Haney sits down with Maki to dig into the evidence behind cardiovascular risk reduction — and what people can actually do about it. They cover the full landscape of risk factors beyond just LDL cholesterol, the emerging science on inflammation, what particle size and ApoB testing actually tell you, what the research on saturated fat and red meat does and doesn't show, and how to think about statins versus lifestyle when it comes to lowering risk. They also discuss how to evaluate industry-funded nutrition research, and why the advice to eat real food and cut processed foods may be the clearest signal in an otherwise complicated field.

"Lower for longer is better when it comes to LDL cholesterol and ApoB. And starting earlier in the atherosclerosis process is probably better — like saving for retirement, what you save early gives you the most benefit." — Dr. Kevin Maki

Research, industry funding, and how to evaluate nutrition science

Mike Haney: So to put a little context around this — we've done a couple of episodes recently on cardiovascular risk. We talked to Dr. Matt Budoff about assessing risk, sort of the diagnostic ladder from blood tests up to imaging, which is really his specialty. And then we talked to Dr. Ronald Krauss about sort of basic lipidology, just how do particles become plaque and what does that progression of disease look like and how much does particle size matter, which is something we might get into later today as well. And what I really wanted to cover with you, given your background, is, okay, then what do we do about it? I'm somebody who's taken Dr. Budoff's advice and I've gotten my testing and I now know I've got maybe some risk factors, some high cholesterol. And so you've spent a lot of time, decades doing all sorts of research from epidemiology to clinical trials around a lot of topics, but particularly around cardiovascular and lipids. Before we dive into that, by way of that bio, one of the things I found interesting about your background as opposed to some of the other folks I've talked to is that you are a research scientist. You're not a practicing cardiologist. And I'm curious how you think, given the breadth of work that you've done — and I know you work with a lot of cardiologists as co-authors on papers and things — how do you think it changes your perspective or how you approach your research as somebody who's really living in the research as opposed to working with patients in a different kind of context?

Kevin Maki: Sure, well my research is really clinical research, so it's on patients. What we've been doing over the last 30 plus years is essentially looking at ways to intervene to lower cardiometabolic risk. So risk for cardiovascular disease and diabetes in particular. And so what we're often focusing on is how do we assess someone's risk? And then based on that assessment, intervene in ways that are going to lower the risk. And so much of what I've done has focused on both lifestyle and pharmaceutical interventions to lower risk, hopefully before the disease is present. But once the disease is present, then the question is, well, how do we keep that from progressing and how do we prevent further manifestations of the disease?

Mike Haney: Well, great, that very much fits into what we're going to talk about today. The only other thing I wanted to ask you briefly before we dive into this, because there's another just aspect of your bio I found interesting, is that you've done most of your career at private research institutions. And I think that's an aspect of the research world that people may not be as familiar with. I think we're all kind of familiar with the university-based research, particularly as it's been in the news a lot more lately. I wonder if you could just tell us a little bit about what the private research world looks like. How do you figure out what to study? How do you make money? What's the difference between private and say university research?

Kevin Maki: Sure, well I started out in the VA system, so was a research scientist in the Department of Veterans Affairs, and I was happy there. I thought I'd spend 40 years there and retire. We had a new director come into the center I was in and he had other plans. He said, we're turning this into a neuroscience center. I was not a neuroscientist, so he invited me to find other employment. And I ended up joining a private research center. I didn't really know what a private research center was until a short time before I ended up working at one. And so at the private research center, I ran the nutrition and metabolism research unit for 10 years. And that was with Michael Davidson, who's a preventive cardiologist. And so a lot of the research that we did was funded by industry, although not all of it. When I say industry, that's pharmaceutical companies who are developing new drugs, and then also food companies that have a product and they'd like to demonstrate some benefit of that product to substantiate a claim and that claim may be for advertising or there is an FDA process to approve health claims. And so we did a lot of studies on products but then in addition to that throughout my career I've done work on one side to pay the bills, you know, to bring in enough money to pay the bills, and then I've also pursued my own research interests and I often do that in collaboration with universities. And so I have an academic appointment at Indiana University in the School of Public Health and then I have several collaborators at various universities that I've worked with for years to pursue the things that I'm most interested in. And sometimes those are not the things that pay the bills, really.

Mike Haney: And do private research institutions — do you ever get government money? Can you do things that are NIH funded or is it all sort of private industry funded?

Kevin Maki: I am a co-investigator on a number of NIH studies and studies funded by things like the USDA. But a lot of the funding that we get comes from commodity boards. So as an example, we just recently published a study looking at using avocado to replace saturated fat and added sugar. We call it SOFAs or solid fats and added sugars. We've done studies with things like beef and dairy and almonds and so forth. So we do have funding from the federal government as well as commodity boards, as well as industry, which would be pharmaceutical companies and food companies.

Mike Haney: This is probably a good place to address this. I think this might come up later when we talk about a recent red meat study you did. There's a real kind of inherent, I think, backlash, particularly online and in the kind of influencer sphere, around industry funding. And we've talked to lots of scientists here who do industry-funded studies. And so as a journalist, I am not reflexively dismissive of an industry-funded study. But it's probably worth — because you've spent so much of your career doing this and doing good quality research, and I didn't mention this in the bio, but you've been the president of the National Lipid Association, you've worked with the American Heart Association, you're a leading researcher in this space, which means that you have done enough good work over the decades that your peers and colleagues respect what you do, which to me signals that you're not just doing sort of what the beef industry wants you to do. But I'm wondering, how do you think about how people should look at funding sources, what does it mean when something's industry funded, what can we do to kind of help people put into context whether or not that matters and how it might matter.

Kevin Maki: Sure, I think that what people need to recognize is that if you wait for NIH to fund all of the important questions, especially in nutrition, what I say is I'm going to die of natural causes before a lot of the important questions get addressed by NIH-funded research. And so industry, whether it's the pharmaceutical industry or the food industry, they will fund research. And what annoys me, frankly, is when we publish a paper and the response is, industry-funded, we can't believe it. Well, if somebody has a criticism of the methods we used or the interpretation of the results that we got, I'm definitely open to criticism and discussion about that. But if it's reflexively, well, it's industry funded, so we can't trust it, then I would ask the question, well, who is going to fund that research? And so the real question is, was the research done in a sound way? And I've spent 35 years or so designing and conducting clinical trials to test products using good methods. And in a study, you ask a question. And of course, often the question that's asked is going to be very relevant to a product. So if a pharmaceutical company is trying to get approval for a product, they have to design studies. The FDA approves those studies going forward. And then the studies have to show results that support the efficacy and safety of the product. And so in the pharmaceutical industry, in fact, you have many more checks and balances in the research with clinical monitoring and with FDA review and so forth than you do in a university setting where there are many fewer checks and balances. So of course, the question that gets asked is going to be developed in collaboration with the funding source. And so you have to keep that in mind. But beyond that, it's really a matter of, was the research well designed? Is the interpretation appropriate? Are the methods of analysis appropriate to support the conclusions that are drawn in what end up in a published paper?

Mike Haney: And I imagine this is true for others — we had Chris Gardner in here a while ago, and he does a lot of nutrition RCTs and has done industry-funded stuff. And he pointed out that there are times you do those studies and you get effectively a null finding. And I would imagine for industry-funded studies, that's — if it's being done well, if they're hiring good researchers to do it, they have to know that's a possibility that sometimes they're just not going to get the response back that they want. And even when that happens, you are, as long as you were able to, still going to publish those results.

Kevin Maki: Right, and I should make a couple of points here that I think are important, especially in the pharmaceutical industry. Every efficacy trial is registered, and then the results get posted, they get published. So years ago, it used to be that results that didn't support the product would be put in a drawer, and they wouldn't see the light of day. That is not the case currently. With food industry-funded studies, there is that issue. And so we basically will not take on a study to test a health benefit of a product unless the results are going to be published, with a couple of exceptions. The exceptions really relate to, as an example, testing a formulation of something. So it's a proprietary issue. We know from the start it's proprietary. It's not to support a health benefit. And so in those cases, we may run a study and agree upfront that it's up to the sponsor what they want to do with the results. But most of the studies we run, if they're testing a health benefit, we say no matter what the results are, we're going to number one, register the trial so it's transparent, and then number two, publish the results no matter whether they support the claim that the study sponsor would like to make or not.

Mike Haney: That's really helpful context. I appreciate you kind of going into that more deeply because again, I think it's such an oversimplified and often misconstrued sort of aspect of this when these things get discussed online. And a lot of what I think we'll talk about today given your experience in this is that kind of meta level of research, not just what we found, but how do we find what we find and how should we think about it? Because I'm not a scientist, I'm a journalist, so my job is just that communication aspect of it. So I'm trying to be that intermediate layer between the public, who's often getting a vastly oversimplified headline — and I understand sometimes why my colleagues do that in our industry — and the scientists who are doing the very careful work and trying to help people understand.

With that as context, let's move on to cardiovascular risk. And maybe we'll just start here. What do we know about — at this point, what's the sort of collective knowledge, the synthesis about what we know about our ability to actually reduce cardiovascular risk? And let's start with cholesterol, because we'll talk about all the factors, the risk factors that go into that. But what do we know about sort of cardiovascular risk reduction and what's possible?

The big four risk factors and what Framingham taught us

Kevin Maki: Sure, well, we can go all the way back to 1948 when the Framingham Heart Study started. And so that study has been going continuously since 1948, first in a group of 5,000 residents of Framingham, Massachusetts, and then eventually in the offspring of those participants. And now I think they're on the offspring of the offspring. And so that study started because at the time it started, the general view was that atherosclerosis, hardening of the arteries, was just a consequence of aging, and there wasn't much you could do about it.

And what they showed, and many other studies since then have showed, they identified four big risk factors. And the big risk factors were elevated cholesterol, elevated blood pressure, smoking, and diabetes. So those are the big four. And so the first question is, well, these things are associated with risk. So people with elevated cholesterol or elevated blood pressure were more likely to have a heart attack or a stroke. And the next question becomes, well, is it causal? Is that relationship just correlation or is it causation? And so the next step in the process is to intervene in some way to lower the risk or to attempt to lower the risk. And you do that with randomized controlled trials. And so we have lots of evidence now for those big four risk factors.

Three of the four we have good evidence from clinical trials. With smoking it's pretty hard to randomly assign people to smoke or not to smoke. So we're pretty confident about that, but we don't have clinical trial evidence. But lowering cholesterol and lowering blood pressure reduce the risk of cardiovascular events. With type 2 diabetes, especially, it's a little more complicated because lowering blood sugar is associated with reduced risk, but the risk in diabetes seems to be driven by not just blood sugar levels, but also other factors that are associated with diabetes, like blood pressure, like lipids and inflammation and some other things. And so it gets a little more complicated there, but especially for cholesterol lowering and blood pressure lowering, we have decades of evidence now from randomized controlled trials to show that intervening to lower those risk factors reduces risk of cardiovascular events.

Mike Haney: And you mentioned those big four, and I know that has now expanded, and you have a very catchy acronym for remembering what all of the risk factors are. Maybe tell us what — I think it was FLASH, and now I believe it's FLASH-GLICK. So explain what that is.

Kevin Maki: Sure. This covers the major risk factors. So the original FLASH part is family history, low HDL cholesterol — what we have at times referred to as good cholesterol, but it turns out it's a little more complicated than that — age, smoking, and hypertension. So family history, low HDL cholesterol, age, smoking, and hypertension. That's FLASH. And then looking at the GLICK part of it, G is for glucose, and that's glucose metabolism. So blood sugar metabolism, not just glucose itself, but also insulin resistance, pancreatic beta cell function that contributes to the development of type 2 diabetes. And then L is for lipids. And so that's LDL cholesterol, which is what we've traditionally focused on the most, but there are many other aspects of lipids that are important that we can talk about in more detail in a bit. I is for inflammation, and it turns out that I think is an important factor in cardiovascular risk, and I think that's the next frontier where we'll have interventions to address inflammation.

And then C is for coagulation, blood clotting, and K is for kidney function. And so FLASH-GLICK covers the main risk factors. And I think that when clinicians are evaluating a person's risk, they need to consider all of those risk factors. And then there are some of them that are widely considered. And then others — I'll give you one example — Lp(a) is a type of lipoprotein particle that is associated with risk, but it's rarely measured. Only about 2% of Americans are getting their Lp(a) measurement done. And so that's an example of something where I believe that we can do a much better job of identifying people at increased risk. And then when you find increased risk, we have good ways to lower that risk, and there are also new ways to lower the risk that are in development.

Mike Haney: Yeah, and I want to talk about the sort of the interaction of all of those different things, because I think this story does often get oversimplified down to cholesterol and often just sort of bad cholesterol, good cholesterol. You know, that's what we get tested. We all get that every year. If we go in for a physical, those are the numbers that we see. But just the fact that there's what, 10 letters in that acronym tells us there are a lot of factors that go into this and a lot of interplay, and the relative contribution of those risk factors is going to differ depending on the combination of them and depending on individuality and that kind of thing. So I want to talk about a couple of them. I want to just spend a minute on the inflammation piece of it. Just in prep for this, I saw there was a Scientific American article this week, kind of a popular article about inflammation. And it was framed as, you know, scientists have uncovered the real secret to cardiovascular risk and it was largely a restatement of things that I think would have sounded very familiar to you, which is that inflammation plays a real key role, but we don't quite know yet. So colchicine, if I'm pronouncing that correctly, is one of the drugs that's been, or interventions that's been experimented on a lot. Where do you stand on that and what do you think we know and don't know about inflammation's role?

"If you wait for NIH to fund all of the important questions, especially in nutrition, I'm going to die of natural causes before a lot of the important questions get addressed. The real question is, was the research done in a sound way?" — Dr. Kevin Maki

Inflammation as the next frontier in cardiovascular risk

Kevin Maki: Well, the first thing is that we have decades of data now showing that increased biomarkers of inflammation — the most common one is high-sensitivity C-reactive protein — high C-reactive protein is associated with increased risk. So we have lots of evidence to show that. And then we also have evidence that if you lower LDL cholesterol, for instance, that lowers risk, but it lowers risk especially well in people with increased inflammation. So one of the points I want to make is that we have certain levers that we can pull right now: lowering LDL cholesterol, lowering blood pressure, keeping glucose under control, avoiding smoking. These are levers that we can pull. They have good evidence behind them. I'll mention one more, which is GLP-1 receptor agonists, which are used for control of diabetes and for weight loss. They lower inflammation. And I think that the cardiovascular disease benefits that have been demonstrated for GLP-1 receptor agonists may be in part or maybe even largely driven by their effects to lower inflammation. So what do we have, what do we really know about inflammation? Number one, it's associated with risk. Number two, we know that if you lower LDL cholesterol, that lowers risk in people with risk that's related to increased inflammation.

And then we have some evidence from studies with measures that directly address inflammation. So we have colchicine, as you mentioned, and then there's another drug, canakinumab, that has been studied. With colchicine, the results have been a little bit mixed, but generally favorable, but not universally so. With canakinumab, the results were favorable, but with a caveat — the drug is very expensive, and with that particular drug, there was a bit of an increase in risk of infection. So, trade-offs there. We also have things like icosapent ethyl, an omega-3 fatty acid drug. That's been shown to lower risk of cardiovascular events, but we usually think of that as a drug to lower triglycerides, but the reality is that the triglyceride lowering doesn't seem to drive the risk reduction. I think the risk reduction may be driven by reducing inflammation.

And then there's a drug under study right now, and we're going to have the results this year from this study called ZEUS, and that's a drug called ziltavecomab. And in that drug, it's a monoclonal antibody to IL-6. So what's IL-6? Well, it's an interleukin that basically is driving inflammation — it's part of the inflammatory response. So when it's elevated, that means there's increased inflammation. And people with chronic kidney disease have elevated levels of IL-6, elevated levels of inflammation, elevated levels of cardiovascular risk. And so this drug is being tested to lower inflammation in people with chronic kidney disease. And in that ZEUS trial, we'll know the results later this year. If those results come out being positive, then we'll have three separate drugs targeted at inflammation directly, plus information from a couple of types of drugs — an EPA drug, icosapent ethyl, omega-3 fatty acid drug, and with the GLP-1 receptor agonists. So all of those together will really strengthen the case that number one, inflammation is really increasing risk of cardiovascular events, and number two, if you intervene to reduce inflammation, it will lower risk.

Mike Haney: You mentioned in there that the GLP-1s — and it reminded me that obesity isn't necessarily in that kind of risk factor acronym. Is that because obesity is essentially a proxy for the inflammation, that inflammation's coming from the adipose tissue, so if you just have more obesity, more adipose tissue, you're gonna have more inflammation? Or is obesity kind of separately a risk factor apart from the inflammatory effects?

Kevin Maki: So it's controversial as to whether it should be included because obesity is definitely associated with increased risk for various adverse outcomes. Heart attack, stroke, atrial fibrillation, heart failure, chronic kidney disease — all of these are related to obesity. People who have obesity have increased risks for all of those things. And then we have some evidence from metabolic bariatric surgery, or weight loss surgery, that if people lose a significant amount of weight and keep it off with surgery, they have lower risks of all of those things I mentioned. And then we have evidence from the GLP-1 receptor agonist studies that show that they lower risk with patients who have obesity.

So the question though is whether obesity should sort of stand on its own as a risk factor or is it working through those other risk factors that I mentioned. Certainly obesity is associated with increased triglycerides, low HDL cholesterol, increased risk of kidney disease, increased inflammation and so forth. So generally I think that that FLASH-GLICK acronym, if all of the modifiable risk factors there are addressed — and for some of them we have better evidence than for others — then I think you're kind of covering it. But one of the ways to address some of those risk factors is through weight loss, and that can be done through lifestyle, pharmacotherapy, or surgery if somebody needs a marked amount of weight loss. We have drugs right now that are getting much better and the newest drugs that are in development, they're producing weight loss similar to what you see with surgery. And so I think we may be entering an era when surgery really takes a backseat and pharmacotherapy is primary.

LDL cholesterol, ApoB, and why lower for longer is better

Mike Haney: Yeah. Well, let's dive into the cholesterol aspect of that, because I think we've talked about some of the other pieces of those kind of 10 risk factors. And as you said, some of those are pretty obviously modifiable — just stop smoking. Some are not. Like if you have family history, you have family history. Or if you have kidney disease, you have kidney disease. But cholesterol, I think, is where this is going to come back to for an awful lot of people. So when we think about risk reduction, how much can changing our lipid profile affect that risk reduction and what's lost in the basic story of good HDL, high bad LDL, low?

Kevin Maki: Well, HDL turns out to be much more complicated. You know, 40 years ago when I was in training, learning about HDL cholesterol, we said, HDL — you know, H is for healthy, we think of it as you want it to be as high as possible. And it turns out HDL cholesterol is a strong predictor of risk, but attempts to modify HDL cholesterol with drug therapy, with lifestyle therapy have not proven beneficial. And in what's called Mendelian randomization studies, where you look at genetic variants, genetic variants that affect LDL cholesterol affect risk. Those that affect HDL cholesterol do not affect risk. And so HDL is pretty complicated. It's a risk predictor, but we no longer consider it at present a target of therapies. So the targets that we focus on are mainly LDL cholesterol and non-HDL cholesterol. Now I'm going to say something here because people have heard the term ApoB, or apolipoprotein B.

In my view, the main driver of increased risk is an increase in the circulating concentration of particles, lipoprotein particles, that are atherogenic. Now we measure LDL cholesterol and non-HDL cholesterol — and I'll just define non-HDL cholesterol: it's total cholesterol minus HDL cholesterol, so everything that isn't cholesterol carried by HDL particles. Well, it turns out that LDL cholesterol and non-HDL cholesterol I think are really proxies for the number of circulating atherogenic particles. ApoB is a direct measure because each of those circulating atherogenic particles has one molecule of ApoB in it. So ApoB is a better predictor than either LDL cholesterol or non-HDL cholesterol, but in the U.S. we don't routinely measure it.

And so we use these other things that are not quite as good, but they're still pretty good. And so one of the things that we need to think about is how much can you modify something without having an adverse effect? Well, when it comes to LDL cholesterol, turns out you can turn that way down with lifestyle and then if needed, drug therapies, and you can go to really low levels. With blood pressure, if you go too low, well, the person's not gonna do so well. With blood glucose, you can reduce it, but you can't go too low, so there's a window below which you run into problems. With LDL cholesterol, you could have somebody who starts with a value of 160 milligrams per deciliter and with a combination of lifestyle and drug therapy you could get that number all the way down to maybe 30 milligrams per deciliter. So it's a lever that can be pulled — but not just a little bit, it can be pulled to larger and larger degrees. And we have lots of evidence that lowering LDL cholesterol, which I think is a proxy for lowering the number of atherogenic particles in circulation, will lower risk. And the question is, well, how much? And the answer is a little more complicated than we've appreciated until recent years. So in clinical trials, when you lower LDL cholesterol by one millimole per liter, which is about 39 milligrams per deciliter, over five years or so, you lower risk of an event by about 22%.

But if you look at observational studies that have longer follow-up periods, the benefit is more. It's about 32% per millimole per liter. And if you look at people with genetic variants that lower LDL cholesterol, you find that there's even more benefit. So it's about 54% reduction in risk per millimole per liter lowering of LDL cholesterol with a genetic variant that does so. So it turns out it's lower for longer is better for LDL cholesterol, but with the caveat that LDL cholesterol I think is really acting as a proxy for the circulating level of atherogenic particles. And then we can talk more about what those atherogenic particles are because they're not all equally bad. All of the ApoB particles are bad. Some are a little bit worse than others.

Particle size, Lp(a), and what advanced testing actually tells you

Mike Haney: Well, that's a great setup for where I want to go next, which is into particle size. We talked a bit with Dr. Krauss about particle size. And I think for folks who pay a little bit more attention to this or read anything about it, they hear about large fluffy particles or ones you don't really have to worry about. It's the small dense ones that you have to worry about. And we're going to get to interventions in a minute. But there may be some difference on what interventions are affecting which type of particle. So how do you think about the particle size story as it relates to risk?

Kevin Maki: Well, the particle size story is complicated. There are many good theoretical reasons to believe that the small LDL particles are more atherogenic. They don't interact very well with receptors on the liver, so they tend to float around for a long period of time. They get into the arterial wall and they interact with proteoglycans in the arterial wall and they stick there. They also don't carry as many antioxidants, so they're more susceptible to modification. So for all of these reasons, I think that it's reasonable to think that the small particles are worse than the large particles.

But that doesn't mean the larger particles are not problematic. And so I'll give you a couple of reasons why the big particles are not something to be dismissed. Number one, statin drugs, which lower LDL cholesterol, they preferentially lower the larger particles and they show benefit. Also, people with familial hypercholesterolemia, they tend to have a lot of really fat, fluffy LDL particles, and they develop early atherosclerosis. And so the large particles are not benign.

But then beyond that, you have a couple of other things beyond LDL particles. So you have Lp(a) particles — I mentioned Lp(a). Ron Krauss, when you talked to him, talked about Lp(a). We have evidence from genetic studies, Mendelian randomization studies, that Lp(a) is causally related to atherosclerosis. And there are a variety of reasons I won't go into all of them, that these particles are even worse than your standard LDL particle. Just mention a couple of them. They seem to be pro-inflammatory and also pro-coagulatory, so they promote blood clotting. Also, they are involved in the process of aortic calcification. So, they're bad actors. And right now, there are drugs in development to lower Lp(a), and there are a couple of types of drugs that have a modest effect to lower Lp(a). But when Lp(a) is elevated, that's bad because on a per-particle basis, they seem to be about six times as atherogenic as standard LDL particles.

Lp(a) — I mentioned that it's not getting measured right now in clinical practice very often. It really should be, because it's an indication of increased risk. And even if we can't target Lp(a) lowering right now with a drug that's available, we know how to lower risk by lowering LDL cholesterol, lowering blood pressure, addressing inflammation and so forth. And so you can do those things to lower risk even if some of the risk is being driven by elevated Lp(a).

Mike Haney: And I'm glad you mentioned that. We sort of advocate for folks to ask their doctor about an Lp(a). I did with my doctor because I do have a high ApoB, high LDL. And the way I sort of think about it is that the Lp(a) number tells me a little bit about how much I should worry about those sort of borderline other numbers. Turns out my Lp(a) is pretty low and that's largely genetic, we believe. So as you say, even without a drug, if there's not much we can do about it, it's still definitely something that's worth measuring. What do you think about, on that measurement side, what do you think about the particle size measurements, which are again a thing if people really want to dive deep into the diagnostic world — you can pay to get the NMR and figure out your actual particle counts.

Kevin Maki: Well, I think that there is some value to particle size. If you have a predominance of small, dense LDL particles, what that often means is that for your level of LDL cholesterol — the thing that we focus on mostly in clinical practice — you're going to have a higher ApoB level. And so you're going to have an elevated particle concentration. And so there's this concept of discordance. If you have an LDL cholesterol level of say 100, which is just about the median in the population right now — half above, half below 100 — well, your ApoB level might be reflective of a value of 100 for LDL cholesterol. In about 70-ish percent of people, their ApoB and their LDL cholesterol are concordant, meaning that one reflects the other. In about 30% of people, you're going to have higher or lower ApoB than would be predicted based on your LDL cholesterol level.

And so who's most likely to have elevated ApoB? It's people with higher triglycerides, lower HDL cholesterol, and it's also people with very low LDL cholesterol levels. So in particular, people on drug therapy who have a low LDL cholesterol level — some of them still have an elevated ApoB. And so it's a little complex. I think the particle size is important in part because it's going to tell you something about — it's going to be related to your ApoB concentration. And people with a predominance of small dense LDL particles are often the people who have higher ApoB than you would expect based on their LDL cholesterol measurement.

Mike Haney: Yeah, and we should mention that ApoB is not widely tested, but also a relatively cheap test. If you want to ask your PCP to add it on to your blood panel, it's pretty easy to do.

Kevin Maki: Yeah, and the particle concentration kinds of tests, the NMR and the ion mobility test, they give you essentially the information you get from ApoB, but they give you more information on top of that. More information can be better in the right hands of somebody who knows how to interpret it, but for many clinicians, more information just confuses them because they don't know how to interpret it. They don't know how to put it into context. And then you end up with more questions than answers. So I kind of like focusing on LDL cholesterol, non-HDL cholesterol, and ApoB. But in the right hands — like in a lipid specialist's hands, or somebody who's gone through the additional effort and training to be able to interpret the NMR or the ion mobility test results — they can be valuable beyond an ApoB. But the challenge for most clinicians is they get these results, they don't really know what to do with them.

Mike Haney: Well, I'm glad you mentioned that the large fluffy particles are not completely benign because again, I think that's a story that often gets told in the sort of YouTube health circles of, my LDL might be 200, but it's really not a problem because it's all large fluffy and so I'm perfectly fine. And I do like the idea of sort of A, putting that cholesterol number in the context of those other risk factors, which really matters, but also just sort of simplifying to — if you have any of those other risk factors, nevermind if you have some actual plaque buildup, if you've done a CAC or something else, if you have high LDL, there is still some associated risk there. We know that, that's a very clear story and you should start to think about lowering it.

"On a per-particle basis, Lp(a) particles seem to be about six times as atherogenic as standard LDL particles. And only about 2% of Americans are getting their Lp(a) measurement done." — Dr. Kevin Maki

Saturated fat, seed oils, and the "compared to what" problem in nutrition research

So to maybe move on to that — I think the thing most people are gonna, I think the two levers most people are gonna run into if they're in that situation, we've gone to the doctor, we've got the high ApoB or the high LDL, is diet and medication. So let's talk about diet first. And I think saturated fat is again, if we're kind of going down that funnel, the doctor's gonna say, clean up your diet and they're gonna say cut saturated fat and they may even say cut red meat. And I want to talk about your red meat study. You've done a bunch of red meat studies, but particularly the one you did a couple of years ago. But let's just start with the saturated fat story. How much is saturated fat a causal lever for lowering — not just LDL but ultimately lowering cardiovascular risk, which is what we ultimately care about?

Kevin Maki: Right, well, I think there's one thing that's very certain, and that is that increasing saturated fat in the diet will increase the LDL cholesterol concentration. There's no question about that. Now, the dietary guidelines for Americans say consume less than 10% of calories from saturated fat. Average intake in the U.S. right now is about 11%. So we're not far away from that less than 10% on a population basis. And if you take average intake of about 11% and cut it in half, that's going to lower LDL cholesterol by roughly 5 to 8% or so.

And so it's a factor, it's an important factor. Another somewhat less quantitatively important factor is dietary cholesterol. Each 100 milligrams per day increase in dietary cholesterol raises LDL cholesterol by about two milligrams per deciliter, but it does flatten out. So when you get up to four or 500 milligrams, that relationship flattens out. We think about factors in the diet that raise LDL cholesterol, and that's mainly saturated fat and dietary cholesterol. We used to talk more about trans fats. They also raise LDL cholesterol, but industrial trans fats have been more or less eliminated from the U.S. diet.

But we also have to balance those against factors in the diet that lower LDL cholesterol. So what lowers LDL cholesterol? Well, one is unsaturated fats. So mono and polyunsaturated fats lower LDL cholesterol. Another factor that lowers LDL cholesterol is protein. And this is often underappreciated. Both animal proteins and plant proteins lower LDL cholesterol when compared to carbohydrate. So in other words, if you replace some of the carbohydrate in your diet with protein, whether animal protein or plant protein, you're going to lower LDL cholesterol some.

And the interesting thing is that for reasons we don't fully understand, plant proteins do so to a larger degree than animal proteins. Okay, so we've got unsaturated fats, monos and polys, and then we've got protein. We've also got viscous fiber that lowers LDL cholesterol. We've got plant sterols and stanols, which are found in food to some degree — corn oil, as an example, is high in plant sterols. And then you can also buy supplemental plant sterols. You can buy margarine-type spreads. And there are little shots that you can buy that have plant sterols and stanols. They lower LDL cholesterol as well. And then weight loss. So if somebody loses 5% of their body weight, that's going to tend to lower LDL cholesterol as well. So it's really the balance of cholesterol-raising and cholesterol-lowering factors in the diet.

And while I think saturated fat is important, I don't think it's the end of the story. And what is often promoted — things are oversimplified to say just lower your saturated fat intake and that's kind of the end of the story. Well, it's a little more complicated than that. I would say that what we should be focusing on is lowering saturated fat and also lowering refined starches and added sugars, and then replacing those with things that lower cholesterol levels like unsaturated fats and also proteins with an emphasis on plant proteins because they seem to have a little bit larger effect. So it's a balance.

I'm also going to just comment on one thing. You hear a lot of talk about seed oils and how terrible seed oils are. The story, the narrative is they're pro-inflammatory, and actually the evidence doesn't really support that, at least the evidence from studies in humans. We just published a paper where we had about 2,000 people. We had blood levels of linoleic acid, the main fatty acid in seed oils, and the higher the blood level of linoleic acid — which is an essential fatty acid, and therefore it's from the diet only because the human body doesn't manufacture linoleic acid — the higher the level of linoleic acid in the blood, the lower the level of biomarkers of inflammation. And so again, the focus is lower saturated fat and cholesterol, but also increase those factors that lower LDL cholesterol.

I'll make one more point about saturated fat. There may be other mechanisms — there have been other mechanisms proposed for why saturated fats may be connected to cardiovascular disease. Some have proposed they're pro-inflammatory, some have talked about in cell membranes they reduce membrane fluidity and so forth. And some of those are plausible, but we don't really have strong evidence to support them. That doesn't mean that we might not in the future. But again, the heavy emphasis on saturated fat — while I think reducing saturated fat has a place, I think it's been over-emphasized, and some of the other factors in the diet have been under-emphasized. One more point, and then I'll let you ask the next question, which is healthy dietary patterns are characterized by high intakes of whole grains, fruits and vegetables, nuts, seeds, legumes, non-tropical oils, and seafood, and limit what I call the four white poisons. Now, that's tongue-in-cheek. I'm not saying we should eliminate these things from our diet, but we probably, in the average American diet, consume more than is optimal of the four white poisons: saturated fat, salt, refined starches, and added sugars.

Mike Haney: Well, yeah. And I think that the point on seed oils and, I think to some degree, saturated fat — what I like about the way you frame both of these is not just about cutting, it's about what you replace it with. A phrase that I hear you use a lot is "compared to what." And I think about that in terms of like, okay, cutting out the saturated fat. And we've seen the same thing in the seed oil studies, right? What you replace the seed oils with has a lot of effects. So the seed oil industry likes to publish studies in which they go, look, seed oils are really healthy, but the comparison is that we replaced them all with refined carbohydrates and people got less healthy. And it's like, well, right. If you eat a Snickers bar instead of that cup of seed oil, then you're not necessarily going to do better. But if you replace it with an avocado or an olive oil or a kind of healthy fat, you might get a different outcome there. On the saturated fat side, I take the point that it is perhaps overemphasized because it is sort of the simplest story and it is causal, right? It's one of the few things that we know does have this relationship. I guess sort of two questions — this will lead us into the red meat discussion. What do we know about outcome-based risk reduction? So we know saturated fat can cut our LDL cholesterol, we know that these other cholesterol-affecting things, protein — what do we know in the research about then the downstream actual CVD risk reduction of making these changes? Is that a clear story?

Kevin Maki: Well, I think in some elements, it's clear. In other elements, we have to rely mostly on observational evidence. So observational evidence is where you collect data and then you look for correlations, as opposed to clinical trials where you take people at risk, randomly assign them to one intervention or one treatment group versus another, and then follow them over time. So in terms of cardiovascular outcomes, the two largest outcomes clinical trials that we have are the PREDIMED study and the CORDIAPREV study. They were both with Mediterranean dietary patterns and in both of them there was 25 to 30 percent lower risk of major adverse cardiovascular events in the groups assigned at random to receive a Mediterranean dietary pattern as compared to what they called a low-fat dietary pattern, but it wasn't really that low in fat. It's kind of emphasis on reducing saturated fat. So what I would say is we have a little bit of clinical trial evidence — so the strongest evidence is for a Mediterranean dietary pattern.

But most of what we know in terms of actual outcomes is from observational studies. And that's where you're basically measuring things and then saying, as an example, here we have five groups of people, lowest, next lowest, middle, high and highest level of saturated fat intake or red meat intake or whatever intake. And then we're saying, do the people with high intake have higher risk than people with low intake? And here's the challenge. The challenge is that there are many things that are associated and it's difficult to control for all of them statistically. So if you look at red meat as an example, people who eat a lot of red meat also have other lifestyle habits that may be associated with risk of cardiovascular disease. So high versus low red meat consumers — the high consumers tend to eat fewer fruits and vegetables, have higher body mass index, they're more likely to smoke, they have lower education levels on average, and you have lots of differences. Well, the way we deal with that is we make statistical adjustments and say, we've adjusted for all of these potential confounding variables, and there's still a relationship there.

And so I'm trained as an epidemiologist, so my training is in epidemiology, nutrition science, and exercise physiology. And during my career, I've seen time after time where the epidemiology, which often gives us the right answer, but it doesn't always give us the right answer. So I would say that I have a healthy level of skepticism in areas where the recommendations are primarily based on epidemiology observational evidence, and I have much more confidence when that is supported by results from clinical trials. Now there are two kinds of clinical trials. One is outcomes like PREDIMED and CORDIAPREV. The other is on biomarkers. So biomarkers of risk like LDL cholesterol, blood pressure, markers of inflammation and so forth, they can be very helpful.

And so I would say that what I want to see if I see an observational study that shows an association — I want to see number one, strength of association, number two, consistency of that association in different populations across different investigators and so forth. I'd like to see dose response. So the higher the level of exposure, the greater or the lower the risk. And I'd like to see biological plausibility. And that's where I think a lot of the recommendations that are primarily based on observational evidence, the biological plausibility is the part that is the weakest. And so I'll say that in many cases, epidemiology leads us in the right direction. In some cases, it hasn't. And where we don't have great clinical trial evidence for biomarkers and for outcomes, I say, okay, I'm okay with making a recommendation. Just acknowledge the uncertainty in that recommendation.

The red meat evidence: what the research actually shows

Mike Haney: Right. Well, I think it's a good lead into the red meat meta-analysis that you did. As I mentioned, I think your first red meat study was in 1999. You've done a bunch over the years, but I think it was in late 2024 or 2025 you did a big meta-analysis of a lot of the red meat studies that have been done. And the headline in the press was, red meat doesn't cause heart attacks. And that is not, in fact, I think, what the actual takeaway from that study was. But I think it did a little bit upend some of traditional advice, which I think, as you pointed out, is surprising because it was consistent with results you've gotten over 20 years of studying this. Maybe tell us about what did you find in that red meat study and the relationship between red meat consumption and cardiovascular risk?

Kevin Maki: Right, and so I should emphasize that what we evaluated was cardiovascular risk factors, so biomarkers of risk. And in that particular meta-analysis, we looked at 16 studies to evaluate effects of red meat compared to different controls on cholesterol levels and on blood pressure. So blood pressure was the simplest — there was just no difference with regard to blood pressure. As far as cholesterol levels go, that was a little complicated. Comparing, say, red meat to poultry. And in that particular meta-analysis, we were looking at beef specifically, which is the most commonly consumed red meat in the U.S. So in 15 of 16 studies, there was no difference. In one study, there was a difference. It was a little bit of an odd study because it was a study where there was a very low calorie diet used.

Now to be transparent and to stick with our initial plan, we reported the results based on the studies that qualified. And based on that, LDL cholesterol was slightly higher with beef as compared to the comparators. When you eliminate that study, then there were no differences. But I do want to make a point. It's always, what do you compare it to? If you compare beef to poultry, you see no difference. If you compare beef to carbohydrate, then you see a little bit of a difference. If you compare beef to a plant source of protein — legumes, things like lentils or nuts and so forth — you're gonna have a lower cholesterol level with those plant sources of protein. I want to be clear, but the sort of traditional advice to consume white meat rather than red meat, there is no difference in cholesterol levels when people consume poultry versus beef as an example. And we illustrated that in a paper we published in 1999, and again in a paper we published in December of 2025. In that study, we gave people two servings a day of chicken or beef. The chicken was lower in saturated fat than the beef. At the end of one month of two servings a day feeding of chicken, the LDL cholesterol level was 112. One month on beef, two servings a day, the LDL cholesterol level was 112. Why, with beef that had more saturated fat, did you not see an elevation in cholesterol compared to chicken? Well, the reason is, if you look at the fat in beef, about half is saturated, half is unsaturated. And of the saturated fat, it's roughly half and half stearic acid versus other saturated fatty acids. And the thing is that if you plug that into a prediction equation, the predicted effect of the fat is zero. And that's in fact what we saw. So if you compare beef and chicken, no difference in cholesterol levels. Now you can hypothesize that there may be other mechanisms, things like heme iron and so forth that could be important. But as far as cholesterol levels go, no difference between white meat and red meat. And to be fair though, plant sources of protein compared to animal sources like poultry or beef would tend to lower cholesterol levels.

Mike Haney: This is where I want to get into the kind of, what this means in the real world, because you had a nice piece — I think a couple of years ago — about the difficulty of making dietary recommendations based on nutrition studies, because nutrition studies are just tricky, especially compared to drug studies, right? In a drug study, we go drug versus placebo. There's a very clear contrast. In nutrition studies, we always have the compared to what? And while I really like your point about having to balance epidemiology with clinical trials — and of course, the challenge with clinical trials is they're very specific, right? A clinical trial has to, by definition, go a particular dose in a particular population for a particular length of time. All those things are specific. And so if we alter one of those, then maybe we do get a slightly different outcome. And so when it comes to something like, how should I think about how much meat goes in my diet — whether that's red meat or white meat — both of which are going to have a little bit of dietary cholesterol, a little bit of saturated fat in them. I saw, I think, in that paper that the average red meat consumption in the U.S. is something like 1.8 ounces a day. And I was like, all right, if I take that over 365 days a year, sure. But in the real world, nobody sits down and eats 1.8 ounces of red meat, right? The way you consume red meat is a burger that you get at the pub that might be a third of a pound and it's on a bun that's made with white carbs, and it's maybe got some mayo on it or something else and you're eating fries along with it, or you're eating a steak at the steakhouse. And so how do you think about how to take the results of something like that meta-analysis or the RCTs that you've done and that sort of very clear mechanistic explanation of like, look, there isn't actually that much LDL-raising saturated fat in these things, in the context of how people live in the real world and how they actually consume these things, and what do you do with that information as somebody who's trying to work on your cholesterol?

Kevin Maki: Yeah, that's where it is a challenge, and it's a challenge to have messages that are clear to consumers, but that take into account the nuance. And so you mentioned precisely the issue. So is it the beef in that burger that is really the problem or is it all of the salt and carbohydrate — refined carbohydrate — that is in there. Is it reflective of a lifestyle? So what I tend to emphasize is that we want to eat more of certain things that we're not eating enough of. So whole grains, fruits and vegetables, nuts, seeds, legumes, non-tropical oils, and seafood. And we want to prepare those things to the degree that we can in a way that is not adding a lot of salt, added sugar, doesn't have a lot of refined carbohydrates. So we talk about hamburger, for instance. Well, we could have a hamburger on a whole grain bun. We could choose a burger that is made with leaner beef. Now, this isn't the one you're going to get at the pub, but if you're making it at home, you can use leaner cuts of beef. Now, it's not the fat in the beef that is raising cholesterol, at least compared to white meat, but higher fat is associated with higher energy density, and that's one of the factors that contributes to overeating, essentially.

Using a whole grain bun, including fruits and vegetables with it. Maybe instead of french fries, which are deep fried and high in fat, which raises the energy density — maybe it is a baked potato and the baked potato maybe instead of having butter and sour cream on it, maybe has olive oil on it. So it's largely about taking the things that people like to eat and helping them to figure out what things can you substitute that you're still going to enjoy but are going to be lower in those, what I call four white poisons: saturated fat, salt, refined starches, and added sugars.

The challenge is, of course, that simple messages are difficult. And I don't have a way to make the complexity of nutrition extremely simple, but I think that there are some simple messages that you can deliver. And largely it's about identifying things in the diet that we'd like to cut back on and thinking about how can we replace those or augment them with the foods we'd like people to eat more of. And I'll make one more comment. Average intake of unprocessed red meat in the U.S. is about 1.6 ounces a day, but on top of that there's about an additional ounce of processed meat. Now, processed meat includes both processed red meat and processed white meat, like chicken nuggets would be processed. So, the things that I say are cut back on processed meat, also cut back on foods that are deep fried and foods that have a lot of added fat. When you're going to use fat, try and focus on those unsaturated sources of fat. So things like olive oil or corn oil or canola oil as examples instead of, say, butter, sour cream, anything deep fried, etc.

Mike Haney: The last point I just wanted to make about saturated fat, which I've heard you mention and I think reinforces the message that all this nutrition advice comes back to, is that a big source of saturated fat in our diet is in fact processed foods. It's the frozen pizza that you're getting. It's the chicken nuggets, the fast food that you're getting. Those tend to have pretty high concentrations of saturated fat. So one way to cut that out of your diet isn't necessarily don't ever eat red meat again. It's eat real food.

Kevin Maki: Yeah, that's right. The new dietary guidelines are fairly controversial, but I'll say there are a lot of things in the guidelines that I like, and the emphasis on eat real food, cut back on highly processed foods. And I would just say highly processed foods and anything that's deep fried. Those are two areas where Americans eat much more than is optimal. And making substitutions for those really moves the needle in the right direction.

"It's not the beef in that burger that is really the problem — it's all of the salt and refined carbohydrate. The simple message is cut back on processed meat, foods that are deep fried, and anything with a lot of added fat." — Dr. Kevin Maki

Statins versus lifestyle: when to start, how low to go

Mike Haney: Well, let's get to — in the time we have left — the other thing that people are going to use to lower this, which is medication. And statins is the one that most people are going to come into contact with. We could do a whole show about statins and the evidence around them and the controversy around them. But I'll maybe just cut to sort of my core question around this. And this relates to an experience I had. So I have high cholesterol. My ApoB is about 130. It's been pretty high. I went and got the CAC test after doing my podcast with Dr. Budoff. And my score was four. And my PCP said, I'm not worried. Lp(a) is low, no family history, I'm pretty fit, diet's okay. Said, I'm not worried about it. And I said, I'd like a low-dose statin prescription because I'm not convinced, based on everything I've read and even what we've just been talking about here today, about how much I can move cholesterol with just diet or lifestyle alone. I'm not going to get it from 130 to 70 with just lifestyle. And to your point earlier, lower for longer is better. I'm 50, so I'm not starting at 30, but I've hopefully got some years left here. And so I went on a low dose statin and I'm only maybe 30 days into it, so I haven't tested yet.

So I guess my question is, why do we emphasize the idea of lifestyle first — let's see what we can do with lifestyle before we go to a statin — acknowledging that there are some side effects and some real side effects that people have, but it's a deeply studied drug, very high safety profile compared to a lot of other things, particularly compared to a lot of supplements that people might try instead of a statin. And I'm not pro-pharmaceutical here, but just from a risk reduction standpoint, it feels like the emphasis on lifestyle first may just be setting people up for kind of a failure because, okay, I'm going to make all kinds of really hard changes to my diet. I'm going to cut out a whole bunch of stuff that I like. And then maybe my cholesterol comes down five or 10 points. It's still too high. And now I'm going to go to a statin, but in the time that I've been messing around with diets and trying to change things, maybe I've got more plaque buildup when I could have just taken this drug and gotten that big impact that we can get from these drugs from the beginning. So how do you think — it's a lot of preamble — but just how do you think about this balance of statin versus lifestyle in terms of risk reduction?

Kevin Maki: Yeah, it's not a question of who will benefit from LDL cholesterol lowering. It's a question of in whom is the benefit sufficient to justify the risks, because all drugs have some risks associated with them, the potential side effects, and the cost — cost in terms of a person's time for follow-up, additional testing, and cost to the healthcare system. And so we have a new set of cholesterol management guidelines, or dyslipidemia management guidelines. And essentially they divide people in primary prevention — so that's for people who have not had a heart attack or a stroke or a bypass surgery — into different risk groups. So 10-year risk less than 3% is considered low. From 3 to 4.9% is considered borderline. From 5 to 9.9% is considered intermediate. 10% or higher is high risk. And so the first thing is we shouldn't look at ApoB or LDL cholesterol in isolation. We should think about what are all of the other risk factors and then estimate a person's risk. And then you have to look at these other things, like you mentioned having a coronary calcium score that was low. But it's not zero. So there is some atherosclerosis in there. One of the challenges is that coronary calcium only shows up with plaque that's been there for a while, essentially. And so that doesn't mean there isn't some plaque brewing in there. And with an ApoB of 130 — my personal view, this is not guideline recommended — but I had terrible genes, and so I can thank my parents for giving me some horrible genes and so I went on a statin at a very young age and then I had a coronary calcium score when I was 55.

And I was not happy with the results. So then I really got to better living through chemistry and cranked up the pharmaceutical intervention at that point because I realized that even though I had been on a statin for years, I was still laying down plaque. And so I think coronary calcium is a great way to make a decision, to help make a decision. Then the question becomes, do you want to wait a few years and have that done again and see how things look? Or do you want to be more aggressive now? My personal orientation would be to say, we have three goals for LDL cholesterol, and those goals are less than 100, less than 70, less than 55. And I'd like to see everybody's LDL cholesterol less than 100. If you can get there with lifestyle, fantastic. If you can't get there with lifestyle, then the question is, well, is your risk high enough to consider drug therapy?

And statins are the drugs for which we have the most evidence, but there are others as well, like ezetimibe, also generic. And ezetimibe does not have the side effects generally that are associated with statins. Statins do slightly increase the risk of diabetes. In some people, they are associated with muscle aches, although many fewer people than believe they have statin-associated muscle aches. People given a high-dose statin who had never taken a statin before — about 9% of them had intolerable muscle aches. But about 4.6% in the placebo group also had intolerable muscle aches. So, about 5% of people or so have muscle aches related to taking a statin. And in those people, you know, there are alternatives available.

So what I would say is the most important thing is meet those goals, and in primary prevention it's less than 100, and it's a discussion with your doctor about what are the risks and benefits and costs, and how do you balance those? But when in doubt, I would favor just do what you need to do to meet those goals. And you mentioned ApoB — the corresponding goals for ApoB: I mentioned 170 and 55. The corresponding ApoB goals are 90, 70, and 55.

The case for earlier, more aggressive primary prevention

Mike Haney: Okay. Well, I think we're just about up at time, but maybe just as a way to leave it — you mentioned primary and secondary prevention there, and I think you did some work recently on primary prevention. My read of this is that we're learning more about the amount of risk reduction we can get by intervening, by doing primary prevention. In the past, it was more, okay, if you've already had an event, then we're going to intervene more aggressively. But we're now learning that we can intervene aggressively even as part of primary prevention and still get pretty good risk reduction. Where do you see that going and how do you think that might impact how we think about this kind of aggressiveness of intervention at earlier stages?

Kevin Maki: Well, I think that one of the challenges is that we've been firing blind. So we have coronary calcium, that's a good indication, but as I mentioned, you can have plaque that is non-calcified and progressing. And so I think in the future, we're going to have much better imaging modalities that are cost effective, and I think AI is going to help with that. And then we'll be able to identify plaque and really get more aggressive in those people with plaque.

But what our meta-analysis in primary prevention showed was a couple of things. Number one, the relative risk reduction in primary prevention actually appears to be larger than in secondary prevention. Well, what do I mean by that? Every millimole per liter — 39 milligram per deciliter — reduction in LDL cholesterol in primary prevention was associated with a 30% relative risk reduction for a major adverse cardiovascular event. In secondary prevention — people have already had, say, a heart attack or a stroke or bypass surgery — it's about 20%. So the relative risk reduction is higher. I want to emphasize absolute risk reduction is still going to be larger in secondary prevention because you have higher absolute risk, so lowering that little bit is still a larger absolute benefit.

But there were two particular findings from our meta-analysis. We did subgroup analyses, and two groups had greater benefit. The lower risk group — so when we took our sample of studies, it was 13 studies, and divided them in half, the half that were at lower risk at baseline had the largest relative risk reduction. And then the other subgroup that had a larger risk reduction was people with inflammatory conditions. And so lowering LDL cholesterol is beneficial. I think the earlier you start in the process, the greater the benefits. So like saving for retirement, what you save early gives you the most benefit at retirement time. Well, the early intervention to prevent those plaques from forming and to get them at an early stage seems to be better. So lower for longer is better and starting earlier in the atherosclerosis process is probably better. The only trouble is that we don't know who has atherosclerosis brewing and who doesn't except by doing a coronary calcium score. But that's problematic because calcified plaque has been there for a while. So to get at those early stages, we don't have good ways that are non-invasive and inexpensive to identify those people. So there's work to do, but from my perspective, lower for longer is better when it comes to LDL cholesterol and ApoB.

Mike Haney: Well, I think that's a great note to end it on. So appreciate your time today and all the insights. Thanks so much.

Kevin Maki: Alright, thanks so much for having me.