Jan 20

START HERE (Pinned)

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  • If you know little to nothing about cholesterol->
    • And you want to learn the basics->
      • You can check out my Simple Guide to Cholesterol series. It’s full of illustrations and is written for laypeople. Enjoy!
      • Likewise, I have this video that goes over the basic markers for cholesterol while on a low carb diet. (Pictured to the right)
    • You can enter your cholesterol numbers into our popular Report tool to check them against many risk calculations at the same time.
  • If you’re wanting to know about my research->
    • You want an overview->
    • You want the most recent breakthroughs->
      • 1/2/2018: In this latest video, I demonstrate massive changes to my LDL Cholesterol over 5 stages in a matter of days. LDL 207 to 103 mg/dL in seven days with high carb, up again to 146 on mixed, down again to 113 on high fat. (Pictured to the right)
  • If you have seen your cholesterol rise considerably on a low-carb high-fat diet (like myself):
    • You may want to first visit the FAQ.
    • I would strongly encourage you to read through this blog and my own journey revealing the Inversion Pattern. Key moments were the Identical Diet experiment and the Extreme Cholesterol Drop experiment that I wrapped around the first presentation of my data for the Ketogains Seminar.

May 18

Beyond the Lipid Hypothesis (Part 3): What’s Insulin Got to Do With It?

It Began With a Question…

In the two previous parts of this series I covered what I had learned about how foam cell and plaque formation occur, and the process and circumstances of LDL modification. Throughout learning and writing about those topics I kept thinking about Ivor Cummins’ presentation, in which he discussed insulin’s role in heart disease. Although I found the presentation compelling, it also left me with a few questions. For one, I wondered if insulin was somehow involved in the actual process of disease, or whether insulin resistance was merely just a very early red flag for an overall unhealthy system. Was insulin resistance and hyperinsulinemia a contributory factor or was it merely a proxy marker for something else going on that was causal? 

If it was a proxy marker, what exactly caused the hyperinsulinemia and insulin resistance that also resulted in increased risk for cardiovascular disease? From my understanding “overstuffed fat cells” could result in insulin resistance of fat tissue, but what of other factors like smoking or stress? Do they also cause the same problem? Perhaps these answers should have been obvious, but I wanted to really understand, which led me to digging in-depth into the research on the topic.

How does insulin relate to heart disease?

As I continued my research on heart disease risk factors, I saw that peripheral symptoms like high blood pressure 1, 2, hypertriglyceridemia 3, 4, low HDL 5, 6, high hs-CRP 7, large waist circumference 8, and others 9 that went “hand in hand” with hyperinsulinemia (and “insulin resistance”) almost every single time.  

an insulin molecule

Insulin Molecules

Indeed, when looking at people who have already had heart attacks, if  one was looking for symptoms of diabetes (de facto hyperinsulinemia) who were not already diagnosed as diabetic, a whopping 3/4 of the people were hidden diabetic (again, hyperinsulinemic by definition).10 Likewise, the reverse is true: people with diabetes 11, and perhaps also hyperinsulinemics in general12, 13, are at a higher risk of cardiovascular disease. I have seen this correlation explained away by saying it is due to the high rates of diabetes in those who are obese. But, the question nagged at me: could the hyperinsulinemia that comes with diabetes, and often with obesity, be a contributing factor to the progression of the disease on some mechanistic level?

No Smoke, No Fire

To get a clearer idea of the situation, I began by looking at the initial indications of heart disease.  I hoped to find studies that showed whether those indicators are present when insulin is not elevated, or whether an increase in insulin exposure could be associated with a progression in the disease. The information that I found, with the help of Richard Morris of the 2KetoDudes podcast, happened to address this exact issue. In short, the original studies, and additional follow up study (involving rabbits and dogs) he mentioned, demonstrate that – at least in the animals used – when the animal is prevented from making insulin the ability to develop atherosclerosis appears to cease, or is significantly lessened 14. On the flip side, once exogenous insulin is introduced into the pseudo-diabetic animals, they appear to develop atherosclerosis “normally” 15, and in the case of the dog study, it appears to only develop atherosclerosis in the arteries in which they were injected with insulin.16

As always, animal models should be taken with a grain of salt. But the proposed model does provide a framework with which to work off of when comparing it to human cases of the disease. Although the evidence so far isn’t conclusive it does appear as though, even in humans, that insulin could also be an exacerbating factor. This is supported by worsened cardiovascular outcomes for diabetics who use primarily insulin for controlling hyperglycemia compared to other therapies.17 Additionally, one study demonstrated that in those with Familial Hypercholesterolemia the difference between those who had had a Myocardial Infarction (heart attack) and those who didn’t was that those who did have a heart attack were less insulin sensitive, and had higher insulin levels.18

Looking Beyond the Plate

If hyperinsulinemia is mechanistically involved in the progression of atherosclerosis then how could the other lifestyle risk factors for atherosclerosis be explained? For example, how could atherosclerosis be a disease of hyperinsulinemia if – for example – smoking increases the risk but does not also increase insulin resistance and hyperinsulinemia? Often I heard hyperinsulinemia referred to as something influenced by diet, namely carbohydrate levels in the diet, but I wondered if this were truly the only influence. 

Non-dietary environmental factors have been said to demonstrate an effect over heart disease risk. Could it be possible that these too are influencing insulin sensitivity and levels? The first step to finding out the answer to this question was to see if non-dietary risk factors can induce hyperinsulinemia, or worsened insulin sensitivity. The four risk factors I saw referenced most frequently were stress 19, sleep 20, infection 21, and smoking 22. All of these appear to be linked to increased risk of heart disease, and thus if insulin is truly such a crucial factor they must induce hyperinsulinemia or worsen insulin resistance in some capacity. The first clue I received that this may in fact be true was Ivor Cummins mentioning on his podcast appearance on Ketogeek that smoking and infection do in fact result in insulin resistance and hyperinsulinemia. In fact, digging into these claims, I found evidence that this was true, not only for infection 23 and smoking 24, 25 but for poor sleep 26, and some evidence pointing towards acute 27 and chronic stress,28 as well. Non-dietary risk factors do appear to influence insulin sensitivity, and hyperinsulinemia.

Merely a Red Flag?

Insulin certainly appears to relate to heart disease, but is this purely association – as is likely the case with high triglycerides or high remnant cholesterol – in other words, merely a sign of trouble elsewhere? Or, could hyperinsulinemia mechanistically contribute to the worsening of heart disease? In the research I’ve done so far, I found some interesting, although nowhere close to conclusive, hints. By no means are they proven mechanisms, nor are they all encompassing ones. These are merely minuscule puzzle pieces in an overwhelmingly large puzzle, but they may provide insight into certain facets of this chronic disease.

So what are these possible factors then? I found a few choice in vitro studies which show that insulin may have some interesting effects on certain immune cells – namely macrophages, dendritic cells, and T-cells. Perhaps not-so-coincidentally some of the influence that insulin has on the immune system ties in to some aspects of atherosclerosis.

In one study, for example, insulin inhibited T-cell’s anti-inflammatory functions thereby promoting further inflammation.29 In other words, insulin kept the immune cells on “high alert” possibly providing one reason for the higher inflammation in people with developing atherosclerosis. But, insulin’s influence on immune cells stretches far further than promoting inflammation alone.

What Goes In…

As mentioned in part 1 of the series, the special immune cells macrophages, central to the formation of foam cells via the intake of damaged LDL, may actually become better able to take in more damaged particles when exposed to insulin. In vitro, macrophages exposed to insulin doubled their expression of scavenger receptors, which resulted in an 80% increase of oxidized LDL uptake.30 

A dendritic cell.

Scavenger receptors ‘recognize’ and take up damaged or apoptotic cells and other debris in the bloodstream, including damaged LDL, and an increase in their expression turns macrophages into lean-mean cleanup machines.   If modified LDL were readily available for the macrophages to take up, this would result in increased amounts of cholesterol trapped (or perhaps more accurately, “collected”) in the arteries. The effect of insulin on immune cells doesn’t appear to be limited to macrophages, as similar results were found with regards to dendritic cells (DCs), which typically act as messengers to T-cells to provide information about pathogens but can also contribute to foam cell formation. In vitro, exposure to insulin upregulated their uptake of damaged LDL, increasing their formation into foam cells, just like what occurred with macrophages.31

… Must Come Out

But, insulin’s potential influence doesn’t stop there. The study on macrophages also showed that insulin may also inhibit cholesterol efflux from cholesterol engorged macrophages.30 Cholesterol efflux, in this case mediated through a transporter called ABCA1, work to remove cholesterol from the foam cells to HDL, so it can be thrown out (if damaged), or recycled. Although foam cell formation and cholesterol efflux are two very small parts of a very complex disease, if this works similarly in vivo (in the human body) this may shed some light on one reason how hyperinsulinemia might relate to atherosclerosis, especially longer term. It would also demonstrate just how complex the life of a foam cell truly is, and how certain environments may result in pathological outcomes.

The Life and Death of a Macrophage

But beyond even the function of a macrophage, insulin appears to affect their lifespan as well. Mouse derived macrophages exposed to insulin in vitro were less likely to “retire” themselves (a process called apoptosis; essentially, cell suicide) than those that were not exposed to insulin.32 So, not only would macrophages be more active, but also active for longer than usual, in hyperinsulinemic states, assuming the mechanisms apply in the body the same (or similar to) how they do in lab studies. But just like fat cells, or liver cells, or many other cell types, macrophages can become insulin resistant. According to in vivo mouse studies, macrophages taken from obese mice were less receptive to insulin than normal (in other words insulin resistant to a degree).33 Just as anywhere else, if a macrophage becomes sufficiently insulin resistant it no longer “sees” the insulin and acts as though it isn’t there. The result, is that the ‘longevity’ effect on macrophages no longer works and they are more likely to become apoptotic when faced with certain stressors.34 A large amount of apoptotic macrophages can result in plaques with a “necrotic” core 35, which is one of the hallmarks of unstable plaques more likely to rupture. If macrophages also become more insulin resistant in humans as they do in mice, this may be one (likely of many) contributing factors to unstable plaques and disease progression.

What Does It All Mean?

Assuming that the insulin signalling effects are similar in the human body as to what occurs in test tubes, and mouse derived cells in some cases, the effects may explain some of the later stages of atherosclerosis. If the framework is correct, we are seeing a situation in which particles in the body are being damaged en masse, being pulled over, and the cholesterol stored – either until they can be disposed of and recycled or for some further purpose that is currently unknown. When inflammation – and insulin – is high, such as from environmental factors like poor diet or smoking, this process is accelerated, made more efficient, by the macrophages ability to bring in this material – damaged LDL in this case – being increased through increased expression of scavenger receptors (garbage collectors).

 

A ceaseless onslaught of damage decade after decade…

This is the job of the macrophage with scavenger receptors at hand – to pull out potentially harmful debris and dispose of it or send it back for recycling if it would be beneficial to do so. In the case of cholesterol accumulated as a result of damaged LDL being “pulled over”, it is stored within the macrophages until it can be given to HDL. But, if insulin and inflammation remain chronically high, perhaps this efflux to HDL is delayed, and perhaps even the work and longevity of macrophages is impaired as well.

The general pathways may actually be entirely appropriate in the case of acute danger and damage – just as inflammation is helpful in the shorter term to fight off infection or help heal a wound. The issue appears to be when these reactions are no longer acute. The inflammation doesn’t cease, the insulin resistance doesn’t resolve, the hyperinsulinemia worsens, the damage that initiates it all never goes away. An immune response driven to the breaking point over the course of decades.

The Story Continues

The above only touches on a miniscule amount of the influence of insulin, as the cells with insulin receptors are numerous, the effects have likely only just begun to be documented, and I’ve only just begun to look into this area. There are many other areas to explore, including how insulin resistance could influence the energy distribution system and other peripheral markers like remnant cholesterol. As such, this is not meant to be a full explanation for why and how hyperinsulinemia may exacerbate atherosclerosis, but rather to share what I have learned so far, in order to document the exploration into the topic, ready to be corrected, or updated, as time goes on.

Even of the mechanisms described here aren’t accurate, as may be the case with any in vitro or animal study, at the very least it can be said that chronically high insulin goes hand in hand with very, very bad things. If something is chronically causing insulin resistance and hyperinsulinemia (like sleep deprivation, smoking, or poor diet) it may just be better to avoid it as best as possible to preserve your health. Likewise, if one has hyperinsulinemia and signs of insulin resistance, it may be time to take a close look at the environment you’re living in, before it is too late.
Sources

1 Ferrannini, Ele, et al. “Insulin Resistance, Hyperinsulinemia, and Blood Pressure.” Hypertension, American Heart Association, Inc., 1 Nov. 1997, doi:10.1161/01.HYP.30.5.1144.

2 Zhou, Ming-Sheng, et al. “Link between Insulin Resistance and Hypertension: What Is the Evidence from Evolutionary Biology?” Diabetology & Metabolic Syndrome, BioMed Central, 31 Jan. 2014, doi:10.1186/1758-5996-6-12.

3 Lewis, Gary F, and George Steiner. “Acute Effects of Insulin in the Control of VLDL Production in Humans: Implications for the Insulin-Resistant State.” Diabetes Care, American Diabetes Association, 1 Apr. 1996, doi:10.2337/diacare.19.4.390.

4 Al-Mahmood, AK, and N Hoque. “Dyslipidemia in Insulin Resistance: Cause or Effect.”Bangladesh Journal of Medical Biochemistry, Bangladesh Journals Online, 2014, doi:10.3329/bjmb.v7i1.18576.

5 Reaven, Gerald M. “Insulin Resistance, Compensatory Hyperinsulinemia, and Coronary Heart Disease: Syndrome X Revisited.” Wiley Online Library, American Cancer Society, 2 June 2017, 10.1136/bmjsem-2017-000236.

6 Saku, Keijiro, et al. “Hyperinsulinemic Hypoalphalipoproteinemia as a New Indicator for Coronary Heart Disease.” Journal of the American College of Cardiology, vol. 34, no. 5, Nov. 1999, pp. 1443–51. CrossRef, doi:10.1016/S0735-1097(99)00372-1.

7 Yang, June S., et al. “Association between Fasting Insulin and High-Sensitivity C Reactive Protein in Korean Adults.” BMJ Open Sport & Exercise Medicine, vol. 3, no. 1, June 2017, p. e000236. CrossRef, doi:10.1136/bmjsem-2017-000236.

8 Tabata, Shinji, et al. “Waist Circumference and Insulin Resistance: a Cross-Sectional Study of Japanese Men.” BMC Endocrine Disorders, BioMed Central, 12 Jan. 2009, doi:10.1186/1472-6823-9-1.

9 Duvillard, L., et al. “Chronic Hyperinsulinemia Does Not Increase the Production Rate of High-Density Lipoprotein Apolipoprotein AI: Evidence From a Kinetic Study in Patients With Insulinoma.” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 33, no. 10, Oct. 2013, pp. 2460–65. CrossRef, doi:10.1161/ATVBAHA.113.301597.

10 Gyberg, Viveca, et al. “Screening for Dysglycaemia in Patients with Coronary Artery Disease as Reflected by Fasting Glucose, Oral Glucose Tolerance Test, and HbA1c: A Report from EUROASPIRE IV–a Survey from the European Society of Cardiology.” European Heart Journal, vol. 36, no. 19, May 2015, pp. 1171–77. PubMed, doi:10.1093/eurheartj/ehv008.

11 Stamler, J., et al. “Diabetes, Other Risk Factors, and 12-Yr Cardiovascular Mortality for Men Screened in the Multiple Risk Factor Intervention Trial.” Diabetes Care, vol. 16, no. 2, Feb. 1993, pp. 434–44. CrossRef, doi:10.2337/diacare.16.2.434.

12 Lakka, Hanna-Maaria, et al. “Hyperinsulinemia and the Risk of Cardiovascular Death and Acute Coronary and Cerebrovascular Events in Men: The Kuopio Ischaemic Heart Disease Risk Factor Study.” Archives of Internal Medicine, vol. 160, no. 8, Apr. 2000, p. 1160. CrossRef, doi:10.1001/archinte.160.8.1160.

13 Després, Jean-Pierre, et al. “Hyperinsulinemia as an Independent Risk Factor for Ischemic Heart Disease.” New England Journal of Medicine, vol. 334, no. 15, Apr. 1996, pp. 952–58. CrossRef, doi:10.1056/NEJM199604113341504.

14 Duff, G. L., and G. C. McMILLAN. “The Effect of Alloxan Diabetes on Experimental Cholesterol Atherosclerosis in the Rabbit.” The Journal of Experimental Medicine, vol. 89, no. 6, June 1949, pp. 611–30.

15 Duff, G. L., et al. “The Effect of Alloxan Diabetes on Experimental Cholesterol Atherosclerosis in the Rabbit. IV. The Effect of Insulin Therapy on the Inhibition of Atherosclerosis in the Alloxan-Diabetic Rabbit.” The Journal of Experimental Medicine, vol. 100, no. 4, Oct. 1954, pp. 371–80.

16 Cruz, A. B., et al. “Effect of Intra-Arterial Insulin on Tissue Cholesterol and Fatty Acids in Alloxan-Diabetic Dogs.” Circulation Research, vol. 9, no. 1, Jan. 1961, pp. 39–43. CrossRef, doi:10.1161/01.RES.9.1.39.

17 Currie, Craig J., et al. “Mortality and Other Important Diabetes-Related Outcomes With Insulin vs Other Antihyperglycemic Therapies in Type 2 Diabetes.” The Journal of Clinical Endocrinology & Metabolism, vol. 98, no. 2, Feb. 2013, pp. 668–77. CrossRef, doi:10.1210/jc.2012-3042.

18Sebestjen, M., et al. “Fibrinolytic Parameters and Insulin Resistance in Young Survivors of Myocardial Infarction with Heterozygous Familial Hypercholesterolemia.” Wiener Klinische Wochenschrift, vol. 113, no. 3–4, Feb. 2001, pp. 113–18.

19 Stress and Heart Health. American Heart Association, 2014, www.heart.org/HEARTORG/HealthyLiving/StressManagement/HowDoesStressAffectYou/Stress-and-Heart-Health_UCM_437370_Article.jsp.

20 American Heart Association. “Quality of Sleep Could Increase Heart Risk — Go Red For Women.” Go Red For Women, 13 Mar. 2018, www.goredforwomen.org/about-heart-disease/heart_disease_research-subcategory/quality-of-sleep-could-increase-heart-risk/.

21 Roivainen, M., et al. “Infections, Inflammation, and the Risk of Coronary Heart Disease.” Circulation, vol. 101, no. 3, Jan. 2000, pp. 252–57. Crossref, doi:10.1161/01.CIR.101.3.252.

22 Smoking & Cardiovascular Disease (Heart Disease). American Heart Association, www.heart.org/HEARTORG/HealthyLiving/QuitSmoking/QuittingResources/Smoking-Cardiovascular-Disease_UCM_305187_Article.jsp.

23 Sammalkorpi, K. “Glucose Intolerance in Acute Infections.” Journal of Internal Medicine, vol. 225, no. 1, Jan. 1989, pp. 15–19.

24 Facchini, F. S., et al. “Insulin Resistance and Cigarette Smoking.” The Lancet, vol. 339, no. 8802, May 1992, pp. 1128–30. Crossref, doi:10.1016/0140-6736(92)90730-Q.

25 Reaven, Gerald, and Philip S. Tsao. “Insulin Resistance and Compensatory Hyperinsulinemia: The Key Player between Cigarette Smoking and Cardiovascular Disease?” Journal of the American College of Cardiology, vol. 41, no. 6, Mar. 2003, pp. 1044–47. Crossref, doi:10.1016/S0735-1097(02)02982-0.

26 Broussard, Josiane L., et al. “Impaired Insulin Signaling in Human Adipocytes After Experimental Sleep Restriction: A Randomized, Crossover Study.” Annals of Internal Medicine, vol. 157, no. 8, Oct. 2012, p. 549. Crossref, doi:10.7326/0003-4819-157-8-201210160-00005.

27 Shiloah, E., et al. “Effect of Acute Psychotic Stress in Nondiabetic Subjects on -Cell Function and Insulin Sensitivity.” Diabetes Care, vol. 26, no. 5, May 2003, pp. 1462–67. Crossref, doi:10.2337/diacare.26.5.1462.

28 Aschbacher, Kirstin, et al. “Chronic Stress Increases Vulnerability to Diet-Related Abdominal Fat, Oxidative Stress, and Metabolic Risk.” Psychoneuroendocrinology, vol. 46, Aug. 2014, pp. 14–22. Crossref, doi:10.1016/j.psyneuen.2014.04.003.

29 Han, J. M., et al. “Insulin Inhibits IL-10-Mediated Regulatory T Cell Function: Implications for Obesity.” The Journal of Immunology, vol. 192, no. 2, Jan. 2014, pp. 623–29. Crossref, doi:10.4049/jimmunol.1302181.

30 Park, Young M., et al. “Insulin Promotes Macrophage Foam Cell Formation: Potential Implications in Diabetes-Related Atherosclerosis.” Laboratory Investigation, vol. 92, no. 8, Aug. 2012, pp. 1171–80. Crossref, doi:10.1038/labinvest.2012.74.

31 Lu, Hao, et al. “Insulin Enhances Dendritic Cell Maturation and Scavenger Receptor-Mediated Uptake of Oxidised Low-Density Lipoprotein.” Journal of Diabetes and Its Complications, vol. 29, no. 4, May 2015, pp. 465–71. Crossref, doi:10.1016/j.jdiacomp.2015.03.005.

32 Iida, K. T. “Insulin Inhibits Apoptosis of Macrophage Cell Line, THP-1 Cells, via Phosphatidylinositol-3-Kinase-Dependent Pathway.” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 22, no. 3, Mar. 2002, pp. 380–86. Crossref, doi:10.1161/hq0302.105272.

33 Liang, Chien-Ping, et al. “Increased CD36 Protein as a Response to Defective Insulin Signaling in Macrophages.” Journal of Clinical Investigation, vol. 113, no. 5, Mar. 2004, pp. 764–73. Crossref, doi:10.1172/JCI19528.

34 Han, Seongah, et al. “Macrophage Insulin Receptor Deficiency Increases ER Stress-Induced Apoptosis and Necrotic Core Formation in Advanced Atherosclerotic Lesions.” Cell Metabolism, vol. 3, no. 4, Apr. 2006, pp. 257–66. Crossref, doi:10.1016/j.cmet.2006.02.008.

35 Seimon, Tracie, and Ira Tabas. “Mechanisms and Consequences of Macrophage Apoptosis in Atherosclerosis.” Journal of Lipid Research, vol. 50, no. Supplement, Apr. 2009, pp. S382–87. Crossref, doi:10.1194/jlr.R800032-JLR200.

May 17

Low Carb Breck ’18 and an Update on Remnant Cholesterol

[UPDATE May 18th, 2018: The very gracious Kerry Ireland has transcribed the video for us — see below]

My presentation at Low Carb Breck is finally up!

 

Transcription for Cholesterol is a Passenger, Not a Driver

Cholesterol is a Passenger, Not a Driver

Transcript of https://www.youtube.com/watch?v=0LuKwsz9Woc

Transcribed by Kerry Ireland from https://www.facebook.com/kerryscomms/

Published 12 May 2018
Dave Feldman
CholesterolCode.com

Video Length—28:16

_________________________________________________________________________________

<start of video>

www.lowcarbdownunder.com.au

Animation: Logo for Low Carb Down Under

[Slide: Low Carb Brek 2018]

00:12

[Slide: Cholesterol is a Passenger, Not a Driver]

00:19

[Dave starts]

Alright guys. I’ve got something really special for you today. So, buckle up. Because I have put a lot of work into putting all of the things I know into a single analogy.

00:28

First of all, conflicts of interests. None

But I will tell you about a great bunch of great individuals at the end of the talk.

00:34

[Slide: Bio]

My bio

I don’t really want to spend a lot of time on. I’m a software engineer. I’m obsessed with lipids, conducting crazy n=1 experiments. You could just google Dave Feldman and cholesterol. You’ll find plenty on me.

0:45

I like to call myself a cholesterol traveller now because I’ve move lipid numbers up and down several times through a series of experiments and I’ve brought my LDL as high as 368, down to 98, all since the last time I was here. But how am I doing this?

1:03

Well, I like to say that I’m working from a theory that seems to continue to keep on working. And what I’m happy about is that I managed to solve the two biggest problems. The two biggest problems are that I am talking to two audiences all the time.

1:14

[Slide: Two audiences, two problems]

Fortunately, for the experts, they prefer that I don’t simplify the language and to be fair, they’ve got a good point.

But I also can’t tell an entire audience of lay people all about lipidology very easily. I am still kind of learning about it myself.

So, I am excited, because this analogy will be a way for me to get you the abstraction that I see, the way that I see it. Because the most important message is the one I want to get across to you as to what cholesterol is a passenger in.

So, without further ado, I bring you a wonderful story.

1:48

[Slide: A tale of five problems.]

So, in a dystopian future, our country is hit with a massive flood. And the president turns to the secretary of engineering, that’s a future cabinet position, by the way.

He says, “Ok, well the houses are fine because it’s the future and everyone can work from their home. Its alright but we still need to be able to get food to them. How are we going to do that?”

The engineer says, “Actually, its fine. We have got a really large company on the shoreline that can get the food from outside the country and ship it inside. And that’s the Intestine Delivery Co. It has exclusive rights to get all of the food that’s gathered from the outside and it has special ships, these brown ships (I’m keeping it colour coded, so remember ‘brown’), to deliver that food around to all of these different houses.

Fantastic. Fantastic. But, after a little while they realise that it is still kind of uneven. Some of the houses are getting it sooner than others and unfortunately some of the houses aren’t ready to use the food at the time that they need it. So that brought us to the second problem—a lack of local storage.

The engineer says, “No problem. No problem. We are going to have these food banks that we’ll have all around these different neighbourhoods and then that way, as the ships come around, sure, they’ll feed food to the houses. On top of that they’ll re-up the adipose food banks.”

Fantastic.

Now we come to the third and most serious problem. And, that is that we still have mis-distribution. These neighbourhoods aren’t able to talk to each other. The adipose food bank can sometimes have enough, sometimes it doesn’t, sometimes the ships have enough to carry and sometimes they don’t. And so, we have not got to deal with the hardest problem of all—balance distribution.

For this, the Secretary of Engineering worked with his whole team and he got a lot of work done and he says, “We just need one central player.”

I give you the Liver Delivery Company.

This one is great because, guess what, not only will all of the brown ships eventually make their way there but also all of the food that got lost and spilled out into the water and no-one could capture. That will all eventually make their way here as well. They have their own special purple boats and that too can deliver this food all around to the different neighbourhoods.

The President is like, “This is fantastic. So let me see if I got this straight. Food that is coming from outside the country, that’s coming into the Intestine [Delivery Co], well then that is actually going to be loaded onto the brown ships, that’s going to be distributed. And, then all of the stuff that is in the food banks that spills off or spills off from trying to deliver it to the different houses, that’s also going to make its way to the Liver [Delivery Co] and that, those purple boats are going to counter balance the amount that’s coming from the brown boats?”

“Yes.” The Engineer says, “That’s exactly right. In fact, when there’s more that’s coming in from the outside, then that actually means that there’ll be less that needs to get pulled from the food banks and, ultimately, delivered via the Liver [Delivery Co]. Likewise, it counterbalances in the other direction.”

And surprise, I’ve been talking about Lipids this whole time. This is why I don’t have a shining future as a magician.

05:03

[Slide: Lipid Analogy Legend]

Yes, the houses were cells.

The fatty acids were the boxes. And, of course, if you have three of those boxes, you have triglycerides.

That, of course, was energy being distributed everywhere. But the main thing that I wanted you to focus on, the reason I really wanted to drive this home, is all the way up to this point my story has been about only one thing—distributing food, which was actually just fat-based energy.

So, what were the means of delivering the food?

05:28

[Slide: Schematic]

Well, on the brown line we’ve got Chylomicrons. Chylomicrons start with a whole bunch of fat-based energy. They eventually become Chylomicron remnants and where do they end up? They end up back at the Liver. The Liver has its own line, which has VLDLs and IDLs. Once they are emptied of all of their energy, they return back but there is something missing from this schematic of course.

But remember this is the energy-delivery portion. If you are watching this on a video, I would be fine if you paused it right now, pondered that for a day, and come back to this next part. Because the moment I bring up the “C” word everything is going to fall apart because it has too much attention associated with it.

So, now, let’s get to the FOURTH problem—support.

[Slide: 4th Problem: Support]

The President turns back to the Secretary of Engineering and says, “You’ve been doing such a great job but unfortunately the flood wiped out all of our emergency services. Do you think there is any way, you with your smarts, could figure out a way that we can still get that support around to the houses?”

He said, “Yeah. You know what we’ll do, since these purple boats are the most present of all the boats that are sitting around in our country, we are going to outfit them with the special care package. Now, granted, their first job will still be delivery. The first job is still delivery. The second job is support.”

6:55

Naturally what I’m talking about here is cholesterol.

So, I want to reemphasise this again because this may be the most important slide and you might not realise it.

First job is delivery. It doesn’t both deliver and support. It first delivers and then it supports.

That’s extremely relevant to the rest of this analogy.

07:14

[Slide: Analogy/Fat-based energy]

So, without question, as we’re watching in the first job, we’re seeing this counter balance between chylomicrons and VLDLs in delivering fat-based energy. And then, after the chylomicrons deliver their energy they have clocked out, they’re done. The VLDLs take about as much time to deliver the energy and they then have a second job. They hang out in the neighbourhood. They chase off pathogens. They get endocytosed into the cells for additional repair, right? They’ve got a second gig and they take that second gig pretty seriously.

07:45

[Slide: Schematic]

So, now we can add the LDL to our schematic and the HDL to our schematic even though I haven’t talked about it yet you just need to know this, with this little dotted line I’m talking about two different sides. Energy delivery on one side. Support on the other side. Very relevant when you are looking at these cool graphs I get to make that you’ll see in other videos.

08:04

[Slide: Graph entitled, “Three-day average of dietary fat, with a two-day gap vs LDL-P cholesterol”]

This one, of course, I showed at the last Breckenridge talk, where I was pointing out that I was able to have dietary fat on a three-day average and isolated about right when I needed to do it in order to get resulting LDL-P. LDL-P the support boat, right?

8:23

Why was I able to do that, do I theorise? Well, now you are starting to get it. You are starting to get the abstraction. I had less dietary fat coming in from the Intestine Delivery Co, which resulted in my body needing to up-regulate VLDLs. What do VLDLs eventually clock out and become? LDL-P, that’s right.

Likewise, when my dietary fat was high, sure enough, my LDL-P was low.

So, don’t take my data for it.

Let’s talk about the emerging data in the Low Carb High Fat Community.

8:55

[Slide: Emerging Patters of LCHF Cholesterol]

Now, I use to lament that Doctors that I was meeting early on, low carb doctors, they had this great wealth of data from their own patients on cholesterol numbers. And, in the spirit of being careful what you wish for, I started this website and now I see, like, a dozen or more lipid profiles almost every single day. Like it has really ramped up to get to ridiculous levels. But the neat thing is that we can now see the patterns that I was looking for in the first place. You might be surprised to find this out but, metabolically healthy low carbers (the key is that they are metabolically healthy). You would think, as I certainly did, as you go from overweight to lean what would happen to your cholesterol? It would go down, right? It would go down.

But it doesn’t! It actually goes up.

But what about if you go from sedentary to high energy, high energy demands? Anyone?

It goes up!

It goes up!

Now, I keep looking at this from the abstraction I just showed you and I keep thinking, wait a sec. If the triglycerides are still staying low but I’m seeing more of the purple boats, should I be concerned? I don’t know that I should.

10.13

So this is when the hypothesis was born. It’s the one I’ve been working on for quite a long time now. This is an overly brief version. Basically, high LDL cholesterol and particle count on a low carb high fat diet can be a reflection of higher VLDL secretion and use. The key is ‘and use’. These guys are actually needing to drop off these triglycerides at a higher rate and therefore becoming low density lipoproteins. Wouldn’t it be great if we had a profile that showcased this perfectly?

Some of you already know where I’m about to go.

We now have what we call the Lean Mass Hyper-responder.

10:47

A hyper responder if someone who goes on a low carb high fat diet and they see their cholesterol go up substantially. Lean mass hyper responder was something I identified back in July. I wrote an article about it and honestly it was kind of a ‘testing the waters’ thing. I wanted to write this article and I wanted to see what the response was. I half expected a lot of people to write in saying, “No. No. No. Actually I have an LDL of 200 or I have a triglycerides below 70. I am actually very sedentary. I have all of these other issues. Etc.”

No. On the contrary, I got inundated. This is the most commented on post of any of that I’ve had on the blog, thus far. There are people all around the world, and many of you medical professionals on low carb, you probably know a few, that are a lean mass hyper responders. They tend to be very lean. They tend to be very athletic.

11:38

[Slide: Tear Down this Hypothesis]

Now, this all sounds great.

What’s the first thing you want to do?

And this is why I’m so glad that Ivor took place before me. We are all about the root cause.

Do you want to know how you know an engineer … they are their own worst critic. They have to be because their fellow engineering friends are constantly challenging them. They need to challenge themselves first.

I love this quote:

11.59

[Slide: The great tragedy of science—the slaying of a beautiful hypothesis by an ugly fact. Thomas Huxley]

BRING ON THE UGLY FACTS

One of the advantages I have been able to have with the little bit of my name equity moving up is I’m actually nearing about 10,000 followers on Twitter. I get to actually get responses to the people that follow me and they’re not all fans of low carb high fat, let me tell yah.

So, I put this out.

12:23

Question for those in the know: Are there any studies that show high LDL with high CVD in spite of having low triglycerides?

And, in doing so, I managed to get one response from Dr T. Hats off to Dr T for this one. From our friends at Framingham. And, actually, I really liked this sample size. Because it was people that didn’t already have cardio vascular disease and after excluding users for lipid-lowering therapy. That’s a big deal to me. I don’t like gene or drug studies. That’s a talk I can do all by itself.

Well, sure enough. I get into the chart. And I’m like, ok, so their baseline here, they have it at an odds ratio zeroed out at triglycerides below 100, LDL below 100, Low HDL-C. Which by the way was below 40 for men, below 50 for women.

Naturally, as you would expect, if you have a high HDL-C, odds ratio being lower is better, you have the best version, if your triglycerides are below 100, your LDL is below 100 and you have high HDL. That’s like the ideal profile, right?

So, we would expect, if LDL got flipped and we started looking at 100 and above, the odds ratio would probably also flip, right? … go to like 1.3 and 1.4. No! Actually, it’s the next-best risk marker and its right next to it at 0.7.

Well, ok. Maybe this was including a lot of people that had an LDL of 105 and 110.

Fortunately, though, they also had a category for people who had an LDL of 130 and above. How many people get prescribed statins for 130 and above? That’s the high risk category, right?

14:00

Actually, its identical. It’s a 0.7.

As you can see on the confidence interval, on the right side, this isn’t a fantastically large study, but unfortunately I wasn’t able to find any fantastically large studies.

I got really ornery and I built this graphic.

14:13

I pushed it around on social media. I really, genuinely, and not in a trolly kind of way, truly, trying to ping all of the biggest pro lowering LDL experts that I know.

If you ever get bored you can look through my twitter feed you can see me doing this.

I said, “Look. Look. Look. You guys are saying we shouldn’t take comfort in having low triglycerides and high HDL Cholesterol when our LDL cholesterol is high. Can you bring me just one study? One study? The best study you can. So long as it’s not a drug or gene study. One that shows that we have higher rates of cardio-vascular disease.”

Anyone want to guess how many studies I got?

Zero

I am actually hoping, genuinely hoping, that this feed in this video will help inspire some people to bring more into comments. I’m sure there’s a chance that there’s some out there. But, I still haven’t seen it yet.

15:05

[Slide: Remnant Cholesterol]

What I am thankful for is that it brought me around to something that most people don’t know about even in the low carb community. It’s called ‘Remnant Cholesterol’.

15:15

[Slide: Remnant Cholesterol, from Wikipedia]

I think Wikipedia summarises this really well.

They say, look, remnant cholesterol, also known as remnant lipoprotein, is a very atherogenic lipoprotein composed primarily of very low-density lipoproteins, that’s these guys. And intermediate-density lipoproteins, that’s these guys.

“Stated another way, remnant cholesterol is all plasma cholesterol that is not LDL cholesterol or HDL cholesterol.”

This was a big moment for me because before I read any further studies, I said this is actually a perfect match, for what it is that I believe is ultimately the root cause of the disease.

Let’s go back to our analogy again. Right.

I’m not worried about this. What am I worried about? I’m worried about this. There’s not good engineering reason, and I state this all of the time, for a lot of energy to be parked in the blood.

I cannot think of one and I have not had anyone present one to me yet.

I have to emphasise, once again, when you think of things from a first job, second job, is it really that high levels of triglycerides are atherogenic or even, as the remnant cholesterol people are saying, that it’s a more atherogenic particle? I don’t think so. I think it is a failure of the VLDLs from being able to drop off energy, fat-based energy, version of triglycerides.

What do you suppose remnant cholesterol is highly correlated with?

Well, I’ll actually drive it home. I forgot I had this slide in here too. So I’ll have to fit this one in to really drive this point home.

VLDL to LDL lifecycle

How long do you think that VLDLs last in the blood in a normal lipidemic person?

Any guesses?

An hour! Yes!

30 to 60 minutes

How long for IDL?

Less than 30 minutes.

Now, if it doesn’t get absorbed by the liver, how long do they stay in that support role as a low-density lipoprotein?

2 to 4 days.

In other words, 98-99% of the rest of their lifespan is for that long.

So, yes, where I was going was [inaudible], sure enough it correlates closely with insulin resistance.

17:28

[Slide: Plasma RLP-C in Secondary Dyslipidaemia—Insulin Resistance]

In fact, remnant cholesterol correlates much closer to insulin resistance than what I have seen with LDL, as Ivor brought up.

17:34

[Slide: Remnant cholesterol as a cause of ischemic heart disease]

Same thing with ischemic heart disease. Notice, by the way, as HDL is going down, remnant cholesterol is going up, even with LDL hardly moving at all.

17:43

[Slide: Premature myocardial infarction is strongly associated with increased levels of remnant cholesterol]

Myocardial infarction: Remnant cholesterol was the lipid fraction most associated with premature myocardial infarction.

17:55

[Slide: Extreme Non-fasting Remnant Cholesterol vs Extreme LDL Cholesterol as Contributors to Cardiovascular Disease and All-Cause Mortality …]

My favourite of all. All-cause mortality

Which graph do you think you would like to be in?

The LDL moving up or on the Remnant Cholesterol moving up?

18:04

[Slide: A Simple Comparison]

Here’s a simple comparison. Someone I’ve worked with a lot throughout this whole period. They had about 177 total cholesterol and an LDL-C of 121. HDL 40. HDL is a little bit low but triglycerides are 80.

That looks pretty good, right?

And now on low carb high fat, two and a half years later, they have a total cholesterol of 284, an LDL-C of 201, HDL-C of 71 and triglycerides of 58. This is actually at the cut points of a lean-mass hyper-responder.

Yet, on the left side, they have remnant cholesterol of 16 mg/dl. They actually have a lower remnant cholesterol on the right side even for as high as the cholesterol numbers are.

Well, let me give you a little bit more of a challenge. After I reveal who this person is. (Slide reveals it is Dave Feldman, the speaker)

18:56

[Slide: Craig Moffit, 40]

I want to talk about Craig Moffit who, by the way, contributes a lot to our website. Thank you, Craig.

He also will have some data that I will share with you in a second.

Would you guess that he is a lean-mass hyper-responder? Yeah. He is actually very thin and very athletic.

His total cholesterol is 457 mg/dl

(Audience gasps)

His LDL-C is 335 mg/dl

His HDL-C is 109

Triglycerides are 67

He is the picture of a far-end lean-mass hyper-responder so you would at least expect remnant cholesterol to probably go to scale, right? Like it’s probably a bit higher, anyway? You could probably do the math right now.

Actually, 13 mg/dl. It’s actually just one pip higher than mine on my last test.

19:48

[Slide: How do you calculate remnant cholesterol?]

How do you calculate remnant cholesterol?

There is a caveat to that, which I’ll say in a second.

Yes, you just take your total cholesterol, you subtract your LDL, you subtract your HDL.

You can be forgiven if you thought that actually this whole time total cholesterol was those two added together. No. That reminder is those VLDL boats, those IDL boats and specifically the cargo of cholesterol that is inside them.

The caveat that I want to fit in, a lot of you already know this. LDL is typically a calculated number from the Friedewald equation. So that is a little bit of a confounder, but all of the studies are built on the Friedewald equation. In that sense, there’s a little bit of fuzziness. Generally speaking, I tend to find this looks pretty good.

This is what’s neat.

20:27

[Slide: CholesterolCode Data for Remnant Cholesterol]

I literally calculated this, just morning.

CholesterolCode Data from our site, for remnant cholesterol, we have a whole bunch of submitted labs that people have and I created the criteria of an LDL cholesterol of 200 mg/dl or above, right. That, by the way is well into range of familial hypercholesterolemia. Which means your doctor will give you two medications before you can leave the office. Right? There’s probably statin police around the corner. He just calls them in, or something.

With triglycerides of at least 10mg/dl or below. What’s neat is we now have a lot of entries, just on the site, of 456 (total). Of that, I found 138 that met this criteria. How many of those hyper-responders who were typically on a high fat low carb diet for the highest, medium highest and medium risk categories combined: we found 9. For the Medium low risk category: 44. For the lowest quintile of remnant cholesterol: 84.

So over 90% of those who have submitted in concern to our site about their high levels of LDL cholesterol, and in particular I am picking them out for those that have over 200 and above. Over 90% of them have very low remnant cholesterol.

21:53

[Slide: Caveats]

Now, I do have some caveats.

This presentation doesn’t discuss the influence of glucose and glycogen and so forth. And if you follow my work, you know, and my whole phase 2, is based on being able to manipulate that as well.

Also, I do believe there are bad reasons for higher LDL cholesterol, however, they are typically related to still having higher triglycerides and, for that matter, also with HDL, you do want to keep an eye on low HDL. That’s actually genetically influenced.

So, how am I doing on time?

Ten Minutes!!! Yesssss!!!!!!

OK, I’m excited about that. That analogy I worked on for a long time.

This is great. We can actually look back at the inversion pattern that I had from the prior talk

22:38

[Slide: The Inversion Pattern Revisited]

and you guys probably remember this for those who have already seen it. For those that haven’t, real quick.

22:43

[Slide: Dietary Fat Inversion]

The inversion pattern as I’ve found in my data. I’ve shown this over and over again with the large number. I’ve had a total of 88 blood draws at this point. Insane engineer.

As it turns out, if I were to take my cholesterol this morning, then I would look back to the three days of dietary fat and I would find that they had the greatest influence on what my LDL-C would be and likewise, it’s also a three-day window for LDL-P but there’s a two-day gap.

Craig Moffit, I didn’t get a chance to include it, he actually replicated this experiment entirely with four different data points. You can look it up on the CholesterolCode.com site where he also talks through. I don’t have the slides for it but he basically did exactly the same thing and proved the same inversion pattern for both LDL-C and LDL-P.

What’s neat is, in the summer of last year, we got a bunch of people together for the KetoFest cholesterol experiment, which by the way just opened its kick starter, small plug.

23:45

[Slide: Ketofest Cholesterol Experiment—July 11–17, 2017]

July 11-17, we managed to get a bunch of people to eat a very low-calorie but still ketogenic for three days and everybody did a water fast. Then we all took a blood test. One blood test. Then gorged out on fat for three days and took a second blood test.

What do you suppose happened?

First, I posted the hypothesis before the experiment began.

I said I suspected that it would get much lower.

24:10

[Slide: Photo]

I’m thankful for PTS diagnostics who helped pay for all of the bloodwork.

We got people like this guy who helped to contribute and people like these people to eat a bunch of the fat. They were all a part of it.

Voila!

[Slide: “Broken Ladder” Graph]

We ended up with what I like to call the ‘broken ladder’.

23:22

You see on the left side, the Friday, of all of the tests that were drawn. You see on the right side the Monday of the second of all of the tests that were drawn and all that fat that was eaten in between.

What do you see most of those lines doing? Going up? Down? Sideways?

Actually, about 19 had a decrease of between 5 to 38% of their LDL cholesterol. Only 3 had an increase. It was only 1 or 2%.

Now, you look across the board, if you take them all across the board …

25:57

[Slide: Average change in LDL-C]

… there’s a drop of 16% of their LDL-C in three days for a total [drop] of 25.7 mg/dl.

25:07

[Slide: The Feldman Protocol one year later]

So, let’s look at that protocol for the last time I’d done this at Breckenridge, that part on the left is actually what I had shown from before. We had had a 100% success rate, so far, and that was when we had a lot less people. Now it is approximately 85% of a success rate.

There are some caveats that we found that I think I also have a slide here for, but at that time nine had tried out of curiosity, 10 had used it to get their doctor off their back.

Well, between Comments on twitter, Facebook, CholesterolCode, Reddit, blogs, we have somewhere over 100 people who have tried it. We’ve lost count. But it’s absolutely amazing that it is still holding to that 85% success rate given how many people have done this.

Last time, at least 4 people had used this to improve their life insurance rate. At my last count, I found 13. All low carbers. Again, I kind of blame Jeffrey Gerber. He was the first to tweet out about that.

26:01

[Slide: Possible Protocol Pitfalls]

So, look, here’s the possible protocol pitfalls if you are considering doing the Feldman protocol.

Anecdotally, these anecdotes these elements have been the most common.

Use of MCT or coconut oil, we kind of discourage because that seems to be a confounder.

This is also a new one. Use of coffee. Sorry. It seems like coffee does in fact have some different effects on the lipids and has had impacts for our protocol results.

Also, some with hypothyroidism appear to have some unexpected results and that’s also worth pointing out.

26:28

[Slide: Summary]

So, in summary, more VLDLs may be trafficked on a low carb high fat diet for fuel.

I know I haven’t talked about ketones. I know I haven’t talked about glucose. But I’m telling you it’s a big elephant in the room that nobody talks about. You get a lot of direct delivery of fatty acids via VLDLs. And, this may result in a higher presence of its later stage as an LDL particle, resulting in, of course, in what it carries, the passenger—LDL cholesterol, right. This may not only be appropriate but may be mechanistically necessary. This all relates back to why there’s so much overlap with remnant cholesterol, even though they are coming to very different conclusions than I am. I don’t believe VLDL and IDL … let me just put it this way. I don’t believe any lipoprotein is atherogenic. I believe broken systems are atherogenic.

So, remnant cholesterol is a far stronger indicator of risk of both heart disease and all-cause mortality than LDL-C.

Finally, remnant cholesterol typically drops on a low carb diet.

I think the reason that there hasn’t been a lot of attention on remnant cholesterol is because there’s not a drug for it yet.

(audience laughs)

It’s just my opinion.

27:43

[Slide: Thank you, Patrons!]

I wanted to thank my Patrons because I don’t accept any money from any business entity. I have made that a rule up front because I didn’t want to compromise the integrity of the data.

I am honoured to have 109 people who directly pull money out of their pockets, small amounts, that actually allow for this research to happen. So, please, if you could thank them for me.

(applause)

28:10

[Slide: Thank you for watching]

Thank you so much. I hope you enjoyed this.

<ends>

A Quick Update on Remnant Cholesterol

I wanted to give a reminder that I’m still very early on in my research of Remnant Cholesterol. We’re working through a lot of studies to find what is most applicable.

Many have asked me for what range I consider best, and I continue to point out that my opinion is still very new on this and subject to change.

So take it with a grain of salt for now, but I’d speculate the following:

  • Below 20 mg/dL (0.49 mmol/L) is generally optimal
  • Around 20-30 mg/dL (0.49-0.78 mmol/L) is generally medium risk
  • Above 30 mg/dL (.78 mmol/L) is higher risk

I will have a follow-up article on Remnant Cholesterol soon that will be much more in-depth and probably likely to refine the cut points above.

May 11

Top Ten Lipid Related Studies

Note from Dave–

For the record, Siobhan reads many more studies than I do — and probably you too. This is why I call her our Senior Researcher here at CC. So I asked if she had to narrow down a “Top 10” list for our readers, and as always, she did not disappoint. Enjoy!

 

10. Total Cholesterol Inversely Associated with ACM In Women

Is the use of cholesterol in mortality risk algorithms in clinical guidelines valid? Ten years prospective data from the Norwegian HUNT 2 study.

doi:10.1111/j.1365-2753.2011.01767.x.

The Reason: The study looked at death rates from all causes (All-Cause Mortality; ACM) in relation to total cholesterol levels, and even went so far as to stratify by gender. For women, the higher the total cholesterol the lower the All-Cause Mortality, and Cardiovascular Disease Mortality. For men, it was a “U” shaped curve (higher mortality at both higher and lower ends of total cholesterol). This highlights how potentially complicated cholesterol is as a risk factor and the potential hazards of applying results from one group (men) to the entire population which may result in potentially damaging outcomes.

“If our findings are generalizable, clinical and public health recommendations regarding the ‘dangers’ of cholesterol should be revised. This is especially true for women, for whom moderately elevated cholesterol (by current standards) may prove to be not only harmless but even beneficial.”

9. Lipoprotein(a) Structure and Function Review

Lipoprotein(a) and its role in inflammation, atherosclerosis and malignancies

doi:10.1007/s11789-017-0084-1

 

The Reason: While there are still many things to learn about Lipoprotein(a), a review paper covering what we do know so far can clear up many misunderstandings before they appear. This paper also covers a little bit of Lp(a)’s wound healing and tissue repair functions, as well as general structure.

“Earlier works agree that Lp(a) accelerates wound healing and tissue repair, and therefore Lp(a) provided an evolutionary advantage to humans […]”

8. Undiagnosed Diabetes in People with Heart Disease

Screening for dysglycaemia in patients with coronary artery disease as reflected by fasting glucose, oral glucose tolerance test, and HbA1c

doi:10.1093/eurheartj/ehv008

 

The Reason: While not strictly related to the lipid system, heart disease is a topic that comes up frequently when studying lipoproteins. This study helps provide more context to what is going on “under the hood” in those with heart disease – as it demonstrates that when testing for signs of diabetes in those with heart disease, a full ¾ of them who had been considered “non-diabetic” previously either were diabetic, or were at high risk of developing diabetes. Take note that the testing they had done didn’t include insulin, so whether the remaining quarter of people were truly nondiabetic remains unknown.

“In addition, the total proportion of patients identified with diabetes and other forms of dysglycemia varied from 90% using the ADA criteria for FPG + HbA1c to 73% using the WHO criteria for OGTT = FPG + 2hPG.”

7. Lipoproteins as Part of the Immune System

Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host.

doi:10.1194/jlr.R300019-JLR200

 

The Reason: This review covers a topic that I rarely ever see addressed – the involvement of lipoproteins in the immune system. Not only do lipoproteins bind to pathogens to help with their disposal, and help with repair after injury, but they are also upregulated during inflammation and infection. These lipid profiles can be an important symptom of underlying issues that provide a window into how the system is doing overall, and for understanding how the processes of defense and repair work.

The [Acute Phase Response] induced during infection/inflammation protects the host from further injury […]”

6. Macrophages’ Role in Atherosclerosis

Macrophages and Their Role in Atherosclerosis: Pathophysiology and Transcriptome Analysis

doi:10.1155/2016/9582430

 

The Reason: Although lesser known than some other components to the disease, macrophages play multiple roles in the development of atherosclerosis, even beyond being necessary for the formation of lipid laden foam cells. Some of these include initiating and sustaining the inflammatory response, and aiding in repair. Even foam cell formation is more complex than it appears at first glance, and this paper covers the complexities quite well.

“LDL serves as the primary source of lipid accumulation in the arterial wall during atherosclerotic lesion development. In vitro studies have demonstrated that intracellular cholesterol accumulation is caused not by native but by atherogenic modified LDL.”

5. Impact of Inflammation on HDL Levels and Function

Effect of inflammation on HDL structure and function

doi:10.1097/MOL.0000000000000333

 

The Reason: A more in-depth look at what impact inflammation has on HDL levels, structure, and function. This information is not only important for understanding the lipid system as a whole, but also to grasp what may cause lower HDL levels, and why structure (and function) matters even beyond levels in themselves, but also why the levels are important and what they represent about how the system is functioning as a whole.

“We would propose that these changes are advantageous during infections and following acute injuries. For example, decreasing reverse cholesterol transport or increasing LDL oxidation would increase cholesterol levels in macrophages where it could stimulate host defense and repair.“

4. High HDL, Low TG Yield Better Risk Odds Regardless of LDL Level

Is Isolated Low High-Density Lipoprotein Cholesterol a Cardiovascular Disease Risk Factor?

doi:10.1161/CIRCOUTCOMES.115.002436

 

The Reason: This analysis uses data from the Framingham Offspring Study, but puts a new spin on it to separate out people with high or low HDL levels, high or low triglyceride levels, and high or low LDL levels (with varying cutoffs for LDL and triglycerides). The results were that irrespective of LDL levels (ranging from <100, >100, >130) risk for heart disease was nearly the same so long as you had high HDL and low triglycerides. This makes sense as low triglycerides and high HDL is typically associated with better metabolic health, and although the data is not definitive by any means it does raise some interesting questions about whether the same holds true for people with very high HDL, very low triglycerides, and LDL far above the cutoff point they listed (AKA Lean Mass Hyper Responders).

“[…] high HDL-C […] was consistently associated with reduced CVD risk[.] This association persisted even when high HDL-C was accompanied by higher LDL-C (≥100 and ≥130 mg/dL) or higher TG (≥100 and ≥150 mg/dL), but was no longer significantly [sic] protective when both LDL-C and TG equaled or exceeded 100 mg/dL.”

3. Overview of Cholesterol Levels and Risk of Disease, All-Cause Mortality

Towards a Paradigm Shift in Cholesterol Treatment. A Re-examination of the Cholesterol Issue in Japan.

DOI:10.1159/000381654

 

The Reason: Typically, when hearing about cholesterol levels in the mainstream (and sometimes even in smaller niches) it is often referred to as bad, and the higher it is, the worse it is. However, this study provides a bit of a different perspective, with higher total cholesterol being related to lower incidence of certain diseases, infectious death, and lower all-cause mortality. The correlations are particularly interesting when combined with the thought of serum cholesterol often being portrayed as a dose-dependent poison, when reality may be a fair bit more complicated than that.

“[…] all-cause mortality was essentially inversely correlated with LDL cholesterol levels in both men and women.“

2. Cholesterol Accumulation Is Not the Initiating Factor to Atherosclerosis – Arterial Thickening Is

Neovascularization of coronary tunica intima (DIT) is the cause of coronary atherosclerosis.

doi:10.1186/1742-4682-9-11

 

The Reason: Although cholesterol accumulation via foam cell formation does occur later down the line in atherosclerosis, there appear to be many steps that occur before that happens. Namely, arterial thickening to the point of neovascularization (the artery becoming thick enough to require additional blood supply; thickening occurring from mechanical stress or damage) being a key initiating factor. While lipid deposition is still involved in the process once neovascularization occurs (via vascular remodeling and proteoglycans), the key point is that lipid deposition is not the initiating factor for the disease, but rather may actually be arterial damage and remodeling.

“This neovascularization, originating from adventitial vasa vasorum, is observed prior to the appearance of any atherosclerotic features except an increased dimension of DIT.”

 

1. Insulin, Insulin Resistance Differentiating Factor for MI Occurrence in Those with FH

Fibrinolytic parameters and insulin resistance in young survivors of myocardial infarction with heterozygous familial hypercholesterolemia.

 

The Reason: The study took two groups of people with Familial Hypercholesterolemia (FH; an umbrella of genetic causes for high cholesterol levels) and separated them based on whether they had experienced a myocardial infarction (MI) or whether they hadn’t. Interesting, the differentiating factor between the two groups wasn’t LDL, as you might expect, but rather other factors like triglyceride level, insulin level, and level of insulin resistance, among others. This may provide information to point in a direction for investigation for people with non-genetically high LDL but otherwise low markers for insulin resistance.

There was no difference in total and LDL cholesterol between the two groups. Patients with previous myocardial infarction had significantly higher levels of insulin, insulin resistance, triglycerides, t-PA antigen, PAI-1 antigen and activity, and significantly lower values of HDL cholesterol.”

May 09

LCCholesterolChallenge Update – The First Contender

It’s hard to believe it was almost three months ago that I posted the #LCCholesterolChallenge and I hadn’t heard a peep. This wasn’t for lack of pinging many of the biggest LDL-lowering experts I could find on Twitter and through social media. In fact, this is the most tweeted and retweeted graphic I’ve used to date.

I’m happy to say we had our first attempt to meet the challenge late last week. Grats to Brian Edwards for giving it a good college try.

He submitted the study, “Coronary Heart Disease Risks Associated with High Levels of HDL Cholesterol”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4187512/

So let’s compare the study to each item in the challenge:

“normal, non-treated”

Yes! I’m happy to be looking at neither a drug nor genetic study.

“(1)High HDL”

Yes! This study specifically stratifies for HDL groupings.

“(2)Low Triglycerides”

Alas, no — the study doesn’t stratify for low triglycerides.

While the mean average of triglycerides gets lower with each step higher in HDL, this isn’t the same as categorically excluding higher triglyceride participants from that group. In fact, there certainly were some given the high standard deviation reported. Thus, a few higher risk individuals that would’ve been singled out by this original rule of the challenge could tip the scales.

(3)”High LDL”

No as well. This wasn’t stratified either.

“HIGH RATES OF CARDIOVASCULAR DISEASE”

This one was somewhat odd as Brian seemed very insistent that *any* amount of CAD was a high rate. He pointed out the participants were selected for this study for not having it, yet some developed it on follow up — even in the group with the highest HDL. I definitely felt any reasonable person wouldn’t interpret “any” heart disease as the same as “high” heart disease.

I asked what he’d consider an “average” rate of CAD, leaving it to him to define. Thus, “low” would certainly be below average. Eventually, I offered up:

I’ve already said I’d be happy to accept a reasonable source. Here — the first link under googling, “chd rate by age” is http://www.heart.org/idc/groups/heart-public/@wcm/@sop/@smd/documents/downloadable/ucm_449846.pdf …

Ironically, even in spite of the higher alcoholism, the last two columns shown in the study were still under the average when compared to the heart.org data. So even if TG and LDL had been stratified, the existing rates would still be lower than the mean.

Thus, no — we don’t have high rates of CVD shown. This was actually already alluded to quite a bit from the study’s own graph:

(Click to zoom in)

Third Party Judgement Request

To Brian’s credit, he requested a third party decision and I think Jason gave a very well articulated one:

Brian:

Jason. @DaveKeto doesn’t think I answered the challenge. What do you think? We need a neutral judge. http://meandgin.blogspot.com/2018/05/i-met-low-tg-high-hdlc-high-ldlc.html …

Jason Jodway:

I personally would not say you met the challenge for 2 main reasons: 1) It was never suggested nobody would get CAD. 2) The challenge explicitly states *both* high HDL *and* low TG. That paper doesn’t let us actually stratisfy by that criteria. The trend does not properly

Dialog Paused

I’ll concede this experience was a bit mixed. While I thought we were having a productive dialog (or at least the beginnings of one), I was stunned when Monday morning Brian took to his blog to insist I had made several statements and imposed new requirements that I hadn’t. I brought this to his attention, but he made no effort to correct the record and instead let it stand.

For a brief moment, I was tempted to show Brian’s statements of what I said side-by-side with the actual tweets that were being mischaracterized. But this would just be an investment of time I don’t have. If people are interested, they can look it up themselves.

Thus, for the time being, I’ll have to put this dialog with Brian on pause. I’m kind of a stickler about having an intellectually honest discussion.

Final Thoughts

All things considered, I’m extremely happy Brian has taken part in the challenge and I sincerely congratulate him for giving it a solid try. And of course, I’m certainly looking forward to new challenges — of which I hope there are many!

May 05

Weight Gain Experiment – Progress Update

Before getting started, let me again emphasize that I highly discourage anyone else doing this experiment. As I’ve warned both here on the blog and on YouTube, this experiment has both short and long-term risks. In order to gain weight, I’m inducing a constant state of heightened insulin (duh!) to accumulate fat.

Patrons –> I have an accompanying video to this blog post you can watch here.

The Schedule

As you can see above, I’m now in the purple phase of a Controlled Standard American Diet which consists of two foot long sandwiches and a medium pepperoni pizza (Carbs 381g, Protein 301g, Fat 177g).

On Monday morning (May 7th) I’ll get a DEXA scan and a full spectrum blood test.

Click here to see all tests...
Apolipoprotein A-1, Apolipoprotein B, CBC With Differential/Platelet, Comp. Metabolic Panel (14), Cortisol, C-Reactive Protein- Cardiac, Fatty Acids- Free (Nonester), Ferritin- Serum, GGT, Glucagon, Hemoglobin A1c, Homocyst(e)ine- Plasma, IGF-1, Insulin and C-Peptide- Serum, Interleukin-6- Serum, Lipid Panel, Lp-PLA2 Activity, NMR LipoProfile, Thyroid Panel, Vitamin B12 and Folate

Then I’ll switch a Controlled Keto Diet which consists of 10 eggs, 8 oz of cheddar cheese, 2 pork sausage patties, 60ml heavy whipping cream, 2.5 oz almonds (Carbs 24g, Protein 128g, Fat 205g).

I plan to get a standard blood panel three days later on the 10th which will include a CMP, CBC, Fasting Insulin, hsCRP, NMR and basic lipid panel. Following this will be one more full spectrum test on the 14th and one more standard panel on 17th.

Daily Metrics

In addition to the labs taken and body scans, I’ll be capturing certain markers daily until the 19th:

  • Waking Glucose
  • Waking BHB (Ketones)
  • Waking weight
  • Waking blood pressure
  • Waking %SpO2 & PRbpm
  • Around 10am Glucose
  • Around 10am Total Cholesterol, LDL, HDL, TG (CardioChek)
  • Bedtime Glucose

Progress Thus Far

I find it endlessly ironic that so many people figured this would be “fun” since I could just “pig out” on anything I wanted. To be sure, I was actually trying to limit my carbs to grains in particular. So there was very little fructose or table sugar relative to my non-keto diet before. I ate a lot of pizza, buns on burgers, meat pies, bagels, croissants, etc. This was mainly due to (1) my having mild fructose malabsorption, and (2) keeping carb variations down to limit variables.

Sure enough, I got nearly all the symptoms I had listed last year in my Adventures in Carbland Parts I, II, and III. GI Stress, dry scalp, postprandial drowsiness, broken circadian rhythm, and acne. Yay.

But wait, there’s more! I have three new things that have been quite troublesome:

  • Persistent cough / heavy breathing. While I’ve had to deal with this a few times before in the carb swap experiments, it’s much worse this time around. Even walking around the block I find I’ll cough a bit and sometimes have to take deeper breaths or yawn.
  • Lack of productivity. I’m definitely not as much of my workaholic self. For instance, I usually find few TV shows worth stopping and watching. I’m usually doing something else while one is on. Now I feel like I can just veg in front of the TV pretty easily. I also don’t pop out of bed as quickly in the morning. I’m glad I have to take those metrics (from above) right away or I think I’d just lie there another half hour instead.
  • Less joy. Maybe it’s just these other symptoms that are bringing down my mood, but I certainly feel a bit more malaise when on this diet. I can’t wait to flip the switch back to keto soon.
  • Persistent Headaches*. I put a star next to this one as this has been mainly predominant since returning from the hiatus and moving from an uncontrolled carb diet to a controlled one. In the uncontrolled I had a lot of diet soda, whereas I have only water in the controlled — so there’s a decent chance this is a withdrawal from the caffeine. That said, it seems to be getting worse (not better) and it has now been three and a half days since starting the controlled phase.

 

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