Showing posts with label LDL. Show all posts
Showing posts with label LDL. Show all posts

Tuesday, January 14, 2025

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 20th. 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 19th and run the 50k on the 20th. 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.







Friday, April 19, 2024

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 - 




















Monday, December 11, 2023

The Study That MIGHT Change Lipidology


Last weekend, UCLA cardiologist Dr. Matthew Budoff presented preliminary baseline data at the World Congress on Insulin Resistance, Diabetes, and Cardiovascular Disease that could theoretically, potentially, eventually, help turn the fields of lipidology and cardiology on their heads. 

The first of its kind prospective (ie. forward-looking) study directly assesses arterial plaque and calcification in a population of individuals with extremely high LDL-C resulting from a very low carbohydrate diet (Why this happens HERE). This population, while not entirely uncommon, is largely unstudied and may offer a number of clues to the true nature of lipid behavior and cardiovascular disease. 

Why is this? Because these individuals have very, very high LDL-C - an average of 272 mg/dl. Remember, conventional medical guidance considers an LDL-C above 100 mg/dl to be "high" while average is something around 120 mg/dl. 272 mg/dl is way past the 99th percentile and is more than 40% higher than the American Heart Association's threshold for automatic, no-questions-asked high-intensity statin therapy. Factor in the subject's average age of 56 years and they should, in theory, seem like a no-brainer for lipid-lowering therapy. 

These people should be at extreme risk for cardiovascular disease, should they not? Well, yes...if the traditional paradigm is correct. But the lipid-heart hypothesis is not nearly the settled science the AHA, pharmaceutical companies, and the medical establishment would have you believe. Instead, there are I believe two principle theories by which atherosclerotic cardiovascular disease may develop: 

  •  Theory 1 is that LDL-C and LDL particles themselves are the direct, primary, and uniquely necessary elements of atherosclerotic disease. Elevated levels of LDL particles and LDL-C increase your risk for such disease by increasing the chance that, over time, more and more of these particles will become trapped in the wall of the blood vessel and ultimately lead to the development of plaque, arterial occlusion, etc. This is the common theory advanced by the medical industry. 
  • Theory 2 is that LDL particles damaged as a result of oxidative stress or hyperglycemia are the target of immune cells whose function is to trap the damaged particles for recycling and removal. When poor metabolic efficiency, hyperglycemia, and increased oxidative stress lead to an excessive number of damaged LDL particles, this process occurs at a greatly increased rate. The development of plaque, arterial occlusion, etc. is fundamentally an inability of the body to remove and recycle these damaged particles as quickly as they accumulate. I've written many thousands of words about why I favor this theory. 

Now the subjects in this study are excellent candidates to test these theories because they not only have very high LDL-C, but also good metabolic health (HDL = 90, Triglycerides = 64, BP = 117/76, A1C = 5.4%). This means the key sentence in Theory 2 ("poor metabolic efficiency, hyperglycemia, and increased oxidative stress...") is of limited relevance and allows a unique opportunity to compare the two theories. If Theory 1 is correct, these individuals should rapidly develop cardiovascular disease. If Theory 2 is correct, they should not.

So far we only have preliminary, baseline date, which you can watch be presented HERE, but which I'll summarize briefly:


CAC and plaque scores for low-carb and control groups


  • The researchers assessed two direct measures of atherosclerotic disease - coronary artery calcification and a "total plaque score" (calculated via CT angiography). These were measured in both the low-carbohydrate group and a control group matched for age, metabolic health, etc. The only major difference between the two groups was LDL-C, which was more than twice as high in the low-carb group. 
  • The researchers will assess both of these metrics again in another year to assess any disease progression in each group
  • The majority of subjects in each group had coronary artery calcification scores (CACs) of 0, indicating no calcification (CACs of significantly at-risk individuals commonly range from 100-400 or higher).
  • Total Plaque Score is calculated from 0 to 45 (0-3 at each of 15 different potential plaque sites). In the low-carb group, the median subject had a TPS of 0 with an interquartile range (the middle 50%) of 0-2. No subject had a TPS greater than 12. The control group had a median TPS of 1 with an interquartile range of 0-4. The difference between the two groups was not statistically significant. 
  • There was no difference in CAC or TPS between the low-carb, high LDL-C group and the control group.
  • There was no relationship in either group between LDL-C levels and measured plaque.



Now, it should be noted that CACs and TPSs of 0 are not particularly remarkable. In fact a little more than half of 56 year olds have a CAC of 0 (you can play around on this NLHBI site if you'd like to see). Its normal and healthy to be free of coronary calcification. But what makes this study so potentially fascinating is that these subjects aren't considered "healthy" in a traditional sense. Years of extremely high LDL-C should predict the impending doom of atherosclerosis, but so far at least this group shows little and often no disease progression whatsoever. In fact, their cardiovascular disease state is indistinguishable from matched subjects with good metabolic health and no elevated LDL-C. 

We'll have to wait until 2024 for follow-up results, in which actual plaque progression in each group will be compared. But if two groups with similar metabolic health yet vastly different LDL-C levels continue to demonstrate identical disease states (or the lack thereof), it would lend significant credence to the notion that metabolic health and other associated factors, rather than LDL Cholesterol, drive chronic cardiovascular disease. Ideally, this would help launch a number of other studies to further challenge common assumptions and explore underappreciated aspects of lipidology and cardiovascular disease. Will that be the case? TBD...





Thursday, August 17, 2023

Summer Health Update Part 2 - What 3 Pounds of Meat Every Day Does To Your Blood Work

 

While my neurological health remains a few percentage points short of ideal, I’ve also been increasingly in touch with other aspects of my health as I continue to seek optimal recovery. The amount of “general health” bloodwork I’ve sought, measured, and ordered has increased significantly and, with that in mind, I’ve decided to share the most recent round of (semi-) comprehensive of blood work.

Conventional wisdom suggests that eating a diet high in meat and fat is dangerous for cardiometabolic and chronic health. For over a decade, I’ve progressively ignored that conventional wisdom. For years, this meant eating a lower carb (for an athlete, at least) paleo-type diet. Since my vaccine reaction, it has meant consuming various degrees of low-carb and ketogenic diets. And for more than a year now, it has meant more than 90% of my diet as beef. While I was largely sedentary for the first two years of my illness, the last several months have featured increasing amounts of exercise.

Despite the extended lack of activity and the ostensibly hazardous dietary reliance on meat and fat, you can see below that my chronic health markers are generally quite good. Below are the relevant results from my latest check-in and my commentary on each of the metrics. My recent diet and exercise statistics for reference:


Background statistics - 

Height – 6ft 3in        Weight – 161 lbs.         Age - 32y, 7m

     

8 week exercise averages –

~47 miles/week hiking and jogging, 2-3/week ~20 min strength training


8 week dietary averages –

~3320 calories/day        

70.5% fat/27.1% protein/2.4% carbohydrate (~19g/day)

48% saturated fat/48% monounsaturated fat/4% polyunsaturated fat


3 day dietary averages –

~3430 calories/day

71.2% fat/23.7% protein/5.1% carbohydrate (~43g/day)

48% sfa/48% mufa/4% pufa

 

 

 

 

Triglycerides – 87 mg/dL (Reference range 0-149)

I eat tons of fat, but don’t have tons of fat moving around my blood. What gives? Well, your triglyceride levels don’t reflect fat consumption or triglyceride production by the liver. Trigs reflect fatty acid utilization and fat metabolism. If you efficiently metabolize/utilize fat for energy, you should have low triglycerides. Common recommendations suggest under 150 to be normal, but realistically 150 is pretty sketchy and any values north of 100 suggest room for improvement.

 

HDL – 68 mg/dL (Reference range >39)

HDL levels are primarily responsive to two factors – triglyceride levels, and fat consumption. Elevated triglycerides resulting from metabolic inefficiency subsequently lead to a reduction in HDL-C (you can read about why here!). Meanwhile, fat consumption directly increases the concentration of the structural lipoproteins that eventually form HDL particles. Ergo, low trigs + high fat consumption = high HDL.

 

Triglyceride/HDL Ratio – 1.28

Not a unique measurement, but a reasonably meaningful reflection of metabolic health. Because poor metabolic health increases triglycerides and subsequently decreases HDL, a ratio between the two is a decent proxy for metabolic health. Conventional wisdom would suggest something like 3.5 to still be a fine value, even though cardiometabolic disease rates start exploding once you inch above this level. Personally, I wouldn’t feel great about anything higher than 1.5-2. For fun, I’ll include comparisons to bloodwork taken the day after a brief spring “binge” (3 days of higher carb, higher calorie consumption) as well as the day I ended an 8 day extended fast.


 

April “Binge”

April Fast

June

Triglycerides

127

84

87

HDL-C

50

52

68

Trig/HDL Ratio

2.54

1.61

1.28

 

LDL – 113 mg/dL (Reference range 0-99)

Just about the least meaningful standalone marker out there, despite the medical and pharmaceutical indu$try’$ endle$$ obe$$e$$ion with $elling $tatins in order to force it lower in basically everyone. You can read tens of thousands of words I’ve written about the problems with LDL here or here if you’re interested. I’ll say this for now though – LDL is hyper-agile in a metabolically healthy person. My values can effortlessly bounce between roughly 100 and 200 depending on what I eat on any given day. I don’t care to ever see numbers lower than that, as I see no benefit whatsoever (and, for whatever its worth, low LDL is associated with significant increase in death and disease for several plausible reasons). Furthermore, you’ll note that despite consuming tons of fat and saturated fat, this value is actually slightly below the population average, even if its slightly above the recommended level. That’s because saturated fat is absolutely not the prime driver of LDL levels.

 

Apolipoprotein B – 84 mg/dL (Reference range <90)

ApoB is the structural protein that forms LDL particles, and is slowly beginning to replace LDL as the en vouge cardiovascular risk measure (It is a better measure than LDL, but is subject to many of the same flaws as well). This value reflects the number of LDL particles in circulation, and you’ll note once again that despite eating tons of fat my values are actually below average and in the “approved” medical range. 

 

LDL/ApoB Ratio – 1.35

My ApoB, which reflects LDL particle count, is in the recommended range, but my LDL cholesterol is still high. How does this work? The answer lies in particle size – fewer ApoB particles carrying a given amount of cholesterol suggests those particles are on the larger size. This matters for a couple reasons – small particles indicate poor metabolic efficiency, while being themselves highly susceptible to the oxidative and glycemic damage that commonly triggers the immune-mediated atherosclerotic process. A ratio of 1.2 or so is a common cut point in the literature, with ratios below that suggesting significant cardiometabolic risk. I’ve previously forced mine as low as 1.15 with just a couple days of higher carb consumption, but would prefer not to see values below about 1.3 in typical conditions. Prior comparisons included here as well.

 

April “Binge”

April Fast

June

LDL-C

108

180

113

ApoB

94

139

84

LDL/ApoB Ratio

1.15

1.29

1.35

 

C-Reactive Protein - <1 mg/L (Reference range 0-10)

CRP is a measure of systemic inflammation. You’d like to see this number as close to zero as possible, generally speaking, and the reference range extending to 10 is flat-out crazy. In the absence of some other relevant factor like a recent race, I’d really hate to see even a value of 2. Unfortunately, LabCorp doesn’t report values below 1, meaning you never really want to see an actual value on one of these tests. The one time I managed to have this tested at another lab, it was at 0.2.

 

Hemoglobin A1C – 5.1% (Reference range 4.8 - 5.6)

HbA1C is a measure of long-term blood sugar (specifically a measure of how many red blood cells have been glycated by sugar in the blood). Its commonly used to assess or monitor diabetes status. Values for HbA1C exist across a fairly narrow band – 5 is great, 6 is pretty terrible (though plenty of people hit 8, 9, or even higher). Current guidelines consider 5.7 or higher to be “prediabetes” and you really don’t want to see this above the low 5s.

 

Glucose – 95 mg/dL (Reference range 0-99)

This is on the high side for me, as fasting glucose usually bounces around between about 85 and 95. I don’t think a single number is worth all that much when you can just look at A1C and capture a long-term picture, but it’s a normal enough number regardless

 

Insulin – 1.7 uIU/mL (Reference range 2.6-24.9)

Arguably the single most important measurement on here in my view. Insulin is a storage and growth hormone secreted primarily in response to carbohydrate consumption. Chronically elevated levels of insulin are instrumental in metabolic dysfunction and contribute to the insulin resistance that defines diabetes and so much of cardiometabolic disease. The normal reference range of “less that 25” is absolutely off the rails. A person with fasting insulin levels in the 20s is so metabolically sick. Just ridiculous to label it normal in any sense of the word. This is a number you want in the low to mid single digits, with numbers closer to 10 more than sufficient to disrupt optimal metabolic health and function. As mentioned, carbohydrates are the primary driver of insulin levels. I consume very few, and thus have very low fasting insulin.

 

HOMA-IR - 0.4

The Homeostatic Model Assessment of Insulin Resistance is a simple, non-invasive method of estimating an individual’s resistance to insulin using fasting glucose and insulin values. Insulin resistance is a prime driver of heart disease and other chronic diseases, and quite literally is diabetes. HOMA-IR values under 1 are considered optimal, with values north of 2 indicating moderate or greater insulin resistance. A low HOMA-IR and high insulin sensitivity are generally to be expected when consuming a low-carbohydrate diet. I'll add the binge/fast comparison here as well


 

April “Binge”

April Fast

June

Glucose

106

66

95

Insulin

11.4

1.3

1.7

HOMA-IR

3.0

0.2

0.4

 

Uric Acid – 3.5 mg/dL (Reference range 3.8-8.4)

Say it with me – “red meat doesn’t cause gout.” This is bit of nonsense that continues to be propagated throughout nutrition and medical circles, but it doesn’t reflect reality. Uric acid is a nitrogen-containing compound that forms from the breakdown of purines, which are indeed found more abundantly in animal products than in plants. But then a healthy person just pees the uric acid out, while a metabolically dysfunctional individual will not. Which is why elevated uric acid levels are tightly linked to insulin levels, obesity, and metabolic syndrome, while mine is out the bottom of LabCorp’s reference range.

 

Vitamin D – 39.1 ng/mL (Reference range 30-100)

This is lower than I’d like. The reference range says above 30 is fine but would realistically like to be double that. I already triggered neuro symptoms trying some vitamin D drops so now the strategy will be a bit more eggs, salmon, and mid-day sun before maybe assessing again.

 

Thyroxine (T4) – 1.2 ng/dL, TSH – 1.14 uIU/mL (Reference range 0.82-1.77, 0.45-4.5) 

My thyroid hormones are perfectly normal.

 

Blood pressure – 110/70, 110/64 mmHg (Reference range <120/80)

These are my two latest doctor’s office BP readings, although I somewhat regularly measure my own BP and find these values to be quite typical. Elevated blood pressure is really just another manifestation of chronic insulin resistance, rather than salt consumption or any other acute dietary factor (I literally drink salt in my water for whatever that’s worth). Its only chronic carb/sugar consumption and elevated insulin that will raise blood pressure, so again optimal measures are unsurprising.

 

Testosterone: Total – 183 ng/dL, Free - 4.4 pg/mL (Reference range 264-916, 8.7-25.1)

And here’s the one that was actually a problem. Normal testosterone for a healthy 30-something should be a few hundred points higher than this. This proved to be a big sign that I wasn’t eating enough, as downregulated hormone production is one obvious consequence of underfueling (this is just one reason that “calories” is a quasi-worthless way to approach weight and metabolism). Unsurprisingly, I was more sluggish than I should have been and slowly losing weight as well. But while my testosterone was quite low, the good news is I’ve since rectified the problem pretty much by just eating more. A month later, my total testosterone was up to 543.



There you have yet...meat and fat aren't killing me yet!





Tuesday, May 9, 2023

The Problematic Paradigm of LCL-C, Part 12

Part 12 - The Effects of Diet on LDL-C, As Told By Energy Delivery


Previous - Part 11 - The Effects of Diet on Markers of Cardiovascular and Metabolic Health


In the previous, penultimate section we touched on the ways in which macronutrient distribution affects common markers of cardiometabolic health. One incredibly popular marker still remains, though, and that is of course LDL-C.

There are a couple good reasons to save LDL-C for last. For one, it doesn’t move in a consistent direction with carbohydrate restriction in the way HDL-C, triglycerides, or blood sugar might – how it moves depends on who is restricting carbohydrates. But mostly, we’re discussing it last because this entire series focuses on the shortcomings of the modern cholesterol paradigm, in which LDL-C is the central player.

To be clear, I am not making the claim that nothing in the world aside from energy delivery affects LDL-C levels. For example, plant sterols (essentially the plant version of cholesterol, but not usable in the human body) lower LDL-C to a certain degree. But, as has been explained at length in this series, I am making the claim that energy delivery is the primary driver of LDL cholesterol levels. And furthermore, that this energy system is driven primarily by what you eat.

So…what happens to your LDL-C when you eat more carbs, or, perhaps, what happens when you eat less?

 

Personal Anecdote

Early last month I consumed a fairly prodigious amount of cheese (and more – the reasons why are here, but aren’t important) over the course of a weekend before having my blood drawn the next day. My LDL-C on that morning? 108mg/dl. This was on the heels of some significant fat consumption – a three day average of 192g of saturated fat, some 8 or 9 times more than the USDA recommend the average person eat in a day.

Just 13 days later, another blood draw returned an LDL-C of 180 mg/dl. In the intervening days, I consumed a maximum of 152g of saturated fat and averaged only 83g per day. Clearly, saturated fat consumption didn’t drive the extreme increase in LDL-C, as it is traditionally thought to do. So, what happened?

The important missing information is that the second blood draw came on day 3 of an extended fast, meaning I had literally consumed nothing – zero grams of fat – the two days prior. My LDL-C was elevated for the exact reasons that have been outlined at length in these writings – increasing LDL-C is an unavoidable consequence of utilizing fat for energy.

 

Low-Carb Trials and LDL-C

We don’t need to rely on my stories for evidence though – studies indeed demonstrate that healthy individuals will see a rise in LDL-C during extended fasting.1,2 Healthy individuals moving to a very low-carbohydrate diet experience the same, just as we would expect.3–7 Note the use of the word “healthy” here – these are individuals without significant metabolic dysfunction. They neatly fit the profile we’ve described of a metabolically healthy individual with excellent health markers that experience an increase in LDL-C as a consequence of trafficking triglycerides for energy.

But what if they weren’t healthy? Imagine instead a study that enrolled only those with metabolic dysfunction, obesity, and insulin resistance. These individuals might very well already have elevated LDL-C alongside poor markers of metabolic health, a consequence of poor triglyceride utilization, increased return of triglycerides to the liver, and compensatory VLDL production. The traditional cholesterol paradigm would likely be aghast at the suggestion that these individuals consume more fat, with their LDL-C already considered a risk to their health and the increased fat, surely, likely to elevate it even further.

But of course, this is not what happens. As many studies that demonstrated, the common finding in these individuals is indeed lower LDL-C following the transition to a low-carb, high-fat diet.8–21 Of course, an energy delivery model of lipid metabolism explains clearly why this is the case – reduced blood sugar and insulin levels allow for improved fatty acid utilization, increased triglyceride clearance, reduced triglyceride return to the liver, and the gradual reduction of excess VLDL production. Much like my fasting example above, a traditional paradigm that suggests fat consumption as the prime driver of elevated LDL-C levels simply cannot explain these observations.

(You may notice here that these findings, taken together, suggest that over a long enough time frame an obese individual restricting carbohydrates would experience BOTH an initial decrease in LDL-C and then again increasing LDL-C levels following a return to normal weight and metabolic health. Of course, every other possible marker of health – HDL-C, triglycerides, blood sugar, body fat, blood pressure, etc. – would be much closer to optimal by the end of this journey)

 

Conclusion

If you’ve read the first eleven sections on this topic, nothing written above is surprising or even new. While the traditional paradigm continues to stress carbohydrate consumption in an effort to lower LDL-C, it is overwhelmingly clear that this approach may or may not have the desired effect but will certainly contribute to worsening metabolic health. I’ll end this series with the conclusion from my paper on cholesterol and lipid metabolism:

 

“This paper is absolutely not intended to make the argument that elevated LDL-C via an energy-driven increase in endogenous VLDL production is a metabolic state for which one need necessarily strive. Instead, this particular metabolic presentation is examined at length because it succinctly highlights the failure of the lipid-heart and diet-heart hypotheses that have undermined public health for decades. It is not a metabolic state towards which one needs to strive, but, far more importantly, it is also does not appear to be a metabolic state of which one needs to be afraid. The full body of scientific evidence, massive in both scope and depth, makes this incredibly clear.

What this paper is meant to argue is that the myopic focus on LDL-C and total cholesterol and the demonization of dietary fat must begin receding from medical, nutritional, and public consciousness if chronic health is to improve in western society. It is absolutely meant to highlight the indisputable evidence that every legitimate marker of chronic and cardiometabolic health – HDL-C, triglycerides, modified LDL particles, and others – has been repeatedly and overwhelmingly demonstrated to improve with a decrease in carbohydrate consumption. The understanding that poor triglyceride utilization, driven by insulin resistance and excess carbohydrate consumption, is the primary factor in metabolic dysfunction is crucial to recognizing the failure of conventional guidelines in addressing these risk factors. An energy deliver model of lipid metabolism best explains the available interventional evidence and wide range of lipid observations, existing in stark contrast to the abject catastrophe that is an entrenched paradigm of outdated and anti-scientific dogma pushing unsuspecting persons quickly and aggressively towards dyslipidemia, disease, and death.

The lipid-heart hypothesis has been allowed to survive for so long because the broad relationship between LCL-C and cardiovascular disease will always exist in an insulin resistant population that overconsumes carbohydrates. While the relationship is loosely valid in a diseased population, it should not be considered good enough for the purposes of preventing or especially treating cardiometabolic disease. Instead, the goal in both cases must be to prevent or reverse the underlying insulin resistance and the host of hyperglycemia-induced damages that occur alongside it. Only when this happens, when lipids are fairly viewed as an energy delivery system rather than as a disease state, can cardiovascular, metabolic, and chronic health truly be improved.”

 

 

Key takeaways

  • LDL-C is increased when a metabolically healthy person significantly reduces carbohydrate consumption, either through fasting or a low-carb diet
  • LDL-C is reduced when a person with poor metabolic health reduces carbohydrates, because previous elevations were driven by metabolic dysfunction rather than fat consumption
  • Advocacy for an increase in carbohydrate consumption has variable effects on LDL-C, a marker with little to no independent relationship with cardiovascular disease, while clearly and consistently worsening every other marker of cardiometabolic health

 




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