- If you know little to nothing about cholesterol->
- If you’re wanting to learn more about why cholesterol could be higher, particularly on a low carb diet->
- You can watch Dave’s recent presentation for Stanford University on the Lipid Energy Model.
- You can also check out the Lipid Energy Model poster here
- You can also check out or Frequently Asked Questions (FAQ) here
- If you’re looking to better understand the risk associated with high cholesterol on a low carb diet->
- If you’d like to understand possible benefits of cholesterol and the immune system, you can read Siobhan’s overview article on the topic here or watch her presentation here
- If you’d like to learn more about lipoprotein(a), you can watch Siobhan’s presentation on it here
- Lastly — you can always just ask us anything our Questions Page. (Just be aware our site does not constitute medical advice and we always recommend consulting with your doctor.)
In recent months, there has been a growing focus in Lipidology on the phenomenon of high cholesterol levels for those going on a low carb diet. In particular, there have been recent case series published in the Journal of Clinical Lipidology discussing this specifically. This increased interest is certainly welcome, and we definitely advocate for expanding research on this important topic as it has been a central focus of our work for over five years.
It should first be emphasized neither myself (Dave Feldman) nor my colleague, Siobhan Huggins, are medical professionals and this doesn’t constitute medical advice. Moreover, we frequently make this distinction to those following our work. That said, while much of our research isn’t in a formal setting, we have accumulated a great deal of data and analyses that we’ve found helpful to ourselves and others. And, we’ll soon be partnering with doctors Spencer Nadolsky and Tommy Wood on a coming clinical study that will be testing these high levels of cholesterol and its association development of atherosclerosis. (More on this below)
The term “hyper-responder” has been used within the low carb community for several years, and it generally refers to those who see a substantial increase in their total and LDL cholesterol levels after adopting a low carb, high fat diet. We believe the term was first used by Dr. Thomas Dayspring in relation to this dietary outcome (originally discussed in an article on LecturePad.org, but this site is longer available).
The Low Carb Lipid Triad
We believe there is a particular lipid profile of enormous interest that goes beyond simply higher LDL cholesterol (LDL-C) seen in hyper-responders. It’s the combination of high HDL cholesterol (HDL-C) and low triglycerides (TG) alongside it. This is actually much more common in those having adopted a low carb diet who appear in excellent metabolic health. And we believe it’s an extremely important clue in helping to explain why LDL-C is higher in these individuals. We’ll go into this in further detail in the next part of this series.
Studies on those with this “triad” of high LDL-C, high HDL-C, and low TG are limited. But of those studies we’ve found, this profile associates with a low risk of cardiovascular disease overall, though slightly more than its counterpart triad with low LDL-C.
In this Framingham Offspring study, we highlight the odds ratio of those both with LDL-C ≥ 100 and 130 under the “High HDL-C” column (≥ 40 males, ≥ 50 females), and triglycerides < 100. (Colored markings and overlay mine)
In this observational cohort study of 2906 men aged 53 to 74 years free of IHD at baseline, we see this relationship as well. (Colored markings mine)
Thus, while these studies are not explicitly on those consuming a low carb diet, that may give us the most insight we can for the time being on what the risk level may be with this particular lipid profile.
Conversely, low HDL and high triglycerides are well established in the literature as key components to Atherogenic Dyslipidemia and Metabolic Syndrome overall. These profiles are strongly associated with Coronary Artery Disease and all-cause mortality.
Lean Mass Hyper-responders
The phenotype “Lean Mass Hyper-responder” (LMHRs) is a subset of these hyper-responders, and are characterized as having an extraordinarily pronounced lipid triad. These were first defined myself in an article on Cholesterol Code in July of 2017.
There are exactly three criteria for LMHRs:
- LDL cholesterol of 200 mg/dL or higher
- HDL cholesterol of 80 mg/dL or higher
- Triglycerides of 70 mg/dL or lower.
Much of the reason this phenotype was referred to as “Lean Mass” is that many who presented with this pattern were often very lean and/or fit while on a very low carb diet. But this term was strictly observational. We have since observed a few outliers that have been slightly overweight, but none as of yet that have been obese.
While counterintuitive, generally the highest levels of total and LDL cholesterol in the low carb community are found almost exclusively in LMHRs. Where it is often observed marginally higher cholesterol is found in those with poor health, LMHRs often presents with very low risk markers across the board, such as low blood pressure, waist-to-hip ratio, inflammatory markers, and HOMA-IR to name a few.
There has been speculation of a genetic component that might result in these substantially higher levels, such as a polygenetic FH or ApoE4. But shared data among this community has continued to show a wide genetic variability with no predominant genetic variants yet identified. Moreover, existing studies from Volek and Phinney on low carb athletes show a near ubiquity in this pattern as well. (At right, see Figure 1 from the study)
A Possible Model to Help Explain
We believe higher total and LDL cholesterol levels in those going on a low carb diet can be in part explained by greater synthesis, secretion, and turnover of triglyceride-rich VLDL, thus leading to a higher resulting quantity of LDL particles, particularly with LMHRs. This “Lipid Energy Model” is being developed by our team and we hope to have it published in the future. For a brief overview, you can visit our Lipid Energy Model poster, or watch my presentation to Stanford.
New Attention by the National Lipid Association
Recently, the Journal of Clinical Lipidology has published case series on this phenomenon, Keto diets, not for everyone and Extreme elevations of low-density lipoprotein cholesterol with very low carbohydrate, high fat diets. These data include some patients with concerning outcomes, such as the case of hypertriglyceridemia (high TG, rather than low) and xanthoma development.
To be sure, we’re not aware of any in the series published that meet the criteria of Lean Mass Hyper-responders, but this term is mentioned prominently in these articles and may result in some confusion that the phenotype can apply to everyone observing increased LDL cholesterol from diet without regard to HDL and triglycerides. Again, this phenotype is defined by all three all three cut points (per above), not LDL-C alone. Moreover, we would likewise agree that low HDL-C and high TG (characteristic of Atherogenic Dyslipidemia) is a concerning profile whether one has high or low LDL-C.
As our site was mentioned in the initial case series, we submitted a Letter to the Editor for our response. However, our letter was rejected. We’ve since published it as an Open Letter to the Editor which you can read here. We’ll continue to seek productive engagement with the National Lipid Association as we appreciate their exceptional ability to help move this research forward.
To speak plainly, if you’re a Lipidologist reading this now and you’ve been instinctively skeptical of our work, it’s entirely understandable given the high saturation of poorly researched advice given to patients found on the internet. Winning trust for our unique circumstances may take time for many in this important field, but we’ll continue to do our best in accomplishing it. Please be aware we’re always interested in discussing this crucial topic with professionals, sharing our community data, and helping in any way we can to further advance research in this important (and in our opinion, understudied) phenomenon.
Our Coming Clinical Trial on LMHRs
A year and a half ago we founded a fully qualified 501(c)(3) public charity, the Citizen Science Foundation. It was started in large part because we wanted to raise money for clinical trials to take this important data to the next level. And I’m pleased to say we’ve successfully crowdfunded a study that is now in IRB. This study will enroll 100 Lean Mass Hyper-responders and capture high resolution CT angiograms on each, both at the beginning and end of the trial one year later. With these comparison scans, we’ll have strong data on progression of plaque volume to better understand the true risk level for this phenotype.
We’ll have much more to share on this coming study once we’ve reached approval from the IRB.
Note from Dave – this post is actually a complete “unroll” of my Nov 2019 twitter thread. We’ve linked it many, many times and thus Siobhan rightfully pointed out I should just place it in CC as its own post. As always — and with emphasis — this is not medical advice.
This site has been uncharacteristically lacking in posts the last month and a half, mainly due to a large number developments behind the scenes. Here we’ll be providing a summary of what’s been happening:
New Heights for Own Your Labs
- This was in large part due to our new video and website overhaul. We’re actually quite pleased with the functional updates especially, as we wanted better searching and selecting compared to our original version.
- While we’re quite ecstatic for the extraordinary increase, it has certainly required a bit more bandwidth on our part, particularly for Siobhan, who heads up operations for OYL. This now has her working significantly longer than she was before and thus we’re doing some back office reshuffling on resources to make OYL a much more central role to her responsibilities.
Lean Mass Hyper-responder Study IRB
Myself, I’m still very much engaged in working toward completing the IRB process for the LMHR study.
I’ll concede, it’s some of the most intensive collaboration and detail deliberation I’ve experienced in a long time. Quite a bit of work is being injected in getting the foundation of this study properly set forth.
- Many, many rules. While I can’t discuss these things openly until the IRB is approved, I’ll just say there are a number of different expected procedures and processes in both setup and execution of the study that certainly exceeded my original expectations.
- And the documents… to say we’ve had many documents to write and revise (and revise again, and again) would be an understatement. There’s just a lot of work that is required in getting this set for its launch.
All that said, I feel quite blessed to have such a strong team to work with in making this happen. Many thanks to Spencer Nadolsky, Tommy Wood, and our partner center (which we hope to announce soon).
Siobhan and Lipedema
One recent and personal development is the possibility Siobhan may be diagnosed with Lipedema. This hasn’t been a confirmed diagnosis yet, but she’ll be seeing a specialist this coming week to find out with greater certainty.
The origin of this being a possibility was actually due to her recent #EpicFast experiment. In posting pictures at the end of the experiment, many familiar with Lipedema reached out to her on the topic given her weight loss distribution was very characteristic of the condition.
Unsurprisingly, Siobhan has ramped up her research for this topic and has already begun making headway on better understanding the condition. To be sure, she starts off with several advantages given her background already in lipids, inflammation, and of course, her extensive wealth of prior bloodwork throughout her metabolic transformation. Many (like myself) are predicting bring a lot of new innovation to understanding this important and prominent disease.
Presentations, for Limited Engagement Only
I decided early in the year to keep presentations at a minimum. I had already turned down a few offers simply because I had too much on my plate with the IRB. But I went ahead and did four over the last two weekends. They all had a few subtle differences, but shared much of the same material. I’ll concede this was a bit more exhausting than I was expecting given the existing work load, but it was nice to unload some of our latest advancements for the Lipid Energy Model.
The videos won’t be posted for a while, but we’ll add them to an article here when they are.
For almost a year now Own Your Labs (OYL) has been in a kind of “Soft Launch”. It originated from our efforts to gather anonymized data such as through our #BloodTestingDrive at several conferences. Put simply, we’ve sought to (1) get people easier access to bloodwork, and (2) promote greater open science by putting together a publicly archived, yet anonymized set of advanced bloodwork and demographic data.
Affordable Private Labs = Independence
I know this is going to sound like “marketing speak”, but I’m quite serious when I say this – we want everyone who wants to order their labs privately to have the freedom to do so. Which means helping people find the labs they are looking for as affordably as possible, which means keeping our profit margins low AND encouraging comparison shopping. Yes, we even list our favorite competitors on our home page given current recommendation and experience in the community (which I’ll list here as well: Direct Labs, Ulta Lab Tests, Walk-In Lab)
A very large number of people have told us over the years that they’d love to get their bloodwork privately instead of waiting for every time it was setup through their doctor’s office. Often they’re interested in the same tests we are (like fasting Insulin, C-Reactive Protein (CRP), or NMR Lipoprofile) that simply aren’t ordered at all by many medical professionals. And while we’d always encourage everyone to take this data back to their doctor, we agree they should have the freedom to get it in the first place.
Because of how many tests Siobhan and I get on a regular basis (“power users”) and a bit of negotiating behind the scenes, we have an in of sorts with LabCorp which is how we got this pricing. Moreover, as we build on volume of tests with others through, this will give us stronger negotiating with LabCorp in the future to potentially get better pricing.
So in short, yes, our prices are pretty great. But again, that isn’t the real reason we started OYL…
Give Everyone the Option for Citizen Science
The second (and really, biggest) reason we started OYL was to give everyone the option to contribute their data anonymously. We want to build a large, publicly accessible dataset available to formal and citizen researchers alike. If so many of us are getting these advanced tests on our own, why not share it with the community along with some basic demographic data? This will be especially useful for the low carb demographic given how little open data is available for this group.
So we set it up OYL to make this its central theme. You can either (1) use our service as you would any other online, or (2) submit your data to get a “Citizen Scientist Discount” of 10% off the order.
While we had no idea just how many would opt for this choice, I’m pleased to say it’s about 4 out of every 5 who have used OYL to date!
We don’t yet have the anonymized data pool posted as we want to collect a high quantity of submissions to even further anonymize it for those participating. But we will likely meet that threshold in the coming months and launch it here at CC.
Now Ready for Prime Time
When we launched OwnYourLabs.com last year it was a simple cart system in a WordPress site. It has been growing ever since, which is great. However, it had a number of things we wanted to improve on. The number of tests listed were limited to 10 a page, it couldn’t sort alphabetically, and the consent to submit anonymized data required a tricky use of a special coupon code tied to our Terms of Service.
As of yesterday that’s all history. Now OYL is far more intuitive and easy to use. Tests are now in an infinite scrolling list with a real time search. Sorting can be done either in the drop down or by the column you prefer such as the name or price.
Best of all, we have a new consent checkbox that both opens the demographic form and applies a 10% discount all in the same click.
While both Siobhan and myself are partners in OYL, it’s been much more a labor of love than a Big Business Venture. Currently we forward all proceeds toward the Citizen Science Foundation. That said, it’s popularity is taking up more and more of our time, and this refresh might be taking that to the next level.
I certainly welcome the challenge of greater and greater volume to OYL to build this data pool (CSDA) and to help take us take this chapter of Citizen Science to the next level. I’m excited to see the many different analyses it will inspire from both formal and citizen researchers.
It’s been pretty darn busy these days as we’ve had a lot going on with the LMHR Study, platform development for OwnYourLabs.com, and some recent work on the Lipid Energy Model paper. Now most of my data has come back for the Eating Window Experiment, but I haven’t had the time to do a full write up. That said, I will at least give the preview on my OxPL-apoB data and why I find it so exciting.
What is the OxPL-ApoB assay?
This description I’m taking directly from the Boston Heart Diagnostics website, which is also where I get the assay:
Oxidized phospholipids are found on all apoB-containing lipoproteins, namely, LDL, VLDL, and especially Lp(a). When taken up by the artery wall, oxidized lipoproteins accelerate atherosclerosis, thereby, increasing the risk of myocardial infarctions, strokes, and calcific aortic valve stenosis. Oxidized phospholipids are highly pro-inflammatory and contribute to many diseases of aging. Clinicians can use OxPL-apoB levels to reclassify patients into higher or lower risk categories allowing better personalized care.
(For the remainder of this article, I’ll just refer to OxPL-ApoB as simply “OxPL”)
To be sure, I have a complex opinion regarding the elements described above and how this plays into the larger topic of the immune response. That said, I definitely do think this assay has enormous value and have been literally talking about this for years before it was even available.
Even as long ago as the fall of 2018 I was speculating on this comparative value…
If you’re a bit lost right now, don’t worry, you don’t need to know the biochemistry on this. The big takeaway is that I’ve long waited for this metric as I’ve believed all along it would (1) provide very powerful data on cardiovascular disease risk (and lots of data certainly suggests this), and (2) that in spite of low carb hyper-responders having very high LDL, I’ve long hypothesized their OxPL values would be generally low.
This is an important metric to determine given OxPL loosely correlates with ApoB in typical diet populations, thus I’ve been speculating something quite contrary to the existing data I’ve been able to find in the research to date.
OxPL-ApoB and Risk
One phenomenal scientist who has done incredible work in the field on this is Sam Tsimikas. He has conducted many trials and closely tracked OxPL levels in both humans and animals across many different study designs.
I became much more aware of his work a couple years ago and even found this older tweet with regard to one of my favorite graphs:
The above graph is taken from this study (Tsimikas et al) and has Lp-PLA2 on one axis and the ratio of OxPL over apoB. The OxPL/apoB ratio is something I’m particularly interested in, and its association with cardiovascular risk is unsurprising, but more on that in a later post.
Since gaining access to the OxPL assay at Boston Heart Diagnostics, I’ve used it a total of seven times over two experiments, the OxLDL Replication Experiment and this recent Eating Window Experiment. Here are my OxPL, ApoB, and Lp-PLA numbers for all phases:
The reference range for the OxPL-ApoB assay is <5.0, 5.0-7.5, and >7.5 nmol/L for “Low”, “Borderline”, and “Increased Risk”, respectively. All my metrics to date have been under 5.0 thus far, but this is what I was predicting overall. Interestingly, there is a clear difference between each experiment within this lower range (2.8-3.8 with the Replication Experiment, and 0.9-1.4 with the Eating Window Experiment).
The OxPL-ApoB/ApoB ratio is extremely low at a range of 0.007-0.021 across all tests. And for what it’s worth, I suspect this will prove common among those with the Low Carb Lipid Triad, particularly Lean Mass Hyper-responders. But only wider data collection will help confirm/disconfirm if this will be the case.
Again, this is preliminary, but certainly exciting. I’ve waited a long time to test this assay repeatedly, and I’m happy to see it falling in line with my general expectation given this context. There’s still plenty more variety to look forward to, both in my own experiments and the reported values of others.
Of course, I suspect this confirms a generally lower risk assessment given existing research in this area, but we can’t say for sure either way. Hence the importance of the LMHR Study as well as regular case data coming in from the LMHR community.