
A while ago a podcast aired (episode 317) from Sigma Nutrition Radio that referenced concern of low carbers having high LDL cholesterol (LDL). But in particular, that they shouldn’t take comfort in having high HDL cholesterol (HDL) and low Triglycerides (TG). This was meaningful to me as it was referencing the “Lipid Triad” (high LDL, high HDL, low TG) that is of keen interest in my research.
I reached out to the host, Danny Lennon, and asked if they’d be up for having me on to talk about it, which he worked out with the original lipid guest, Alan Flanagan. We squeezed it in while I was traveling and shooting the CC documentary, so I was a little sleep deprived, but all-in-all I think it went really well (Episode 321, which you can listen to here). In fact, I went further and did a #ListenThread on Twitter which you can read here.
Response Article
Yesterday morning, Danny was kind enough to let me know an article dropped at Sigma Nutrition that sought to answer key points I brought up in the podcast. I was quite excited about this, actually. As you know, I’m very keen to explore this topic, particularly as it relates to not only cardiovascular disease risk, but all cause mortality itself.
The goal of this article is to zero in on some specific points made in the podcast episode with Dave. So rather than go into every individual point made in that discussion, this article will focus in on points Dave made in relation to four concepts:
1. The ‘Lipid Profile-Centric Model’
2. Atherogenic Dyslipidemia and the ‘Lipid Triad’
3. Remnant Lipoproteins
4. Inflammation
The article then takes each of these proposed areas in segments, which I’ll do likewise with responses below.
Segment 1) The ‘Lipid Profile-Centric Model’
In this first section I’m quoted here from the podcast:
Dave Feldman [10:37]: “I think conventional medicine, especially in lipidology has a kind of lipoprotein centric viewpoint which is to say that lipoproteins are themselves pathogenic or in particular at least Apo B containing lipoproteins, LDL particles especially that they themselves at a certain concentration level will drive atherosclerosis. And what I sort of want to put on the table is something that I would call a kind of lipid profile centric model, which is to say that I want to distinguish how much it is that a lipid profile drives the disease especially of atherosclerosis or whether or not it’s the disease that drives the lipid profile…”
Which is responded in the article with:
The first key point to note here is Dave’s suggestion that conventional medicine has a “viewpoint” that ApoB-containing lipoproteins (especially LDL) “at a certain concentration will drive atherosclerosis.” This phrasing suggests that the causal role of ApoB (and LDL) in driving atherosclerosis is simply a competing hypothesis, with as much claim to be correct as others. But this is just not the case. Within the lipidology and cardiovascular sciences community, that LDL-C and ApoB-containing lipoproteins drive atherosclerosis is not considered a mere “viewpoint”, but rather an established fact with sufficient proof to deem LDL-C causal.
What follows for the remainder of the segment are a series of studies that look at LDL-C alone (not in combination with HDL-C and/or TG). This is counter to my proposition with the “Lipid Triad” to begin with, and why I had called attention to a lipid profile-centric comparison.
Applying Bradford Hill for Causality
Interestingly, they bring up three of the Bradford Hill criteria, Temporality, Biological Gradient, and Reversibility. I’m actually a big fan of Bradford Hill, and to be sure, he has nine criteria. There are many that are important here, but one missing that is of particular importance (indeed, it is argued as the most important): Consistency. This is especially relevant to the examination of the Lipid Triad.
Consistency of findings.
https://www.healthknowledge.org.uk/e-learning/epidemiology/practitioners/causation-epidemiology-association-causation
Have the same findings must be observed among different populations, in different study designs and different times?
In other words, high LDL should result in high atherosclerosis consistently across the variety of lipid profiles we see in the populations of interest.
There shouldn’t be a sizable population we can find with generally high levels of LDL, yet low levels of atherosclerosis, even if they have high HDL and low TG.
The Low Carb Cholesterol Challenge
And indeed, this is why I developed the “Low Carb Cholesterol Challenge” two years ago in the attempt to collect evidence on this very key criteria:
Hello! If you follow me, you know I keep pinging pro-LDL lowering experts on this key question, but still haven’t gotten anything yet. So I’m making it a fun graphic for us all to use and hopefully get some great responses soon! (What would it mean if we didn’t?) pic.twitter.com/hOCtUApyxH
— Dave Feldman (@DaveKeto) February 13, 2018
I even have a “finder’s fee” of $1,000 for anyone who can help us get a study that meets or beats the existing Lipid Triad studies showing low CVD instead.
Segment 1 Conclusion
In the conclusion, it states:
Feldman’s Claim: The disease drives the lipid profile (i.e., reverse causality).
Again, this isn’t my claim. Reverse causality assumes atherosclerosis itself is the cause and high LDL is the effect, specifically. Rather, I’m pointing to the lipid profile as a result of a disease, potentially several — such as Type 2 Diabetes. And these diseases can likewise associate with higher cardiovascular disease.
Example: Type 2 Diabetes and Its Associated Lipid Profile
For example, we already know Type 2 Diabetes can result in a specific lipid profile and likewise have a strong association with heart disease risk.
Type 2 diabetes is associated with a cluster of interrelated plasma lipid and lipoprotein abnormalities, including reduced HDL cholesterol, a predominance of small dense LDL particles, and elevated triglycerides (1). These abnormalities occur in many patients despite normal LDL cholesterol levels. These changes are also a feature of the insulin resistance syndrome (also known as the metabolic syndrome), which underlies many cases of type 2 diabetes.
https://care.diabetesjournals.org/content/27/6/1496
Note that second sentence, “These abnormalities occur in many patients despite normal LDL cholesterol levels.” So high or normal LDL, we still get greater risk with T2D alongside low HDL and high TG.
Dyslipidemia is a major underlying risk factor contributing to the excess CVD risk, and is usually more atherogenic in the presence of diabetes. It is uniquely manifested by raised levels of triglycerides, low levels of high-density lipoprotein cholesterol, and smaller, denser, and more atherogenic low-density lipoprotein particles.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2941780/
“More atherogenic in the presence of diabetes” can likewise be read in the reverse, “less atherogenic in the absence of diabetes”.
Again, if we know a disease (in this case T2D) associates with a particular lipid profile and that disease likewise associated with increased CVD (even where LDL appears normal), why not remove both? Why not look at high LDL where HDL is high and TG low?
Consistency is indeed relevant. We should apply this criterion of Bradford Hill.
Segment 2) Atherogenic Dyslipidemia and the ‘Lipid Triad’
This segment more specifically aims at HDL and TG individually and classifies these markers as “systems biomarkers”.
Systems biomarker: biomarker which provides indications of underlying cardio-metabolic processes, but are not causal independently.
I’m actually quite happy with this distinction as it is a roundabout way of agreeing with the lipid profile-centric standpoint. Indeed, I think it something systemic that typically influences the levels of these markers.
However, the segment goes on to say:
Thus, while LDL particles do possess varying degrees of atherogenicity, the fact remains that all LDL particles are atherogenic. To argue that in the context of high-HDL/low-TGs, LDL-C is not atherogenic, implies a causal role for HDL and TGs, which is not established on the basis of the current evidence.
Not at all. It doesn’t imply a causal role for the levels of these markers, it implies a causal role for that which results in the levels for these markers.
Are there diseases that can drive these lipid profiles that likewise drive the cardiovascular disease they become associated with? And again — if this is so — why wouldn’t we want to subtract this confounder to test the hypothesis?
In this context, for the ‘lipid triad’ to be true, it must demonstrate that high LDL-C alone is not a risk factor for CVD, independent of its relationship to other correlated biomarkers. <More studies provided that look at LDL in isolation>
This rounds us back to LDL in isolation. Because we keep coming back to this point regarding study quantity, I think I’ll take some time to illustrate this problem with an analogy…
Analogy: BMI Study Quantity vs non-BMI Study Quality
BMI stands for Body Mass Index. The equation is BMI = kg/m2. It is used widely in studies as a very simple measurement that tends to correlate loosely with being under, normal, or overweight.
Obviously, it has problems given many people who are muscular would be considered as a “high BMI” and one can have lots of, say, visceral fat with a pot belly, yet a “normal BMI”.
Generally, having higher BMI will likewise associate with a greater risk of cardiovascular disease. And generally, those with higher BMI going on a diet to bring it down to “normal” levels with reduce their cardiovascular risk.
Of course, if BMI were the only measurement we had, then it would be the best one (and technically, the worst one too). But we have others that are more accurate to assess if you’re actually overweight that are clearly better.
Yet what if we had 100,000 studies using BMI, and this was a couple orders of magnitude greater than studies around any other measurement? Would that make BMI the best marker given the volume of studies, regardless of its lower quality when compared to other metrics? If other studies came forward showing, say, DXA scans were much more accurate in assessing this same risk, could it be countered that these studies were too few in number next to the wealth of existing BMI data?
Ironically, this is already happened many times over with the lipid hypothesis. For example, at the point LDL cholesterol was isolated for examination there were many more studies using total cholesterol. And at the point LDL particles were gaining focus, there were many more studies on LDL cholesterol, and so on.
Segments 3 and 4, Remnants Lipoproteins and Inflammation
I’m not going to spend much time on these segments as they were actually discussed in secondary fashion. See context of the quotes mentioned in the transcript to better understand.
All Cause Mortality?
Throughout the discussion I bring up All Cause Mortality (ACM) frequently. Between all of us the phrase is mentioned 18 times.
ACM is extremely relevant to this discussion given there is a great deal of literature regarding lipoproteins/cholesterol and the immune response (here’s one of our articles on it). We need to see the complete balance on outcomes to determine a benefit.
For example, lower LDL is associated with greater risk of cancer. This doesn’t mean low LDL causes cancer, it could be in many cases the cancer caused the low LDL. But either way, if we look at populations with low LDL and they end up dying proportionately more by cancer, that means they will be dying proportionately less by non-cancer diseases (such as CVD, of course).
When talking about mortality, we care much more about “the when” (ACM) than the “what” (specific cause). The what only tells us useful information when we know the when as well. Otherwise, you could correctly say that rock climbing without safety equipment “reduces risk of dying by a heart attack substantially”.
The Unanswered Question
There are two underlying interests I have in the “Lipid Triad”:
- Do we see low levels of cardiovascular disease in populations of normal, untreated people who have the combination of high LDL Cholesterol, high HDL Cholesterol, and low Triglycerides?
- Do we see low all cause mortality (greater longevity) in populations of normal, untreated people who have the combination of high LDL Cholesterol, high HDL Cholesterol, and low Triglycerides?
I believe the answer to both of these questions is “yes”, but I don’t know for sure. I’ve sought to connect with experts who would answer “no” and how they come to this conclusion.
I love the way you analyze and explain things.
Thanks, that’s very kind. 🙂
As I see it, the first question to ask any skeptic is whether a cholesterol rise in response to diet (keto, fasting, SFA) is a sign of a healthy person. Before there is any discussion of whether the profile is healthy, establish whether the people exhbiting it are. The name LMHR implies that they are, all the published LMHR studies have pre-selected lean, healthy people to isolate the effect. Because we need to look at people with exceptional cardiorespiratory fitness (and thus very low risk of IHD) to see the effect reliably, and will not reliably see it in people at higher risk but will see something else, we should be checking whether doubters are willing to face this reality, to state this fact clearly, because it is the one “health” question around the triad that we can be certain of the answer to. No “rebuttal” can skim over it – indeed, it should be the main focus of discussion – is this reaction overall a sign of exceptional cardiorespiratory health? Yes. Why? Discuss.
In retrospect, I almost wish I had never included “Lean Mass” as part of the Lean Mass Hyper-responder term. It was more observational, yet many assume it is a qualifier — but the only qualifiers are the cut points (LDL≥200,HDL≥80,TG≤70), which as you know, simply predicted this physical appearance pretty commonly.
To your point (and your recent work on it), I likewise believe that cholesterol changes (particularly LDL rising) can be indicative of a healthy lipid metabolism, whether powered by fat or carbs. Or to put it another way, I’ll bet the degree of change in this profile going from one metabolic pathway to another (either fat-based to carb-based or vice versa) will likely associate with better metabolic health.
Many thanks for your hard work on the subject, Dave.
Appreciate the comment, Paul. Cheers!
I think this chart that Ivor Cummins uses in presentations is germane to this discussion. But I can’t find the source.
I found the source: Apolipoprotein B and non-high density lipoprotein cholesterol and the risk of coronary heart disease in Chinese, https://www.jlr.org/content/48/11/2499
Dave and Siobhan, Do you know if there are other studies similar to this one that show low CVD risk with high AboB when it accompanies other healthy cholersterol markers like high HDL and low TG? This seems significant. Am I missing something?
Thanks for all your great work.
Hello Dave,
I have been following Keto diet for 3 months now and lost 20 pounds. I had my annual bloodwork done recently and my LDL-p counts increased by 50% compared to prior to going on Keto. I follow diet doctor for Keto related information and i came across a post as below :
Dave Feldman is trying to gather as much data as possible about people who have had this experience, and over time, it may very well provide valuable information. If you are a hyper-responder and would like to be part of his ongoing research, please get in touch with him by commenting on one of his posts at http://www.cholesterolcode.com.
I would like to get in touch with you regarding your research.
Regards.
Hi! Currently, it’s really helpful to gather a lot of data points so we can suss out patterns and outliers, and the causes for both. If you are comfortable doing so, you could post your full results (even just HDL, total cholesterol, LDL, and triglycerides are great) and any questions if you have any!
Thanks so much for wanting to contribute and reaching out. 🙂
Please find the Lipid markers from before and after going on Keto: Age (30)
Before: HDL – 24, LDL – 111, Triglycerides – 109, Total – 157
After: HDL – 39, LDL – 155, Triglycerides – 119, Total – 218
Thanks! Regarding these, were these both done 12-14 hours water only fasted, out of curiosity?
I’ve done Keto for 18 months over the objections of my primary care doc, my nutrionist, my cardiologist and my well-meaning family and friends. In addition to the Keto, I stopped taking the statins which I had taken for 15 years since they had not seemed to do much except make my muscles ache. The result of my 18 month self-experiment has been that my serum glucose has dropped below 95, my TG is lower than when I was on Tricor, my HDL is up, my BMI dropped from 39 to 29.5, my energy levels (and exercise) have increased, my thyroid hormone and other hormones have moved into normal levels and I feel great ( I do miss the carb-rich foods, esp. rice ). However, despite the abundance of quantitative and qualitative datapoints indicating that I am “Well”, it seems my caregivers are focused upon one datapoint which is that my LDL is “elevated” and I should stop with the HFLC, no-statins diet and get my LDL back to “safe” levels.
As a data scientist, it is puzzling to me that medical science gathers data and finds correlations but then they “make jumps” from correlation to causation and then, entire classes of medications and treatments are developed, but the initial jump from correlation to causation is never verified even years later.
If I ran data from crime scenes around the world, and I found a high correlation between the presence of an ambulance at the crime scene and a violent crime having occurred at that crime scene; if I conclude that lowering the number ambulances in the city will lower the amount of violent crime and I get the city to lower ambulances, and then I run the numbers after a year and I note that the number of ambulances at violent crimes has decreased so I must have been right !
But all you proved is that if you decrease ambulances, there will be fewer ambulances ! You know nothing about the *cause* of violent crime; As Indiana Jones says in “Raiders of the Lost Ark” , “They’re digging in the wrong place !” https://yarn.co/yarn-clip/011189ff-42fb-411a-965c-cb67b483c2b6
Hi Carlo – thanks for sharing your story and thoughts! Hopefully you have found a way to discuss this with your healthcare team in a way that gets your thoughts and concerns across. Although I’m not a doctor so can’t say how you should handle your own health, if you’re looking for further resources to help with these discussions we do have this post from Dr. Nadolsky from a more cautiously pessimistic perspective which may help to see where they’re coming from and the evidence supporting that perspective, and we also have this presentation from Dave from a more cautiously optimistic perspective as well in case it may be of interest.
Of course it also helps to remember that doctors are health consultants whose job it is to give you advice that they feel will best help you achieve better health – likely what your team is doing as well. However, if you do disagree, it is up to you to decide if their advice is something that helps you reach your own personal health goals.
I hope whatever you decide, you find it suits you well!
Hi Julian,
We’re not doctors and can’t give medical advice so can only comment with our thoughts and any resources that may be of interest.
If you’ve seen your total cholesterol and LDL significantly increase from a low carb diet this would meet the definition of a hyper-responder.
Further, it looks like you fit the profile of a Lean Mass Hyper-responder e.g. someone who is typically lean, active, and powered by fat (e.g. on a low carb/ketogenic diet). You may be interested in the Lean Mass Hyper-responder facebook group as there are many there with similar profiles who explore the latest research regarding it, their experience, their perspective, and how they’ve approached having the profile (e.g. taking steps to move away from the profile and how they did so, sticking with it but getting additional testing to keep an eye on things, etc).