The Fasted 50K and Heavy Cream Cholesterol Experiment - Preview

 

The purpose of this piece is to preview a bit of an experiment I’m intending to perform in the near future. I’m calling it the “50k and Heavy Cream Cholesterol Experiment” because, well…I’m going to run 50 kilometers and drink a lot of heavy cream and sample lipid levels a number of times. Read on for details, reasoning, and predictions.

The Plan

The plan, broadly speaking, is to asses the effects of both an excessive dose of running and excessive saturated fat consumption on my lipid levels (LDL-C, HDL-C, triglycerides). These two interventions won’t be concurrent, but stacked immediately on top of one another over the course of a handful of days. Ideally, the plan is to begin this next Monday, January 20^th. I say ideally because a major factor in the timing is finding a day when I’m healthy enough to even run the 50k. As I’ve described recently, I still commonly miss days of exercise (and work) due to neurological complications. And of the days I’m healthy enough to get out the door to run, on exceedingly few could I reasonably hope to run a reliably strong 50k. This makes finding a good opportunity to carry out this experiment in the course of normal day to day life difficult at best. But as luck would have it, I’m on vacation this week and have a reasonable expectation of feeling pretty good when I return.

So, fly home on Sunday the 19^th and run the 50k on the 20^th. Beginning that evening and continuing for 3 full days after, I will consume a purely carnivore diet with as much saturated fat and dietary cholesterol as I can tolerate. The aim will be to consume several thousand calories per day above baseline, but exact numbers will depend on how exactly it feels to so greatly overindulge multiple days in a row (Despite the name I used in the title, I will not be consuming only heavy cream. Massive quantities of it, yes, but also meat, cheese, and butter). Baseline diet, for the record, is an animal-based ketogenic diet averaging about 80% calories from fat and fewer than 10g of carbohydrate per day.

The planned schedule is as follows:

Monday AM: Lipid Panel #1/Baseline

Monday AM: 50 kilometer run

Monday PM: Lipid Panel #2

Monday PM – Thursday PM: Heavy saturated fat consumption

Tuesday AM: Lipid Panel #3

Tuesday PM: Lipid Panel #4 (non-fasted)

Wednesday AM: Lipid Panel #5

Thursday AM: Lipid Panel #6

Friday AM: Lipid Panel #7/Final

 

What I’m Hoping to Measure

As you almost certainly know, the traditional paradigms surrounding diet and cholesterol suggest that consuming too much saturated fat and dietary cholesterol drives an increase in serum LDL cholesterol levels (in turn considered to be the prime driver of atherosclerotic cardiovascular disease). I, however, object to that paradigm, believing instead that the greatest factor influencing LDL-C levels is the body’s reliance on lipoproteins as an important delivery system.

Probably the most important cargo that lipoproteins carry are triglycerides, to be either stored as body fat or used as an energy source by the body. Which brings me to an important caveat that I’ve yet to mention – the 50 kilometer run will be carried out entirely in the fasted state. I will be consuming exactly zero calories before or during the run, not eating anything on the day until after my post-run blood draw.

This is a fairly extreme measure of course. Exceedingly few people ever run that far in a fasted state, and ever fewer (possibly zero?) have ever measured the effect of that effort on lipid levels. The American Heart Association and others suggest that saturated fat consumption is the greatest factor in raising cholesterol levels, with a lack of exercise a strong contender for number two. Conventual wisdom also tends to suggest that LDL-C levels don’t change rapidly, but instead over weeks or even months. It would stand to reason, then, that LDL-C should probably be largely unchanged between my first and second blood draws. Perhaps they might even tick down a fraction, as the intervening hours between the first and second blood draws will maximize typical guidelines for lowering cholesterol (plenty of exercise, zero fat consumption). If instead LDL-C increased during the run, it might require an update, or at least a caveat attached, to the typical paradigm.

Lets skip now to the final blood draw. This is, clearly, the extreme opposite end of the spectrum with respect to traditional cholesterol risk factors. I won’t exercise the three days between the 50k and the final blood draw, but I will eat so, so much saturated fat. And its flipping so aggressively from one extreme to the other that makes this fun. Again, a traditional medical mindset would suggest that LDL-C should clearly increase throughout the week as I binge saturated fat and dietary cholesterol. It may not increase a lot, as its only for a few days, but one would certainly expect it to start trending up in the face of such prodigious fat consumption (Just for fun – the AHA recommends capping saturated fat intake at ~13 grams per day. I intend to consume 25-30 times more than that each day. Essentially a month’s “worth” of saturated fat per day). So again, if the so-called expected outcome is not observed, it may suggest a shortcoming of the current conventional wisdom.

I’ll further expand on the day 2 blood draws momentarily, but the intervening lipid panels are largely to track trends throughout the week. I intended to skip the middle three blood draws at first, as its really the first and last days that will capture the full effect, but decided it would be more interesting to have a more complete dataset.

 

Predictions

Baseline/LP1 – I will have, by conventional standards, elevated LDL-C at baseline. I don’t know how elevated necessarily, but certainly it will be a number that would concern your average physician. On the contrary, I expect reasonably high HDL-C and low triglycerides that would be quite good by conventional standards. All of these values derive from the fact that I am a metabolically healthy individual consuming an exceedingly low-carbohydrate diet and thus relying on fatty acids for energy.  

LP2 – I expect LDL-C to rise fairly noticeably during the course of the fasted 50 kilometer run. Reliance on stored body fat for energy (or really, the hormonal effects of fasted exercise) will drive a significant increase in the breakdown of stored body fat, which should be largely trafficked through the liver and packaged in VLDL particles. The triglycerides in these VLDL particles will be taken up extremely rapidly by working muscles, causing the VLDL to convert to longer-lived LDL particles. This continuous effect will cause there to be an acute increase in cholesterol containing LDL particles, and thus an increase in measured LDL-C. In addition, I expect measured triglycerides to be extremely low for the same reason (most likely below my “personal best” of 66 mg/dl) as my working muscles rapidly take them up for energy.

Final/LP7 – The expectation here is that this result will also defy conventional wisdom. Not only will the extreme consumption of fatty animal products fail to raise my LDL-C, it will acutely lower levels to below baseline. Rather than relying heavily on stored body fat for energy, I’ll be doing the exact opposite. I’ll be creating a hormonal environment that more heavily emphasizes the storage of fat rather than its breakdown, thereby reducing the production of VLDL particles that would typically move my stored triglycerides around my body. Fewer VLDL particles means fewer LDL particles and thus lower LDL-C. Its worth noting, however, that this effect won’t be as great as it could be due to the compressed timeframe of this experiment. The average lifespan on an LDL particle is in the three and a half day range, and three and a half days before my final blood draw I’ll be producing huge number of VLDL/LDL particles during and immediately after my fasted run. A couple more days of binging would ensure these excess particles would be completely recycled, but frankly I don’t want to do this for that long, so…

Day 2/LP3 – Saving the best for last. This is, to me, the real meat of my experiment. I have strong preconceived assumptions about how the fasted exercise and the fat binge will effect lipids, but the blood draw on Tuesday morning is for me the one that ventures into the great unknown. And frankly, in a lot of ways, it ventures into the collective scientific unknown, as I don’t think anybody has ever documented the effects of such an extreme scenario on lipid levels.

Let’s first asses what this blood draw might look like if we only consider the energy deliver nature of lipids. Remember again that LDL particles have a typical lifespan of 3+ days. This blood draw, maybe 17 hours after the second, will represent only ~20 percent of the lifespan of a typical LDL particle. And while the massive effort between the first two blood draws should generate a significant acute increase in LDL particles, nothing about the rest and recovery after lipid panel 2 should differ greatly from what I’d be doing three to four days earlier. That is to say, there shouldn’t be much reason for the number of particles produced to differ greatly from the number being recycled. It may even be the case that energy demand remains so high in the immediate aftermath of the run and the second blood draw that LDL-C could fractionally increase if I don’t eat enough or quickly enough to fully blunt that effect. So, from a purely energy driven perspective, LDL-C levels at or just above those in lipid panel 2 might be reasonably expected (with triglycerides returning closer to baseline as well).

But…what if energy (and cholesterol) weren’t the only important components being trafficked by lipoproteins? What if another effect were present that could also drive a noticeable change in LDL-C levels? This, essentially, is what I’m hoping to test.

It may be that a very important and underappreciated element that LDL particles transport…is just themselves. After all, lipoproteins are made largely of the same phospholipids that comprise cell membranes throughout the human body. And it could very well be the case that an acute insult to enough of those cell membranes – for example, the damage caused by running 50 kilometers – could cause many LDL particles to be taken up by the cells as raw materials for the repair of these damaged membranes (and/or the creation of new ones).

If this were the case, a reasonable proportion of the existing LDL particles in circulation might leave the bloodstream earlier than expected, thus decreasing LDL-C from the energy driven expectation outlined just above.

To be clear, I don’t have a reasonable guess for what my LDL-C will look like on Tuesday morning. Something wildly different than expected on the post-run or post-binge panels would require some reevaluation of the energy delivery paradigm. However, I’m not making any particular prediction for this lipid panel. I do strongly believe, however, that a decrease in LDL-C from lipid panel 2 to panel 3 would be indicative only of this proposed effect – the endocytosis of LDL particles for the repair of cellular damage. And I think demonstrating this effect would, in theory, go a long ways towards further understanding a transport model of lipoprotein function and even the underlying causes of atherosclerotic cardiovascular disease. If that decrease is in fact observed, I’ll of course have plenty to say about it after the fact.

Summary

So, there you have, in two thousand words – a weeklong experiment to test the extremes of lipid mechanics and assess the ways in which a lipid transport system may best explain lipid behavior. To the best of my knowledge, this is a novel demonstration, at least at this extreme. Studies have demonstrated that a great energy deficit raises LDL-C, and numerous individuals (myself included) have lowered LDL-C while binging on fat. But the extreme, hyper-condensed nature of this N=1 experiment is, I think, without parallel. In particular, the second day’s blood draw, on the back of a such a significant physiological event, has the potential to demonstrate a possible underappreciated characteristic of lipid behavior in the human body. Whether this ultimately demonstrates something significantly novel, or only highlights the importance of lipids in energy deliver, or goes up in flames entirely, remains to be seen. But, regardless, results and summaries should come soon after. To be continued.

2024 In Review Part 3 - Impaired Brain Metabolism and How to Deal with It

 

Part 1 Here, Part 2 Here

As I outlined in the previous section, the major long-term issue I’m dealing with at this point is widespread impaired brain metabolism - Most areas of my brain are deficient in their capacity to produce energy through traditional means. What I’m going to do here is expand a bit on what that means and how that works.

In a standard, simplified framework the brain is considered to run entirely or nearly entirely on glucose. This makes the cells of your brain and nervous system distinct from nearly every other cell in your body, which can seamlessly blend glucose and fatty acids as fuel sources in various proportions. Your muscle cells, for example, can freely convert fatty acids to energy through a process called beta-oxidation, essentially the “burning” of pure fatty acids.

But beta-oxidation doesn’t occur in the brain or nervous system. Thus, the typical understanding (which is indeed true in a general sense) is that the brain must use glucose for its required energy production. What happens in a range of neurodegenerative and other neurological conditions, however, is that your brain simply doesn’t take up and utilize glucose to a degree sufficient to meet energy demands. I would contend that the reason this usually happens, typically in an aging, metabolically unhealthy population, is related to chronic hyperglycemia, hyperinsulinemia, and insulin resistance. The same insulin resistance and chronically elevated insulin that characterize diabetes and other chronic metabolic conditions manifest in the brain as well (you may have heard Alzheimer’s referred to as “type 3 diabetes” at some point) and usher in a gradual, years-long degradation of metabolic function.

That situation, obviously, does not apply to me. My metabolic health is fantastic, and there was no gradual onset over the course of years or decades. My onset was acute, the result of whatever exact autoimmune reaction was triggered in response to the Pfizer Covid-19 vaccine. While my onset was clearly sudden, its hard to establish exactly how sudden. It may have been nearly instantaneous with the initial autoimmune manifestation, or it may have been exacerbated over months of severe autoimmune symptoms. Regardless, it was not the typical insidious onset you’d see in chronic neurodegenerative disease.

PET Scan Results

So what does my testing show? Unfortunately, there aren’t a ton of clues. The way a PET scan works is by essentially administering an IV of radioactive glucose and observing the reactive signature “light up” as those radioactive molecules are utilized in the brain. The more glucose each part of the brain uses, the brighter and redder that area will show up on a scan. A localized red spot, for example, might indicate a tumor greedily gobbling up glucose at an increased rate. Conversely, areas that take up less glucose than you might expect are a blue-green color. This is what you might see a dementia patient slowly losing functional capacity as their ability to convert glucose to energy wanes.

My brain had a lot of blue and green areas, indicating widespread failure to take up and/or utilize glucose at a level consistent with my brain’s energy needs. But there isn’t much more to it than that. The PET scan doesn’t tell us exactly what is damaged, or how and why that damage prevents proper function (although I do have ideas). I also don’t have a neat and tidy number attached to the result - There’s no highly quantitative assessment that lets me tell you how deficient my brain function is. I also don’t know anything about the rest of my nervous system, which may very well be suffering from the same defects. The only thing I really know for sure is that my brain doesn’t produce energy properly and that attempts to force it to through basically any level of mental effort result in a range of neurological complications as it ultimately fails to meet the demand, instead propagating whatever inflammatory damage drives symptoms for hours, days, or even weeks after the effort.

Dietary Approach to Impaired Brain Metabolism

 

Thankfully, the other thing I know for sure is how best to handle this situation to hold myself together as well as I’m able. That notion that your brain only uses glucose for energy? That’s highly simplified, and alternative sources can be leveraged to provide various degrees of relief. Unfortunately, this is a topic on which most physicians appear to have stunningly little education or understanding, which has led to more than a couple dead-end conversations with neurologists who frankly have no understanding of brain metabolism (more on that at a later date, but it includes one doctor trying to tell me that because she didn’t know what they meant, that the test results may be unrelated to my symptoms and that I was probably just depressed. She then tried to prove her point by googling impaired brain metabolism and showing me the first result…which listed only epilepsy, Parkinson’s, and Alzheimer’s as typical manifestations of such brain dysfunction).

I’m going to try to keep it pretty basic, but I do want to at least touch on the three main alternative sources your brain can use to produce energy – alcohol, lactate, and ketones. There’s also a fourth “alternative” – the increased consumption and utilization of glucose itself that occurs in response to exercise.

I mentioned previously that alcohol consumption was fairly pivotal in cementing my understanding of my current situation. The fact that alcohol very clearly improves my symptoms and aids recovery from acute severe episodes drastically limits the number of problems I could be dealing with. But alcohol is an easily available source of brain energy, and in fact its one that healthy people prioritize to a degree when they consume it. This isn’t really for “good” reasons – alcohol can’t be stored in the body and is acutely toxic, so your body will make efforts to use it as an energy source in order to clear it from the bloodstream. In a healthy person, this manifests in part as a downregulation of glucose consumption in the brain and a partial replacement of that energy flow with alcohol instead. For me, glucose consumption is chronically decreased anyway, so alcohol just serves to fill in the gap and make me “whole” for a certain period of time.

As I discussed previously, I was strategically using alcohol this year more often than I would have liked from an overall health perspective. I wasn’t drinking for or to any real level of intoxication, just consuming a deliberately gentle flow of a few drinks maybe two to three times a week. It was, very literally, strategic, and often necessary to keep myself semi-functional for another day. This is something I’ve felt the need to do far less frequently in a ketogenic state.

The next alternative fuel source is lactate, which is tough to separate from the increase in glucose utilization during exercise, so we’ll discuss them together. Lactate (or the very closely related lactic acid) is often viewed somewhat negatively or as a “waste” product because it increases in the bloodstream during strenuous exercise. However, in reality its just a byproduct of typical metabolism and only increases in the blood when the ability to clear it can’t match production. Its production increases even at lower levels of exercise intensity, and one of the manors by which it can be cleared is to be taken up by cells (including those in the brain) and converted to pyruvate for direct energy production. Thus, the increase in lactate metabolism during exercise provides an additional partial source of brain energy.

The degree to which that helps me is unclear, however, because it generally happens in concert with increased glucose uptake. A variety of glucose transporters become more active and efficient during exercise (for good reason – to readily provide you with fuel). Its extremely apparent that this effect still occurs for me as well, despite the general impairment of glucose utilization. Its really quite a weird phenomenon – If I’m just barely well enough to get out the door to exercise, I can begin a slow walk/jog/hike and eventually my neurological health will improve. How long that takes seems to depend on how poor I feel – at functional baseline, its 15-20 minutes before function and feeling both start improving. When I’m worse, it can take closer to an hour – and when I’m in that poor of a state, I can continue to noticeably improve for hours if I continue to exercise. To that end, some of my best stretches of health have actually occurred as a result of hiking trips in the mountains. Not only do I completely avoid cognitive strain, but several hours a day (plus some lasting effect after the fact) of increased glucose and lactate metabolism provides sufficient energy availability for basically an entire day.

Now the most important one, in my opinion – ketones. In a low-carbohydrate, low-insulin environment your liver converts some fatty acids to ketone bodies, which can serve various functions including as a fuel source. Ketones are functionally unique from their parent fatty acids in a number of ways, but the most important for the purpose of this discussion is their ability to be directly taken up by the brain and nervous system as an energy source. Thus, a person in a consistent low-carb/low-insulin state can expect to have access to a consistent stream of ketones for energy.

This consistency is a major differentiating factor when compared to other alternatives like alcohol, carbohydrate binges, or exercise. Alcohol and massive carb spikes are of course temporary, acutely unhealthy manners by which a person can increase energy availability. And despite my desire to run and hike all day, exercise is ultimately temporary as well. Ketones, however, are not. Ketones are forever. Provided, that is, that you maintain an environment conducive to their production.

An important note on ketones is that their contribution to the brain’s energy requirements is not demand-driven, but supply-driven – the uptake and utilization of ketones is proportional to their concentration in the bloodstream. Thus, a “standard” ketogenic diet that you or a family member or a friend have probably tried won’t actually help me all that much. The traditional advice to remain under 20 grams of carbs per day will typically only elicit low levels of ketone production, and thus low levels of ketone-based energy. This is basically irrelevant for a person who only endeavors to manage blood sugar and curb sugar cravings, but makes a great deal of difference for me.

Not only is my focus on limiting carbohydrates to something like 5 grams per day, but I also moderate protein intake (as it has a mild insulinogenic effect) and maximize the fat percentage of my diet. This “therapeutic” ketogenic approach focuses on maximizing the concentration of ketones in the bloodstream, and thus the degree to which ketones can provide relief in the face of impaired glucose metabolism.

Unfortunately, the ketone levels I’ve found are necessary to truly prevent the onset of symptoms haven’t really been obtainable in the context of “normal” food consumption. For me, for now, it seems only extended fasting or a heavily fat/oil-based diet that even further minimizes protein and incidental carbs can raise my ketones to the levels necessary to approach true non-symptomatic function (For context – a person on a standard mixed diet usually has ketone levels of 0-0.1mmol/L, a “standard” keto dieter might hang out at 0.5, I bounce around between about 1 and 3, and need something more like 3.5-4+ to ward off symptom onset).

There are other methods of temporarily elevating ketones above my standard baseline. One is exogenous ketones, suddenly widely available in the last couple years. These work great, raising ketone levels by 1-2mmol/L for a couple hours. However, they are quite expensive and only temporary. That said, I do keep them on hand and use them sometimes to escape potentially calamitous situations. Another shortcut, so to speak, is to drink MCT oil. Medium chain triglycerides are essentially too short to be efficiently burned or stored the way longer chain fatty acids would be. Instead, they are preferentially converted to ketones, even if the person drinking them isn’t consuming a ketogenic diet. This is less effective than exogenous ketones, in additional to being kind of tedious and slightly gross. But its very cheap when purchased in bulk, so I do consume several servings a day at strategic times (ie. During work) in an effort to support ketone levels and minimize symptom onset.

Conclusion 

So that’s basically it. My brain doesn’t properly produce energy through traditional means. If I don’t diligently care for the situation, it quickly becomes dire and I’m relatively easily knocked on my ass by simple mental and cognitive tasks. I am, at baseline, still made bedridden by the job I’m trying to work every day. The reason I make it to work more days than not, the reason I can mostly hide my symptoms while I’m there, and the reason I’m able to even go for a brisk walk (let along run multiple hours at a time), is because I approach each day in a deliberate, evidence-based fashion that leaves little wiggle room if I hope to remain functional. The combination of a therapeutic ketogenic diet, ketone-raising supplements, and as much exercise as I can manage keep my brain functioning far above where it otherwise would be. At all hours of the day, I am, often through multiple avenues, closing the substantial gap between the energy demand of my brain and nervous system and the critical shortage of supply that otherwise exists.

The hope in 2025 is not that I will magically get better, because I think at this point it would be naïve to assume that’ll ever happen at all, let alone soon. The hope is simply that I can manage things at a high enough level so as to continue showing up to work while cobbling together enough exercise that I feel like I can, indeed, exercise. The hope is to string together days and weeks away from work that allow for real adventure, be it running or otherwise. And the hope is, at least temporarily, to be fit and healthy enough to accomplish something cool by the end of the year, whatever that may be – and to prove that my life can be completely ripped apart, left broken by autoimmune disease and brain damage, but that I can still exist fully on the other side.

 

 

Why a Couple Pieces of Fruit Sent My Triglycerides Through the Roof, and How it Relates to Chronic Health

A Demonstration of the "Energy Delivery" Nature of Lipid Mechanics

Last Monday, I had my blood drawn and triglycerides measured at 103 mg/dl. On a Tuesday test they spiked to 241 mg/dl and by Thursday had once again returned to a baseline of 106 mg/dl.

I didn’t “cheat” on any of these blood draws. They were all standard, appropriately fasted tests that no clinician would ever take issue with. So what happened to cause these dramatic changes?

The answer, in short, is that I ate a bit of fruit. Two bananas and an apple to be exact. But a little fruit obviously doesn’t usually send a person’s triglycerides skyrocketing, so it’s the context that make this demonstration so interesting and illustrative.

 

What I Did

 

To be clear, this is hardly the world’s most rigorous experiment. It really wasn’t an experiment at all, just a decision to measure an effect I knew would occur during a planned real-life event. I had been eating only meat for the last couple weeks and was now planning to reintroduce a bit of fruit to my diet. As such, my reliance on stored body fat was going to decrease and create a prime opportunity to illustrate the energy delivery nature of lipid mechanics. The conventional wisdom that chronic fat consumption drives gradual changes in lipid levels is broadly incorrect and insufficient to explain lipid behavior, and the expected rapid changes during this dietary transition would serve as a demonstration of this reality.

So anyway….I ate nothing but meat for a while before reintroducing a small amount of fruit last Monday with my dinner (2 bananas, an apple, some ground beef). I had my blood drawn for three lipid panels during the transition – Monday (before introducing fruit), Tuesday, and Thursday. The total fat and carbohydrate consumption in the days leading into and during the transition are given in the graph below. 

The Results 

Full lipid panels are given in the following chart. As can be seen, dramatic changes in triglycerides were observed, with values spiking significantly on the second day before returning to baseline shortly thereafter. LDL-C changes are also fairly dramatic, but LDL-C + VLDL-C levels decrease gradually across the 3 tests. While the triglyceride changes were the main point of the demonstration, the LDL/VLDL changes also occur in a manner that can be much better explained by an energy delivery model of lipid behavior rather than the standard “fat consumption” paradigm. The second graph shows how dramatic an outlier this triglyceride result was compared to my typical values. 

Date	4/8/24	4/9/24	4/11/24
LDL-C	137	109	120
HDL-C	56	43	49
Triglycerides	103	241	106
VLDL-C	18	42	19
LDL+VLDL	155	151	139

What This Shows

What this essentially demonstrates is the degree of reliance on fatty acids for energy in the complete absence of carbohydrates. In a low glycemic, low insulin environment stored triglycerides are being broken down rapidly and returned to the liver to be packaged and distributed to the body within VLDL particles. The extreme lack of insulin and high reliance on fatty acids for energy means this is happening at an increased rate – It shows up on the lipid panel as a moderate increase in LDL-C.

**Quick refresher/explainer on terminology and physiology - fat entering the liver is converted to triglycerides and packaged into lipoproteins called VLDL. VLDL carry cholesterol and triglycerides away from the liver to the muscle and fat cells of the body. VLDL are typically short-lived and are converted to LDL particles after they offload triglycerides either to the cells of the body or back at the liver. LDL particles have a longer lifespan (days instead of hours) and carry primarily cholesterol around the bloodstream. VLDL-C and LDL-C refer to the amount of cholesterol contained within each particle class. LDL-C, but not VLDL-C, typically goes up when larger amount of triglycerides need to be trafficked for energy because the higher number of VLDL particles offload triglycerides quickly and convert to LDL. More background info can be found here**

Why not elevated triglycerides though? Because despite my body producing more triglyceride containing VLDL particles than the average person would, blood levels of triglycerides remain unelevated due to their rapid utilization. In essence, the total fatty acid throughput – first from body fat to liver, then in VLDL from liver to muscle (and, for some, back to body fat) – is high, but the levels in the blood at any given time are not.

The introduction of even a small amount of carbohydrates demonstrates the rate at which triglycerides were moving around. Upon consumption, they elevate the blood sugar and their removal from the bloodstream prioritizes them as an energy source over the significant flow of triglycerides. Because it takes some amount of time for newly liberated fat stores to travel to the liver and be repackaged in VLDL particles (and perhaps because insulin does not spike high enough or fast enough after limited carb consumption to immediately “shut off” fat breakdown), there will for some time be a build-up of triglycerides leaving the liver waiting to be taken up by the body.

The carbs delay these triglycerides and, combined with the triglycerides being provided by the rest of my dinner, cause the high throughput to come to an abrupt halt. The next morning, a full 13 hours fasted, the backlog still fails to fully clear, resulting in high measured triglyceride (and VLDL-C) levels. Given a bit more time, however, this backlog does indeed clear as fewer VLDL particles are produced.

Just two days after the spike, triglycerides levels return to Monday’s baseline level. Carbohydrate consumption remains but, overall, things have now changed. The small carbohydrate contribution to energy is no longer additional to the heavy reliance on stored body fat, but instead replaces a portion of it as the breakdown of stored body fat is throttled back a degree. Fewer triglycerides are mobilized from the body’s stores and so the brief excess of energy supply no longer exists.

This same effect can be observed in my LDL-C and VLDL-C levels as well. Remember, reliance on these lipoproteins for energy transport is a prime driver of LDL/VLDL cholesterol. As such, those combined values are highest during my first blood draw but decrease gradually over the next two as less fat is mobilized from my body’s stored reserves. With less stored fat being liberated, less fat is necessarily trafficked to the liver to be packaged and distributed in VLDL particles. The “build-up” effect can be clearly seen on the second blood draw, where VLDL-C spikes as the VLDL particles fail to offload triglycerides and convert to LDL particles. The failure of these VLDL particles to appropriately (ie. quickly) convert to LDL causes the sharp decrease in LDL-C as old LDL particles are removed from circulation without being replaced. LDL-C rebounds to a degree on the final draw despite lower VLDL production because these previously long-lived VLDL particles have now finally converted to LDL.

 

 

What This Implies for Chronic Health

 

This particular demonstration is a unique sort of one-off that won’t apply to most people in most situations, but it is nonetheless relevant to chronic metabolic health as well. While my demonstration succeeds in creating an “energy back-up” in the short term, it is that same backlogged delivery of triglycerides that serves as a hallmark of chronic metabolic dysfunction. In short, it is the precisely the same mechanisms – prolonged VLDL residence times and increased triglyceride levels due to delayed or failed triglyceride uptake at the periphery – in each case. The underlying reasons, however, differ.

In my case, as has been covered, the backlog is very brief and is caused by essentially dropping some carbohydrates into a fast-moving river of fatty acid energy. But in chronic cases, the build-up is more gradual and subject to progressive long-term forces. When a person chronically overconsumes carbohydrates, becomes insulin resistant, increases fat stores, and so forth, triglycerides are in certain ways both more prone to enter the bloodstream and more resistant to leaving.

They fail to leave the bloodstream in an appropriately quick manner for largely the same reason as in my experiment – chronically elevated blood sugar forces a prioritized reliance on carbohydrates for energy. This isn’t a major issue in any acute sense, but becomes one when carbohydrates are chronically consumed in excess. Many of these carbohydrates, in the form of fructose, are in fact converted to triglycerides in the liver and join the flow of VLDL particles to the periphery. Additionally, an overweight, insulin resistant individual will become dulled to insulin’s fat-storage effects. While typically the consumption of carbohydrates and corresponding increase in insulin makes it very difficult to liberate body fat, this effect is progressively reduced in cases of insulin resistance. Now, triglycerides in the body’s fat stores are inappropriately broken down and trafficked to the liver for packing in VLDL particles.

When this person chronically consumes carbohydrates, increasing insulin levels and extending VLDL residence time, they contribute to a backlog of these additional sources of VLDL/triglycerides. When the VLDL are unable to offload triglycerides properly, they must be returned to the liver and be offloaded there instead. This is in fact the most critical source of excess triglycerides entering and exiting the liver. When excess triglycerides are returned to the liver, they join the aforementioned additional sources of triglycerides in being packaged again into VLDL particles and leaving the liver to join the triglyceride backlog. For as long as carbohydrate consumption remains high and insulin levels remain elevated, this risks becoming a progressively more serious issue, as triglycerides are increasing unable to be offloaded to the cells of the body and instead returned to the liver to join the ever-growing backlog once more.

The end result, in this case, is chronically elevated triglyceride levels that can’t likely snap back to healthy levels in a day or two. Increasing triglycerides directly lowers HDL-C and increases VLDL production, ultimately leading to the increase in LDL particles and LDL-C commonly assumed to be the cause of chronic cardiovascular disease. In fact, the increased presence of triglyceride-rich lipoproteins is (through the action of CETP) among the actual instrumental drivers of such disease, as the presence of excess triglycerides also generate smaller damage-prone LDL (and HDL) particles. As these effects are secondary to excess carbohydrate consumption, they will necessarily be accompanied by a trend towards increased development of advanced glycation end-products, depressed nitric oxide availability, increased free radical production, and other hyperglycemia-induced facets of compromised vascular health. 

  

Conclusion

In short, I was able to briefly replicate a very unhealthy state that those suffering from metabolic dysfunction experience on a chronic basis. Importantly, the lipid changes observed during this demonstration can only be explained by the demand for energy transport, not by fat consumption. While my failed triglyceride metabolism was effectively a mirage caused only by the unique, acute introduction of carbohydrates, the chronic state is reached by millions and millions who overconsume carbohydrates habitually. This triglyceride backlog and failure of fatty acid metabolism is an instrumental component of cardiovascular disease progression that can be largely moderated or reversed by a shift away from traditional, carbohydrate-based dietary guidelines. 

Further reading on the topics addressed above can be found here - 

• Terminology and Overview of Lipid Classes
• Triglyceride Mechanics - General, Dysfunctional, Efficient/Low-carb Dynamics
• Consequences of Poor Triglyceride Uptake
• Other Factors Influencing Atherosclerosis

Colorectal Cancer is in the News Again. Don't Blame Red Meat

 

Colorectal Cancer in the News

NBC News and other prominent outlets are currently reporting on a dramatic increase in both rates of colon cancer and colon cancer mortality among young adults.¹ These news reports, based on a recent publication from the American Cancer Society, suggest a substantial uptick in the disease but can only theorize as to what might be driving it.² While the ACS report itself is only a dry statistical report, various news outlets and the public health experts they interview hypothesize a number of potential causes, typically of an environmental or dietary nature. One of these potential causes, is of course, meat consumption. So now seems like as good of time as any to discuss why I believe there is no legitimate evidence whatsoever linking meat (most specifically, red meat) consumption to colon and colorectal cancer (CRC) incidence.

Lets start with the ACS report itself, which reports increasing incidence of 6 of the top 10 cancers. For example, cancers of the breast and pancreas ticked up very slightly (less than 1% over five years), while cancers of the prostate and kidney were among those increasing most rapidly (upwards of 3% over five years). Colorectal cancer, on the other hand…is not increasing. So why all the headlines? I think part of it is that CRC makes for a trendy headline of sorts, as its been a particular mainstream focus in the last decade or so (more on that in a minute). The other reason is that, while CRC rates are not increasing overall, they are indeed increasing (between 1 and 2 percent) among people in their 30s and 40s. Perhaps even more relevantly, rates of CRC morality in that demographic are increasing as well.

 

Rates of CRC and other select cancers in adults under the age of 50

So rates are increasing among younger adults in which the disease tends to be relatively rare, but are not increasing overall. What might cause this to be the case? I certainly have a suggestion, but it won’t be the same you see in traditional medical and health circles. If you search the internet for CRC prevention advice, you’ll quickly find (along with advice to exercise and refrain from smoking) advice from the American Cancer Society to limit red and processed meat, from the CDC to limit animal fats, and from Harvard to remove as much meat as possible from your diet (“Red and processed meat has been the dietary factor most consistently linked to colon cancer”). ^3–5

None of these claims and none of these recommendations, though, are based on more than weak epidemiology (i.e. survey data). And while potential explanations (curing nitrates in processed meat, for example) have been sought to explain the association between meat consumption and CRC, I believe a much more obvious causal explanation exists both to explain the general association between red meat consumption and CRC AND the recent uptick in young adult incidence of the disease.

 

Increasing Focus on the Meat-CRC Link

 

It’s often presented as an obvious cause and effect, that red meat consumption is tightly linked to and often instrumental in causing CRC to develop. But the evidence does not support these typical claims. Let’s start in 2015, when the International Agency for Research on Cancer (IARC) prepared a study for the World Health Organization on the potential carcinogenic properties of meat. ⁶ Based (ostensibly) on this paper, the WHO issued a report declaring red meat to be a Category 2A carcinogen, describing it as “probably carcinogenic to humans.” This notion, that beef and other red meat may be cancer-causing, has become increasingly prevalent in the years since.

 

However, I would argue that the claims made by the IARC/WHO are deeply flawed for a number of reasons:

1.       The IARC report did not, in fact, find significant evidence that red meat consumption is linked to cancer in humans

2.       The epidemiological studies that do link meat consumption to cancer are very limited, and typically find only a small effect

3.       The studies linking meat consumption to cancer fail to take into account significant confounding variables.

             

When you first saw the alarming report on the nightly news in late 2015, you’d have been mistaken for believing the WHO made their claims on the back of a significant body of evidence. After all, the WHO is quick to point out that more than 800 studies were examined as part of the report. How many of these 800 studies detailed a significant link between red meat consumption and CRC, you might wonder…

Its certainly not 800. In fact it certainly doesn’t even appear to be 8. Included among those 800 studies were 29 that examined CRC specifically, and of those 29 only 14 showed positive associations between red meat consumption and CRC. But read that sentence again…. Its 14 studies that showed a positive association, not 14 studies that showed a statistically significant connection between CRC and red meat consumption. In fact, in their public report the very first study the IARC references among those 14 says this:

 

“Intake of red meat was positively but not statistically significantly associated with colorectal cancer"⁷

 

So, again, to be very clear – there were not 14 studies that found a scientific, statistical link between red meat consumption and CRC. There were instead 14 studies that demonstrated some vague, uncertain positive relationship between the two. However, the IARC and WHO made the choice in their reports to misrepresent these weak relationships as scientifically valid, when in fact they are anything but. And since every piece of epidemiology is going to pick up a vague, uncertain trend in one way or the other, we can be fairly confident the other 15 demonstrate some vague, weak, unscientific trend in the opposite direction. So while the totality of the evidence examined found no scientific link between CRC and red meat consumption, and the weak, non-significant trends were equally split between positive and negative, the WHO still made the decision, based on jaw-droppingly weak evidence, to label red meat a probable human carcinogen.

 

Why The CRC-Red Meat Link Still Sometimes Exists

 

Ok, ok….the IARC report didn’t support its own conclusions or its headlines. But there are, indeed, some epidemiological studies out there that show a genuine, significant scientific link between CRC and red meat consumption. There was even one in the public IARC report!⁸ So now let’s talk about why that link still isn’t what it seems, and what dietary factor I ultimately think is to blame for the uptick in young adult CRC.

**A quick aside – if you aren’t familiar with the concept of healthy user bias, now would be a good time to acquaint yourself. You can do so in detail HERE, but in short – healthy user bias is the concept by which people who want to be healthy do things they believe to be of benefit to their health. The opposite is "unhealthy user bias," in which people who don't care about their health don't mind doing things that are considered unhealthy. Because recommendations to avoid meat predate nutritional epidemiology by more than two decades, there has never been a study unbiased by the widespread belief that meat and fat are unhealthy. Healthy user bias is a massive problem in epidemiology because its effectively impossible to account for all the habitual differences between “healthy” and “unhealthy” individuals. It’s a problem made all the more massive by the fact that so many researches apparently don’t even make an attempt. For example, failure to adjust for a multitude of factors is how you end up with the consistent finding that red meat consumption “causes” as many or more accidents than it does cases of chronic disease^9–11**

 

Ok, now…A case study –

The same year as the IARC report, researches at Loma Linda University released a study claiming that "Vegetarian diets are associated with an overall lower incidence of colorectal cancers."¹² This study, basically, followed nearly 100,000 Seventh-Day Adventists for six years and compared self-reported diet to incidence of colon cancer. Because meat consumption is frowned upon in the religion, only half of the participants were meat-eaters. What they concluded is that vegetarians, compared to those who consume meat, were 22% less likely to develop colorectal cancer. This translates to roughly a 5% chance that a vegetarian, and a 6% chance that a meat-eater, would develop colorectal cancer during adulthood. And yes, this finding was statistically significant. 

 But it still doesn't mean meat causes cancer. Why? Healthy user bias and confounding variables. It is standard scientific practice to attempt to adjust for HUB, but is not possible to do so completely. Lets specifically examine meat-eaters vs. vegans, using the data from this study, to illustrate why. 

 

 

 

What you might notice at first is that the vegans in the study actually had more cases of colorectal cancer than did the meat-eaters. 7 percent more, to be accurate. But just stopping there would be very bad science indeed, as there are a number of other factors that can influence the results. For example, the meat-eaters are slightly younger and thus less likely, all things considered, to develop cancer of any kind. When the researchers apply the statistical process known as "adjustment" to the age variable, they can eliminate age as a factor and find that, age-adjusted, the vegans actually had 11 percent FEWER cases of colorectal cancer. 

But we can't just adjust for age. You'll also notice that meat-eaters are more overweight, more likely to smoke, more likely to drink, more likely to have diabetes, less likely to exercise, etc. This is (un)healthy user bias in action. Researchers adjust for these as well, with little impact on the final numbers. But what I want to focus on is not what they do adjust for, but what they don’t – namely, sugar and processed carb consumption, blood sugar, and insulin levels. You’ll note in the chart above that I specifically highlighted the diabetes rate of the meat eating group, and with good reason -

 

1. Diabetes is fundamentally a disease of insulin resistance and increased insulin production tightly related to prolonged overconsumption of high-glycemic (sugary) carbohydrates and obesity

        2. Insulin is a potent growth factor

        3. Cancer is a disease of uncontrolled growth, and cancer cells typically overexpress insulin receptors

 

It should not be surprising then, to find that individuals with increased insulin levels are far more likely to develop colorectal cancer. For example..

"An increased concentration of plasma C-peptide was statistically significantly associated with an increased risk of colorectal cancer (relative risk [RR] for the highest versus lowest quintile of plasma C-peptide = 2.7, 95% confidence interval [CI] = 1.2 to 6.2; P-trend = .047)"¹³

"Colorectal cancer risk increased with increasing levels of C-peptide (P-trend = .001), up to an odds ratio (OR) of 2.92 (95% confidence interval [CI] = 1.26–6.75) for the highest versus the lowest quintiles"¹⁴

"Cancer mortality was significantly higher in those with hyperinsulinemia than in those without hyperinsulinemia (adjusted HR 2.04)"¹⁵

*Note that C-Peptide is a measure of insulin production

 

In fact, a long list of studies show that individuals with high levels of insulin production are as much as 200 to 400 percent more likely to develop colorectal cancer.^16–24 But despite insulin's massive role in the development and progression of cancer, it is partially unaccounted for in the study above. We know, with a high level of certainty, that the meat-eating group had higher insulin levels, largely due to the drastically higher rate of diabetes but also the increased obesity (tightly connected to insulin levels) and the great likelihood that the meat eaters are also consuming more sugar and processed carbohydrate (healthy user bias).

Now it is true that obesity and a clinical diagnosis of diabetes are adjusted for, but the vast majority of meat-eaters did not have diabetes. Still, the massively increased rate of diabetes doesn't exist in a vacuum. Diabetes as a clinical diagnosis really just reflects a certain threshold of insulin resistance, not a discrete state. Which is to say that the meat-eating group has more diabetics because the entire group has higher insulin levels, meaning more people will be past the diabetic threshold. The critical point, then, is that this group will also have more "pre-diabetics" and more people with moderately elevated insulin. But without any adjustment made for the consumption of sugar, the consumption of processed grains, actual blood sugar levels, or actual insulin levels, the influence of insulin is allowed to persist. Certainly, then, the meat-eating group is to at least some degree more likely to develop colorectal cancer for reasons that have nothing to do with the consumption of meat. 

In fact, the end result of the study suggests, based on indirect survey data, that meat-eaters are 14% more likely than vegans to develop CRC. Contrast this with the consistent direct findings that individuals with the highest insulin levels are more like 2-300% more likely to develop CRC. These studies together suggest that high insulin is something like 15-20 times more powerful than high meat consumption in predicting the development of future CRC. When insulin is that much more powerful a predictor, it only takes a small degree of negligence in accounting for it to end up with results like the one is this study. Are meat-eaters 14% more likely to develop CRC because meat is driving the disease or because their more sedentary, processed-carb lifestyle results in elevated insulin that isn’t fully being accounted for?

You can see how glaring an oversight it is, then, to ignore the impact of insulin when you attempt to link meat consumption to CRC using only epidemiological survey data. Remember when I pointed out the one study in the IARC report linking red meat to CRC at a statistically significant level? Not only did that study not measure or adjust for sugar consumption, processed carb consumption, blood sugar, or insulin levels, they didn't even adjust for diabetes! If you then further layer in the pile of direct, controlled trials that demonstrate the capacity of a high fat, low-carb diet to improve blood sugar and lower insulin levels, the claims that meat consumption is causing CRC become even more difficult to believe.^25–35  

Conclusion

The following facts are all true:

1.      The link between meat consumption and CRC development is based only on a small number of epidemiological surveys, and the degree to which these studies suggest meat ostensibly increases one’s risk is quite small.  

2.      Elevated insulin levels predict CRC development as much as 20 times more strongly than does high levels of meat consumption.

3.     Epidemiological studies incompletely account for insulin levels to varying degrees, with some ignoring blood sugar, insulin levels, and diabetes entirely.

4.     Replacing sugar and carbohydrates with meat and fat lowers long-term blood sugar, lowers insulin levels, and improves markers of glucose metabolism and diabetes.

 

The following facts are also true:

1.       Diabetes rates are increasing more rapidly than CRC rates

2.       Diabetes rates are increasing in children and young adults³⁶

 

I’m sure its entirely obvious where I’m going with this by now, but I’ll share an image from last year’s post on red meat and diabetes to drive home the point:

 

 

Red meat doesn’t cause diabetes and in fact can be instrumental in reversing it. In reality, this discussion on CRC is basically just “red meat doesn’t cause diabetes” with extra steps. Red meat consumption has never been legitimately linked to the development of CRC - A minority percentage of epidemiolocal papers suggest a weak link between the two only by utilizing survey data that fails to fully account for meaningful confounding factors.

On the contrary, insulin levels are directly, strongly, and significantly linked to the development of CRC. As reflected by ever-increasing rates of diabetes and ever-earlier onset of the disease, population levels of blood sugar and insulin continue to increase. If one begins with the (scientifically-valid) premise that impaired glucose metabolism, elevated insulin, and other diabetic complications are directly influential in the onset of CRC, it is effectively inescapable that the increasing rates of diabetes (and young adult diabetes) must portend an increase in young adult CRC as well.

To the degree than any dietary factor is influencing the increase in CRC incidence and mortality, it is these – excess consumption of sugar and processed carbohydrate, chronically elevated blood sugar, and long-term elevated insulin are directly involved in the development of CRC. Red meat, for decades now lumped with smoking, drinking, sugar, and a sedentary lifestyle as the vices of chronic disease, is occasionally caught in the crossfire of weak epidemiological science.

News articles and “expert” advice will likely continue to focus on the minor, weak, indirect link and urge you to prudently fight CRC by eliminating meat despite the lack of evidence to support this position. I’ll do the opposite – if you want to reduce your risk of colorectal cancer, focus on the direct link more than an order of magnitude stronger. Reduce your insulin levels by reducing or eliminating sugar, grains, and other processed carbohydrates, and make a real, meaningful difference in your risk of developing cancer, diabetes, and a host of other chronic diseases. Don’t blame the meat.

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