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.)
We’ve been quite proud of how well we’ve set up efficient budgeting with our research partners for this important study. Lundquist and our bloodwork providers are providing strong discounts along with Keto Mojo and GB HealthWatch completely contributing their products and services.
Unfortunately, there’s one area of cost we don’t have much control over: travel and lodging.
Rising Costs for Travel, Participants
At the time we were building our projected expenses, it seemed likely we could negotiate packages between plane, car service, and hotel coming in around $250 combined per person, per trip. And to be fair, that was pretty realistic in December 2020 when travel industries were struggling, which was when we published this video.
However, the IRB process didn’t happen in short time as we’d hoped. We weren’t fully approved until August of 2021 when I announced the study launch. Unsurprisingly, as travel across the nation has resumed in those nine months, prices for all these travel services have increased, which is where we are now.
There have been a handful of other expenses that were unanticipated. One of our bloodwork partners has required us to set up a specialized account for clinical trials that involves greater expense. Another overseas bloodwork partner needs samples shipped as frozen throughout the trip, which costs quite a bit. And we did add a $50 meal voucher per trip for participants as recommended strongly by our research partners to accommodate their stay.
All together, we believe we’ll need to raise an additional $97,000.
OwnYourLabs.com Contribution
The good news is that our other venture, OwnYourLabs.com, has been accumulating proceeds throughout 2021 to contribute directly to the Citizen Science Foundation. I’m pleased to announce this totals $51,000, thus cutting the amount we need to raise to $46,000.
(And also, props to each and every one of you who bought your labs through OwnYourLabs.com as all of them contributed directly to this study!)
How You Can Help
There are three primary ways you can show your support:
Contribute directly to the Citizen Science Foundation. Again, we are a fully qualified, 501(c)(3) Public Charity. Naturally, this is the easiest and most direct way to help. The contribution is generally tax deductible – please talk to your tax preparer for more details. It’s worth noting we have a 0% admin overhead, save third party services (such as credit card processing).
Order your private bloodwork through OwnYourLabs.com. Proceeds are continuing to accumulate for further funding directly to the CSF to support this study. Moreover, if you opt in, you can further help citizen science by volunteering your anonymized data for a discount (see site for details).
Share, retweet, repost – spread the word! Obviously, the more you can help us let others know about this important cause, the better. 🙂
Make no mistake, 2021 has been a watershed year for us. There have been many substantial developments both in what has been completed and what has just begun.
New Research Spotlight for Siobhan Huggins
Early in the year my colleague, Siobhan Huggins was diagnosed with Lipedema and quickly shifted focus to this and related conditions. In a very short time, she has developed a number of hypotheses that she has since presented on, with more presentations planned (including Low Carb Boca this upcoming January). She is also now communicating closely with leadership at the Lipedema Project to see where future collaboration on this important topic may be useful to the community and for seeking to increase the knowledge on Lipedema where possible. As a result, just last last week Siobhan was selected as Program Co-Director for the upcoming April Symposium, which will focus on ketogenic diets for Lymphatic and Fat Disorders.
After an extensive process for the protocol, we received official IRB approval and announced the study on August 27th. This study will be focusing on LMHRs and borderline LMHRs, and note it is still recruiting.
Our new paper for low carb impacts on lipids and the Lean Mass Hyper-responder phenotype was published in Current Developments in Nutrition. Here’s the direct link:
You can watch this interview from Diet Doctor where my coauthors and I discuss this paper in depth:
Lipid Energy Model Paper in Development
I know it’s been a long time coming, and you can see much of its progress through this time in our poster, my Stanford presentation, or even the super simplified, Lipid Energy Model in a nutshell (just 5 minutes). But there have still be plenty of updates to expand the model since then.
The new collaboration of Nick Norwitz, Adrian Soto-Mota, and myself have helped shaped the model for its coming submission for publication. I’m incredibly honored to be working with such extensive talent and can’t wait until we finally have our 1.0 up in the literature.
Debut of the Triad and All Cause Mortality
A recent analysis was performed with the Women’s Health Study data that concluded the highest LDLc levels correlate to the highest All Cause Mortality (ACM) where compared to low and mid ranges of likewise HDLc ≥ 50 and TG ≤ 100 levels. The process in how it came to this finding is very interesting and worth a coming post of its own which I’ll be doing in collaboration with a biostatistician.
Of special interest, the event actually helped to solve one of the largest problems in this space I’ve long struggled to tackle. For some time I’ve wanted to fashion a criteria for analyses that would be “pre-approved” as much as possible by all major voices in this debate. This would be the ideal given it would be in place before approaching the datasets we’d apply it to. But in reality, this was also likely near impossible given the wide variety of opinions across the spectrum on what the right methodology might be.
Fortunately, this current analysis and its originating criteria were widely accepted and shared by prominent voices for low LDLc (including many I’ve long discussed this with online). Its final iteration excluding standard attributes of metabolic syndrome is of special significance, and exactly what I was hoping given this helps better stratify toward metabolic health. In other words, over a short time we not only have mutual interest in looking to the triad vs ACM, but a lot of agreement on the specific parameters to use for the approach. This helps provide an important roadmap for our coming analyses.
Note from Dave: This is a guest post from Nick Norwitz on our just released LMHR paper. This post also has a live “Corrections / Clarifications” section (at bottom) which we’ll be updating as needed. We welcome and look forward to all constructive corrections and comments to our paper.
Four of my colleagues and I just published a paper in Current Developments in Nutrition on the Lean Mass Hyper-Responders (LMHR) phenotype.
Now, if you’re familiar with the phrase “LMHR” – or if you are an LMHR yourself – then the findings of this paper will be akin to the statement “water is wet.” Nevertheless, the majority of people, including those in the medical community, are not aware of this fascinating metabolic phenomenon. That’s not a slight against anyone; it is simply the state of affairs.
So, let’s change that. What is a “Lean Mass Hyper Responder?”
But the elevations in LDL exhibited by these lean persons on low-carb diets had two peculiar features that set it apart from other forms of high LDL:
Extreme LDL Increases
First, the LDL increases were much larger than those typically associated with living an unhealthy lifestyle. When most doctors think about high LDL related to being unhealthy and eating a poor diet, they think about levels in the high 100s. But lean people on carbohydrate restricted diets were anecdotally observing LDL levels of 200, 300, 400, and even 500 mg/dL or more.
In fact, some LMHRs exhibit LDL levels as high as persons with homozygous familial hypercholesterolemia, a rare and devastating genetic condition (1 in 1,000,000) that likewise associates with very early heart disease.
Very High HDL and Very Low Triglycerides
Second, when lean people do see increases in LDL on a carbohydrate restricted diets, they tend to be accompanied by very high HDL (so-called “good cholesterol”) and very low triglycerides (TG), fat in the blood. This pattern of high HDL and low TG is exactly opposite the profile of “atherogenic dyslipidemia,” which is defined by low HDL and high TG, and is, at present, the predominant risk factor for cardiovascular disease (Libby, 2021).
Simply put, when lean people on low-carbohydrate diets saw increases in LDL they were quite often in the context of otherwise excellent metabolic health markers. Therefore, Dave created a set of three cut points that combine to define what would become the LMHR phenotype:
LDL cholesterol ≥ 200 mg/dL
HDL cholesterol ≥ 80 mg/dL
TG cholesterol ≤ 70 mg/dL
Now, before moving on I want to emphasize that the definition of LMHR is based on these three thresholds and NOT on any measure of leanness or BMI. The word “lean” is in the title because the people who were anecdotally reporting high LDL, high HDL, and low TG tended to be lean.
In other words, the name “LMHR,” posed in 2017 was itself a sort of prediction: maybe leaner and metabolically healthier people are more likely to exhibit increases in LDL on a low-carb diet?The name is the hypothesis.
Study Suggests that LMHR Exist!
Being Leaner & Having Lower TG/HDL Predicts Larger LDL Increases on a Low-Carb Diet
It was a long time coming, but we finally put that hypothesis to the test in a scientific study.
In this new study, published in Current Developments in Nutrition, we collected survey data from people who had been low-carb for >2 years, who were not on statins, and who had lipid data from before they started their low-carb diet as well as recent lipid data from on their lowcarb diet.
Then, rather than massaging the numbers to conform to our hypothesis, we engaged in a “hypothesis-naïve exploratory analysis” in which we took all the data we had on respondents — including age, sex, BMI, and current and pre-low carb LDL, HDL, and TG levels — and asked a computer to tell us which factors were most strongly and reliably associated with increases in LDL after starting a low-carb diet.
The results were clear. No matter how we approached the question (be it multivariate linear regressions or hypothesis-naïve computer-generated decision trees [Supplemental Figure 3]) we found that having lower BMI and a lower TG/HDL ratio associated with larger increases in LDL.
Hypothesis-naïve exploratory analysis finds that having lower BMI and a lower TG/HDL ratio associates with larger increases in LDL on a low-carbohydrate diet.
The relationship can be clearly seen in the bar graph below. The further you go to the left, the lower the BMI. The further you go to the back, the lower the pre-diet TG/HDL ratio. And the height of the bar is the median increase in LDL.
Picking out the LMHR
After establishing that those who are leaner with lower TG/HDL ratios exhibited larger increases in LDL with carbohydrate restriction, it made sense to try to separate the true LMHR (those who met all three cut-points) from the larger cohort and see how different they really were…
Of the 597 participants that met the inclusion criteria, 112 were bona fide LMHR (which is a lot, considering many people don’t believe LMHR exist). And, true to their name, they were Lean!
The average BMI of a LMHR was 21.9, as compared to 24.5 for the rest of the low-carb sample in this study (between group p = 1.04 x 10-11). Furthermore, LMHR exhibited higher LDL, higher HDL, and lower TG, with mean values of 316, 99, and 47 mg/dL respectively.
And, importantly, LMHR did not differ in terms of their pre-diet LDL when compared to the non-LMHR population. In fact, median pre-diet LDL was 135 mg/dL in non-LMHR and 135 mg/dL in LMHR. Exactly the same! This finding is consistent with the notion that, unlike familial hypercholesterolemia, the cause of LDL increases among LMHR is unlikely to be genetic (see more below).
In the Lean Mass Hyper-Responders (LMHR) paper, the average LDL, HDL, and TG of LMHR were 316, 99, and 47 mg/dL on low-carb, respectively. This was despite normal pre-diet LDL levels.
A LMHR Case Report Shows the Phenotype is Partially Reversible
Now, you’ve probably sensed a lot of enthusiasm from me, but don’t mistake intellectual excitement about a fascinating observation for a suggestion that high LDL levels in LMHR are benign.
Setting my own hypotheses aside, we do not yet know if the risk associated with high LDL is any different in the context of LMHR as compared to any other context. And most experts would agree that high LDL is dangerous, regardless of cause.
That said, this very question — is high LDL harmful in LMHR? — is currently being assessed in a prospective study (data from which are expected to drop in 2023). And I will be vocal about the data when they emerge, whatever they say.
Nevertheless, for the time being, many or most LMHR patients and their doctors are concerned about their high LDL. That said, many of those same people find a low-carb way of life to be tremendously beneficial for their various metabolic disorders. This begs the question, can you “fix” the LDL problem (perceived or true) through lifestyle? The answer, yes — at least partially.
As part of this study, we also wrote up a case series of five patients who were LMHR or nearLMHR. These patients all exhibited extraordinary increases in LDL upon starting a ketogenic diet. And, importantly, all were tested for genetic mutations associated with high LDL and all tested negative, supporting the notion that being a LMHR is not a genetic condition but a metabolic phenomenon.
One patient saw his LDL increase from 116 to 665 mg/dL (no surprise, he was the leanest.)
All of the patients refused, or were intolerant of, statins and instead opted to reintroduce a moderate amount of carbohydrate, ~50 – 100 grams, in order to transition from a very lowcarb ketogenic diet to a diet that was still low-carb (<130 grams net carbs per day).
Impressively, all participants saw their LDL drop by at least 100 mg/dL, with larger drops occurring on those with high levels. The patient who saw his LDL increase to 665 mg/dL exhibited a 480 mg/dL drop in LDL by doing nothing more than adding about a small, sweet potato’s worth of carbs per day.
Stop and think about that for a second. In this context, a sweet potato per day could drop LDL by almost 500 mg/dL!
Subject
Lipids
pre-VLCD
VLCD
LCD
LDLc Decrease
IA*
Total Chol
214
797
294
-480
LDLc
116
665
185
HDLc
81
122
95
TG
84
50
72
TG/HDLc
1.0
0.4
0.8
MI*
Total Chol
209
698
497
-223
LDLc
122
583
360
HDLc
72
97
122
TG
54
70
67
TG/HDLc
0.8
0.7
0.5
RO
Total Chol
197
311
180
-124
LDLc
137
239
115
HDLc
45
65
54
TG
62
56
36
TG/HDLc
1.4
0.9
0.7
NM
Total Chol
179
387
272
-122
LDLc
113
317
195
HDLc
49
59
61
TG
86
54
56
TG/HDLc
1.8
0.9
0.9
AN
Total Chol
218
423
318
-100
LDLc
141
336
236
HDLc
57
69
66
TG
98
74
64
TG/HDLc
1.7
1.1
1.0
Future Directions
This is only step one, putting the LMHR phenomenon on the map. This paper suggests that LMHR are real and, if I do say so myself, really interesting!
In my opinion, no true student of health and/or medicine can observe this phenomenon and not be intrigued.
But what this paper does not do is explain the “how.” It likewise can’t evaluate the risk. Those are the subjects of upcoming projects.
This paper describes a phenomenon. It does not explain the mechanism nor comment on risk.
Saturated fat intake was not measured; however, it seems highly unlikely variations in saturated fat intake can explain the findings as this would assume that, across the study sample of 597 people, lean people and those with good metabolic health preferentially and reliably consumed more saturated fat.
So, for those who want to protest that “LMHR just ate more saturated fat” (and we get this a lot), I’d want to ask: what do you think about the flipside of such an assertion. Is it reasonable to assume that eating saturated fat is strongly, and possibly causally, associated with being leaner and with better metabolic health markers? (For more on this, see Supplemental Figure 5 from the paper.)
The phenomenon is likely metabolic, not genetic. This is supported by at least three lines of evidence in this study:
LMHR have normal pre-low carb LDL levels. In fact, in the study, pre-diet LDL levels were exactly the same between LMHR and non-LMHR.
It’s been anecdotally observed that LMHR who gain weight exhibit drops in LDL, despite no change in their genetics.
Most importantly, genetic testing in the six patients in the case series were negative. Genetic testing performed on other subjects not reported in this study have also been negative.
Corrections / Clarifications
The current publicly available LMHR manuscript is an unedited version https://academic.oup.com/cdn/advance-article/doi/10.1093/cdn/nzab144/6446805 To facilitate scientific transparency and collegial discourse, we made the full database and statistical code publicly available, though a link in the manuscript. We welcome feedback, including any problems in the statistical code, for incorporation and/or correction in the final manuscript. These issues have been identified for correction in the final manuscript, some of which relate to discrepancies between versions of the R-code application:
Figure 1. “Potentially unreliable data” should be n=288 and “>130 carb intake” will be changed from n=23 instead of n=24.
Table 1. % M/F will be changed from 60/40 to 57/42. Data rows for Current TG and HDLc were reversed and will be corrected.
Table 3. Between group p-value for prior TG/HDLc will be changed from 3.7 x 10-16 to 3.5 x 10-16. Frequency for male in LMHR group will be changed from 56% to 43%.
Supplemental Table 1. Current HDLc p-value will be changed from 4.26 x 10-8 to 4.09 x 10-8. Current TG p-value will be changed from 0.079 to 0.080. Other minor rounding errors will be updated.
Supplemental Figure 1. The 2nd (left to right) lower bar will be changed from 76 to 61 mg/dL.
Supplemental Table 2. AIC for the BMI will be changed from 7227 to 7214. AIC for the prior TG/HDLc + BMI will be changed from 7230 to 7213.
Supplemental Figure 5A should indicate baseline BMI as an effect modifier, not mediator, among other forthcoming clarifications.
Additional clarification: Cardiometabolic risk factors are often considered as those comprising the metabolic syndrome, exclusive of LDLc, such as in this recent CDC study. To avoid unintended interpretations, we will add the word “otherwise” to the abstract conclusion as follows:
These data suggest that, in contrast to the typical pattern of dyslipidemia, greater LDLc elevation on a CRD tends to occur in the context of otherwise low cardiometabolic risk.
BREAKING: Last night I posted a tweet (see below) curious if any data scientists would be interested in querying one of the major longitudinal datasets (such as UK Biobank) on the “Lipid Triad” (high LDL-C + high HDL-C + low triglycerides) vs All Cause Mortality.
To my great surprise, an anonymous donor has come forward who is interested in funding this analysis to publication for $20,000.
If you or anyone you know is a data scientist who would be interested in this endeavor, please reach out to me via twitter (@daveketo) or via comment below.
My primary costs are the many frequent and expensive blood tests I take for this research and data. Any size donation is appreciated. Thank you for your support!
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