Ep. 347 Expanding Perspectives on LDL, Lipids, and LMHRs with Dave Feldman
- March 27, 2024
- No Responses
I am honored to reconnect with Dave Feldman today. Our last encounter was in December 2020, for Episode 128, where we delved deeply into the topic of cholesterol.
Dave is an engineer by profession. He is profoundly clever and commands great respect within the low-carb and keto community due to his willingness to challenge prevailing narratives, encouraging us to explore alternative perspectives on lipid metabolism and reconsider our understanding of LDL, particularly in the context of lean mass hyper-responders like myself.
In our discussion today, we dive into how LDL became so vilified, with Dave shedding light on several crucial research findings. We explain what low-mass hyper-responders are, examine biases and cognitive dissonance, touch on Dave’s new LMHR study, and discuss the Miami Heart study, a longitudinal study of the roles of LDL and plaque burden. We also explore the impact of ApoB and reflect on the essence of science as a pursuit of truth, and Dave shares what lies ahead for himself and his research.
I trust you will find this conversation engaging and thought-provoking.
“I wanted to think as much as I could about how I could challenge my core beliefs. I also had a superpower, not many other people have. I am an engineer, not a formally trained scientist.”
– Dave Feldman
IN THIS EPISODE YOU WILL LEARN
- Why LDL is considered a villain
- How AMRs and APB lipoproteins have influenced how we look at risk stratification
- What is a lean mass hyper-responder?
- How a low-carb, high-fat diet can improve the metabolic health of lean mass hyper-responders
- How Dave, an engineer turned scientist, challenges conventional wisdom in the health and wellness space
- Dave discusses a study on plaque progression in healthy individuals, focusing on correlating LDL levels
- How we are at the forefront of finding the significance of lean mass hyper-responders and LDL
- Dave shares the next thing he and his team will look at to substantiate his findings on lean mass hyper-responder
Connect with Cynthia Thurlow
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- Check out Cynthia’s website
- Submit your questions to support@cynthiathurlow.com
Connect with Dave Feldman
Previous Episode Mentioned
Transcript
Cynthia Thurlow: [00:00:03] Welcome to Everyday Wellness podcast. I’m your host, nurse practitioner, Cynthia Thurlow. This podcast is designed to educate, empower, and inspire you to achieve your health and wellness goals. My goal and intent is to provide you with the best content and conversations from leaders in the health and wellness industry each week and impact over a million lives.
[00:00:29] Today, I had the honor of reconnecting with Dave Feldman. We last connected for the podcast in December of 2020 for Episode 128, which was a deep dive into cholesterol. Today, he returns and we focused in on how LDL has gotten so vilified with Dave identifying several key pieces of research, what is a low mass hyper-responder? The role of bias and cognitive dissonance. His new LMHR study in Miami Heart, which is a longitudinal study looking at the role of LDL and plaque burden, the impact of ApoB, the role of science as being truth seeking, lastly, what’s next? What’s on the horizon for Dave and his work?
[00:01:20] One thing I want to point out to listeners is that although Dave Feldman is an engineer, he’s incredibly smart. He is very well respected in the low carb and keto space, largely because he is challenging the narrative. He is encouraging us to think beyond maybe some of the principles in which we have been trained and to consider alternative perspectives to the way that we look at lipids and in particular looking at LDL and these lean mass hyper-responder individuals, of which I am one of them. I know you will enjoy this conversation.
[00:01:59] Welcome Dave back to the podcast. Always a pleasure.
Dave Feldman: [00:02:00] Thank you for having me.
Cynthia Thurlow: [00:02:03] Yeah, so we will definitely have links back to our original discussion. It’s hard to believe that was three years ago. How is that possible?
[laughter]
I think the pandemic has just had me. It’s like I’ve been in a time warp, and now the recognition that it was really a long time of our lives where we felt very disconnected and not able to get together in person. But I would love to start the conversation today on what are your thoughts on how LDL has unfortunately gotten vilified over the course of the past 50 years, and how has that influenced the way that not only clinicians have practiced, but the way that the research has gone and vis-à-vis we will eventually dovetail into talking about the amazing research that you are doing right now. But why is LDL thought of as the villain?
Dave Feldman: [00:02:53] Well, that’s a fairly easy question to answer because I bring forth this evidence in an effort toward getting that context in front of everyone, and I did it upon announcing the study that we’ll be discussing now.
[00:03:07] I think a seminal moment was the work of Brown and Goldstein from the 70s. They are two clinician scientists. They were seeing a patient a that in their own words, would define the course of their life past that point. It was two siblings. But in particular, there was this little girl. It’s a heartbreaking story, but she had a disease. It’s going to be a mouthful, homozygous familial hypercholesterolemia, and this disease it results in two things that are quite striking, one is that children born with this will have extremely high levels of LDL cholesterol, and I’m talking 500, 600, 700. They will likewise develop early cardiovascular disease, adverse cardiovascular disease, and unfortunately, will exhibit symptoms of it such as angina at like say age 3 and heart attacks as early as 5 or 6.
[00:04:02] And so, as you can imagine, coming up until the 70s, there already was a lot of discussion on saturated fat, on how that can impact cholesterol levels and how cholesterol levels might be related to cardiovascular disease, going to experiments decades before that with the rabbits and other animal models and so forth. And this sort of felt like the linchpin for everybody is, as they were examining this and as they published on it and would ultimately go on to win the Nobel Prize with their work, not just with LDL, but the LDL receptor.
[00:04:29] It became more and more clear in the perspective of many people that, “Okay, this is really it. This is the causal agent,” These components that carry this cholesterol, called low-density lipoproteins, LDL that are found in the blood. We can see this association is tight association between them being extremely high levels here and this corresponding cardiovascular disease, because these children, they were just born, so they don’t have type 2 diabetes, they’re not smokers, they’re not type A personalities right away, they’re just kids. And so, at that point, that really kind of set the stage as it were for thinking of LDL as truly causal towards the outcome cardiovascular disease.
Cynthia Thurlow: [00:05:14] And it’s interesting, as a clinician, obviously, my background is in Cardiology, Critical Care Medicine, and so having prescribed hundreds of thousands of statins over a long trajectory of my life, sometimes retrospectively, thinking very appropriately, given the patient population we are working with, but that was at a time, for the most part, when we were looking at a standard lipid panel. So, for listeners, total cholesterol, LDL, HDL, and triglycerides, and from that making decisions about medical therapy. And there’s a lot more to LDL, this low-density lipoprotein than what’s from a basic lipid panel. So, let’s talk about how now lipid management has kind of evolved. There’s more testing that can be done to kind of look and examine at these. And so, looking at particle sizes and looking at ApoB. And for anyone that’s listening, I highly encourage you to go follow Dave on YouTube because he does a beautiful job of explaining very complicated concepts and makes wonderful analogies. And the ApoB one in particular about pizzas and pizza boxes is fantastic. How has the information that we now have with NMRs and ApoB, lipoprotein(a), how have these things influenced looking at risk stratification?
Dave Feldman: [00:06:38] Well, first of all, when I was coming into this space, no doubt many of your listeners and this included me, I would hear about this small dense versus big fluffy discussion. And I had actually first thought about it from Bullock and Finney. They were pointing how there isn’t indeed literature that shows small dense tends to have a high association. If you have a high amount of small dense LDL particles in your blood stream, they tend to be smaller, they’re denser because their composition is more protein than lipid, versus these “big fluffy,” they’re more buoyant LDL, still an LDL classification, but they’re larger, they’re more fat enriched, less protein as a composition. And I’m going to level with you. Just about as fast as I was starting to conceive of this lipid energy model, I kind of considered all of these things, including the small dense, big fluffy, as all downstream outcomes of this metabolic health context.
[00:07:42] So, you’re going to the scene of an accident, and different people are going to focus on different things based on what they believe causes car accidents. So, some people are going to be like, “Nah, I think it’s mainly a slippery road.” “No, actually, I think it’s construction nearby. There seems to be more accidents where there’s construction nearby.” Then you have some folks who say, “Actually, we’re sure, it’s tires. Car tires are highly associated with car accidents.” And then somebody else comes in, they go, “Actually, it seems like car tires that are a little flatter seem to be more associated with car accidents.” And the original tire person is going to say, “No, actually, all car tires, if we interventionally take away car tires, you get less car accidents because less cars are driving around.” But in reality, they’re all kind of right with regard to that’s what’s associated with the scene. The problem is that we can’t easily see the real causal agent. So, it’s important to recognize that something can in fact be part of the causal pathway. They can be involved in the process. And LDL particles or rather ApoB-containing lipoproteins, and it’s the more technical term, these complexes, they are part of the process of atherosclerosis. The question is, are they injecting themselves into the arterial wall and creating the accident that’s there, or are they being pulled in through other processes which we might get a chance to talk about, such as inflammation? There’s now more of an understanding that inflammation induces a greater transportation of LDL particles to the scene, to the site of the inflammation. So, now you can look at things like analogies, such as emergency workers. Are they a part of that as well?
[00:09:26] Now, I caveat all of this with the emphasis that I’m not going to make the claim of any of these being something I’m confident is truly the cause, because it very well could be that the lipid hypothesis, as Brown and Goldstein were looking at, and as you know, your fellow doctors would say today, is true, but that’s why we always needed to get clear streets with good weather, without construction nearby. We needed to find a population like the ones we’re looking at now, that I would argue, that I believe have a functional lipid metabolism, who do not have these other confounders that are making it more difficult to look at the scene of the crime, does that kind of make sense?
Cynthia Thurlow: [00:10:09] Yes. And for listeners, I want to identify that one of the reasons why I think this is such an important topic of conversation is that I myself am one of these individuals who has high LDL, high HDL, low triglycerides. And Dave and his team have coined this phrase, lean mass hyper-responders. And so, I would love to be able to share with the community what this represents, because I can tell you for 10 plus years, my own physicians would say to me, “Cynthia, you’ve got high LDL. Your total cholesterol is high arbitrarily. Your HDL is high, so we’ll just leave it there, we’re not as stressed about it.” But now that I’m 52, it has opened up kind of a pandora’s box of conversations, and so this is why this research is so important to help people understand that, “Yes, there are individuals who have a phenotype,” and we’ll talk about what that is, that actually have this kind of familial propensity for whether it’s through diet or some of it’s a little bit genetics, I think mine is probably both, that have this lean mass hyper-responder phenotype. So, let’s talk a little bit about that, because I think it really is interesting, and I think it’s one of those things that when we first met, I kept saying, “I’m one of your people, definitely one of your people.”
Dave Feldman: [00:11:33] Yeah. So, let’s talk about it. Let’s go all the way back to 2015. I go on a low-carb diet. My dad and my sister get inspired to jump on the diet around the same time I do. They get their blood work first, and I warn them in advance that I’ve heard on the forums because I’m fairly new to it. It’s possible their cholesterol might go up a little bit just to be weary. Their cholesterol hardly moves. But then I get my blood work. Mine is through the roof, it’s doubled, it’s more than doubled. I had historically had an LDL cholesterol between 110 to 130, which is right at the average for a male of my age at that time. And now, all of a sudden, it was 240. My LDL cholesterol was 240. And naturally, I just completely panicked. This is even before keto was as well known. It was typically known as low carb, high fat, or LCHF.
[00:12:24] And had it not been for both my dad and my sister as two other reference points, this might have not been as interesting as it did almost instantly to me, because why is that the case? And both of them would concede this, so I’m not speaking out of turn. They’re not as metabolically healthy as I was, especially at that time, because I was also doing running. And along with the running, I was leaner. I was as lean as when I was heading into college, so I just felt like a fountain of youth. I was so ecstatic about low carb, high fat.
[00:12:52] And then, like so many people that I talk to day in and day out now, all these things improve to the point where you’re just excited to get your blood work. And then there’s just this one thing, the total and LDL cholesterol had shot through the roof. Well, okay, the only thing I could find on people on a low-carb diet who saw the cholesterol go high were two articles, one from Peter Attia and the other Thomas Dayspring, and in both cases, they referred to people who experienced this as a hyper responder.
[00:13:21] So, flash forward two years later, at this point in time, I’ve done a lot of experimenting, and I’m probably leaving out a lot of the story as to what I think is happening mechanistically, but we probably talked about it in the first one. But at that point in time, I’d seen enough to where I said, “Okay, we cannot look at LDL in isolation anymore, because there really is this phenotype, not just of a triad of not just high LDL, high HDL, and low triglycerides, but for people who are especially metabolically healthy, but also very lean observationally, it seems like we should call this something different, not just hyper responder, but lean mass hyper responder.” I didn’t even want to say just lean, but like lean mass. And I just kind of put it out as a blog post. It was almost like, “Hey, I feel like because of how much my blog cholesterol code is getting so much of this feedback, this is the pattern I continually recognize. And it makes sense with this energy model that I’d been working on up until this point.”
[00:14:18] And that exploded. That article where I designate lean mass hyper responder for the first time, we have over 1000 comments. I want to say something like that, which my blog was only known by the biggest geeks in low carbon. I said, “Wow, this is really something.” And I thought back then, “Okay, now I just need to get lipidologists interested, that’s all I need to do. I just need to knock on the doors of the right people.” I thought maybe Dayspring himself or Peter Attia himself would be very interested to where I could start just getting research going. And I thought it’d be more of like a handoff, like, “Hey guys, I did the early pilot work. Here’s this lean mass hyper-responder phenotype.” Guess what? Now we actually do have a population of people who seemingly don’t have some dysfunction or illness or something related to why their LDL would be high. It may in fact be physiological. And if it is, I mean, all these reasons why you should go ahead and be interested to study, but you probably know where this story goes from here and that’s not what happened.
[laughter]
Cynthia Thurlow: [00:15:16] I do, and I think listeners might be interested in kind of hearing how that trajectory has moved. One thing I want to make sure that I kind of iterate, and I will also echo this in the intro, is that you are so well respected and so well revered within our community because it has really forced us to think differently than the kind of rigid, dogmatic principles that many of us were schooled in. And so, I thank you for the work that you’re doing, because I know that it’s not easy when you are fighting against conventional wisdom.
Dave Feldman: [00:15:47] Well, thank you for the kind words. I’ll concede that when I came into this space, I had a bit of a Hollywoodized version, I guess you could say of a scientist in my mind. You watch a movie, and they’re usually the coolest head. They’re usually the most open minded. There’s the prototypical scene where there’s the professor and they’re jotting down the conventional schematic on the chalkboard, and then there’s this typically our protagonist, who says, “Have you thought about this?” And then the ultra-scientific minded professor goes, “That’s a great idea, we had never considered that.” And then they start working out the differences, and that becomes like when the music sets in. I guess I grew up with a lot of 80s movies.
[00:16:39] But, yeah, it’s not that way, as much as I would hope that it would be. And this is not to suggest that there’s any overt wrongdoing. Rather, they’re humans too. Scientists, doctors, all of us, all of us, we have a worldview, we have things that we’re looking for to confirm our worldview. We’re naturally, unconsciously biased against those things that break down our worldview. And so, I wanted to think as much as I could about what I could do to challenge my core beliefs. But I also had one other superpower, not a lot of other people do, which is, I’m not a formerly trained scientist. I am an engineer. I am a platform architect. And I want to say this without it coming off as anything more than what it is, but I always had a very easy exit door on standby at any moment in time, because if I could just get to a point where I could feel confident, I was wrong, no problem I can step right back out of here, because I do a lot better, frankly, in my career, when I’m not doing this. It’s not a career move, I’m never going to reach the kind of status, income, etc., that I can get as a platform architect, making next generation gambling platforms like I have been doing in Vegas.
[00:17:48] So, yeah. Is there a lot of other ways in which this is fulfilling? 100%. And I’m so thankful that our community is so receptive to this. You mentioned people respecting me. I respect the people. I cannot even believe how much things have come together to advance this study that we’re about to talk about. But that’s literally what I did to finish off the timeline of what I was mentioning earlier, after knocking on doors, after writing emails, and realizing I wasn’t going to get anywhere with the conventional scientific community. I just said, “What the heck? What’s the worst that could happen?” I’m just going to go to the low-carb community itself and say, “I just ask you to bring me the money.” So, then we could just write a check to a bona fide research institute like the Lundquist Institute, headed by Dr. Matt Budoff, and just have them do it for us. Have a bona fide research center actually conduct a clinical study where we could gather this data ourselves, find out for ourselves. And I’m just so thankful that that worked. But there’s no way I could have done it without hundreds, thousands of people both contributing and also hooking me up network wise with the right people to make this happen.
Cynthia Thurlow: [00:18:58] Yeah, it’s really interesting and I think most people probably don’t realize how challenging it can be to raise money to do research and to do it in an objective, high integrity fashion. It’s very easy for industry research to get made because there’s endless financial resources and they have biases, whereas you’ve entered this saying, “Okay, let’s prove or disprove this hypothesis.” So, this recent study that came out, and I was down a rabbit hole between Twitter, YouTube reading about this. Let’s talk about this new research because this is really Dr. Budoff’s presentation, which I watched. It’s really encouraging that we are on the forefront of finding what is so significant about molecular lean mass hyper responders and LDL?
Dave Feldman: [00:19:50] Yeah. So first, let me tell you the baseline design of the study. What we’re doing is we’re recruiting 100 folks that are near this phenotype. They’re borderline lean mass hyper responders. Here’s the eligibility criteria, LDL of 190 or higher, which is you know 190 is a special number because in the existing guidelines if you are 190 or higher, you should be on the maximal dose of statin because you’re assumed to be very high risk. And there’s no other criteria to it, it’s just an LDL of 190 or higher, it doesn’t matter if you’re super fit, if you’ve got everything going for it doesn’t make any difference. But also, in addition, with the triad, an HDL of 60 or higher and triglycerides of 80 or lower, again, a little more of a relaxed version of the lean mass hyper-responder phenotype. Outside of that, there’s other cardiovascular risk factors which are part of our eligibility criteria. So can’t have a prior diagnosis of atherosclerotic cardiovascular disease, you can’t be hypertensive, things along those lines.
[00:20:49] So, what we’re doing is we’re recruiting 100 of folks that meet this eligibility. They’re getting flown to the Lundquist Institute in UCLA. They’re getting a baseline scan with a high-resolution heart scanner that you’re familiar with called as coronary CT angiography, or CCTA. It’s fantastic because it can basically– it has spatial resolution that can detect plaques as small as a millimeter or even smaller in some cases. And after getting their baseline scan, they will return a year later and then get a second scan. So, it’s called a longitudinal study for that reason that we’re looking at these scans to see to compare them over time. And we want to find out if at a population level, there is a substantial increase in their plaque volume, as indicated by these scans, which would be what would be expected per the present lipid hypothesis, the work we were just talking about with Brown and Goldstein. If you’ve got folks who have say an LDL, for example, you watch the presentation, we have one such person that has an LDL of 590. So, that’s already getting close to the children Brown and Goldstein were looking at, would we observe that, indeed, not only as a population are they developing more plaque, but on top of that, is there a correlation between their own internally, between their own LDL levels and the plaque being presented and its progression.
[00:22:12] Now, that’s the baseline design of the study. At the time we’re putting this together, I’m asking around and I’m saying, “Hey, is there any other data sets that exist out there that also are getting CT angiography on healthy subjects, on people who are metabolically healthy?” The short answer is at that time, “No,” there wasn’t. But there was one that I didn’t realize was about to be completed called Miami Heart. And once I found out from Dr. Budoff that it was possible for us to do a match analysis between our group and Miami Heart, I said, “We got to do it. Let’s see if we can add that in addition to our existing study design.” So that’s an important context, because that analysis could get done before our study was completed, because we could do it against the baseline scans, those first hundred scans which got completed in February.
[00:23:01] So, I wanted to lay that groundwork so that people understand these are two different things, but they’re both very relevant. Of course, we want to know how the plaque of our group compares to a matched control from Miami Heart. And also, we want to find out what the progression the longitudinal data shows for our population as well. Unfortunately, there’s not longitudinal data for healthy controls that are out there as of yet. But that’s okay, that may be in the next study, we’ll see.
Cynthia Thurlow: [00:23:29] Yeah, it’s very exciting. And so, walk us through the findings that were looked at, because I’m looking at all the information from Miami Heart as well as your study that was done kind of looking at where they were at baseline and then the matched cohort.
Dave Feldman: [00:23:45] Yes. In fact, I just realized I probably should pull up those slides now so that I can have them for additional reference. So, yes, the exciting part is that the one-to-one match is phenomenal. I’m going to say upfront that it was far closer than I thought we would be able to achieve. And to be sure, when I say we, I mean really Lundquist, because they’re the only ones who get to handle the data internally, but they definitely knew what I wanted. My hope was that their statistician could bring it as close as possible, hopefully without things like multivariant analysis, especially to some fairly large degree, which is a lot of times how that happens.
[00:24:30] I don’t know how much you’ve listened to me discuss adjustments and modeling. I don’t want to make it sound as if I’m completely dismissive of it, but I think the problem is when you’re working with very novel populations like ours, the issues with adjusting existing data based on expectations is you have expectations, there’s underlying assumptions, so what model exists out there that would predict, for example, the lean mass hyper-responder phenotype? I know of none. So, already I would prefer that we find a way to stratify an existing population that’s already similar in every respect as much as possible, while having just a huge difference in LDL, that’s the best experimental angle you can come at this with.
[00:25:08] And Miami Heart had a population of 2400, so it had a nice large population. We had 80 of our 100 that were within age range, so we could take those 80 and then stratify, their statistician inside of Lundquist was able to stratify out 80 that hit these matches. Are you going to be able to show this slide in the edit? You should show this slide in the edit to see how tightly this matches up.
Cynthia Thurlow: [00:25:31] Absolutely.
Dave Feldman: [00:25:32] Basically, the age is 55.5 between both. The body mass index is maybe the one other thing that’s of a reasonably significant difference between the two. The keto group is 22.5, whereas Miami Heart is 25.8, but they’re both extremely healthy. The HDL is high in both groups, exceptionally high. Triglycerides are exceptionally low. That’s one other place where they diverge somewhat, but they’re both in very healthy ranges, and nearly everything else is next to identical. The male population percentage is the same, the ethnicity is the same, even things like blood pressure, it’s so close, as is A1c as is hypertension. Even past smokers, there’s two past smokers in both populations.
[00:26:21] Okay, so I built this up pretty well, but it’s because in looking at, that was the first thing that I looked at. I was just excited how close to one to one it is. So, the major graph you’re going to be looking at is the one that shows– You could say it basically shows the total plaque score sorted between two sides, on the left side, there is the keto CTA group, lean mass hyper responders, or borderline lean mass hyper responders, on the right is Miami Heart. The reason I say sorted is you can actually see that they go up in a curve going from no plaque, which is over half of those in our cohort and about half in Miami Heart’s cohort. And then you can also see, overlaid on the plaque. The total plaque score as it goes up, you can see LDL levels. So, you can see how much LDL levels do correlate with plaque. And, spoiler alert, this is one of the major findings already.
[00:27:13] They don’t, LDL does not correlate with the total plaque score that was seen in both populations. And that already was one piece of what was exciting. But what was, of course, the one we’re most interested in is there a statistically significant difference between these two populations? And the answer to that question is no, there’s not a statistically significant difference between in spite of our population having an average time of 4.7 years, nearly half a decade, at an LDL of 272, there was no statistically significant difference in plaque with the Miami Heart cohort of the same age with an LDL of 123. In fact, one thing that was especially interesting is that our group actually trended lower. To be sure, still not a significant difference between the two, but if the lipid hypothesis was assumed to be kicking in, even if just at a slower rate, presumably it would be flipped that actually our group would be trending toward higher plaque levels, even if not yet fully diverged.
[00:28:15] Now, I’m on a caveat, understandably, this doesn’t mean that I believe our group is necessarily doing better. Again, not a statistically significant difference. And I know Dr. Budoff and other researchers would want me to point out it’s still relatively small, even though 80 is a nice large number that I like, it’s not hundreds to thousands or anything along those lines. So, it’s fair to point out that this is preliminary. That said, with all of those caveats, do I think this is a very powerful first step? Unmistakably. I think that this was an analysis we could all be very excited to be releasing as the very first step in what’s going to be many more steps to come.
Cynthia Thurlow: [00:28:53] So for benefits of listeners that perhaps are less familiarized with the research process, what’s the next thing that you and your team are going to be looking for to be able to further substantiate this lean mass hyper-responder piece?
Dave Feldman: [00:29:10] So, you could kind of think of them as two things running in parallel. One of them is the risk, which all of us are certainly interested in. It’s also very easy to understand for the average person, you want to know, “Look, it’s high LDL associating with high levels of plaque.” The other is the mechanistic. Okay, the why? Why is this happening? That’s the lipid [unintelligible 00:29:27] model. And for that, I really want to draw special attention to my good friend and collaborator, Nick Norwitz. I’m sure you’ve heard a lot about him, you should have. He’s been instrumental in or getting much of this into the literature. He’s been the first author on most of our papers, and he’s just been an exceptional comet in helping us move particularly the mechanistic side forward, but he’s also more involved on all fronts, including on the risk front. So, I wanted to make some special notification for his level of effort into this and what’s coming ahead, because there’s going to be a lot of things coming into 2024.
[00:30:01] But on the risk side, getting back to the risk side, next steps are we need to have this published. The abstract should be getting published in any day now. I haven’t heard back just yet when it happens, but then there’s also the full manuscript. The full paper should be getting published. I can’t speak to the timing on that because, as you know, you’ve got to go through the review process, and that is difficult to predict is about the best way I could put that.
[00:30:26] Then in February, we will have completed all scans, all second scans, so the longitudinal data will have been entirely collected. I expect we’ll have at least one to two months, possibly, of the drafting of the paper including the analysis. But I also want to be mindful of Lundquist time. And another component is we know just how novel these data are to where there’s going to be a lot of emphasis on trying to be sure our t’s are crossed and our I’s are dotted, understandably.
[00:31:00] If it’s as big as I think that it may be, then I can understand why there would be the maximal amount of scrutiny toward these data. But then there’s one more component, which you may already be aware of, which is that we’re also trying to raise funds for a companion study. Because as amazing as one study can be, science is ultimately built on replication. And rightly, we should already be looking ahead to how we’re going to get another study off the ground. And that study, there’s a few components that I feel like I can speak to right now, which is that it’ll probably be more relaxed criteria than the current one. The current one needed to be a bit tighter, especially to get through IRB. But now we’ll actually have risk data that we can take back to the IRB to say we could go with something a little more relaxed than the criteria I mentioned earlier. And in addition to that, we intend to have a control group. The exact context, all of that’s still sort of getting worked out, but those are sort of the baseline details, and what it’s worth, that’s what we’re holding our own conference for in Las Vegas in mid March to help raise funds for.
Cynthia Thurlow: [00:32:03] That’s really exciting. And so, when you were talking about looking at these next steps and then looking at mechanistically what’s going on, what are your thoughts about people that are over producers of cholesterol or over absorbers? Where does that fit in? Is that something that you feel comfortable speaking to? Because I feel like one of the things that I’m trying to do with this cholesterol series for the podcast is to kind of provide a broad perspective, differing perspectives, but provide a broad perspective about those of us that fit into these different buckets and looking at different philosophies. There are definitely people who are like Dayspring for one who will say, “You need to test for this Boston Heart Test, looking at markers of cholesterol production versus absorption.” Do you have any thoughts there? Do you feel comfortable speaking to that? I don’t want to put you on the spot.
Dave Feldman: [00:32:56] No, I can just tell you upfront. I already separate myself from the pack a lot. Just even earlier, I was mentioning why I don’t think big fluffy and small dense is even that relevant to me. What I’m interested in is what I’d be perceiving as homeostasis, what seems to be controlled. Do I feel as though the body is being successful at what it’s trying to do? Because if I do, if I feel like it’s being successful, then I start with the perspective that actually is by design. So, it would be like if an alien ship came down and we’re popping open the hood, and some people are like, “Yeah, this looks like very advanced technology, except for that component there, I think that component is probably a design flaw. They probably made a mistake there.”
[00:33:41] I don’t start with that perspective if it’s doing amazing things. And it seems like every single time we– Because, I’m sorry, you probably know this. Throughout history, there has been time and time again where we as humans have said, “This seems to be a design flaw with the human body that we would later have to correct ourselves about.” There’s the appendix, there’s tonsils, those are recent examples. Probably one of my favorite examples of all time, which might be somewhat analogous here, is for the longest time, it was assumed the human body made too much blood. And that’s why therapeutic bloodletting was considered to be such a strong means of healing for so long across many different domains.
[00:34:24] And there was an ounce of truth in that pound of mistake, because indeed there is versions of therapeutic bloodletting as it were. The problem is that we sometimes get fixated on what we think are the examples and get caught in something that’s known as a Simpson’s paradox. Simpson’s paradox is when there’s a large overarching confounder or multiple confounders, that if we just identified them, we would start to get smarter about recognizing why it’s telling a different story than what we thought it is. I’m telling you what I believe is the major confounder, which brings me back to homeostasis, which brings me back to dysregulation. I’m an engineer. Kind of boring this way and kind of annoying in that I’m saying, “I think it’s more complex than the way you’re describing it.” You want to say that we’re just naturally overproducing ApoB-containing lipoproteins. I am not saying that. I’m sure we’re not. I’m just saying I probably take more to convince than most people do, particularly when I’m seeing populations like ours that seem to have more to tell in the story than even the children Brown and Goldstein were looking at.
[00:35:32] For example, they were showing things like tendon xanthomas, you’re probably already familiar with that in this population. Are we seeing this with lean mass hyper responders? Are they developing things like tendon xanthomas for a likewise level of LDL? if they’re not– And again, I can only go off of anecdotal reports thus far. I think that’s a clue not worth ignoring. I think that that’s an important thing to consider. So, yeah, when you’re talking about things like hyperabsorption, hyperproduction. The hyper, that word is being derived from historical data in a context outside of low carb. And I hate to be that guy, but I’m going to be that guy and say, “Until we’re seeing what the engine is like in the context of low carb,” which I believe definitely involves transportation of lipids in this context, this milieu of cholesterol complexes that are these lipoproteins, I just don’t think we can say a lot on that yet. I don’t think we can even be sure about the hyper part. Even lean mass hyper responders, that name may get changed in the future if it’s not truly hyper responders, may not even be responder, we’ll see.
Cynthia Thurlow: [00:36:39] Well, and I think this is very important, that one of the things I really value in my interactions with you is that you, in a very thoughtful, methodical way, challenge conventional dogma, but do it in a way where you’re incredibly respectful. And this is something that, for everyone listening, we should never be rigidly dogmatic. Certainly, what I learned as a nurse and a nurse practitioner in my training is very different than how I feel about many things now and that’s– We are designed to be lifelong learners. And so that’s why I think your message in particular is so important to get us outside our comfort zone and to start considering alternative perspectives. And this is why, as I’ve mentioned before, I think your voice is so valued.
[00:37:24] And Nick Norwitz, for anyone who’s listening who doesn’t know who he is, he has a PhD from Oxford. He’s a Harvard medical student right now. He’s absolutely brilliant. I hope one day to have him on the podcast, but trying to coordinate with his clinical schedule, it is a bit challenging. Dave, you’ve already kind of mentioned what the next steps are. Is there anything else that you are leaning into right now that you’re interested in, that’s inspiring you to dive down a rabbit hole? Anything else right now that you’re looking into, research wise?
Dave Feldman: [00:37:50] You know, I’ve thought about this a lot. I’ve thought about, if I just count on the lipid research to be self-perpetuating, maybe I am coming to this point where I can count on great folks like Nick, like Adrian Soto-Mota, who’s been also instrumental. David Ludwig is taking a lot more interest in this, and of course, Dr. Budoff himself. One thing that does, I think, capture my imagination a lot, and we’re getting into it in the documentary that’s getting filmed around this story is how this happens and keeps happening. How is it that if we’re right, if indeed this context could explain high LDL cholesterol as not being the concern it was thought to be? Again, if. How is it that we get to a point where there’s such pushback on even capturing the data? That’s been one of the most fascinating, unimaginable things to me from the beginning.
[00:38:46] Is long before I was doing this research, there were people who were cholesterol skeptics for longer than I’ve been alive. And of course, there were going to be a number of people who went on low-carb diet, their cholesterol went through the roof, and they were like, “Whatever, I don’t care.” For those people, it seems obvious, “Hey, if you’re set on going in this route and you’re refusing treatment, why don’t we go ahead and capture data on you just like we’re doing with this study? It’s a natural history study. You seem to be doing this whether or not we even think that it’s high risk or not. Let’s just go ahead and capture this data.” I am still dumbfounded by how many people are insistent that we shouldn’t even be doing this at all, that even capturing the data, even suggesting there’s a study going on, could itself be encouraging for some people to not seek treatment, but I could just as easily turn that around.
[00:39:30] Actually, if you feel confident that the lipid hypothesis will be demonstrated, this is the best population ever, because these are the detractors who are refusing treatment. We could be proving to them and everybody who follows them and their example that indeed there is a high risk, and on top of that, they’re getting these CT angiograms. We could be saving their lives. If indeed the lipid hypothesis is kicking in, there’s like higher occlusion and so forth, they could be finding that out right away. The study itself could have been canceled before this point, had it not happened. And this would apply to anything for which any population is determined to push back on the conventional norms. But on top of that, I do feel like it’s not pro science. Science should be about truth seeking. And I think that in 2023, we seem to still be in that cycle of looking back at all the generations before us and thinking they weren’t as dedicated to truth seeking as we are. And yet, I’m dumbfounded, I really am, by just how much pushback there is on just studying these phenomena, it’s incredible.
[00:40:36] So I think it’s funny because I almost feel like I could just spend a year or two years, three years. I would sort of enjoy, I think, just exploring this topic and trying to bring it forward as somebody from the outside. Again, having that superpower of knowing I’m not as reliant on the goodwill of everybody who’s deeply held in the field, who could otherwise be threatening my credentials or my bona fides or something like that, I don’t know.
Cynthia Thurlow: [00:41:02] Yeah, it’s interesting. Cognitive dissonance can get in our way of considering alternative perspectives. As I stated before, I appreciate you, the work that you’re doing. Please make sure you stay in touch so that we can continue to support your efforts. Please let my listeners know how to connect with you if they would like to contribute to the research that you’re doing, find out more about you, click to your blog, follow you on Twitter. You’re one of the most polite people on Twitter, I have to honestly say. Nothing seems to get you rattled, you’re very, very, very respectful of differing opinions and sometimes people saying some absolutely crazy things.
Dave Feldman: [00:41:38] Well, thank you. Of course, I’m very active on Twitter/X, @realDaveFeldman. That’s also my username for both YouTube and for Instagram. But really X is where I’m probably the most active. Of course, we’d love if anybody came to citizensciencefoundation.org and contributed. Also, be aware we have that event where literally your contribution is your ticket into the event. And it’s in Las Vegas, so it’s an excuse to go to Las Vegas for a weekend, so feel free to come. We also have cholesterolcode.com, which was that blog that ultimately kind of got turned into an information hub. But to be fair, we don’t update it as much because quite literally, a lot of our writing is going into things that are actually getting published in literature. We’re sort of into that phase now.
[00:42:20] And, yeah, just I have to fit in one more broader scale, thank you. Because this citizen science push is truly grassroots in every sense of the word. It just wouldn’t have been possible without people like you, with all the wonderful folks who have made these contributions to make this study happen, who themselves are participants in our current study and will be for our future studies. We’ve managed to do so much from the goodwill of others to push science forward. In spite of not having a big helping hand from like the NIH or other major scientific institutions, we’ve been able to do it by rolling up our own sleeves. And for that, I’m forever grateful.
Cynthia Thurlow: [00:43:05] Well, wonderful. Thank you for all the work that you do, Dave.
Dave Feldman: [00:43:08] Thank you for having me.
Cynthia Thurlow: [00:43:10] If you love this podcast episode, please leave a rating and review, subscribe and tell a friend.
