RHR: The Lipid Energy Model and Lean Mass Hyper Responders, with Dr. Nicholas Norwitz

In this episode, we discuss:

• Lean Mass Hyper-Responders and Dr. Norwitz’s Oreo vs Statin Study
• The Lipid Energy Model: A New Perspective
• Challenging Conventional Wisdom: LDL’s Role in Cardiovascular Disease
• The Problematic Research Ecosystem for Nutrition and Metabolism
• Other Potential Risk Factors Contributing to Cardiovascular Disease
• Future Direction and Concluding Thoughts

Show notes:

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Hey, everybody, Chris Kresser here. Welcome to another episode of Revolution Health Radio. Throughout my career as a clinician, one of the most common scenarios that came up in my practice that was always difficult for me and for patients was when someone who was lean went on a low-carb diet and saw their [low-density lipoprotein] (LDL) cholesterol or [apolipoprotein B] (ApoB) or LDL particle (LDL-P) number skyrocket. Everything else looked good— the blood sugar markers, inflammatory markers, even the calcium score. Overall, their cardiovascular risks seemed low, but they had this very high LDL level. And the question was always, does that matter? Are they at the same level of heart disease risk as someone else who has a very high LDL level, but has other risk factors? These are questions you would think would be fairly obvious and have easy answers to, but the fact is, we didn’t have clinical research that shed light on that answer for this particular population.

That has changed recently with the publication of some studies on the lean mass hyper-responder phenotype, which is this group of people who are lean in body weight but have a pronounced response to a low-carb or keto diet where their cholesterol levels skyrocket. So I’m very excited to welcome my guest today, Nick Nowitz. He completed his undergrad at Dartmouth, where he majored in cell biology and biochemistry, and graduated valedictorian. He completed his PhD at the University of Oxford in the UK in human metabolism and ketosis, and he’s currently in his third year at Harvard Medical School completing his MD. Nick himself was a lean mass hyper-responder, so when he adopted a low-carb and ketogenic diet, his LDL cholesterol went up to 500, which is just insanely high. He shares this publicly and talks about his own journey with this, which eventually led to him pairing up with Dave Feldman and a number of other people who’ve been active in this field, exploring the lean mass hyper-responder phenotype and something that we talked about on the show called the lipid energy model, which seems to contradict, at least on the surface, our dominant paradigm understanding of the role of LDL in the pathogenesis of cardiovascular disease.

These studies were fascinating. They raise many questions. They don’t provide us answers yet, but they raise many important questions and will hopefully point us in a direction where we can continue to advance our understanding of heart disease, which is still the number one [cause of death] in the [United States] and many countries abroad. So I hope you enjoy this conversation as much as I did. Let’s dive in.

Chris Kresser:  Dr. Nick Norwitz, it’s a pleasure to have you on the show.

Nick Norwitz:  Thanks for having me on, Chris.

Lean Mass Hyper-Responders and the Oreo vs Statin Study

Chris Kresser:  Here’s a scenario from my practice that I came across all the time, and it was one of the biggest ongoing questions for me as a clinician and for my patients. A fairly lean person would adopt a low-carb, high-fat diet, sometimes keto, for various reasons. [It] could be they wanted to lean out further, or [that] they were looking for cognitive improvements, or just general health improvements. And all of their other biomarkers [that we were tracking] would improve– inflammatory markers, glucose, blood sugar, regulation, etc. But very often, their ApoB or LDL-P, as we were measuring it at that time, would go up and sometimes it would increase precipitously. We’d see 50 percent plus increases over a couple months or three-month period.  Sometimes those would stabilize a little bit over time, but [other times]  they would just maintain and they would remain elevated. And the conversation I had with those patients always looked something like this– Well, all of your other markers are good, you had a calcium score of zero, you don’t have a strong family history, [and] your blood pressure is normal. Pretty much everything that we can look at looks like you have a low risk for cardiovascular disease, except you have this very high ApoB. And the research that we have right now shows a correlation between high ApoB and cardiovascular events. We don’t know how that applies to someone in your situation, and there’s really no published research to guide us. Empirically and anecdotally, I would assume that if all of these things are getting better, your risk is likely going down. That’s just what makes sense intuitively to me as a clinician, but we don’t really know.

Now, we might know a little bit more. Tell us a little about this study, and what it means for people in that situation and beyond.

Nick Norwitz:   I’ll start by not burying the lead. I found that to be the most engaging approach, then I’m going to wrap proper context around it.

Chris Kresser:  Great.

Nick Norwitz: The study you’re referring to dropped a couple days ago. [The focus was] a lean mass hyper-responder, the phenotype you’re describing. [It’s] when somebody goes low-carb, they’re lean, they’re using it for therapeutic reasons, [and] generally, although not always, [they] see their LDL skyrocket. Now you can talk about ApoB, LDL-P, [and] LDL cholesterol (LDL-C). When somebody is a lean mass hyper-responder, they’re all super-high. I’m going to talk about LDL-C when I’m saying LDL throughout this podcast. If I give you the number, it’s LDL-C, just because it’s very easy to measure and it’s what is standardly measured. Most people register that in [their] mind, like weight, [or] like [body mass index] (BMI); it’s just a common measure. And I’ll reveal [that] I was a lean mass hyper-responder in the case. It’s no secret by now, if you’ve been following along. When I went low-carb in 2019, [my LDL] went up from 95 on a mixed diet to over 500. It was 545 at the peak. And then we did a block of research, which we’re going to get to. We have like eight studies on this topic. But here’s the problem. That scenario [that] you’re talking about [is] one that’s becoming more and more frequent. And yet, our research, for reasons I might get into later, hasn’t been widely publicized.

Now, I think this is something that we absolutely need to talk about as a scientific community. So I engineered what I very much intended to be a very provocative experiment and a demonstration, testing the model we think explains why this occurs. The experiment was, and I announced this before I did it, [that] I’m hypothesizing I can lower my cholesterol from astronomically high levels. The level is so high that if most physicians [saw] it, they [would] either [think it was] a joke, or that you have a terrible genetic condition. Those are the two options, a joke or a terrible genetic condition. But I thought, you know what? Given what I understand, I predict I can lower this with Oreo cookies. Literally…a sleeve of Oreo cookies. That was the intervention — add a sleeve of Oreo cookies to my diet. Now it sounds ridiculous, and in a sense, it is, but what you try to do in science is take models that you have and you want to try to break them. So this was me trying to break my pre-existing model in a very robust and extreme manner, saying, “According to the logic of my model, this should actually work. It sounds ridiculous, but it should work.” And the punchline is [that] it actually did.

So I tested the lipid energy model on myself by predicting I could lower my cholesterol with Oreo cookies. And not only that, I did it in a very controlled manner, then had a washout period and compared it to high-intensity statin therapy with my [primary care physician] and a consultant lipidologist on board. So I wasn’t just doing this rogue. I went before [Institutional Review Board], got [an] exemption and all the bells and whistles to make this ethical. And the finding was that, in just two weeks, or specifically 16 days, a sleeve of Oreo cookies added to my diet– I didn’t reduce the fat, I added Oreo cookies to my diet– reduced my LDL cholesterol by 273 milligrams per deciliter, or 71 percent. By comparison, the statin lowered my LDL by 137, or 32.5 percent, from its respective baseline. And the statin was a six-week therapy. So the punchline here is that, in this tested lipid energy model that I performed on myself, I was able to lower my cholesterol, my LDL cholesterol specifically– the so-called “bad cholesterol”–    by twice as much with a sleeve of Oreo cookies [than with] high-intensity statin therapy. And the Oreo cookies were faster, which, set aside the fact that it sounds ridiculous, is mind blowing. It should be mind blowing for everybody. And that’s kind of the point. It needs to be [something] that isn’t the headline. You look at it and you’re like, “What joke is this?” And you’re compelled to ask them more questions, and you [discover that] there’s some legit science behind this.

Yes, this sounds like a ridiculous N=1. But it’s wrapped around all this really cool emerging science that we have, including really high-tier rigorous science. Right before this Oreo vs statin study came out, we had a meta-analysis of 41 randomized controlled trials also supporting the lipid energy model, which we can talk about. But again, it’s just this data that we had, [and] it wasn’t being talked about enough. So I wanted to do something that would turn heads and get everybody talking about it. That was my goal. We’ll see if it gets accomplished. But that’s the punchline. Now I’ll pause and then we can start to back up and [I’ll tell the story] that led up to this moment.

Chris Kresser:  It’s great. I love that you’re doing this to start a conversation. And obviously, an N=1 study isn’t going to influence public health policy or change [the] paradigm in that respect, and it shouldn’t. But still, to your point, it generates an interesting hypothesis, or potentially takes a step toward validating the theory you’re going to tell us a little bit more about shortly, the lipid energy model. And then working backwards to some of the research that was done previously, [including the] lean mass hyper-responder study comparing calcium scores among people in different populations.

Maybe since we are sort of working backward from the Oreo study, what is the lipid energy model, and how does it differ from the conventional paradigm of understanding the pathogenesis of heart disease, particularly via the role of LDL?

The Lipid Energy Model: A New Perspective

Nick Norwitz: The lipid energy model is a mechanistic explanation for the phenotype that you described when you were painting your patient vignette. When someone goes low-carb, they typically are lean [and] metabolically healthy, and they see this massive increase in LDL, with increases in [high-density lipoprotein] and low triglycerides. So let’s first lay out the observations. You [have] this phenotype [of] lean-mass hyper-responders. They’re defined by this lipid triad [of] high LDL, high HDL, [and] low triglycerides, generally, on low-carb diets. It’s very rare to have this extreme profile not in a low-carb setting. Now, there are also associated observations. For example, it’s not just generally lean people who have this triad. If you look at the literature, there’s a dose-response effect, whereby the leaner you are, the [greater] your increase in LDL. And not only that, but that inverse association between BMI and LDL on low carb diets is dominant and what drives high LDL in people who go low-carb and see [an increase]. This was the topic of the meta-analysis that I mentioned.

A meta-analysis is when you study a bunch of studies, and we studied a bunch of human randomized controlled trials.  You hear about randomized controlled trials, [they’re] the gold standard. We took 41 of those, clustered them, and studied all of them. And what we found across them [was] that, if you look at the RCTs in people who go low carb, only those in lean people show the increases in LDL. Those who are overweight or class 1 obesity [show] no change, and those in Class 2 obesity actually go down. And across all studies, again, there’s an inverse association when you compare the saturated fat. Having low BMI [and] being lean and metabolically healthy actually dominates as a “risk factor” who are high LDL over saturated fat intake. So it’s very interesting. That’s the observation.

Chris Kresser:  A quick question about that, just for people who are not familiar with this study– does that association only relate to baseline factors when people are entering the study? Or if someone is [obese] and then they lose a significant amount of weight, does their LDL go up in a similar way [to] someone who started lean and adopted a low-carb diet?

Nick Norwitz:  Because of that particular study design, I would say baseline. Well, I would say it’s about the snapshot. It’s about the point in time, based on what I’ve seen in literature. If someone started a low carb diet at, let’s say, a BMI of 40, and then stayed rigorously adherent to that and their BMI started to drop, they might actually see a dip in LDL, [and] then it might stabilize. Let’s say they were really good and they got down to a BMI of 25 and [were] very muscular, then their LDL might actually shoot up. So this isn’t something just inherent to lean people who have a genetic predisposition to being lean. This is a manifestation of being lean and insulin-sensitive when you’re low-carb. And we have seen cases of people who started at like 300, 350 pounds and lost so much weight that their pattern inverted, where the LDL started to dip, plateaued, and then shot up when they got really lean. So these are the observations. You’re having a generally good trend, or improvements in health, and then you have this massive jump in this bad marker. What do you make of that? How do you resolve that clinical tension?

The lipid energy model is just the explanation for why this occurs. And the high-level overview is [that] the context people are insulin-sensitive and lean. When you go low-carb, you need to burn more fat as fuel. Your carb stores in your liver (hepatic glycogen [is] the medical term for it) gets depleted, and as it goes down, the system where you buy your circulating fat fuel ramps up. So free fatty acids that are circulating in your bloodstream [have] been released by your fat cells [and] get taken up by the liver. They get packaged back onto the storage form of fat, which [are] called triglycerides. So, you take free fatty acids, pop [them] onto a little glycerol backbone, [which] is a little m-shaped molecule, and then you put that into a trafficking particle, kind of like a little ship, called VLDL, [or] very low-density lipoprotein. And that’s shipped out of your liver, and then your muscle tissue, and your fat cells. You turn that over. The fat that’s being trafficked around inside [the] core of this VLDL gets sucked out to be burned by our muscle [and] stored back in your fat, [thus] replenishing your fat [stores]. And in that process, what happens is the core gets sucked out [of the VLDL particle] so the triglycerides are dropping really rapidly. The VLDL then shrinks [and] turns into an LDL. If you think about taking a sphere and shrinking it, the volume inside is decreasing– that’s the triglycerides going down. The VLDL is now turned into an LDL, and the rim, the surface, needs to go somewhere if you’re reducing the surface area. The surface components include cholesterol, which then gets transferred to HDL particles, so you have a rise in your HDL cholesterol. So you can see, if you ramp up this process, how you end up with high LDL. VLDL turned into LDL because the VLDLs are being [depleted] of their triglycerides so fast, and then high HDL, and you end up with this lean-mass hyper-responder triad.

So [that is] the lipid energy model, and it explains the lean-mass hyper-responder phenotype. And the cool thing about it, like any good model, is [that] it makes predictions you can test. One prediction is, if you put carbs back in your liver, then the driving force for the lipid energy model gets tuned down. And what should happen? Your LDL should go down. So one way to test that is to add back carbs. You can add back any carbs. Oreo cookies should do the trick, and that was the spirit behind the test. Now, you might ask, “Why not add healthy carbs, Nick?” Well, we’ve done that. We had a case series [at the] end of 2021. We did this with five patients. It worked incredibly. The average LDL drop was over 200. One patient had a 480 LDL drop. Then we had an interventional trial recently with 10 lean women. It worked the same. But here’s the thing– you probably didn’t hear about those, because ‘sweet potato lowers cholesterol’ isn’t as [provocative] as ‘Oreos lower cholesterol more than a statin’. So what I did here was shamelessly to get attention for this work, because like I said, I think this is very cool, but it isn’t being talked about a lot. We can talk more about the political environment around this topic. As I say, it’s very charged. But I wanted to give [the] media something to spit out that would, again, make people turn heads and talk about the literature that’s coming out. You’re right, an N=1 is not going to change policy. It absolutely shouldn’t. And I’m not making any health claims at all. I’m not saying Oreos are healthy, or this proves anything about statins or LDL. It doesn’t. The only thing it’s supposed to do is make people drop their jaws, look, and then consider this as something interesting.  It’s just supposed to pique curiosity. And then behind that curiosity, you can dig into, “Oh, there is a meta-analysis of RCTs. Oh, there are institutes like UCLA and Harvard groups that are digging into this. This is really cool. And I want to follow on this journey.” So that was the purpose.

Challenging Conventional Wisdom: LDL’s Role in Cardiovascular Disease

Chris Kresser:  Yeah, makes sense. Can you talk a little bit about the study comparing calcium scores? I think that will be fascinating for people. And then from there we can talk a little bit about how these various findings may cause us to question some of the dominant paradigm ideas of the pathogenesis of heart disease. Because, in theory, if we go by what we know or what the prevailing theory is, if you have a higher number of LDL particles in your blood, that’s going to increase the risk of vascular injury. Then that initiates the process of plaque formation, which then [eventually] leads to a heart attack or some other cardiovascular event. But it may not be as simple as that if this is true. If we have people with very high LDL levels who have calcium scores that are the same as people with normal LDL levels, then that at least introduces a question of why or how is that possible. So let’s start with that study and then go from there.

Nick Norwitz:  Okay. I think you’re referring to the study out of Lundqvist.

Chris Kresser:  Yes.

Nick Norwitz: That is Professor Matthew Budoff. So, this was a study that was spearheaded originally by my friend Dave Feldman, who has put blood, sweat, and tears into this one.  What they did, or are doing, is taking 100 people like me– lean-mass hyper-responders, or very similar to that phenotype, and they’re following them over one year to see [if] super high levels are [leading to] plaque progression. And I’ll add that we’re not just looking at coronary artery calcium scans (CACs), we’re looking with coronary CT angiography (CCTAs). The distinction there is important because CCTAs look at non-calcified plaque as well. The principal investigator (PI) on this study is an expert in this field and is the one [who] helped design the study, determined the one-year timeframe, which, with these levels, he and his team felt [was] sufficient to see if there would be rapid plaque progression. So that’s the question– [in] people with levels this high, do you see rapid plaque progression?

Now, I’ll say the one-year follow-up studies are going to be completed in February, I believe. And then the data needs to be written up and published. But there’s a, let’s call it a cousin study, that was done when all the baseline scans were collected, and the results from that have been announced. The paper communicating them is [currently] under review. I couldn’t speak about the results because they were announced at a conference by the PI.

What they did is take 80 subjects. They couldn’t do all 100, because for the match, which I’m going to talk about, there were some outside the age range of the matching population. But they took 80 of them and then matched them for all the variables they could, except for LDL, to this population, Miami Heart– the generally healthy adults. And [they] said, okay, we’re taking these populations that are equal in age, so 55 years on average, just over half male, and similar with respect to other risk factors, at least as [closely] as we could match them. There are unique things about lean-mass hyper-responder profiles that make it almost impossible to match into the population. That’s a rabbit hole that we can go down if we want to. But [the] bottom line [is], you have these two populations that are as well-matched as they could have been. [And] you ask the question: Given that the one group has very high cholesterol– LDL levels on average were 272 in the keto group as compared to 123 in the Miami Heart group, so that’s almost 150 milligrams per deciliter difference over the average time on keto for the keto group, [which] was 4.7 years– so, close to five years and with an elevation relative to a comparison group of about 150, [the] question is, at baseline, is there increased plaque in the keto group?

A lot of people probably would have thought there would [be an increase], because that LDL is just so high. There wasn’t. There was no significant difference in total plaque score between the groups. If you want to look at trends, because some could say, “Oh, the study [was] just underpowered. Maybe there was a trend in one direction.” And, yeah, there actually was. The lean-mass hyper-responders keto group was actually trending to lower plaque, if there was any trend at all. Again, [there was] not a significant difference. Also, there was no association between the LDL levels and plaque. Across the keto group, some had LDLs of around 200, [with] the highest [being] 591. Was there any correlation between LDL and plaque in these keto subjects? There wasn’t. Now, these are preliminary data that you need to take with a grain of salt. But what I would say is kind of what you said. We have a body of literature, but not in this population. This is kind of the first glimpse we have about what risk might be in this specific population. It doesn’t necessarily change any paradigms immediately; it needs to be validated. Nor should it change any guidelines at this point. But it is interesting data that should make us rethink what we think we know about the currently existing paradigms.

What I would say is there’s a major hole, or let’s not make it a hole, let’s say there’s a major opportunity here, in that the current model assumes that if you have very, very high LDL for a long enough period of time, it will push cardiovascular disease. You will get it. That’s the common, let’s say, internalization of the model. Is that true? Well, think about what data we have. We have animal model data. We definitely have human data. We have Mendelian randomization data showing that ApoB is causal. Causal is a word we can unpack a little bit, because it doesn’t mean sufficient. It doesn’t mean it would actually push bulk flow. Then we have conditions like familial hypercholesterolemia, where there’s a genetic dysfunction in lipid metabolism. But none of these represent a case where there’s apparently a metabolic response in people with a functional lipid metabolism. FH, familial hypercholesterolemia, is a congenital disorder, but the lipid metabolism is broken. The LDL is high, but for a very, very different reason, with potentially different consequences.

So what we have here with lean-mass hyper-responders is a very unique test of the question– can high LDL, as a completely isolated variable, push cardiovascular disease? And the answer to that question is, we don’t know. It’s even heretical to say we don’t know, but the honest answer is that we don’t know. So that’s something we need to explore. Peter Attia says, [as do] a lot of people– ApoB is necessary, but not sufficient. As in, we don’t have data to [show that] it alone can drive cardiovascular disease. So what do you do with that patient you described? What do you do with that patient with incredibly high LDL but no other risk factors? And maybe their high LDL has been that way for, let’s say, five, 10 years. I mean, it has to be a long period of time. Let’s say they came to you with that, and their CCTA is perfectly clean, showing no plaque. What is their risk? We don’t know.

Chris Kresser:  We don’t know.

Nick Norwitz:  And we need to find out more.

Chris Kresser:  And this is where clinicians will diverge based on their perspective. I know Peter, and his tendency in that situation would be to prescribe a statin. His way of thinking [about] it is, all other things equal, if you have two people and they both are free of all other risk factors for cardiovascular disease but one has high ApoB, then the other person who has normal ApoB will be at lower risk, [and] we should therefore do everything we can to reduce ApoB in that person.

Nick Norwitz:  But there’s a flaw in that logic, and [it’s] the “all things being equal.” When are all things equal?

Chris Kresser:  Exactly.

Nick Norwitz:  You can’t snap your fingers and change a biomarker. It requires an intervention. For some patients it’s harder than others, if they’re using a ketogenic diet therapeutically. But no matter what, there’s an intervention that’s changing other variables in the situation of a whole person. So you’re right in what you just said, and if Peter phrases it like that, then he’s probably technically right. But all things aren’t equal, so I reject that premise.

Check out the latest #RHR episode with Chris Kresser & Dr. Nicholas Norwitz as they explore the lipid energy model & the truth behind high LDL on low-carb diets. A must-listen for anyone interested in #HeartHealth & #KetoDiet. Don’t miss out! 🎧 #LowCarbLifestyle #Cholesterol

The Problematic Research Ecosystem for Nutrition and Metabolism

Chris Kresser:  That’s the problem. And also patients have different preferences. Some patients just don’t want to do statin therapy or cholesterol-lowering therapy, and when I explain it in the terms that you just did and I say, “This is what we know and this is what we don’t know. It’s [ultimately] up to you what you want to do here,” a lot of times patients are willing to take whatever perceived risk there is to having high LDL, in part because they feel great. They’ve made this change, often everything else is improved, all of their other biomarkers have improved, and they are not willing to risk possible side effects and other complications with statin therapy for an unknown benefit that is not possible to quantify at this point. So, yeah, it seems to me that this is the million-dollar question. And until what you’ve been working on with Dave and others, we have not really had an active effort to answer this question. The cynic might say [that’s because] there’s not much motivation for this question to be answered by the pharmaceutical industry, which funds a lot of this research. And that’s what is amazing about some of these studies– we should point out that a lot of them have been citizen-funded, which is how they got done in the first place, right?

Nick Norwitz:  It’s really a problematic research ecosystem. It’s really hard to do rigorous studies in nutrition and metabolism with those interventions. The funding is scarce because it’s not really that lucrative. That’s just the incentive structure that we have set up. It’s not pointing fingers at any individual, but it’s the truth. That’s the thing for me, as someone in this space. I look at this stuff, these phenomena, and I’m like, “This is so cool.”  Why is everybody in medicine not like, ”Whoa, we need to explore this,” and getting excited?” I think [it’s] just because people aren’t really aware that this is legit, and I think with a little bit more awareness, we will [see] that will to study it, because it is so interesting. But we need to [raise awareness].

Chris Kresser:  I think that’s part of it, Nick. Another part is, if you think about physics as a scientific discipline, people who are physicists get legitimately excited when there’s a finding that contradicts the dominant paradigm of understanding. [That’s] not always, but very often, the case. I think with medicine it’s trickier, because there’s no public health policy around physics research. There’s nobody out there making recommendations that affect choices that people make on a day-to-day basis about what food they eat, what medications they take, and all that stuff. The stakes are really high, and [then] ego gets involved like it does in all scientific disciplines. [And] there’s a lot of money. There are big forces at play. So it seems more difficult for physicians [and] researchers to have that kind of open-minded, curious attitude in our current scientific paradigm in medicine. I’m not saying it’s good, I’m just saying that that seems to be much less common, that type of curiosity and interest that you have.

Nick Norwitz:  I think that’s probably true on the whole. I guess what I’d layer on to that is [that] there’s just so much in medicine– it’s so broad and there’s so much asked of every practitioner, that at least what I’ve seen in my training [is that] you choose your battle. You choose what you’re really passionate about, and everything else you don’t have time to go into the primary literature for. It’s literally impossible. So you do have to kind of take the word of the authorities to some level. It’s not ideal, and I think we should always be questioning. But I think that there’s a laissez-faire nature and a trustingness which allows certain dogmas to perpetuate. It’s not ideal. Well, it’s not even good. It can retard the process of science. But in the end, I do have confidence that, over the long arc, the data do win out. Which is why I’m so chipper on the whole about this, because the data will show what it will show. It’s a little irritating when certain people characterize the data and misrepresent it, and then you have to go back and clarify again and again in pushing what seemed ridiculous ways, like Oreo vs Statin. But you know what? It’s the process. It’s the one we have, and so you might as well enjoy playing the game to some extent, if I may use that euphemism. Which is what I’m trying to do. If I didn’t take that mindset, I’d be burnt out already at age 28.

Chris Kresser:  Right. When you have people who have built an entire career around a particular belief system or paradigm, if we really try to empathize with them, it can be very challenging and threatening for them to take in information that is antithetical or potentially antithetical to that approach that they’ve spent their entire lifetime supporting and building their career around. And we would still hope that, ethically and with scientific integrity, someone in that position would be open to data that challenges that viewpoint simply because that’s the right thing to do. It’s how science progresses. Being willing to continually prove your own hypotheses false is the basic approach in science. I’m not, to be honest, very active on social media at this point, in part because the vitriol gets so old and tiring, even as an observer, and I’m not involved in it that much anymore. But let’s talk a little bit about the range of responses that you’ve received in the professional medical community, and also amongst citizen scientists and people who are following along just for their own edification and knowledge.

Nick Norwitz:  99.9 percent has been what I hoped they would be, which is, “Wow! This is interesting. Wow! This is cool.” Well, actually, let’s call that 95 percent, and then 4.9 percent make jokes about going to get Oreo cookies or cheesecake, which are clearly jokes. I don’t think many people are actually being persuaded that Oreo cookies are healthy. And we’re pretty clear about caveating that. Of course, there’s the remaining 0.1 percent who don’t understand the purpose or want to make snide remarks. And they can do that, and I understand why they would. It’s going to [inspire] a provocative headline or two. But on the whole, people have been engaging, I think, really authentically and with the interest that I think this was intended to provoke. “Whoa, this is so cool.” And a lot of, “Oh, this is me,” as in, “I am a lean-mass hyper-responder, or I know one, or I treated one.”  I’ve actually gotten lots of emails from resident physicians who are like, “I have lean-mass hyper-responder patients, I’ve been following the story, and this is so cool. I’m so excited.” I got a couple [of] emails from residents who are asking about how they can get involved, [if] they could write up case reports on their patients.

So a lot of it has just been communicating back to us the scientific awe and curiosity that we feel, which is very heartening. Overall, the response has been incredibly robust in terms of the metrics. For example, we talked about incentives a little bit, and research. One incentive is [that] journals want attention. There are attention metrics that papers have. Something called an altmetric score. And our paper jumped to the top 0.5 percent within a day. For reference, [The] New England Journal [of Medicine] is the highest impact factor journal in the world. The average lifetime score for a paper in The New England Journal [of Medicine] is 128. Our score in one day was 1113. So the response was robust. I’ve gotten lots of emails from reporters. The abstract hit like 200,000 views in a day or two. I woke up [on] day two with 2000 emails in my inbox. It’s been pretty overwhelming, but it’s been exciting. It’s the response that I wanted. It’s why I did this experiment, [to have] people coming out and saying, “I want to learn more.” That was the point. I’m not trying to prove anything. I wanted to put forth this uncomfortable tension, that you have this clearly unhealthy intervention, and then what is perceived to be a good response. And the question that’s implicit there is, how do you resolve these things? I’m not presenting an answer. I’m not making a value judgment. But I’m putting forth an uncomfortable question, and [the] job of science, really, is to deal with questions. Particularly the uncomfortable ones. So it’s really exciting that people are coming out and generally expressing curiosity and wanting to learn more about this topic.

Other Potential Risk Factors Contributing to Cardiovascular Disease

Chris Kresser:  Yeah, great. So, I mentioned this a couple of times, and I know [that] the ultimate answer here is we don’t know, but what do you and others who have participated in these studies and are familiar with the lean-mass hyper-responder and lipid energy model hypothesis speculate is going on with people who are lean-mass hyper-responders and have very high LDL and [show], according to these scans, no difference in coronary plaque relative to people with normal LDL? I’m, of course, familiar with the statistics– Nine in 10 people who have high cholesterol, which usually involves high LDL, and who have heart attacks, have at least one other significant risk factor. That kind of goes back to what Peter Attia is saying, [that] ApoB is required but not sufficient on its own to lead to some kind of cardiovascular event. Have any of the studies that you’ve done looked at these other potential factors? And what would you or others in your field speculate might be differentiating factors that drive risk in addition to LDL-C or ApoB?

Nick Norwitz:  Yeah well, there’s a bunch of different studies looking at, often in quantitative manners, the relative risk of different profiles. Things like diabetes, smoking, being sedentary, etc. The specific numbers aren’t really important for this discussion. It’s more about the overall risk profile of any given patient. What does it mean when you only have LDL as the isolated risk factor with everything else being perfect, and where that LDL appears to be not, let’s say, a congenital anomaly, which is a term I’m using for a genetic break like an FH, but it’s part of a parent metabolic response to something? If the answer is the lipid energy model in these cases, if that’s the description or the explanation, then you have to ask [if] the body is doing this for a reason. Does it then follow that this is a short-term adaptive response? Let me put it that way–it doesn’t, per se, follow that it’s long-term healthy. But I would say it might increase the probability that the body is smart enough to figure out, okay, I’m ramping up the system, but I don’t want the system to hurt me at the same time. You know what I mean?

So you probably can read between the lines and guess what my predictions might be. If we were talking about lab rats, I might be more explicit. [But] because we’re talking about human beings and there’s an absence of evidence and I don’t think people should gamble with their heart health, I’m just going to leave it at, “We don’t know and we need more answers.” Because that’s the most honest [response]. Without evidence, it makes sense to take as conservative a position as you can, because this isn’t something you want to be cavalier about and gamble with. That’s why a lot of experts will recommend getting scans, especially if you have had high levels for a long period of time and are a little bit older, because then you can get a sense of what your baseline [is]. What’s your buffer room? It’s very different. I’ve gotten scans. I’m not really surprised that my CCTAs are perfectly clean, because I’m younger. It’s a very different profile if somebody is, say, 55, [and] their LDL is 500 and they have existing plaque. Because then, look, they don’t have buffer room to play with. “Play” being a euphemism here– obviously, it’s not a game. Whereas if somebody has no plaque, you have a little bit more buffer room, so to speak. And so you take it on an individual basis.

Chris Kresser:  Yeah, that makes sense, and I think still many of the other traditional risk factors like blood pressure and family history come into play here. And the fewer of those you have overall, the more buffer there might be. The more of those you have, the less buffer there might be. Unless there’s something very wrong with our understanding of cardiovascular disease. So what’s next? We know what the questions are that are still outstanding. What are you guys working on for future directions?

Future Direction and Concluding Thoughts

Nick Norwitz:  Well, I have a whole list of projects we want to do. A couple that are at the top of my list are, first, finishing the risk study with the CCTAs, and also replicating that in a form with the triad study. I want to know how replicable this phenotype [is]. If we can take people [who] we think would turn into lean-mass hyper-responders, who have never been lean, and control them, how [many] could we prospectively convert into lean-mass hyper-responders? I think it’s a pretty high percentage. I think this is predominantly a metabolic response, maybe with some permissive genetics. But I think under the right circumstances, I’m not going to say almost everybody, but most could turn into lean-mass hyper-responders. But that’s something that’s important to actually prove.

And then another study I’d like to do is, [and] I did this [with] Oreo vs Statin– I demonstrated to myself that carbs are pretty potent. But I’d like to, on a larger scale, do a three-way crossover where we take a population of lean-mass hyper-responders and treat them with carb reintroduction, versus statins, versus ezetimibe. I actually hypothesized [that] ezetimibe might punch above its weight relative to statins, particularly in this population. But that, again, gives us some mechanistic insight, and it will give clinicians valuable insight, too, to provide personalized treatments to their patients. So it’s one of those things that should be very appealing to everybody, and therefore, something that everybody can get behind and hopefully support, including pushing for funding. So I have dozens of projects I’d like to do. Those are some of the top on my list.

Chris Kresser:  For the record, in my anecdotal and published clinical experience over the last 15 years, that’s exactly what I would do if we reached this point where the conversation was, “Okay, you have high ApoB or LDL-P or LDL-C,” whatever it is that we were measuring, and that patient was not comfortable having that high of LDL but they didn’t want to do statin therapy. I would suggest carbohydrate reintroduction, obviously dependent on their other goals. If they were coming from a background of being overweight and they know that eating carbohydrates will rapidly add more weight back on, then we would be careful about that. But in other cases, if they were lean and pursuing low-carb for other reasons, we would be a little bit more liberal with the carbohydrate reintroduction. Not Oreos, generally, this was more of the healthy variety– sweet potatoes, plantains, stuff like that. And almost universally, I saw the same thing that you did. It was very comforting to them to know that they could easily get their LDL to drop like a rock just by eating some carbs for a week.

Nick Norwitz: I want to jump on that because it does provide some of the highlights that direct [the] utility of what I’ve done, even if it sounds ridiculous. Because what we know from clinicians like you treating patients [as] you did, and I’ve seen this again and again, is [that] this can be incredibly effective for patients who don’t have or need therapeutic ketosis. But if clinicians broadly aren’t aware of [this], then it doesn’t present as a clinical option. If the default is, “Oh, you must have a genetic dysfunction or something going on, so we need to treat with pharmacotherapy now for life,” without first exploring the option of a sweet potato, a banana, [or] a mango. I mean, I’m not [yet] a licensed clinician– I’m in my third year of medical school– so I’m not providing medical advice, but in chat groups, we’ve had people respond with, “Oh, these are my numbers.” [I’ll ask], “What’s your favorite carb?” And they’re like, “I like mango.” I’m like, “Eat some mango [and] see what happens.” I try to be very careful with my language here. “If I were you, I might just play around with some mango. I’d eat a large mango per day and just see what happens.” And then they come back and go, “Oh wow! My LDL dropped from like 390 to 100.”

Chris Kresser:  Well, what’s fascinating about it is it doesn’t have to be, in my experience, a lot of carbohydrates. Someone could go from five percent of calories, very low-carb, to 10 percent. Okay, yes, that’s doubling on a relative basis, but you’re still at a very low level of carbohydrate intake, and it can have a huge impact on lipid profile.

Nick Norwitz:  People need to be aware of this. Clinicians need to be aware of this if they’re going to use it as an option. So as ridiculous as it might sound, if Oreo vs Statin captures headlines and people just look one level beyond that, it becomes very obvious. “Oh, if I have a patient like this, maybe I should try to treat [them] with a sweet potato before I start high-dose Crestor and see what happens.” Because it might be twice as effective, and then all they’re doing is eating a sweet potato and they don’t take this medication for life. And everybody’s happier, maybe.

Chris Kresser:  Yeah, absolutely. Well Nick, I really appreciated this conversation. Where’s the best place for people to follow what you guys are up to?

Nick Norwitz:  You can follow me @NickNorwitz on Twitter, and @lipoprotein is Professor William Cromwell. He is the senior author on this project. @RealDaveFeldman was the guy who coined ‘lipid energy model’ and a close, close friend of mine. And then, if you really think this is exciting and it’s important research, there is a concrete way that you can really help us. As I mentioned, attention metrics and the grassroots movement through the citizen science community really helps push the research forward. So if I may be so bold [as] to ask a favor, take the link below associated with this conversation, it links straight to the paper, and share it on social media, in particular Twitter or X, with the link to the tweet. Provide commentary or you can retweet my tweet– right now, it’s my pinned tweet “Oreo vs Statin”– and leave a comment. Those things get picked up and they’re important. And also, if you wouldn’t mind watching, there’s a just under eight-minute video abstract, which my friend put blood, sweat, and tears into animating. It’s doing great. I think [it’s] incredibly enticing. You’ll have fun watching it and it will explain what happened in the study and why it’s so important. You can find that on my YouTube. Again, if you just Google Nick Norwitz, I don’t think there’s another Nick Norwitz among the nearly 8 billion people in the world. I’m not hard to find. So watch the video [and] share it around. Again, this is just about getting chatter going [and] expressing your curiosity. We want to hear about it. You can also leave a comment on the YouTube video. [I’m] starting next week on a subinternship [so] I’ll be particularly busy, but I do try to read all the comments and reply to as many as I possibly can. I think I’ve replied to [around] 800 today. So I will try my best. But I do like to hear from people, so I’d appreciate it.

Chris Kresser:  Great, yeah. We’ll put all that in the show notes on the website so people can easily access it. Nick, [I] really appreciate your time and all the work that you’re doing, and continuing to ask good questions and hopefully move the conversation forward and give us more clarity on these important questions. Because heart attack is still a leading cause of death and it’s of enormous importance that we get more clarity here. So [I] really appreciate the work you’re doing.

Nick Norwitz:  Thank you so much. I appreciate it.

Chris Kresser:  Okay, everyone. Thanks for listening. Send your questions to ChrisKresser.com/PodcastQuestion. We’ll see you next time.

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