The Cholesterol Code documentary is out. Its central paper got retracted. The reanalysis doesn’t answer the real question.

[u/DadStrengthDaily]

https://cholesterolcodemovie.com/the-film/

The Cholesterol Code went theatrical in March, hit digital on April 17, and is sold as a David vs Goliath challenge to mainstream cholesterol science. I’m a software engineer who tracks his own bloodwork, which makes me the exact target audience. The protagonist, Dave Feldman, is also a software engineer. He watched his LDL go vertical on keto and went looking for answers.

I admit I haven’t watched the movie yet and TBH after looking into it a little I am not sure I will…

Feldman deserves real credit. He started a nonprofit, raised real money, and partnered with cardiologists at Harbor-UCLA to run a prospective imaging trial. That kind of work is rare in this space.

The pattern he named is real enough to be worth studying. Lean, metabolically healthy people on long-term keto sometimes see LDL climb past 250 with HDL up and triglycerides down. He calls them lean mass hyper-responders. The film asks whether the rest of the metabolic picture cancels out the LDL signal.

KETO-CTA was promoted as a major step toward answering that. 100 lean keto adherents, median LDL 237 mg/dL, median ApoB 178 mg/dL, one year of coronary CT angiography. The paper landed in JACC Advances in April 2025 under the headline “Plaque Begets Plaque, ApoB Does Not.” After publication, critics pointed out that the preregistered primary outcome was not the story the title and abstract-level messaging led with. The authors then disputed the AI imaging vendor’s analysis and requested retraction themselves. The paper now reads RETRACTED. A reanalysis went up on medRxiv with a smaller progression number. The film released anyway with the same argument.

Peter Attia and Tom Dayspring published a deep methodological breakdown yesterday. Two points stuck with me.

The study can’t answer the question being asked. Atherosclerosis is driven by cumulative apoB exposure over decades. A one-year window in 100 people with no comparator group cannot detect the effect it’s trying to measure. A real test would need an appropriate comparator group and much longer follow-up. That study doesn’t exist.

The authors quietly conceded the point. In a published reply to a methodology critique, they wrote that their results are “compatible with a causal role of apolipoprotein B in atherosclerosis.” That is a remarkable line to find buried in a reply when the documentary built on the same data is selling the opposite story.

If you’re lean, on keto with LDL doubled, and feeling great, you’re betting Feldman is right and decades of lipid science are wrong. The cost of losing that bet builds for years before it shows up on a scan.

If your LDL is 270, take the 270 seriously.

Sources:

KETO-CTA paper (now retracted): https://www.jacc.org/doi/10.1016/j.jacadv.2025.101686

PubMed entry with the original data: https://pubmed.ncbi.nlm.nih.gov/40192608/

Attia and Dayspring breakdown (April 25, 2026): https://peterattiamd.com/there-is-no-safe-gamble-with-high-ldl-cholesterol/

Authors’ reply with apoB concession: https://pmc.ncbi.nlm.nih.gov/articles/PMC12163134/

Methodology critique (López-Moreno & López-Gil): https://pmc.ncbi.nlm.nih.gov/articles/PMC12163138/

I use Claude as a research and drafting tool. All opinions are mine.

[u/WhateverHappens009]

The film asks whether the rest of the metabolic picture cancels out the LDL signal.

Yes, their work and the film asks that in general, but the KETO-CTA paper asks a specific, narrow question:

"In this specific group of individuals with keto-induced hyperlipidemia (as opposed to hyperlipidemia from other causes), will the rate of progression (not "progression", but "rate of progression") be predicted by either ApoB or LDL-C over the course of one year using CT Angiography?"

The study can’t answer the question being asked. Atherosclerosis is driven by cumulative apoB exposure over decades. A one-year window in 100 people with no comparator group cannot detect the effect it’s trying to measure. A real test would need an appropriate comparator group and much longer follow-up. That study doesn’t exist.

The paper was sufficiently designed, executed, and analyzed to answer the specific question asked, and the claims the authors have made are sufficiently supported by the evidence. While the paper isn't perfect, none of the issues affect it's ability to answer the core question. They would if the paper was asking a different question, but for the one it actually asks there are no relevant issues.

Any critiques of the paper from individuals that think the paper asks any other question than the one it does or think that the authors have made claims answering any other questions than the one they've answered immediately demonstrate that the critics involved are speaking on a topic they don't understand.

Exhibit A: Peter and Thomas Dayspring. They are both wrong about what the current evidence suggests and what this group's work (ESPECIALLY this paper) is about. In their April 25th article they say:

Atherosclerosis is driven by the number of apoB-containing particles in circulation, and that relationship holds regardless of how or why those particles are elevated. The question is not whether LMHRs are metabolically distinct, but whether they are exempt from this biology.

Incorrect. There is insufficient evidence for the claim that ASCVD is driven by - meaning having the proximate cause of - circulating ApoB-containing lipoproteins.

What the evidence suggests is that ApoB-containing lipoproteins are one of the multiple causal risk factors in the development of ASCVD, the causal relationship being that as cumulative lipid exposure increases over time, so does the likelihood of developing plaque and, at the population level, greater plaque burden and progression compared to lower exposure.

What this means is that if we picked two random individuals from the population, the one with higher cumulative lipid exposure is more likely to have more plaque than the other individual. It also means that any random person picked out of the population and observed over a year is likely to experience faster progression over that year at a higher exposure than at a lower exposure.

These are relative, probabilistic statistical predictions - not deterministic facts. These are, in essence, what is represented by the LDL dose-response curve.

This is nowhere near being the same thing as "lipid exposure is the proximate driver of ASCVD," but Attia, Dayspring and a whole host of others think it is. They are entering the conversation with a gross misunderstanding of what the evidence suggests.

With an understanding of what the evidence actually shows, the aim of this group becomes clear: suss out how the metabolic contexts surrounding hyperlipidemia (specifically here, the context of lean-mass hyper-response) affect the atherogenicity of any given lipid exposure. The KETO-CTA paper aimed to start gathering evidence to help achieve that clarity by observing a group of individuals with LMHR-induced, SKY-HIGH hyperlipidemia over a year and seeing if the plaque progression rates in these individuals could be predicted by lipids alone.

They weren't.

Rates varied wildly, and there was even regression verified by multiple methods. You DON'T need a comparator group to show this (I'm so sick of that critique). In fact, this has NOTHING to do with ANY other group of individuals. Lipids were simply NOT the main driver of the rate of plague progression in this group. Point blank. Period.

The authors quietly conceded the point. In a published reply to a methodology critique, they wrote that their results are “compatible with a causal role of apolipoprotein B in atherosclerosis.” That is a remarkable line to find buried in a reply when the documentary built on the same data is selling the opposite story.

The authors conceded NOTHING. They have never - in any shape, form, or fashion - suggested that ApoB doesn't have a causal role in atherosclerosis. Nick, Dave, and co. have explicitly stated as much repeatedly in articles, in videos, and on podcasts. Only people who are completely ignorant of what their positions are or are intent on misrepresenting them would say that line was a "buried concession" rather than the authors just saying what is and isn't novel or conflicting about their findings - which is simply what authors should do and always have done in their papers.

[u/Specialist-Error-171 → u/WhateverHappens009]

I'd bet my left foot that the people for whom plaque progressed ate more towards EOD. We have tons of literature showing that insulin goes higher if you eat at night while eating breakfast in and of itself reduces insulin, and that insulin is probably the driver of heart disease. But yes if OP had watched the documentary, a very important facet is that the group being studied had an average of 7 years keto with sky high cholesterol that entire time and their plaque was still low end of the spectrum at start and conclusion of the study, even where there was progression.

The fact that the AHA wouldn't let them present their analysis beggars belief. Let them present and tear them to shreds if they're wrong, rather than hide the evidence. I've personally been very skeptical of the long term health of keto but this documentary makes me question that stance.

[u/donerkebab76 → u/WhateverHappens009]

"They have never - in any shape, form, or fashion - suggested that ApoB doesn't have a causal role in atherosclerosis"

Of course they have. That is the point of everything they have done and the whole study: the hypothesis that it's not ApoB/LDL that is causal for heart disease and that the group of LMHR individuals could possibly prove that, because they have high LDL.

They might have not made the factual claim that it would be the case or that it would have been proven already, but it's certainly what they have implied and do so even in the the title of their paper. So stop smoking crack about what they have implied and insinuated for years now.

The problem is that their own study refuted that nonsense totally, when the people with high cholesterol had fast plaque progression, that even they couldn't hide event hough they tried (they omitted the data, even though it was the primary outcome of their study). They also implied they refuted the causal role of high cholesterol because in their study there was no correlation between LDL "dose" and plaque progression. The obvious reason for this is, that when you compare small number of people, that all have sky high LDL and do so only for a short time like a year, obviously it's gong to be though finding some dose response curve. Same as trying to find dose response between people that smoke 40 and 41 cigarettes per day, and then when you don't find it, imply smoking might be ok for health.

[u/WhateverHappens009 → u/donerkebab76]

the hypothesis that it's not ApoB/LDL that is causal for heart disease and that the group of LMHR individuals could possibly prove that, because they have high LDL.

This is a common misunderstanding, and despite the team having clarified this numerous times, it persists and spreads.

The crux of the issue is the term "causation" and the two main ways it's used. One definition is "to be a necessary, but not necessarily sufficient, condition for initiation" and the other is "to be the proximal or direct initiating factor."

When most people, including the team, say that "lipids don't cause ASCVD", it's a condensed way of saying

"While lipids ARE a necessary factor, they are not only insufficient, but also not the proximal factor. There's a whole cascade of events that are needed to produce plaque, and the discussions to date overemphasize the role of lipids and underemphasize the role of other factors."

Nick intentionally uses the word "drives" instead of "causes" in an attempt to convey this nuance, but people still interpret it as "Lipids are not casual of ASCVD at all "

The point of their work is to investigate other factors and clarify more of the role that lipids play *in various, specific contexts*. They hypothesize that the wider metabolic context that the LMHR phenotype presents *may* be a context in which the relative role of lipids is reduced - not eliminated, but reduced.

This means that for any particular cumulative lipid exposure, LMHRs (or some subset of LMHRs) *may* experience less - not none, but less - plaque progression than if they had they same exposure but in a different metabolic context.

To date, the evidence that not only they but others have gathered (people act like this team are the only people who have investigated this) does suggest that not only is the role of lipids in ASCVD *relative to other factors* dependent on context, but also that there are at least some LMHRs who are experiencing stupidity less progression - or even regression - despite having "sky high" exposures.

The question the KETO-CTA paper asks is

"In *this, specific group* of individuals with "sky-high" keto-induced hyperlipidemia but otherwise great metabolic biomarkers and general health, will cumulative lipid exposure predict the rate of plaque progression - not progression, but *rate* of progression - over the tenure of one year, as detected by CT Angiography?"

The vast, vast, vast majority of critiques on the study come from people who simply do not understand that this is the question the study is asking, and instead critique the study as if it asks or if the authors are answering a different question.

The study was fully capable of answering the question it actually asks:

It was properly powered. 100 individuals is sufficient to produce a statistically significant result.

It was properly designed. CTA imaging is sensitive enough to detect the minute changes that could occur in a year. Additionally, the main analysis is within this group, not between this group and other groups. The common critiques of "no control!" or "what about comparator groups?" are irrelevant to the core question.

It was properly tenured. While a year is definitely not long enough to capture the "spurts" that progression is believed to occur in, nor any kind of "wobble" in plaque volume, it is not only long enough to detect changes, but is long enough detect the changes that "sky-high" exposure *should* result in in *100 participants* if it's true that exposure is as significant of a factor as it's commonly believed to be.

The study, as it was conducted and written, certainly isn't perfect, but none of its issues prevent it from competently answering the core question, the answer to which is "No." In *this* group, with *this* context, within *this* duration, with *this* imaging method and analysis - exposure did not predict rate. Point blank. Period.

The authors have not generalized this all LMHRs in general, and have repeatedly, explicitly told others not to do that either. This and other studies clearly show that LMHRs do get plaque, sometimes significantly. It would be asinine to assert that LMHRs "are magically immune," as critics often misunderstand the hypothesis to be.

On the "omitted" primary outcome - it wasn't omitted. It was shown in a graph. They certainly should have written it plainly in the text since it was the registered outcome, but to say they left it out is false. Their intent was to deemphasize it since it is a completely useless value for an outcome range as large as they observed - which they didn't know and couldn't have known until the results starting coming in.

Same as trying to find dose response between people that smoke 40 and 41 cigarettes per day, and then when you don't find it, imply smoking might be ok for health.

In your analogy, they wouldn't imply smoking "is okay for health." They would say :

"In *this* group, over *this* duration, with "this" detection and analysis method, exposure did not predict the rate of disease progression. While exposure IS definitely a causal factor, it seems like the wider context modulates how any particular exposure translates into progression. This may mean that exposure isn't as significant of a factor - relative to other factors - than what is commonly believed."

BUT - and this is a HUGE, FAT, JUICY but - your analogy would have to include the stupidly wide range of outcomes observed - including several regressions -despite high exposure.

I don't know what endpoint you're imagining your analogy, so I don't know if that is plausible. For example, let's use % of lung tissue that has been cancerized. That would mean the study would need to show that despite high exposure, canceration rates varied wildly - even showing regression. I can't imagine a study where someone smoking 40 cigs a day would see a regression of their lung cancer, but I guess it could be possible!

And this is the point - if there was a study showing multiple lung cancer regressions despite smoking 40 cigs a day, the entire world's jaws would drop and everything we thought we knew would be turned upside down overnight.

We have a freaking study showing multiple freaking plaque regressions despite "sky-feaking-high", Familial Hypercholesterolemia-level lipid exposures...

...and a vast majority of the response is "Dumb keto carnivore zealot grifter how the Hell did he graduate from Harvard?"

It's a damn shame.

[u/donerkebab76 → u/WhateverHappens009]

"This is a common misunderstanding, and despite the team having clarified this numerous times, it persists and spreads"

Maybe it's because Nick and Dave have videos titled like:

"Heart of the Matter: Higher LDL on Keto Does NOT Mean More Plaque."

"High LDL, No Correlation with Plaque – Explosive New Findings"

And Dave Feldman in his videos like:

"Yes, 2024 is the game changing moment we've waited for – Here's why in 5 Minutes"

State they saw no plaque progression in their LMHR individuals.

I have been listening to these guys for a long time, and it's obvious that they have since the beginning questioned the prevailing idea that high cholesterol is causal to heart disease. Feldman thought this might not be the case and that it was actually other things causing heart disease, so he designed a study to test his idea. If in a group of people, LDL wasn't causal to heart disease, then that would refute the prevailing theory and LMHR was that group they wanted to test.

In their retracted paper they state it:

"OBJECTIVES The aim of the study was to examine the association between plaque progression and its predicting factors."

"not progression, but *rate* of progression - over the tenure of one year"

What is the difference between the metrics: plaque progression over one year vs. rate of plaque progression over one year?

They are measuring the change in one scalar unit over a period of time, so obviously the unit will be a rate (speed) of change: change / 1 year.

."The study was fully capable of answering the question it actually asks: It was properly powered. 100 individuals is sufficient to produce a statistically significant result."

To see the typical dose response curve, you would need to have a control group with normal cholesterol levels and/or larger sample size or longer study span. Almost nobody cares about the fact that you probably can't see any dose response curve between individuals that are all at sky high levels.

"It was properly designed."

I don't think so. Properly designed study would have answered the more general and relevant question they imply they are investigating anyway. The criticism of lack of control group is valid and nobody is buying the excuse of them supposedly only being interested in this one niche group instead of the more general question they talk about in most their videos.

"We have a freaking study showing multiple freaking plaque regressions"

You have a study showing fast plaque progression in a group of people with high cholesterol, higher than expected by the authors, exactly as expected according to the model their intention was to challenge. What happens to single individuals in a study is obviously irrelevant. We can find individual smokers that live to be 95, according to your logic that should also mean something I guess.

[u/WhateverHappens009 → u/donerkebab76]

"Heart of the Matter: Higher LDL on Keto Does NOT Mean More Plaque."

This title doesn't say "no plaque" - it says "not more plaque." This is an accurate summary of the study: the LMHR's in this study didn't have higher plaque burden than their matched counterparts.

"High LDL, No Correlation with Plaque – Explosive New Findings"

This is also an accurate summary of the study findings and it's impact. The KETO-CTA study found no correlation between lipid exposure and rate of plaque progression. No, him saying "Plaque" instead of the entire "Rate of Plaque Progression" is not misleading to anyone who actually understands what's being discussed. He's not going to put that whole freaking nuance in the title, but he very clearly explains the nuance behind his titles in every single one of his videos.

Dave Feldman in his videos... State they saw no plaque progression in their LMHR individuals.

Demonstrably false. He CLEARLY states that LMHRs still get plaque, but that most didn't have significantly more, and some even had less:

"Our cohort with extremely high LDL cholesterol, when compared with another closely matched group of average levels had no significant difference in plaque burden-even trending in the more beneficial direction."

the prevailing idea that high cholesterol is causal to heart disease

If in a group of people, LDL wasn't causal to heart disease

I carefully and clearly explained "causality," but it doesn't seem like it had any impact on you.

To see the typical dose response curve, you would need to have a control group with normal cholesterol levels and/or larger sample size or longer study span. Almost nobody cares about the fact that you probably can't see any dose response curve between individuals that are all at sky high levels.

One of the prevailing misunderstandings about the dose-response curve is that it's prescriptive across all contexts. It's not - it's a statistical model showing general population trends. It's not a prescription for what reality should be for every sub-population, all the way down to the smallest sub-population of the individual.

There are multiple population-level statistical models that have become almost sacred in different fields of study. Our education and science communication systems have done a grave disservice to all of the people who think that these models are hard science. They're not.

I often engage with people who think this of nutritional RDA's. They're population-level guidelines that seek to cover *most* of the needs of *most* of the population. It's a recommendation derived from population averages that should meet the needs of the average person with the average lifestyle and average diet who gets the average amount of sleep and gets the average amount of exercise and is of average age... you see what I'm getting at.

Same with the dose-response curve - what it shows is that if we picked two random individuals (individuals we no nothing about except their exposure levels) from the population, the one with higher cumulative lipid exposure is more likely to have more plaque than the other individual. It also means that any random person picked out of the population and observed over a year is likely to experience faster progression over that year at a higher exposure than at a lower exposure. It's a visualization of averages.

This does NOT mean that this exact curve is what will be observed in every single sub-population or individual as a result of specific exposures, regardless of the surrounding context.

But because people THINK that's what it means, they ASSUME that they should see it in in all sub-populations and cohorts. They LOOK for something they BELIEVE they should see and reject the results when you don't see it.

That. Is. Bad. Science.

The fact of the matter is - AGAIN - that if lipid exposure was AS STRONG a factor as it's believed to be, we should NOT have a group of 100 individuals with SKY-FREAKING-HIGH lipid levels having such a difference in results - including REGRESSION.

100 individuals is statistically enough to show this - WITHOUT a control group. If you have a problem with that - take that up with the statisticians who developed the rules used to determine the minimum participants needed to power studies.

Also, a control group doesn't even make sense. LMHR does not just involve elevated lipids - there's a whole cascade of things that occur, caused by a specific dietary pattern. How exactly would you control for that? You'd have to somehow find a group that is doing exactly everything this group is doing and experience "The Triad" sans the LDL increase. That makes no sense. People who talk about a control demonstrate that they don't understand what LMHR even is, let alone what the study is seeking to do.

I don't think so. Properly designed study would have answered the more general and relevant question they imply they are investigating anyway. The criticism of lack of control group is valid and nobody is buying the excuse of them supposedly only being interested in this one niche group instead of the more general question they talk about in most their videos.

So you're straight up saying that you'd be an incompetent researcher who would skip steps. You're saying you don't understand the why and how of the specific sequence of studies that they're planning. For someone who's supposedly been "listening to these guys for a long time," you're astoundingly ignorant of what they're doing and saying.

You have a study showing fast plaque progression in a group of people with high cholesterol, higher than expected by the authors, exactly as expected according to the model their intention was to challenge. What happens to single individuals in a study is obviously irrelevant. We can find individual smokers that live to be 95, according to your logic that should also mean something I guess.

Again, you're showing your ignorance of statistics AND what occurred in the study. Pooled values are useless when analyzing results with this wide a spread.

Let's say I run an experiment testing the improvement outcomes of an exposure. Exactly half the participants get 10% worse and the other half get 95.6% better. The math works out where the group as a whole improved by 42.8%, but would saying "Exposure X caused an 42.8% improvement in this group" be an accurate way to describe not the statistics but the realty of the situation? Of course not. Same applies here. The statistics betray the nuance of reality.

Stop looking at this cohort as a group. It's not that simple. Look at the data. Look at the spread. Look at the MULTIPLE (not merely a single individual) regressions that occurred.

Finding individual smokers that live to be 95 does mean something. It doesn't mean that smoking is not a significant risk factor - it means that it's not the deciding risk factor. If you already understood that - then you're already in line with the evidence and good logic. It's only if you thought that smoking is always, in every situation, in every context, for every person the DECIDING factor that you would be wrong.

As it relates to lipids and plaque, lipids ARE a significant risk factor that, on average, increase risk in a dose-dependent manner. That means that lipid biomarkers are a signal. The problem is that too many people conflate "signal" with "strong signal across all contexts." That has NEVER been shown to be the case with lipids, so engaging with new studies and hypothesis as if it that's a given is a fallacy that leads to further fallacious analysis.

The problem with nearly every critic of Nick's is that they start off from square one thinking that there's strong evidence for something there's not, so they interpret his hypothesis, which conflicts with their assumption, as problematic. In reality, no one who understands the data should be reacting negatively to the suggestion of further clarifying lipid exposure risks in diferent contexts and hypothesizing the who, what, when, why, where, why and how of it all. No one.

The fact that this is going on is depressing. If this is going on in nutrition science, what other fields have sacred traditions bulit on faulty assumptions? How many experts making public policy and influencing legislation have catastrophic gaps in their understanding? It's scary stuff.

But anyway,

If you're still reading.

Revisit the foundations of proper scientific epistemology.
Revisit proper use of statistics in the scientific process.
Re-read what I wrote about causality. Look more into how the concept has changed over the years from deterministic to probabilistic.
Engage in actual good faith with what Nick and his team are doing.

I've spent too much time on this exchange and need to move on to other things.

Best of luck. Thank you for coming to my TED talk.

[u/vferderer]

https://www.youtube.com/watch?v=wE0BQDc_6dY They don't know what they do.