Episode 169: Dave Feldman talks about cholesterol and the ketogenic diet

This episode features Dave Feldman discussing the impacts of the ketogenic diet on cholesterol levels, driven by his personal experiences and extensive self-experimentation.

1. Dave Feldman's personal health concerns led him to explore the ketogenic diet's effects on his cholesterol levels.
2. Despite initial increases in LDL cholesterol, Feldman developed the "Lipid Energy Model" to explain these changes.
3. The episode emphasizes the importance of individualized dietary approaches and monitoring.
4. Feldman advocates for citizen science and community involvement in health research.
5. The discussion provides a nuanced view of how diet affects cardiovascular health, challenging conventional wisdom.

1: Introduction

Hosts introduce Dave Feldman and discuss the focus of the episode. Dawn Kernagis: "Today, we're diving into how diet specifically affects our cholesterol and health."

2: Dave Feldman's Background

Feldman shares his transition from software engineering to health science. Dave Feldman: "My personal health scare was a wake-up call that led me down a new path of discovery."

3: Development of the Lipid Energy Model

Explanation of how Feldman's ketogenic diet led to his cholesterol research and model development. Dave Feldman: "I had to understand why my cholesterol levels rose, which led me to develop a new model of lipid metabolism."

4: Implications for Diet and Health

Discussion on the broader implications of Feldman's findings for public health and dietary guidelines. Ken Ford: "Your work challenges much of the conventional advice on diet and cholesterol."

5: Conclusion

Recap of the main points and final thoughts from Feldman on the future of dietary research. Dave Feldman: "We need more personalized approaches to diet and health, based on individual metabolic responses."

1. Monitor Your Biomarkers: Regularly check your cholesterol and other health markers when changing your diet.
2. Consider a Ketogenic Diet: For those struggling with metabolic issues, a ketogenic diet might offer benefits but monitor health closely.
3. Engage in Self-Experimentation: Use personal data to understand how different foods affect your body.
4. Consult Health Professionals: Always discuss significant dietary changes with a healthcare provider.
5. Stay Informed: Keep up with the latest research on diet, cholesterol, and health to make informed decisions.

Dave Feldman is the founder of the Citizen Science Foundation and is known for his research into the ketogenic diet. Dave is a software engineer by training who embraced a ketogenic diet to avoid his progression toward type 2 diabetes. he joins us on this episode of STEM-Talk to share that journey.

After undertaking the high-fat/low-carbohydrate diet, Dave’ LDL cholesterol spiked. Dave used his training as an engineer to start learning everything he could about cholesterol and lipids. What he learned led him to create the website Cholesterol Code, a research hub for information and emerging data on cholesterol, particularly in the context of a low-carbohydrate lifestyle.

Dave’s Citizen Science Foundation is designed to support projects and research that promote collaborative efforts across multiple disciplines, both in and outside formal scientific institutions.

People

Dawn Kernagis, Ken Ford, Dave Feldman

Companies

Citizen Science Foundation

Books

None

Guest Name(s):

Dave Feldman

Content Warnings:

None

Speaker A
Welcome to stem talk. Stem talk. Stem talk. Stem talk. Stem talk.

Welcome to Stemtalk, where we introduce you to fascinating people who passionately inhabit the scientific and technical frontiers of our society. Hi, I'm your host, Don Carnegas, and joining me to introduce today's podcast is man behind the curtain, Doctor Ken Ford, IHMC's director and chairman of the double secret selection committee that selects all the guests who appear on STEM Talk. Hello Don, great to be here. So today we have a great conversation with Dave Feldman. And Dave is the founder of the Citizens Science foundation, which is a nonprofit established to support projects and research that promote collaborative efforts across a spectrum of disciplines, both inside and also outside formal scientific institutions.

Speaker C
Dave has a background in software engineering, but his journey studying the effects of nutrition on his own metabolic well being led him to a world of self experimentation and a passion for communicating science. Before we get to our interview with Dave, we have some housekeeping to take care. First, we really appreciate all of you who have subscribed to Stemtalk, and we are especially appreciative of all the wonderful five star reviews. As always, the double Secret selection committee has been continually and carefully reviewing iTunes, Google, Stitcher, and other podcast apps for the wittiest and most lavishly praised filled reviews to read on Stemtalk. If you hear your review read on StemTalk, just contact us at stemtalkhmc us to claim your official stemtalk t shirt today.

Our winning review was posted by someone who goes by the moniker Splash eight eight eight and the review is titled Newest Superfan. The review reads, I am so excited to finally have discovered this incredible podcast. I love learning about cutting edge science. As an emergency room doc, I most often listen to field specific podcasts. Broadening my awareness of research across other fields through this show is so enjoyable, especially learning the fascinating biographies of the researchers.

As a mother of older school age kids, I'm always telling my kids that most people follow a non linear path to their careers, so keep an open mind about career options. I love the skillful way Don interviews these amazing scientists to describe the unique path that brought them to the interesting areas of work. Keep up the good work. I'm binge listening to catch up. Well, thank you so much, splash 888.

Don Carnegas
And thanks to all of our other Stemtalk listeners who helped STEm talk become such a great success. Okay, and now onto today's interview with Dave Feldman.

Speaker B
Stem talk. Stem Stem talk. Stem talk. Stem talk hi, welcome to stem talk. I'm your host Don Carnegus, and joining us today is Dave Feldman.

Don Carnegas
Dave, welcome to the podcast. Thank you for having me. And also joining us is Ken Ford. Hello, Don. And hello, Dave.

So, Dave, let's start by learning a little bit more about how a software engineer with a background in game design came to be so enmeshed in the science and pathology of lipoproteins. So we're going to start at the beginning. What kind of kid were you? I was definitely a very nerdy kid. I love to play with legos.

Speaker B
I love to. Once I got my first computer, which was a Commodore 64, I love to code on it. I like to build things. But like many engineers, we're sort of known more for taking things apart. So I enjoyed getting on the inside of things that looked simple externally, like a clock.

And then, sure enough, you get underneath it. And on the inside there's all these gears and wires and other things that could be involved. And that was always very interesting to me. So you've shared with us that your parents were, and I'm quoting this, happily divorced when you were five, and that you grew up splitting your time between Denver and Wichita. So what were the best parts of your childhood?

Well, actually, I would say that I enjoyed connecting with others, as you mentioned, because I was kind of coming back and forth between two households in two different states. That taught me the importance of playing well with other kids because I might only be seeing them for a portion of my time. So building relationships was, I think, very instructive in helping me to understand the importance of collaboration and getting projects going that also could be started and then also stopped at a later point as well. I understand that you've described your parents that you just mentioned, both as graphic artists and a bit of bohemian, sort of hippie spirit types. What did you learn from them that ended up fueling your interest in science or other interests?

Well, yeah, that's part of what's ironic, is that I would say from both of them, I learned the importance of kindness. I think that how you treat others will pay big dividends for how you'll be treated in kind. But I'll concede they probably weren't as much into science as I would ultimately become. One of the things about understanding engineering, especially at a physical level, is getting a sense of how science can explain physics. For example.

Getting back to the clock, you care about things such as friction. But at the same time, I appreciated their approach to finding out things that are in the unknown and better understanding how to pursue that and keeping that wonderment alive, that sort of curiosity, that's something that I've loved about both my parents is that they've always been curious spirits. I think that's wonderful for a child to have parents that are inquisitive and curious, and it's typically transfers to the child as well. Earlier, you mentioned that you took great comfort in taking things apart, and that seems to be a common theme, actually, among some of our guests. And you mentioned the cherished.

Speaker C
You called it a cherished Commodore 64. I remember my first computer outside of the military was a very early Apple II, you know, before they came assembled, you know, way, way. I don't think it was called Apple II then, but it, you know, it was like a motherboard, and you bought parts. And so I understand the excitement of those days, you know, loading the game programs from a cassette tape. I don't know if yours work that way.

There weren't disk drives yet. The floppy drives weren't around yet for personal control. No, I was doing exactly the same thing. That was just the one way in which you could record and keep data for later. There was an adapter that I would buy, which you could adapt in just a normal commercial cassette tape player.

Speaker B
And it was exciting to me that this was even a thing that I could repurpose what was normally recording voice for recording data. And I had to understand how this magnetic tape could contain these ones and zeros that would become so important for me to retrieve later. And yes, once the floppy disk drive came, I was in heaven, because I thought, wow, this has got so much more data that I can now store and retrieve. Yeah, same experience here. The sort of marvel of it all.

Speaker C
And do you remember the sound the cassette tape made? It made this weird sort of data sound. When you, when you actually listen to it on, in audio frequency, it, you know, it was unintelligible, of course, but it had this strange sound. But those were very exciting days for computers. And somehow these little pathetic computers, I think mine was 48k, boosted to 64k with an extra board.

Seemed so exciting compared to the big mainframes that I was dealing with. And the computers in the military. These seem to have so much promise and so exciting. And it really was an exciting time in that the concept of personal computing seemed so foreign at first to everyone, and all of a sudden, it was, wow, we could have the power of what these companies that were usually paying them money to do for us right here at home. Something like word processing, which we take so for granted now, just being able to type something that then is stored in some electronic fashion that you could then distribute in some electronic fashion was revolutionary in the eighties to be done at home.

Speaker B
And it's kind of neat to just reflect back on not only that time then, but just how fast technology has moved in such a short span of time for all of us in our lifetimes, right? The first word processors I remember were uppercase only on my machine. And you had to get different hardware to get the lowercase distenders, you know, the lower pieces of the letters. It was an interesting time. So Dave, your early interest in computers also came about in a time that predated the Internet.

Don Carnegas
So what did you learn in those early days? And I'm just guessing things like learning to write code and building games and exploring bulletin board systems, is that right? That's right. So you would go and meet other likewise computer geeks. Often there would be what you might call back then, meetups, but they were like regular weekly sessions.

Speaker B
And I started hearing about this bbs that was, everyone was getting excited about bulletin board systems. And you really could say this was the precursor to the Internet. What you would do is you would get a modem on your own home computer that would call via phone another computer that was stationed at somebody's house, and they would have their computer set up so that it would be waiting for phone calls. And then they had a modem on their end. And once the call was connected, and it's the same sound you probably used to from AOL back in the days, then suddenly you were connected to that computer and you could access things on that computer, but usually was some kind of program that was set up to handle that.

And that was a bulletin board. And the bulletin board system was the software that we were all connecting with. And then we could like write a message and then post it knowing that other people who are going to call in later would see what we posted. And those were the earliest versions of chatting. And it was electric.

We were all excited, except the problem was it could only take one call at a time, so we would regularly be checking to see if the line was open so that we could log in. And then in order to manage it, you would only get a certain amount of minutes that you could be on any given bulletin board system for your account per day. That was the very earliest stages, I would argue, of this precursor to the Internet. And as you mentioned, this was all back in the early 1980s. And you said you didn't have ready access to computer science curriculum until high school.

Don Carnegas
And of course, high school computer science courses typically contain almost nothing that a computer scientist would recognize. As actual computer science. So it's a good thing then that you like self directed learning, it would seem, I'm guessing. So how did you engage your interest in programming? Well, that's where it gets fascinating.

Speaker B
I didn't really take a lot of computer science courses, either in high school or in college, because I actually enjoyed the self directed learning more. I wasn't good about structured learning. I like to, like many engineers, I am a kinesthetic learner, which is I learn a lot more by doing, and I kind of want to go at my own pace. And while that's very commonplace now, there's a lot of Internet courses and so forth where you can kind of set your own pace and learn at your own speed. This was not how things were done back then.

So it was great to be able to get a book and then actually be able to acquire the software or other tools myself and learn on my own. And that's pretty much what I had been doing since the first time I had a hold of a computer. I liked to trial and error my way through many different things, and that was something that's been a constant throughout my life. There are many different things throughout both my childhood and into young adulthood that I dabbled and was interested in trying out, thinking, hey, this coding, this engineering thing is sort of fun, but maybe that's not really going to be my career. And it wasn't really until the.com boom that I realized that probably was the direction I needed to go.

Speaker C
It would seem that your interest in self directed learning that we've been discussing, in addition to helping you learn about computers and particularly about programming, also has really enabled your current interests in your current work just as well. We'll return to that shortly in our discussion. But it seems that that same style of learning, as you mentioned, has been sort of a theme for you throughout your life. Absolutely. And I have to say, it is a skill.

Speaker B
Like so many other skills, you get used to working on your own toward goals that interest you, recognizing what limitations come with that when you don't have somebody there. That's, for example, filling in a lot of gaps of the foundation that would typically come with structured learning, then that can be a con, but it can also be a pro. There's downsides, obviously, in that you might have holes in your knowledge from what might be more typical of the introductory direction, but by the same token, and this kind of gets down to some foundations of science, by the same token, you might also get biased by a number of existing assumptions that come with structured learning. And so there's something kind of nice about coming from the outside and not having a lot of these preconceived notions such that you have a little bit of fresh eyes on the new thing you're approaching. I think that's true.

Speaker C
And you picked early in your life one of the ideal things to learn that way, which is programming. Maybe not computer science in an academic discipline, but programming is an ideal thing for the person with the right attitude and the right outlook for self directed learning, because every program you write is an experiment, in a sense, and you get feedback quickly on your experiment. So I think that kind of topic really was an ideal first go around for you and learning something on your own, and then you applied that same sort of attitude and spirit to other things. Absolutely. So, Dave, speaking of skills development and kind of thinking about things outside of the box in terms of hobbies, you mentioned that you were a bit of a runner and that you also enjoyed forensics.

Don Carnegas
And when we say forensics, this is a kind of competitive storytelling, not the criminal science version, that might first come to mind. Can you tell us a little bit more about that? Yes. So, first on the running front, that was a bit later in life, and was with the influence of my now wife, she had kind of gotten me into running. I am by no means very competitive on that front.

Speaker B
We'll have to come back to that later. But definitely during high school and college, I enjoyed what is typically called forensics there. Now, normally when you hear forensics, you think of CSI, forensic pathology, and that's not what this is. Forensics is kind of, if you don't know it, it's an interesting competitive storytelling and or competitive debate, but it's what a lot of us in school were coming together for and would then visit other schools. And so, for example, you might have, let's say a ten minute comedy that's like a one man show.

You actually get a piece of material. It has to be published material, maybe from a play, something like that. And like a one man act playing multiple parts. You are then playing the different parts. You have ten minutes to do it, and a judge is taking down notes that they're going to give you later, and you're up against, say, four or five other competitors in the same.

I forgot what they were called at that time. Session or something like that. And you do this for several different rounds, and then you might break into finals if you had the highest judging scores of those of your competitors. And then eventually you might win awards. It was great in many respects, because it taught me some degree of discipline.

It also sort of rewarded that self directed learning because we're not all doing the same thing. In fact, your selection process of what you chose to read and perform was a lot more up to you, which was great. But then there's the other component, which is in that same forensics discipline is debate. And forensic debate is very popular in both high school and in college and does teach you to interact. You have to collaborate with your debate partner, but also you have to be good about making a case and defending your case.

And this, you know, really drew forward the importance of critical thinking. So I learned quite a lot from forensic debate and really appreciated what it brought to me. I can see that would be very helpful throughout your life and even dealing with technical subjects and colleagues and teammates working on a project, your ability to express your ideas clearly in the structure of an argument as opposed to in the structure of just assertions. It's frustrating when your colleagues on a team passionately make assertions, but there's not an argument, it's just an assertion. And so I think that must have been helpful to you.

It absolutely is crucial to anticipate rebuttals if I'm going to make an assertion, just like you said, if I'm going to make a claim the sky is orange, I should already be anticipating what the pushback is going to be if I can go out and double check my own work. Oh, actually, the sky is not orange. And I anticipate people are going to be pushing back on. It may seem self evident to some degree, but I believe any good scientist, for that matter, should anticipate what they're. They should be the best critic of their own work.

They should know what the best arguments are against what they're wanting to assert, because they've built that muscle in their mind of thinking critically about their own work most of all. And you have to do that when you're constantly facing debate, when you have to hold up a proposition and do your best to defend that proposition, knowing full well what we argued against it. Because in a way, you already are doing it yourself. You already are your opponent inside your mind, and that allows you to better structure and understand and present your ideas. Right?

Speaker C
Right. I think that's just as important as being ready to deflect. A rebuttal is to be able to express your ideas in a form that rises to level of an argument, as opposed to just a bare faced assertion. So, Dave, you initially attended film school at Colorado University at Red Rocks, carrying on a passion in your family of movies. However, I understand that your side hustle of doing contract software work at night sort of overtook your original plan to graduate and move on to the movie business.

Don Carnegas
Is that right? Yeah. So it was the joint Cu Red Rocks film program. It was a great program. I loved it.

Speaker B
It was a fascinating contrast, though, because while I was interested in possibly pursuing this, and not many people know this about me, that there was this phase where I was interested in becoming a writer director. I'm taking these classes, and there's all these starving artists on top of instructors that, many of which had gone to Hollywood or some other place where they were trying to shoot film. It didn't work out for them, and they had come back and said, well, this is one thing I can do is I can at least teach you all about it. But just so you know, it's very difficult. It's a very difficult business to be.

In contrast that within the evenings, I had so much development work. I not only could write code, as I was mentioning from earlier, but I had gotten into a lot of the what at the time was big, which was multimedia. There was director, I think it was macromedia director at the time, and Flash. Flash was kind of coming up big, but also lots of other tools that worked with video. And it was, again, all of these things we take for granted now, but just being able to make something that's interactive, where you could feel like you were immersed into a program where you're clicking one thing or another and lots of interaction takes place around it.

That skill was very valuable, and it was paying me really well, such that it became harder and harder to justify trying to work my way through film school. And instead, maybe I should stick to the software development, because it just seems to keep paying such large dividends for the time I'm putting in. So this takes us to 2008, and this is when you moved to Las Vegas to work in what was the lucrative gaming platform business. So while it was financially rewarding to help create platforms that allowed people to, and this is just an example, play blackjack on their phones and chat with other players while doing so, you said that that wasn't really personally fulfilling, but what did you learn from that period? It's fascinating because when you usually say game designer, people think of a video game they may play on PlayStation three, but gaming, as they often call it here in Las Vegas, is these software platforms.

They're doing exactly what you described, where you could play, possibly for money, or maybe it's social gambling, where there's actually some social component to it. But, yeah, the non fulfilling aspect of it was I just wasn't really that much into the subject matter. I'm not as much into slots or playing blackjack on my own time. And it also didn't feel as productive. It didn't feel like I was really contributing in a strong way to the needs of society.

Not that I think that was a necessity, just that there wasn't a lot more I could do. So whenever I wanted to do something charitable, I would say, write a check. But all of that said, I made many great engineering friends here, and I did feel like it was an exciting time, because from a business and entrepreneurial standpoint, I was enjoying a lot of success. Things were moving up pretty quickly, and it put me in a good position for what comes later. Speaking of what comes later, we now move from 2008 to 2015.

Speaker C
When you receive what you describe as the piece of paper that changed my life. What can you tell us about this piece of paper? This sounds intriguing. Yes. So a little bit of setup.

Speaker B
For two years in a row, 2014 and 2015, I had gotten blood work that had something concerning me. The marker called hemoglobin a one c, is well known for seeing if you're diabetic. And it had come in at 6.1 in 2014. And my doctor alerted me that he said, this actually suggests you're pre diabetic. And I recognized the word diabetic because it's quite rampant in my family.

I said, oh, you know what? I think it's just because I've been eating a lot of junk food, pushing this deadline around development. I'm sure that's what it is. The year later, 2015, I was stunned. It came back at 6.1 again because I thought that I cleaned up my diet, I thought that I fixed what I did from the year before.

So the fact that it came back 6.1, I got very concerned. I started to do research, and I came across what's called, what at that time was called low carb, high fat LCHF. Keto wasn't that big of a thing, but it was pretty close to keto anyway, so I thought, okay, I'll try this for a little while. And so I went low carb, high fat, and I was stunned at how good I was feeling and felt very confident that I was addressing the diabetes because my carbohydrates were going down. Diabetes is.

This is a bit simplistic, but basically it's a disease of dysregulation of glucose metabolism. And at least in the case of type two diabetes. And so by just having less glucose, I felt confident, and I would later be proven right, that my a one c would be coming down. Okay. While I'm feeling great, both my dad and my sister, they're getting inspired.

Inspired by what is my success story so far. And pretty shortly after I start, they start, and six months later, they get their blood work back, and they're looking good across the board, they're agreeing that this was just a great move for us, our family. I get my blood work after them, and that's when I get that sheet of paper. That sheet of paper contained all of my blood work, which I was excited to see because I knew it was going to look great. And then I see my cholesterol levels.

My total NLDL cholesterol had almost doubled. A little more than doubled, I believe. I averaged an LDL cholesterol of around 120 to 130, which, if you know anything about it, this LDL cholesterol, which is sometimes called the bad cholesterol, it's supposed to be under 100. That's the recommended level. And so my doctor would occasionally nudge me on the 120 to 130 that he'd prefer if it were a little bit lower.

But it had now jumped to around 240, and that just made my heart sink. At that point, it was very intense for me because I couldnt understand why. Why would my two first degree relatives not see their cholesterol jump up as much as I did? Why was I the one seeing this massive rise and thats a day ill never forget? It was November 27, 2015, and I decided I would go ahead and get a second test because maybe it was just a lab error.

Maybe there was just some, something that happened with the sample. So I ended up getting my second test about two weeks later, in December 9. But between November 27 and December 9, I become obsessed. I can't focus on code anymore. I can't focus on hardly anything.

I have to understand how this is possible. And so I start reading from scratch everything I can around lipidology, the study of lipids. Basically, it's the science around cholesterol. And this weird thing happens where I'm both very depressed, almost as if somebody had died. Like I'm just.

I'm just stricken with fear while simultaneously massively curious. Because the more I'm learning about this system in our bodies that moves around cholesterol, the more it looks like a network, the kinds of networks that I've worked on my whole life in engineering, a lot of the principles I was just talking about with bulletin board systems that would ultimately apply to the Internet. The Internet likewise has a massive array of objects interacting with each other. That is the system that has cholesterol ride sharing alongside it. So these two weeks, I'm actually losing weight because I'm just eating less.

I'm afraid of the amount of saturated fat I'm consuming, or at least fat overall is going to increase my cholesterol. So I get to where I'm almost food phobic, and I'm eating probably about half what I normally do, and I lose a lot of weight. And I'm thinking to myself, you know what? This next test, this next test will be a great test, because if it really is all about this consumption of fat, particularly saturated fat, I know that I'm eating so much less. And if that's true, then my cholesterol should, at a minimum, stay the same, but probably drop.

I finally get that test, and no, it had gone up. It had gone up another 100 milligrams per deciliter. My LDL was now, I want to say 300 3340, and my total cholesterol was 425. And this may shock you, but I may be the only person ever to have experienced some amount of relief in seeing that new lap. The reason is because right in that moment, I knew that there was more to the story.

I knew that it's not that simple, that it's simply the saturated fat that was driving up my LDL levels. There had to have been something metabolic that was changing around these lipid levels. And that's the true launching point, was that December 9 test. That's interesting. Did you check lDl P or APOb at the same time?

At that time, I did. That was the first point in which I started to get what's known as an NMR, or nuclear magnetic resonance test for your listeners. That's a test that does go a bit further than a standard lipid panel, which is what I was getting, what probably most of your listeners are getting. The NMR actually breaks out these different particle numbers. So LDL P, which is what you mentioned, is the vehicle for which LDL C, which is the cholesterol, is found inside of.

So LDL particle count is considered by many lipidologists to be a much better marker for cardiovascular disease risk than LDL cholesterol, because you can have a low level of LDL cholesterol, yet have a high level of LDL particle count. So that's a low amount of cargo of the cholesterol, high amount of LDL particles. Naturally, I'm hoping that my LDL particle count is lower, but it wasn't. My LDL P is likewise much, much higher, and my APOB, which is the major protein that's on top of that particle, which we make it into, that also was a lot higher. So just to further give reference, I'm now talking about my having lipid levels that are in the top 1% of the population.

So understandably, this would be very concerning to any clinician, especially a lipidologist. Yes, for sure. And there are a group of people that, under the same circumstances as you described, their LDL C, unlike you, doesn't really rock it up, but their LDL P does. And that's why I asked. I know several people, you would know their names.

Speaker C
You know their LDL C didn't experience what you experienced, but when they were really seriously doing a ketogenic diet, their LDL P doubled and sort of got their attention. Yes, and to be sure, I want to qualify that. While we may be talking about the mechanism I'm positing for why I think this happens, I always try to take a moment to disclaim that we're still in the area of theory for sure. So, as I would always say, continue to work with your doctor. Much of what I may be describing might give some comfort that this may not be as concerning, but it's still a developing hypothesis.

Absolutely. If you don't mind, I'll go ahead and posit what I think is going on. I believe, and this is what was kind of, I guess you could say, taught to me through my series of experiments that would follow, is I would, after that, December 9, and for the next two, three years especially, I would continually take my blood and track methodically all of the food I was consuming. And I noticed, first things first, that there was a pattern similar to what I just described to you. The less I consumed, the higher my cholesterol levels went, the more I consumed, even in this ketogenic diet context, the lower my cholesterols went.

Speaker B
And I found that to be very curious. And over time, I started to think, well, actually, maybe this is reflecting how much of the lipids are liberated, the lipids being the fat that I'm now powered by, since I'm not being powered by carbohydrates. And maybe that's what also explains why the LDL cholesterol seems to go up and down with it. So this was the beginnings of what I now term the lipid energy model. And so if I'm going to summarize it.

Here's what I think is happening. I think for folks like me and not for my dad and my sister, I am a bit leaner and a bit more metabolically healthy. They would concede this, by the way, I've gotten their permission to admit this. Leaner, more metabolically healthy. People just simply were not taking on a ketogenic diet or even an Atkins diet until it became popular.

Before it was folks who were a lot more, say, obese and overweight, who would just try anything and therefore might try Atkins. So some of those folks, they might see their LDL cholesterol hardly move. Maybe it go up a little bit, but oftentimes it would drop, especially if they were very overweight. Only recently would there be folks like me who would actually try intentionally to be on a very low carb ketogenic diet. And so, in being powered by fat, these stored levels of glucose in my body that came from carbohydrates would get low enough that my body would then want to be powered more by fat, and that includes fat in my own fat cells.

And so as that fat would get liberated, it would need to get trafficked more. So not only are the tissues around my body making use of it more because they're being powered by fat, but I would need to also package them in my liver, and the liver packages them into something called a VLDL. VLDL is the precursor to LDL. A VLDL is bloated with the fat that fat, in the form of stored stored fat, is known as triglycerides. And then that would get trafficked around in the body to both replete my fat cells, again, because they're turning over fat at a faster rate, and to also power my other tissues, my oxidative tissues.

And so, in short, I posit with this model that we need to use more of these vehicles. That includes VLDL, which are turning into ldl at a faster rate and thereby leaving more ldl around that can be detected in the blood work. That's what I think is happening. And as of now, while I may be jumping a bit ahead in the story, we now have a lot of published papers around it, and we're doing more formal science to elucidate this. Let's talk about one of those papers.

Speaker C
You have the concept described in the paper and other places of a lean mass hyper responder. In some ways, I don't like that term. Maybe you'll think of a better one. But it's something that appears in particular in a paper that you are part of in January 2022. It was published in current developments in Nutrition, and the paper was titled elevated ldl cholesterol with a carbohydrate restricted diet.

Evidence for a lean mass hyper responder phenotype. So just to clear up the meaning of a lean mass hyper responder, would you tell us what that is and what are the qualifications to fall into that category? Yes. And that's why it's glad, I'm glad we set this up with that model that I just described. How did this all come together to where we would identify this very wordy name?

Speaker B
Which, by the way, I agree it's not the best name, but I think we're kind of married to it now because it's now quite commonplace in the community. So this is what happened. I'm going to go back to 2017. This is now two years since that fateful piece of paper. These experiments I kept putting out, I kept blogging, I kept presenting on it, and more and more, my blog, cholesterolcode.com, became kind of a central hub for everyone who was interested in this.

And so they kept sharing their data over social media with me, and I kept seeing over and over again, this triad, as in these three markers. So not just the high ldl cholesterol, but a corresponding high hdl cholesterol, the so called good cholesterol and low triglycerides. These three together were very prominent with me versus my other family members, and I would see them have an even greater prominence, be even more extreme, especially on the LDL and the HDL, with some who were much leaner than I was. And oftentimes this counted for even more if they were very athletic, such as if they were runners or cyclists, something along those lines. And that's part of what further helped me understand this model, because if you have less fat mass, then actually you have to traffic it more frequently.

That's the hypothesis that there's a reason for more global redistribution and repletion of these fat cells. And so this became exciting because this phenotype of responders seemed to cross all of these different ethnicities, all these different ages across the sexes. It was shocking how ubiquitous this was and how commonplace it was once you hit this level of very tight carbohydrate restriction, on top of being very lean and seemingly metabolically healthy. And again, if you throw in some fitness, that exasperates it further. But the term hyper responder was a bit too vague, because it kind of meant anybody who sees any increase in ldl so I kind of co opted that term and added lean mass hyper responder.

So we sometimes shorten it to just LMHR. And when I wrote this article in 2017, I honestly didn't know truly how common it really would be. And as of today, its still the most commented on article because it was an explosion. It was like I could really feel it within a couple of weeks just how much this landed, because I had no idea there might have been a bunch of people who were much more, say, overweight, who would say, no, no, no, I have those cut points. I have that triad, a very, very high LDL and high hdl and low triglycerides.

And so let me tell you what that cut point is for anybody listening. It's an LDL cholesterol of 200 milligrams per deciliter or higher, an HDL cholesterol of 80 milligrams per deciliter or higher, and triglycerides of 70 milligrams per deciliter or lower. And just so you know, those three in isolation are already very rare on their own. It's already very rare to find anybody with an LDL standing LDL that's above 200 or an hdl above 80, for example. So those three together, and the fact that so many people were coming forward to report that they had that triad was very cathartic.

It was an extremely impactful experience for me. The one footnote I'll throw in, though, that became very relevant to me in my life later, was I was just following it to its logical conclusion. I kept thinking, you know, how this relates back to the energy model I just described, and I'm writing this at the time in this article. I think this might actually end up applying to children. Like, we don't see a lot of blood work from children because they're not normally getting cholesterol tests.

But it would make sense. It would make sense that they would be more often metabolically healthy, and of course, many of them would be lean. And that became a big deal because I then started getting some parents that were writing in who had children who had reason to get blood work, such as epileptics or those with severe type one diabetes, and also wanting to adopt a ketogenic diet. And sure enough, they too were exhibiting this lean mass hypersponder phenotype. And that became a driver for me, wanting to get the risk data.

Speaker C
One of the things I don't like about that label, though, I can live with it, is you have the triad that you described, and it's a clear. You know, it's a clear thing. It's something that can be measured, and you have clear points where it comes into effect. You said hdl 80 or higher, like that. Right.

But the lean mass part, I'm not sure what leanness means. When you read these papers, it's based on BMI, and you can have a very low BMI and be skinny, fat. Most endurance athletes might fall into that category, or many do, I'd say. And you could be very muscular and according to BMI, be borderline obese or actually obese. And I was thinking that maybe, is it the thinness of the person you're after?

Because that's what BMI is really measuring, or is it the body composition? And I think either. It's fine with me, but I think it would be good if it was more clear which of those with a Dexa scan you could measure body composition, but it might not be what you want. It might actually be, like you mentioned, children. It might actually be their thinness or their shape of their body.

But have you thought about looking at this and see if it holds up under Dexa? Because Dexa would allow you to also learn a lot more about the fat composition, where it's located, and I think it might be useful. Oh, I want all of that data. I would love to just have a large pile of money that I could put out for lots of deeper granular analysis of these lean mass hyper responders. But no, it's really just those three cut points.

Speaker B
And my acknowledgement that it's an observational title for the phenotype. And for what it's worth, there are many such of those in science. Take atherogenic dyslipidemia, which is nearly the opposite. Atherogenic dyslipidemia is characterized by having low hdl cholesterol and high triglycerides with a preponderance of small, dense ldl particles. Now, those are the three criteria, but there's not actually a criterion for the atherosclerosis.

You don't actually. You can have atherogenic dyslipidemia without having atherosclerosis. Well, sure. And you can have atherosclerosis without having those cut points for atherogenic dyslipidemia. Same thing with, like, PCos for polycystic ovarian.

Another one would be metabolic syndrome. Metabolic syndrome. Metabolic is descriptive, but there's actually not technically a metric within those five criteria that is specific to metabolism. It's just observational that it does seem to be impactful towards metabolism. So to be fair, believe me, in 2017, I wish I could go back to the 2017 me and then like workshop titles a bit more.

But yeah, this really was one of those kind of grassroots science y things where I genuinely did not know in July of 2017 just how meaningful my article from then and my designation of this would become relevant to me in 2024. No question. We've been talking about these hyper responders, and my comment was really about whether the leanness matters and are we talking about leanness or body composition? But how prevalent do you think this? You mentioned that you sort of blew up.

Speaker C
You had lots of response. And I remember when the paper came out, a well known author in this area sent me an email and said, have you read this paper? And he basically said, I think I'm one of those. And so a lot of people must fall into that category, but it's hard to get a percentage estimate. Do you have an idea of how large that population is?

Speaker B
Well, part of why this is so difficult to estimate is because of how different these populations are. So if you go to your typical low carb diet, I'll give you a great example. David Unwin is a doctor out of the UK who I literally just retweeted his tweet a couple hours ago, and he emphasized why he is pretty confident. He just almost never sees hyper responders. He almost never sees hyper responders because his patient population just tends to be higher bmi.

They tend to be over 25, many of them in the thirties and above. And so he just doesn't see this phenomenon. But to be fair, patients aren't usually coming to him if they already are, more commonly in a metabolically healthy state. It's a skewed, skewed population you would have as a physician. But take Volek and Finney.

They are scientists, researchers who were very interested in keto as it applies to athletes, and they themselves have a paper from 2018 on this phenomenon because it was so common in their population that they were studying, especially when putting keto athletes against mixed diet athletes, or even high carb athletes, how common it was for there being a ubiquity of higher relative ldl cholesterol in the keto athletic group. And so because these two don't intertwine and interact as often in just an average population that's getting examined, it's not as easy to determine. But what I can say is that we have a Facebook group right now that is focused on the science of lean mass hypersponders and its population. The total number of members in the group is around 11,500 right now. And I would speculate probably about a quarter, maybe 25% are either borderline or full, fully lean mass hyper responders hitting all of those cut points.

Speaker C
And again, that's a skewed population as well, but that's a big number either way. No, and absolutely. This is what's tricky about it is there's just not, just not a really easy way to get a random sampling agreed. Of those who are adopting a ketogenic diet. It'd be a substantial, inexpensive undertaking for.

Speaker B
A very novel question, I shouldn't even say a novel question. I should say for a question that probably people, the juice wouldn't be worth the squeeze. I'll put it that way. Well said.

Speaker A
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Don Carnegas
So Dave, I think our listeners will be very interested in the case report published in Frontiers in Endocrinology in April 2022. So this paper is entitled case hypercholesterolemia. Lean mass hyper responder phenotype presents in the context of a low saturated fat, carbohydrate restricted diet, highlights the case of one of those hyper responders who adopted a ketogenic diet for management of ulcerative colitis. So, can you share a little bit about this case? Yes.

Speaker B
It was great that we were finally able to put a case report out there specifically, and especially one for which there was this level of detail with not only their diet, but also regular lipid testing and getting a CT angiogram at the levels that the patient was at, that they were bouncing between 405 hundred ldl. Remember, I just mentioned that my own LDL was in the top 1% for this patient. Their ldl is comparable to somebody who has the genetic disease homozygous familial hypercholesterolemia, which is a one in a million, that it's very, very rare to see ldl levels this high. And before recently, pretty much the only time you would ever see ldl levels this high was specifically due to a genetic disease that you were born with and for which you would see em at that level. So this was important because we also drew a comparison within this case report with what their final standing scan data, their heart scans, through something called a CT angiogram.

It showed that this patient had no plaque. After a little over two and a half years being on a ketogenic diet at these levels, at ldl levels in the 400, 500s. It also highlighted how saturated fat was not the central determinant of this patient's ldl levels, which is a common thought process. Just like with me early on, I thought maybe the saturated fat was what was driving my hyper response. And while we think saturated fat is a component of potentially higher levels of LDL, we're quite confident is not the central component, particularly within this population of lean mass hyperspotters.

And this case report, I think, illustrated that pretty well. And those folks, how long was that population on an extremely low carb diet? You can see this response relatively quickly, and we know this through both published materials and anecdotally within this lean mass hyperspotter Facebook group. There's probably, I want to say at least a dozen times I've read people seeing it within a month. No, I meant how long were they on that diet previous to having the CT angiogram?

Oh, in the case of this. This case report is for two and a half years. But when you're talking people plural, you know that we have a study of our own that's out of Lundquist, which we haven't chatted about yet. We'll come to that one. That.

Speaker C
That's really interesting, I think. But this was the first. This was the first published that I'm aware of. This is the first published report of a lean mass hyper responder with corresponding CT angiography. Right.

So this individual was basically eating that nutritional plan for roughly two and a half years before the CT, correct? Yes. Okay. Got it. So sort of keeping on this theme, given that cholesterol and lipoproteins are remarkably elevated in this group, what do you feel are the cumulative cardiovascular implications over a long period of time with this group?

And perhaps nobody knows. You've done some work with notable lipidiologists. What do they think about this situation? One can imagine getting a CTA scan and having a good result, and I can imagine lipidologists would still be nervous about a very long term effect that you wouldn't see quickly. What do you think about this?

And maybe it would just be an indication to continue to check, you know, continue to be watchful. What do you think? Yeah, that is the open question. It used to be very early on, while I was theorizing about this, I would say that I feel optimistic, but I just genuinely don't know. And as my profile has grown, I started feeling concerned that people were sort of taking my.

Speaker B
Just saying that as instructive in some fashion. So I would say, okay, I'm cautiously optimistic. Let me emphasize the cautiously. And now it's interesting because I almost don't even say that phrase at all because I feel like it still gets taken as too instructive. I want to double and triple down that this is unknown and we're still at the early stages.

Even for all the work that I feel like we've done and even for the data that I know is going to be released soon, we have something that's published, that's going to be coming out, the very first published data from this larger trial we'll talk about in a moment. I think we can't say what the cumulative effect will be. We do know that there is some heterogeneity in even the population that have familial hypercholesterolemia. We know this because one of the major authors that I'm working with, Doctor Matt Budoff, along with Karam Naseer, who now I'm also working with on another analysis, they've published papers that show those who do have FH who have very high levels. If, let's say they have coronary artery calcification score CAC of zero, then they look no different on their risk level in the future from anybody who has lower levels of LDL comparatively to them who likewise have FH now they would qualify, but that changes if there is a positive CAC score.

So if you have a CAC score that's not zero, that's above that, then it does get a bit more predictive. The problem is, because there was nearly half that had a CAc score of zero and it wasn't predictive when having follow up time. This already starts to say there's just probably a lot more to the story then high ldl alone can be extremely determinative on what your atherosclerotic risk is. Well, almost for sure. I think youre right Dave.

Right. And I think that to steel man the pro lipid lowering position, they would say, look, we can all agree that its multifactorial. The issue is that if we can feel confident ldl is a component, then lean mass hypersponders, even if they prove to be lower risk, could be even lower risk if they had all the same things the same, but they had lower ldl. I am happy to acknowledge that they may be correct. The question that I think is an interesting and important one that we can answer quickly is how big a risk are they right now?

Because there are still going to be populations that are going to choose to forego cholesterol lowering therapy. I think if we're bringing an answer to them, let me give you probably the most obvious examples. The people who I know who have the highest levels of ldl right now, right at this moment, are people like this patient in the case report we just talked about, where they have a very severe medical reason for why they want to have, why they want to be on a ketogenic diet. So if they get really, really low in carbs and they're very lean and they're very athletic, they might see levels like this patient, this case report, where it's say 500, 600, I know some that are like 700, 800. I tell all of them the same thing, which is this is unknown territory.

Of course. This would be considered very concerning. You know, I can't give medical advice, but I think a lot of people in this position would get CT angiograms so that they would at least know where they stand at the moment. And maybe there's further follow up past that point, of course. But do we know enough to say we feel confident you cannot continue with this diet if medication cant bring your levels low enough?

And thats why I became interested in seeing how I could participate in making this happen, getting the research around, studying the risk specifically. Thats the one twist to my story, is after 2017, I was trying to get cardiologists and lipidologists who were researchers interested to do this study. I couldn't make it happen. So in 2019, I went ahead and founded my own public scientific charity, it's Bonafide 501, where we would just raise the money ourselves to pay for the research to happen. So you touched on this a little bit already, Dave.

Don Carnegas
But back in May of 2022, you published a paper in the journal Metabolites, and it was titled Lipid Energy, reimagining lipoprotein function in the context of carbohydrate restricted diets. So can you just explain a little bit more for our listeners what the lipid energy model is and then really expand on its significance? Sure. So the major factor that we would posit is, as you're restricting your carbohydrates further and further, this ultimately results in a lower amount of glycogen stores in your liver. And as you get below a certain threshold, this will ultimately result in a cascade different components that activate more full body lipid turnover.

Speaker B
So you have something we would refer to as hypoleptinemia, which we would later publish on late when we got data on this leptin levels come way down. This can have downstream impacts on the HBA axis and thyroid, and you have greater release of these fatty acids from your adipocytes, your fat cells. So as more fatty acids are being liberated from your fat cells, that means more of your surrounding tissue can make use of those instead of the glucose that they now have less made available to them because you're lower carb and higher fat. That also means, though more of the fat that's getting liberated coming into the bloodstream is getting picked up by the liver. And as it's getting picked up by the liver, it's getting repackaged into triglycerides, which are the stored form of fat and then placed into new VLDL.

VLDL are ApOB containing lipoproteins that the liver secretes. A higher secretion of these VLDL are coming back into the bloodstream, and they are both repleting those fat cells that are liberating the fat at a faster rate and also powering those same tissues that are using the smaller amounts of fatty acids. This, by the way, includes especially the heart cardiomyocytes, the cells of the heart in particular, really like triglycerides off of lipoproteins, and they draw a lot of power off of those in particular. So, in effect, you don't just become a fat burning machine, you become a fat circulating machine. And if you're metabolically healthy, then that's why this has to work with a larger amount of trafficking, a bit more of a network of movement for these carrier proteins to move this fat around in bulk.

Speaker C
That's a good explanation. One of the other things I found interesting about the paper published in metabolites is how quickly that journal reacted to the submission. The journal says it was submitted in 19 April, reviewed, then revised, then accepted, and then published, all in 30 days. I was a journal editor long ago, and maybe because of the advent of the Internet, Internet was not used for reviews then, but FedEx, however, that's unbelievably fast. So they must have a tremendous staff or a team of reviewers, because I can't imagine getting it even reviewed in 30 days.

So that's remarkable. Yeah, we're pretty proud of that paper. It's one of the most read papers they have, and we were going to be very. We love being transparent, and we were going to be transparent with the reviewer comments, which was approved by all within. But there's almost no way to say this without it coming off as kind of a humble brag.

Speaker B
But our concern was that the reviewer comments were so, were positive to the point where it might look like we were doing that on purpose, like we were trying to kind of, you know, signal. But it was well received. And thus far, I have to say one thing that I kind of take as its own signal is we haven't had any challenge. We've not had a single letter to the editor that has found a corrective point to put forward. This isn't to say that I don't think there aren't many more things we need to do to improve on the model, or that we may have gotten some fundamental aspects of it wrong, but we've intentionally reached out and brought this paper to many lipidologists, some of them fairly big names in the field, and I've been impressed that it's been, there's quite a lot that's been acknowledged thus far, implicitly.

Don Carnegas
So, Dave, another paper that we'd like to touch on by Doctor Isabella Cooper was published in December 2023, and it's a study in Frontiers and endocrinology titled Thyroid Markers and body composition. Physician predict LDL cholesterol change in lean, healthy women on a ketogenic diet. Experimental support for the lipid energy model. So could you please share with our listeners some methods around this paper and then also the findings that were reported in this paper by Doctor Cooper. Yes, and I'll concede, of the papers we published, that one I hadn't looked at in a while, and so I am just more kind of an edit comment.

Speaker B
I'm hopeful that I don't get anything wrong, but I'm going to try to try to quote it from memory. I know this is one I should have anticipated and should have had the paper in front of me, but give me just one sec, I'll see if I can summarize it in a way that I'm pretty confident. So this was a fascinating paper in that it was adult women who were already historically on a ketogenic diet and then had an intervention to intentionally bring up the carbohydrates and then actually a further intervention to bring them back to the ketogenic diet. And it was tracked very methodically all the way through really fantastic work, because it was already anticipated by the liponergia model that we would likely see an association between how much their cholesterol levels would change based on their existing leanness and metabolic health. And that's what those data showed, is that those who had lower bmI, the leaner they were, the more likely their LDL would go down.

It would tend to be starting at a higher amount and then would go down at a higher magnitude than those who were not as lean. But of special relevance to us was also on the thyroid, and we saw that while BMI was predictive, free t three was also very predictive. How low free t three went associated very strongly with the change in LDL cholesterol. But the two of them together were extremely predictive, extremely correlative. So, Dave, earlier you mentioned funding and self funding and setting up a 501 to essentially almost crowdsource funding for research.

Speaker C
I think that's exciting in 2019, just to give it a name. You founded the Citizen Science foundation. Could you talk a little bit about the challenges you must have dealt with in establishing a public charity dedicated to propelling scientific research? I imagine it was harder than you first thought. Not for profits always are harder than they look on the surface.

Can you elaborate on this? No question. It's so much. Anybody who's considering it definitely recognize that it's a lot of work. But I think the part that many don't realize is just how much uncertainty there was around all of this.

Speaker B
I didn't know if this would work at all. As I'm putting together this charity, I'm not sharing with anybody what I'm doing because I wanted to do it all at once. I wanted to announce what we were going to try to do, which was to raise money for this study. And, hey, now we have a charity that can take your donations, and it's a bonafide 501 c three, so your donations are tax deductible. But I don't really know how many people are going to reach into their pocket and actually put out money.

I came from the world of technology, and while things like Kickstarters were exciting, usually you get something like, you get a game that you helped to fund. You're a Kickstarter, so you get one of the first devices that came from the Kickstarter, or maybe you're helping to fundraise for an independent movie, and therefore you get tickets to come see the movie. This was unlike anything I'd ever heard before, because I wanted to go to the community and say, I need at least $50,000, because I think it'll be $2,000 per lean mass hyper responder when I bake in the pricing for the CT angiograms and everything else. So I need at least 50,000. And actually what I really want is 200,000.

Well, one of the first advice, the pieces of advice that they give you for Kickstarters is don't ask for anything more than 50,000. That's already a limit that already feels too far away for the people who are contributing. Make 50,000 to be your. Your scope, and then maybe everything else is a stretch goal. And here I am.

I'm saying not only are you not going to get a toy or some kind of product, but we're getting data, and we've never done this before. So we're going to organize a study. We're going to work with a bonafide research center, so that'll be all on the up and up. But we've never done this before. This is brand new.

Put your trust in me and your dollars to try to put this together and make it happen. And I genuinely didn't know once I got into that Houston stage whether I was going to end up with $5 or $500 or $5,000 by the end of the day or by the end of the year. Had no idea. That does sound like a daunting undertaking with lots of uncertainty, but I'm glad it worked out. And following up on that, describe how you came to partner with the Lundquist Institute at UCLA.

Speaker C
I think that might be an interesting story. Yeah. We were looking around for how we could best assess development of atherosclerosis with lean mass hypersponders. And pretty quickly we realized the best test was CT angiography. Doing these CT angiograms yielded very high resolution.

Speaker B
They've gotten so much better in a short time. So it used to be that to get a CT angiogram, you had to experience as much as, say, 20 millisievers of radiation as a frame of reference, year to year, living a year of life just doing nothing at all. You get about 3.5 millisievers, give or take, from the sun and from background radiation. A mammogram, I believe, is something like 0.5 millisievers, and a chest x ray is, I think, a lot less than that. So it's a substantial amount of radiation dosage.

And now they're down to where I myself have had two CT angiograms, and they were two millisievers each. So it wasn't a big ask to see if we could get participants for this study to get these CT angiograms, given how much resolution they have to detect not just calcified plaque, like we discussed earlier, like a CAC, but also non calcified plaque at a spatial resolution of 1 mm or even less in some cases. That's amazing. That's like really excellent data to detect if they are rapidly developing atherosclerosis. And we need to find somebody who was an expert in CT angiograms.

And part of who helped us, who really, like, laid down why they were so good and made that pitch was Doctor Matt Budoff. We got in a meeting with Doctor Matt Buddhoff. He explained not only were these scans great, but the original intent was for this to be a five year study. We figured it have to be five years to get meaningful enough data. He pointed out that, no, it actually one year is more than enough time, especially at the exposure levels we're describing, if the LDL cholesterol, if the LDL particle count, if the APOB is all at these super high levels that we've been describing up until now.

Given the present limit hypothesis, we should for sure see a signal of very rapid developing plaque in our participants with CT angiograms in one year's time. And so that was it. We're like, Lundquist looks like the one we want to work with, and Doctor Matt Booneoff sounds like the guy to take up the charge. Sounds like a good connection. Absolutely.

Speaker C
What is the current state of the foundation right now? Do you have a collection of projects it's currently funding? Well, we have completed the original scope of this first study that I went to Crowdfund, which is for the one I just mentioned, for these participants. They've all had their second scans, and we're now funding or at least raising money for a second study, a sister study, to the lean mass hypersponder study, which I'm calling the Triad study, because it's going to be a more relaxed criteria than lean mass hyper responders. It's, for example, the HDL.

Speaker B
We're going to allow for being lower, the triglycerides higher and possibly more risk factors. Basically, the first one we're doing was more restrictive in that you couldn't have existing cardiovascular risk factors. It already was difficult to get through an IRB to say, we're going to study these folks who have very high levels of LDL cholesterol, who are refusing treatment to find out how high risk they are. And I think we now have enough data that we can go back to the same IRB and say, we now want to do a trial on folks who are more at risk than our original studies participants. But that also makes it more real world.

It makes it more likely that's a. Larger population you would see apply to more people. So following up on that, how do you see the foundation evolving. And how would you like it to evolve? I would love.

Frankly, I would really love to just see this model play out all over the place, not just with ours, but with others, because crowdfunded science is bringing us answers where, frankly, we're just not likely to get otherwise, because there's pretty much, and I was told this early on, there's pretty much two channels to research funding. One is, of course, the coveted NIH, which is government funding. But you're kind of at the whims of whatever they determine is worth funding or some form of business model related funding. There has to be some company involved, there has to be some interest, and typically, that means there's some product that's going to get sold. So when pharmaceutical companies are interested in a drug, it takes a lot of money to get to that first pill that's ready to go to market, and therefore a lot of expenses.

But there needs to still be something that has a return on that investment. And by definition, our return on investment is data and nothing else. We're trying to just get good data to get to the answers. And so I think that we're proving this works. We did succeed at crowdfunding that 200,000.

I told you, we've raised much more than that since that announcement. And we've, I think, managed to achieve pulling this off through a lot of good graces. For example, we have no admin overhead. We don't take any money personally. Nobody gets compensated.

Who's a part of this organization? The only overhead we have are for third party services, like credit card processing or hosting or something like that. But that allows us to correctly advertise that it's practically like a tunnel you're donating to us, which goes straight to the research. So, Dave, I know you touched on this a little bit earlier, and I also know that you're eager to share some news about a study that your team has just completed on 100 lean mass hyper responders in which subjects received a CT angiogram to establish their baseline coronary artery status, and then another one a year later. So, could you describe the findings in terms of atherosclerotic plaque in your group compared to the Miami Heart study group, and also just talk about the findings of that study in general?

Yeah, I'll have to kind of set the stage a little bit more, because the study that I've been describing up until now, the one that, the initial one we've crowdfunded for, which I'll just call the lean mass hypersponder, study, its original endpoints were longitudinal and just against themselves. So there's no control group. It's 100 scans on these, on those meeting our eligibility criteria. So 100 of them, all getting one scan and then getting a second scan one year later against their own timeline. So whenever we fly them to Lundquist, they get their scan, and then they're scheduled to come back a year later to get their second scan.

And then we look at a population level at what their plaque differences are. And as we were starting this, we knew it'd be difficult to get a control group that's attached because it's actually very difficult to find folks who are metabolically healthy, lean, and do not have this hyper response, which, frankly, seems to be supporting the model, is that it's so hard for us to find a control group. But even a mixed diet control group was basically non existent at the point that we were planning this. So that that's an important piece of information in that. Another amazing cardiologist, Karam Nasir, was at that time starting to conduct what's known as the Miami Heart study and the Miami Heart study.

In that study, they have 2400 participants, much more than our hundred, but they're only getting a single scan, so it's cross sectional, and then they follow up. Well, that's fine. I am still excited about the prospect of being able to do a match analysis where we actually take our initial hundred scans and look at them against a matched control group out of the Miami Heart cohort. And that's what we were able to do. That's what this first analysis that got reported on was able to accomplish is once Karam na Sir, who's the principal investigator of Miami, Hart, was able to authorize the sharing of their data with Lundquist, the statistician within.

Lundquist then went forward to see if she could put together a match and indeed was able to put together an excellent match. Basically, there were. Of our 100, there were 80 that matched the age requirements of the Miami Heart cohort. Ours was more liberal, theirs was a bit more restrictive. And so of those 80, once that was isolated, she would then go see if there could be a randomly acquired group within the Miami Heart cohort that could become the matched control, that as closely as possible, matched agent, matched ethnicity, matched cardiovascular disease risk markers, etcetera.

And it's extremely tight. It's very impressive. The average age was 55.5. In both, the ethnicity is a perfect match across the way. The blood pressure, inflammatory markers, they're all, like, nearly identical.

It's extremely close probably the most notable difference is the BMI is lower for our group, but that's not surprising, which kind of bears back to the model and so forth. But also, both groups had very high hdl cholesterol, lower triglycerides. Our cohort was a bit more pronounced, which isn't surprising. But here's the important part. The LDL, indeed, was very different by design.

The LDL for the matched cohort is 123, which, as I mentioned earlier, is, like, right in the average. The LDL levels for r 80 for this match analysis was 272. So, again, we're well into the top. We're actually in the top 10% of the top 1% of the population. And the average time for our cohort is 4.7 years.

So, 4.7 years, an average ldl of 272 milligrams per deciliter. And once the match was done, the plaque was not statistically significantly different between both cohorts. Interestingly, the cohort from our study, the lean mass hypersponders, actually trended toward lower plaque. Overall, there were more that had zero plaque than the Miami heart group, and there were less that had plaque and double digits. I believe ours had total plaque score of just one that was in the double digits, whereas they had, I want to say something like four.

Now, I want to immediately follow up by saying there's still not a statistically significant difference, and therefore, people shouldn't over interpret that, because the only reason it's relevant information is if it was trending in the opposite direction. I think many would assume that the lean mass hyperspotted cohort may not show a statistically significant difference in plaque, but they were on their way. Like, that was already in the work. So maybe that they would be lower risk, but that even so, they were already showing a breakaway from where the Miami Heart cohort came in. So that's kind of a bit of a summary.

But that was the first glimpse ever of a decent sized number of these people that I've been speculating on for eight years now that I'm one of, and what their corresponding plaque levels would be at baseline, at least, and how that would compare to another baseline group that's in a typical mixed population, but also with likewise low cardiovascular risk factors. That is interesting. Will the results be published soon? Yes, it's actually. In fact, it's funny.

I thought there was a chance it might be published before this took place, before we were recording, but I'm pretty sure by the time this is released, it'll be out and published. Oh, that'd be great. So all this said, you've managed to bring your love of film back into your life through the documentary that you're working on. So can you tell us a little bit about that? Yeah, it's pretty exciting.

Jen Eisenhart is. She's also been long in this business of being a documentarian, and she's filmed a lot before. She also filmed fat fiction, and a friend connected us, and we started deciding to capture a lot of what was going to take place as it happened. Regarding both this study and going into this background that my story and how this all came about that's being put together right now, we, I think, got our first footage around, I want to say, the beginning of last year. And it's been kind of exciting because basically, it's following not just this study, but all of these individual stories of people going on a ketogenic diet.

And particularly those folks that have had efficacy who like Nick Norwitz, like Jin Unwin, who's another person we interviewed, they have particular medical reasons for which a ketogenic diet is of special relevance, but also who are dealing with this factor, this extraordinarily high level of LDL cholesterol, and whether or not this is going to be a high risk for them. And I think. I think it's going very well. Obviously, a lot of it's being written as it's happening, including this final analysis with the longitudinal data, because beyond the match analysis, the peace still yet to come is that comparison of the first hundred scans with the second hundred scans. And while I want to continue to manage everyone's expectations that I do believe there'll be an increase in plaque as there would be with any group of 55 year olds, will it be a pronounced increase?

Will we see the kind of levels that we would expect with the lipid hypothesis? Well, this documentary is capturing that in real time, including these findings. All right, so we're going to close our time together by asking the obvious question every film student should be asked. Your favorite film is the 1995 crime classic the Usual suspects, directed by Bryan Singer. So we're going to ask you to defend your choice.

Yes. I really enjoyed that film for many reasons, because I think it is a great example of setup and payoff, which I think all the best films, all the best stories really can. You've probably heard of Chekhov's gun. Generally speaking, if you're a very careful storyteller, you are excellent at rewarding the audience over and over again for not only the setups they see, but the setups they don't. And I think the usual suspects does a really good job without spoiling it.

There's almost an entirely different experience in watching the film the second time around, because now you're watching more for those things you might not have noticed the first time. Well, that's a fantastic answer. I'll have to check that film out, I think. I haven't seen a film in a movie theater since the original Star Wars. I think it was 1976.

Speaker C
I found the audience unbearably rude so that this would be a film to watch, I think, on a computer. I'll concede it hasn't aged well with regard to both the director and one of the actors in it. But if you can set that part aside as a piece of film work, it's quite excellent. Sounds interesting. Well, Dave, it's been fantastic chatting with you today about the work you're doing.

Don Carnegas
And thank you so much for joining us on STEM Talk. Thank you for having me. Absolutely. I appreciate it, Dave. Stem talk.

Speaker B
Stem talk. Stem talk. Stem talk. Stem talk. So that was such a great conversation with Dave.

Don Carnegas
I really think that the work he's doing with Citizen Science foundation is a really interesting avenue to pursue. And I really do believe that the foundation's collaborative spirit is refreshing and something that's really needed in this field. I agree, Don, and I hope the foundation continues to be impactful. It's off to a good start. We certainly need more research funding opportunities beyond only those provided by the government.

Agree with you, Ken. So if you enjoyed this interview as much as Ken and I did, we invite you to visit the Stemtalk webpage where you can find the show notes for this and other episodes at StemTalk. This is Don Carnegie signing off for now. And this is Ken Ford saying goodbye until we meet again on StemTalk.

Speaker A
Thank you for listening to Stemtalk. We want this podcast to be discovered by others, so please take a minute to go to itunes to rate the podcast and perhaps even write a review. More information about this and other episodes can be found at our website, Stemtalk us. There you can also find more information about the guests we interview.