Jan 08

Eating Window Experiment – Design and Prediction

Today I started the #EatingWindowExperiment, which is probably just what you thought it was by the title.

Experiment Design

There are two phases:

  1. Eat baseline diet for five days in the usual 10 hour window (9am, 2pm, and 7pm eating times)
  2. Eat the same baseline diet for five days, but compressed into a 4 hour window -> 4pm, 5:30pm, and 7pm 10am, 12pm, and 2pm eating times (*amended here)

Daily blood tests of glucose, ketones (BHB), and lipids (TC, LDL-C (calc), HDL-C, and triglycerides) will be performed at these times:

  • Within 20m of waking up
  • ~7 am
  • ~9 am
  • ~2 pm
  • ~7 pm
  • ~10 pm

Blood tests for mornings of January 13th and 18th

Labcorp:

  • Apolipoprotein A-1
  • Apolipoprotein B
  • C-Reactive Protein
  • Complete Blood Count (CBC)
  • Comprehensive Metabolic Panel (CMP)
  • Cortisol
  • Fatty Acids, Free (NEFA)
  • Ferritin, Serum
  • Fructosamine
  • GGT
  • Glucagon, Plasma
  • GlycA
  • Hemoglobin A1c
  • IGF-1
  • Insulin and C-Peptide
  • Leptin
  • Lipid Panel
  • Lipoprotein(a)
  • Lp-PLA2 Activity
  • Nuclear Magnetic Resonance (NMR)
  • Oxidized Low-density Lipoprotein (OxLDL)
  • Testosterone, Serum
  • Thyroid Panel
  • Uric Acid, Serum
  • Vitamin B12 and Folate
  • Vitamin D, 25-Hydroxy

Boston Heart Diagnostics:

  • Adiponectin
  • Cholesterol Balance
  • Fatty Acid Balance
  • HDL Map
  • Interluekin-6
  • Leptin (Redundant, but of high interest)
  • Oxidized Phospholipids on apoB (OxPL)

Hypothesis

Honestly, I don’t have a lot to add with regard to the hypothesis. This is more of an exploratory experiment.

If I had to pick one thing I’d predict, I’d lean toward there being a higher fasting glucose and insulin level resulting from the bigger meal of the tighter eating window from the night before. However, that doesn’t mean that these two would be higher in the “area under the curve”. But fortunately, we’d have some data to speculate on that given my high frequency testing throughout the day.

Again – this is more of a “let’s see what happens” experiment.

Dec 28

2020 – Year in Review

Whadda year.

Documentary Interrupted

It’s crazy to think we started it off filming #TheCCDoc across 17 countries and 28 cities across the world (Jan/Feb)…and yet…that’s much, much smaller news than what has happened since in 2020.

That said, we have some excellent footage for #TheCCDoc (36 interviews!) and a new plan to wrap in the LMHR study as well when we finally edit it to together. Should make for a pretty interesting doc by the release.

Click here to see #TheCCDoc Playlist on YouTube

Citizen Science Foundation

Speaking of the pandemic, a very key moment happened at the end of April that was a pleasant distraction – we got our designation as a bonafide Public 501(c)(3) charity by the IRS.

And to my great excitement, I got to break the news in October that we passed our $100k fundraising goal which will be matched to get us to that magic $200k number.

Lastly, I posted our update video on progress with our selected center and the fundraising drive of $30k for travel and genetic testing.

My Experiments

During the summer I attempted to conduct a double crossover experiment of Extra Virgin Olive Oil vs Butter.

… and by “attempted”, I mean I tried and failed — twice!

I rarely cancel experiments, but this was one of only two that I can recall.

However, @ketochow offered to take up the reins of my experiment and it’s yielding some surprising data. So much so, that we’re doing a short replication experiment in addition to this one. (more on both in the coming writeup)

https://twitter.com/DaveKeto/status/1313643723134124032?s=20

My favorite experiment of the year is — hands down — my #OxLDL replication experiment. This is for many different reasons from the replication marker matching, to the OxPL-ApoB and HDL map assays.

So much excellent data.

Siobhan’s Experiments

Meanwhile, my colleague, Siobhan took on the remarkable #EpicFast experiment. I can barely last 2.5 days. And yet her fast lasted weeks. And of course, she extensive blood testing throughout.

Here data is in and the write up will be coming soon as bandwidth becomes available.

Own Your Labs

One reason for tighter bandwidth on both our parts has been the launch of OwnYourLabs.com. We’ve set up an online service where you can order your labs privately directly through us. This has been primarily for service through Labcorp, although we are now testing in beta under Boston Heart Diagnostics as well.

Our primary reason for starting this service was to provide an easy means of volunteering anonymized data to an open data pool. This is strictly opt-in at checkout, but we give a discount where taken.

We exclude first and last name, date of birth, and city to help de-identify. But ask to add some basic demographic information to match with the resulting bloodwork which we are confident will provide great new insights for both formal and citizen scientists alike. We’ll be posting this dataset soon as we’re accumulating enough in the first tranche to better anonymize further.

Moreover, all proceeds go to the Citizen Science Foundation. So it’s win-win-win.

Journal of Clinical Lipidology

Easily one of the most interesting events of the year was our being mentioned in a case series by the Journal of Clinical Lipidology. The “Cholesterol Code Team” was referenced directly in the paper which certainly caught our interest.

This led to an opportunity to both respond and source where we were coming from in a Letter to the Editor which we submitted promptly. Our letter was rejected, but we have it now posted as an open letter which you can find here.

While we know this a controversial topic, we understand it may take some time to bring this important context into the spotlight. We’re confident cholesterol and risk as it relates to metabolism (particularly in a low carb setting) will rise in prominence. We’ll get there.

Presentation to Stanford University

There are many conferences I presented at online this year. But while I don’t want to pick favorites, I was especially honored to present the Lipid Energy Model to Stanford University.

Final Thoughts on 2020

Certainly the Pandemic has impacted us in many ways this year. It interrupted TheCCDoc shooting, delayed the LMHR study development, and added a lot more chaos and uncertainty to our various services and projects.

However, I personally know so many others who have had a much more difficult year. I know many who have gotten very sick, lost their jobs, seen their businesses go under, and/or entirely altered their lives in order to adapt to this “new normal”.

And while I’ve tried to stay away from discussing #Covid19, particularly since it’s gotten so politicized — I have to again express just how thankful I am for all the medical professionals on the frontline of this event.

So yes, we’re counting our blessings, as they say. We managed to secure a lot of victories under very tough and uncertain circumstances.
And as always, much of that thanks goes directly to individual one time contributions and our members / patrons!

Lastly, I hope to be announcing some news very soon into 2021 on the LMHR study. It’s hard to imagine anything will be bigger to us in this coming year… but as with 2020, that’s certainly not a given.

Cheers!

Dec 18

CSF: Powering Milestone and $30,000 from Goal for Travel and Genetic Testing

We’ve reached a key milestone in having our study now being powered as the last step before submission to the IRB. We have $60,000 yet to raise, but we have an anonymous donor matching $30,000 — thus, we need only raise another $30,000 to meet our goal for travel and genetic testing.

For more details see our post from Citizen Science Foundation website here

Click here to Contribute

Nov 24

Open Letter to the Editor – Journal of Clinical Lipidology

On October 30th, the Journal of Clinical Lipidology published Ketogenic diets, not for everyone. It details five cases where lipid levels were substantially altered after patients adopted a low carb diet. Moreover, the case series specifically identifies us, “The Cholesterol Code Team” and points to examples of statements we have on the website.

In contrast, within a general population, there is no shortage of information available on the internet for the public. The Cholesterol Code Team, led by a software engineer and entrepreneur, created a Facebook group for ‘lean mass hyper-responders.’16 The Cholesterol Code Team defines hyper-responders as those “who have a very dramatic increase in their cholesterol after adopting a low-carb diet.”35 Furthermore, “the increase can be anywhere from 50% to 100% or more of original, prediet cholesterol numbers.”35 The Cholesterol Code Team claims ‘we do not know’ whether having high LDL-C on a low-carbohydrate diet is dangerous; it further presents a number of ‘good reasons’ why LDL-C could be so high.35 These include that the “body is transporting more fat for energy to cells due to being on a high-fat diet.”35 Given the weight such statements could have on a significant number of individuals seeking guidance on the internet, it is important to identify and advise patients with similar presentations.

Let me first say that I am and continue to be optimistic for a productive dialog on this crucial subject. Throughout the last five years I’ve sought to share our research and data with the National Lipid Association in particular. I’ve reached out to several prominent leaders both via email and social media. Siobhan and I have attended NLA conferences and took the opportunity to network further.

Their reluctance is understandable given the internet provides a great deal of demonstrably bad information. With that said, this case series seemed an especially appropriate moment to establish our nuanced position and likewise emphasize the research and data informing us. Thus, we drafted a Letter to the Editor within their requirements (450 words) and submitted it.

The editor objected to the phrasing in the second paragraph and whether it could relate back to two of the citations in that context (I can’t speak more to that as this was a private exchange, but I think Siobhan and I felt it was a fair point and were grateful for the feedback). So we sent back an edit to that paragraph that we felt accomplished this and even further emphasized the uncertainty (see final edit below). But we were told the letter remains rejected.

Thus, I’m going to provide this as an Open Letter to the Editor.

Re: Ketogenic diets, not for everyone

To the Editor,

In “Ketogenic diets, not for everyone”, Ira J. Goldberg, et al describes several cases of hypercholesterolemia developing after adopting a low carb, high fat diet. This phenomenon of “hyper-responders” is of interest given its apparent frequency within the low carb community, although studies documenting this occurrence have had varying levels of consistency.[1][2][3][4]

Regardless of which diet is adopted, we agree hypertriglyceridemia is of concern as was detailed in the first case. However, there are many low carb dieters who observe a “triad” of higher LDL-C, high HDL-C and low triglycerides, such as many in the “Lean Mass Hyper-responder” (LMHR) Facebook group discussed. There are studies on non-FH populations that stratify for this triad and find a low association with heart disease. While these studies show lower LDL-C as a marginal improvement, both variations alongside high HDL-C and low triglycerides associate with lower risk.[5][6] However, it should be emphasized we’ve found no studies looking at this triad in cases where LDL-C reaches levels described in the case series.

The paper quotes from our FAQ page, where we state higher LDL-C resulting from a low carb lifestyle may reflect the body “transporting more fat for energy to cells due to being on a high-fat diet.”[7] More specifically, we propose higher LDL-C in this context could be a result of greater synthesis, secretion, and turnover of triglyceride-rich VLDL particles.

To be sure, this “Lipid Energy Model” is a hypothesis, which we emphasize in the same paragraph, and we hope to have a paper out soon discussing it in detail. But there are existing studies that provide evidence to support this perspective. Long-term fasting results in fat adaptation[8], and in healthy lean humans this presents with a rise in serum ketone and cholesterol levels.[9][10][11] Similarly, research on hibernating animals, both in laboratory settings and in the wild, has documented the presence of hypercholesterolemia.[12][13][14][15] Other studies suggest greater reliance on VLDL trafficking during fasted distance traveling in migratory birds.[16][17]

It’s worth emphasizing we frequently state our “cautious optimism” regarding this triad, given existing data mentioned above, but that it is by no means definitive and that further study is crucial. Moreover, we regularly provide information regarding dietary methods of lowering total and LDL cholesterol in a low carb context.

As a number of LMHRs refuse both pharmacological and dietary lipid lowering interventions, interest in studying this profile is substantial. Given these concerns, we’ve successfully crowd-funded a study in partnership with a major research center and will be submitting for IRB approval shortly. Several tests, such as Computed Tomography Angiogram (CTA) will be used to determine the development of atherosclerosis in individuals at both baseline and follow up after one year. We hope this new data will help advance our understanding of risk for this novel phenotype.

[1] Creighton, B.C., Hyde, P.N., Maresh, C.M., Kraemer, W.J., Phinney, S.D., Volek, J.S., 2018. Paradox of hypercholesterolaemia in highly trained, keto-adapted athletes. BMJ Open Sport & Exercise Medicine 4, e000429. https://doi.org/10.1136/bmjsem-2018-000429

[2] Bhanpuri, N.H., Hallberg, S.J., Williams, P.T., McKenzie, A.L., Ballard, K.D., Campbell, W.W., McCarter, J.P., Phinney, S.D., Volek, J.S., 2018. Cardiovascular disease risk factor responses to a type 2 diabetes care model including nutritional ketosis induced by sustained carbohydrate restriction at 1 year: an open label, non-randomized, controlled study. Cardiovascular Diabetology 17, 56. https://doi.org/10.1186/s12933-018-0698-8

[3] Dashti, H.M., Al-Zaid, N.S., Mathew, T.C., Al-Mousawi, M., Talib, H., Asfar, S.K., Behbahani, A.I., 2006. Long term effects of ketogenic diet in obese subjects with high cholesterol level. Mol Cell Biochem 286, 1–9. https://doi.org/10.1007/s11010-005-9001-x

[4] Yancy, W.S., Olsen, M.K., Guyton, J.R., Bakst, R.P., Westman, E.C., 2004. A low-carbohydrate, ketogenic diet versus a low-fat diet to treat obesity and hyperlipidemia: a randomized, controlled trial. Ann Intern Med 140, 769–777. https://doi.org/10.7326/0003-4819-140-10-200405180-00006

[5] Bartlett Jacquelaine, Predazzi Irene M., Williams Scott M., Bush William S., Kim Yeunjung, Havas Stephen, Toth Peter P., Fazio Sergio, Miller Michael, 2016. Is Isolated Low High-Density Lipoprotein Cholesterol a Cardiovascular Disease Risk Factor? Circulation: Cardiovascular Quality and Outcomes 9, 206–212. https://doi.org/10.1161/CIRCOUTCOMES.115.002436

[6] Jeppesen, J., Hein, H.O., Suadicani, P., Gyntelberg, F., 2001. Low triglycerides-high high-density lipoprotein cholesterol and risk of ischemic heart disease. Arch Intern Med 161, 361–366. https://doi.org/10.1001/archinte.161.3.361

[7] Hyper-Responder FAQ, 2016. CholesterolCode. URL https://cholesterolcode.com/hyper-responder-faq/ (accessed 11.5.20).

[8] Carlson, M.G., Snead, W.L., Campbell, P.J., 1994. Fuel and energy metabolism in fasting humans. Am J Clin Nutr 60, 29–36.

https://doi.org/10.1093/ajcn/60.1.29

[9] Sävendahl, L., Underwood, L.E., 1999. Fasting increases serum total cholesterol, LDL cholesterol and apolipoprotein B in healthy, nonobese humans. J Nutr 129, 2005–2008. https://doi.org/10.1093/jn/129.11.2005

[10] Kartin, B.L., Man, E.B., Winkler, A.W., Peters, J.P., 1944. BLOOD KETONES AND SERUM LIPIDS IN STARVATION AND WATER DEPRIVATION. J Clin Invest 23, 824–835. https://doi.org/10.1172/JCI101556

[11] Browning, J.D., Horton, J.D., 2010. Fasting reduces plasma proprotein convertase, subtilisin/kexin type 9 and cholesterol biosynthesis in humans. J Lipid Res 51, 3359–3363. https://doi.org/10.1194/jlr.P009860

[12] Arinell, K., Sahdo, B., Evans, A.L., Arnemo, J.M., Baandrup, U., Fröbert, O., 2012. Brown bears (Ursus arctos) seem resistant to atherosclerosis despite highly elevated plasma lipids during hibernation and active state. Clin Transl Sci 5, 269–272. https://doi.org/10.1111/j.1752-8062.2011.00370.x

[13] Kolomiytseva, I.K., 2011. Lipids in mammalian hibernation and artificial hypobiosis. Biochemistry (Mosc) 76, 1291–1299. https://doi.org/10.1134/S0006297911120029

[14] Chauhan, V., Sheikh, A., Chauhan, A., Tsiouris, J., Malik, M., Vaughan, M., 2002. Changes during hibernation in different phospholipid and free and esterified cholesterol serum levels in black bears. Biochimie 84, 1031–1034. https://doi.org/10.1016/s0300-9084(02)00006-8

[15] Russom, J.M., Guba, G.R., Sanchez, D., Tam, C.F., Lopez, G.A., Garcia, R.E., 1992. Plasma lipoprotein cholesterol concentrations in the golden-mantled ground squirrel (Spermophilus lateralis): a comparison between pre-hibernators and hibernators. Comp Biochem Physiol B 102, 573–578. https://doi.org/10.1016/0305-0491(92)90049-w

[16] Jenni-Eiermann, S., Jenni, L., 1992. High Plasma Triglyceride Levels in Small Birds during Migratory Flight: A New Pathway for Fuel Supply during Endurance Locomotion at Very High Mass-Specific Metabolic Rates? Physiological Zoology 65, 112–123. https://doi.org/10.1086/physzool.65.1.30158242

[17] M, R., R, S., Mr, G., 1999. Seasonal and diel transitions in physiology and behavior in the migratory dark-eyed junco. Comp Biochem Physiol A Mol Integr Physiol 122, 385–397. https://doi.org/10.1016/s1095-6433(99)00013-6

Oct 27

The OxLDL Replication Experiment – Findings – Part I

This experiment was conducted from August 30th to September 14th over three five day phases: a maintenance (weight stable calorie), hypocaloric (low calorie), and hypercaloric (high calorie).

See OxLDL Replication Experiment Design post for further information on setup.

Again, this experiment was executed with the intent replicate the prior OxLDL experiment in April of last year. As such, we have excellent comparison data as well.

But of special interest is the “OxPL-apoB” assay offered through Boston Heart Diagnostics. It was a key consideration given my interest in this metric long before it was even commercially available. (More on this in the next post)

General Observations

Overall, the experiment went very well. I was able to keep eating very close to schedule and exercise roughly equivalent as intended.

I did experience some calf and foot cramping in the late evenings and early mornings characteristic of electrolyte depletion. This took place two days into the Hypocaloric Phase and I responded by adding additional electrolyte supplements along with added salt dissolved in water (food log coming soon). These issues persisted until three days into the Hypercaloric Phase.

And sure enough, the bloodwork coming back after the experiment for both the hypo and hypercaloric phases showed below reference range for both Sodium and Chloride (see data).

Daily Metrics

Each morning within 20 minutes of having woken up I would test: Glucose (Keto Mojo), beta hydroxybutyrate [BHB -> ketones] (Keto Mojo), lipid panel of total/LDL/HDL/triglycerides (CardioChek), and body weight. A few days in I added Acetone (Biosense).

Note in all the graphs below that “v1” refers the first OxLDL experiment and “v2” refers to the replication experiment just completed.

Body weight will be very unsurprising, of course. In each experiment it generally maintained during baseline, dropped in hypocaloric, increased in hypercaloric.

Same with glucose…

LDL cholesterol levels were generally noisy, but did follow the inversion pattern overall, going higher in hypocaloric, lower in hypercaloric.

Now here is where it gets interesting. It’s entirely expected that ketones overall would rise as I went hypocaloric and would fall as I went hypercaloric. But note the largest spike wasn’t after the last full day of the low calorie phase — it was after the first full day of high calorie phase. (Remember these tests are taken the morning of the day listed)

We see this exact same surplus also reflected triglycerides. In fact, this is the most substantial change in all the data collected, and is demonstrated in both experiments, of course.

Lastly, I want to point out this becomes the corresponding nadir for HDL cholesterol.

These last three — BHB, triglycerides, and HDL cholesterol are extremely central to the Lipid Energy Model. In fact, if we didn’t see these change for our controlled setting (thus, removing competing confounders), this it would have provided strong evidence against it.

The important takeaway beyond the general phase-specific patterns is that brief period where we can actually observe what appears to be the “traffic jam” of fuel transport (as reflected in BHB/TG) and turnover (as potentially reflected in HDL-C). Moreover, we have a spike of fat-based energy sources coming in from Chylomicrons that I believe will directly compete with VLDL binding/uptake.

In our coming Lipid Energy Model paper, we will have more supporting studies in particular that are relevant to the triglyceride and HDL-C relationship as it pertains to VLDL triglyceride turnover, but I won’t be going into that here.

End of Phase Bloodwork

After completing each five day day phase I had blood taken that went to two labs, Labcorp and Boston Heart Diagnostics. Siobhan and I already have lots of experience working with Labcorp for the last several years and it’s our primary provider for OwnYourLabs.com. Boston Heart is new for us, but it has definitely been a very positive experience thus far – both in testing and customer service.

I’ve combined the calorie and diet macros, the Labcorp tests from both experiments, and the Boston Heart Diagnostic tests for this experiment into one spreadsheet which you can download here:

Raw Data for Labs (version 0.7)

PLEASE NOTE: As of this writing, the raw data spreadsheet isn’t fully cleaned up with regard to reference range artifacts, etc. We hope to have that done in another pass soon and will update this page (and its version) accordingly.

Not surprisingly, we see many other blood markers in support of the energy model here:

Up Next – Digging Deeper into the Bloodwork

This post was primarily focused on reporting the data coming back and how it related to the Lipid Energy Model.

Next week we’ll dive into the many, many other amazing aspects of this robust dataset and what it can tell us about these markers.