Jan 20

START HERE (Pinned)

Please consider supporting our newly launched Citizen Science Foundation and its central endeavor, the LMHR Measurement Project. Your contributions are making citizen science a reality – thank you!

Apr 27

Presenting the Lipid Energy Model to Stanford University

I was incredibly honored to be invited by Annelise E. Barron, Associate Professor, Dept. of Bioengineering, to present my research to her class and discuss the Lipid Energy Model in depth. Originally, I was going to be flying to the campus to give the talk directly, but with the current Covid-19 crisis all speakers were presenting via Zoom.

This proved to be an excellent opportunity provide an overview for general (not low carb) audience. Overall, the presentation was well received, maintained strong retention, and there was quite a bit of discussion afterward. (Discussion not included in the video)

Apr 26

Videos on Current Crisis to be Archived

I’ve been provided an analysis by a friend in the tech industry who has a firm that performs advanced analytics on social media and particularly YouTube .

This analysis has led me to the very reluctant decision to archive all videos related to SARS-CoV-2 / COVID-19. While the videos themselves are not inflammatory in nature, I’m now convinced the topic itself may have enormous volatility regarding the algorithms YT makes use of (at least at this time).

I can’t discuss him or his firm’s methodology beyond this (and had him sign off on this language before posting).

Comments are turned off for the video announcing this because they can also impact these variables, but you can comment here at this blog post.

Apr 20

Back to the Lipids

Four weeks ago I posted for the first time on Covid-19. On that date, it was relatively new and there was some debate as to how quickly it would or wouldn’t spread. I predicted it would likely spread pretty quickly given the existing rate of change and made several videos on it, even advocating at a personal level for “Flattening the Curve”.

At that time there were 35,070 cases in the US, now there are 792,938 as of the time of this writing. Needless to say, with the current tally at 2.5 million cases and 170k deaths worldwide this is indeed very serious.

While initially in the Raise Awareness phase, I switched over to more general commentary and guest analysis with a variety of opinions, including Tucker Goodrich, Avi Bitton, and Ivor Cummins.

New Developments on the Lipid Front

In the last week I’ve been shifting away from Covid-19 and back toward lipids for several reasons. I have a private presentation coming this Friday, a podcast this Saturday, and I plan to put together a video soon talking through the Triad, which I’ve been discussing in depth with Sigma Nutrition. I’ll share more on these details next week.

March and April were originally meant for the inside-the-US travel and final shooting on the CC documentary, but obviously this is delayed with no clear rescheduling in site. So in the mean time, I’m going to be shifting more toward the book and Lipid Energy Model paper, since each is much more suited to at-home work in the first place.

Apr 20

Lipids and Viral Infections

A Quick Recap

In our last post about lipids and the immune system, we focused about how lipoproteins, particularly LDL, can participate in immune responses directly during infection – both by blocking the infection of cells through multiple mechanisms, and by binding to pathogens to neutralize them. In that post, infections were being referenced generally – both viral and bacterial.

However, in this post, there will be a focus on viral infection in particular in order to highlight some key differences between infection types. This all serves to showcase the complexity of immune responses, but also the fascinating interplay between how viruses try to infect us, and how the immune system utilizes the lipid system to thwart viral infection efforts.

It’s The Differences That Make You Stronger…

Like a game of chess, the immune system needs to think 3 steps ahead.

When trying to find the best solution to a problem, it helps to know the details of what you’re trying to address and change your method of response to target that issue specifically. This means knowing the enemy, if there is one, knowing the tools at your disposal, and combining that knowledge accordingly for the best possible response.

This concept is wonderfully demonstrated when looking at the lipid metabolism differences between viral and bacterial infections. As mentioned in the previous post, in response to exposure to certain toxins like lipopolysaccharide (LPS; a component of some bacteria) production of lipids – like triglycerides, cholesterol, and their carrier lipoproteins, increase.1-2

However, during viral infection lipid production by cells can decrease,3 and cholesterol uptake by cells (including immune cells), via lipoprotein uptake, can increase.4 In other words, although less cholesterol is made by the cell’s own machinery, the cell takes up more cholesterol from lipoproteins during a viral infection in order to compensate. This shift in lipid metabolism in response to some viral infections may be one explanation for the acute decrease in serum cholesterol sometimes seen in response to viral infections as well.5-7

What’s The Use of Low Cholesterol?

Although this concept may seem a bit confusing at first, there are a few clues as to why cells may down-regulate cholesterol production in favor of taking it up from lipoproteins instead. For example, the step that results in this switch lowers cholesterol in a particular part of the cell’s membrane, or outer shell. This in itself results in a protein signal (called interferon) being released by the cell,4 which is used to alert to the presence of viruses.8 This interferon signaling will also signal to any cell that sees it to decrease production of cholesterol, which will loop back around to increasing interferon signaling to spread the message to even more cells in the area.

Interferon is the alarm system of viral infection.

Among many other things, this interferon signaling results in the production of a protein that disrupts cholesterol rich areas in the cell membrane called lipid rafts.9-11 Many different types of viruses take advantage of lipid rafts in our cells as a point of entry, as well as exploiting them for other uses.12 Production of this protein may work to decrease the ability of the virus to infect cells by limiting their entry points.

In regards to this shift in lipid metabolism during viral infection, the authors of one paper on the topic stated the following:

[…] leading the authors to conclude that a lipid code is being detected during innate immunity, which is read out as a signal. This code will also be altered when lipid synthesis is enhanced as occurs, for example, in response to LPS.

How Low Cholesterol is good for anti-viral immunity

In other words the shift in lipid metabolism from infection, and resulting cholesterol distribution in the cell, may help to provide some context as to how to react, and whether the cell should prepare to deal with a bacteria (in which case lipid synthesis would be increased) or a virus (in which case lipid synthesis would be decreased). Because this results in a signal, interferon, this message would be able to be spread in order to warn neighboring cells as to what’s going on, and enact changes that may help decrease their vulnerability against the invader. I also can’t help but point out that although they call it a lipid code, you could very well call it a cholesterol code and be just as accurate!

Hijacking Vs. Competition

Some viruses can hijack our own cellular machinery for their own gain.

This may not be the only reason, however. It turns out that some viruses, after infecting the cell, will hijack the cellular factories and increase production of cholesterol and other lipids for their own gain. Essentially using our resources to assist in their replication.13-16 Perhaps the decreased cholesterol production by uninfected cells is a way to make this hijacking a little bit more difficult, even beyond attachment and entry of the virus.

Both the virus and LDL need to use the same “door” to get into the cell.

Beyond that single effect, although certain cells down-regulate cholesterol production when exposed to viruses or interferon, their intake of lipoproteins increases.4, 17 This may serve an additional purpose beyond just getting materials: some viruses will use the receptors that recognize various lipoproteins to invade the cell18-20, which might make one assume that this would be a bad thing for anti-viral immunity. But, on the other hand, in some cases, lipoproteins can compete for entry with the virus as they’re using the same “door” to get in (called direct competition or competitive clearance) which can decrease the rate of entry for the virus.

In fact, with regards to hepatitis C, a genetically inherited form of apoE, called apoE4, is thought to be more protective against infection and aide in spontaneous clearance (e.g. resolution) as it promotes higher levels of LDL which may compete with viral entry into cells via the LDL receptor.

These high levels of LDL-c [from APOE4] may compete with [infected lipoproteins] for the binding to the LDLR, thus decreasing the entry of the virus.

Hepatitis C virus Clearance and less liver damage in patients with high cholesterol, low density lipoprotein cholesterol and APOE E4 Allele

Neutralized By Lipoproteins

Lipoproteins don’t only serve to be hijacked and used by viruses to sneak past defenses, however. As mentioned in the prior post, the ability of lipoproteins to bind and otherwise neutralize pathogens is certainly notable – and this applies to some viruses too. Both have been noted to occur in vitro with the herpes simplex virus21, and others.22-23 It isn’t just the lipoprotein as a whole that can neutralize viruses, however. Components of lipoproteins, like their identifying proteins, have also been found to be able to bind and inhibit viral infection of cells in some in vitro studies as well.

Like velcro, components of lipoproteins can stick to some viruses rendering them powerless.

ApoA-I, found on HDL particles, has been shown to have antiviral activity in the herpes virus when separated from HDL24 , something that can occur during the response to infection.25 HDL also carries other proteins which have been shown to have antiviral activity including Apolipoprotein A-I Binding Protein (AIBP) 26, and Serum Amyloid A (SAA).27 This isn’t only restricted to HDL, however, as apo(a), one of the identifying proteins on lipoprotein(a), has also been shown to bind to and inactivate the hepatitis C virus in vitro.28

However, even this has a counterpoint as some viruses can also exploit some of these proteins and apolipoproteins to further their infection and replication, either by using them to access receptors, or via other methods.29-31 It seems for every exploit there is a defense, and vice versa. The result of both viruses and human immune systems trying to one-up each other in a battle that will likely never end.

An Ongoing Battle

Just by looking at the different vulnerabilities and defenses against viral infections, it becomes clear that these adaptions on both sides are the result of an ongoing battle that has been raging for time immemorial. While viruses have many tactics to invade, infect, and replicate, so too does our own immune system have special adaptions to shut down points of entry for viruses, limit materials that viruses can use, force competition between viruses and benign particles, and many others.

The immune system stands guard.

It’s unclear whether it may be beneficial to lower serum cholesterol, or cholesterol synthesis, during viral infections – although this question has been asked a few times in some of the papers mentioned. Although lowering cell membrane cholesterol has been shown to be protective in cell cultures, it’s unclear whether cholesterol lowering drugs do this, and if they do to what extent. Trials attempting to answer this question have likewise not shown consistent results either way.

Likewise it’s unclear whether higher baseline cholesterol may be protective, as – although in some cases this has been speculated to be protective – some viruses can likewise hijack lipoproteins, the proteins they carry, or otherwise take advantage of our lipid system for their own gain.

Nonetheless, one thing that is certain is that we have much to learn about how lipids and the immune system interact. It is sure to be endlessly fascinating the more we learn about the complexity, and elegance, of the system, as well as the ongoing war between viruses and our immune system. We here at CholesterolCode will be sure to provide updates as we continue to explore this topic over time.

Citations

1 Feingold, K. R., Staprans, I., Memon, R. A., Moser, A. H., Shigenaga, J. K., Doerrler, W., Dinarello, C. A., & Grunfeld, C. (1992). Endotoxin rapidly induces changes in lipid metabolism that produce hypertriglyceridemia: Low doses stimulate hepatic triglyceride production while high doses inhibit clearance. Journal of Lipid Research, 33(12), 1765–1776.

2 Harris, H. W., Gosnell, J. E., & Kumwenda, Z. L. (2000). The lipemia of sepsis: Triglyceride-rich lipoproteins as agents of innate immunity. Journal of Endotoxin Research, 6(6), 421–430.

3 Blanc, M., Hsieh, W. Y., Robertson, K. A., Watterson, S., Shui, G., Lacaze, P., Khondoker, M., Dickinson, P., Sing, G., Rodríguez-Martín, S., Phelan, P., Forster, T., Strobl, B., Müller, M., Riemersma, R., Osborne, T., Wenk, M. R., Angulo, A., & Ghazal, P. (2011). Host defense against viral infection involves interferon mediated down-regulation of sterol biosynthesis. PLoS Biology, 9(3), e1000598. https://doi.org/10.1371/journal.pbio.1000598

4 O’Neill, L. A. J. (2015). How Low Cholesterol Is Good for Anti-viral Immunity. Cell, 163(7), 1572–1574. https://doi.org/10.1016/j.cell.2015.12.004

5 Hu, X., Chen, D., Wu, L., He, G., & Ye, W. (2020). Low Serum Cholesterol Level Among Patients with COVID-19 Infection in Wenzhou, China (SSRN Scholarly Paper ID 3544826). Social Science Research Network. doi:10.2139/ssrn.3544826

6 Shor-Posner, G., Basit, A., Lu, Y., Cabrejos, C., Chang, J., Fletcher, M., Mantero-Atienza, E., & Baum, M. K. (1993). Hypocholesterolemia is associated with immune dysfunction in early human immunodeficiency virus-1 infection. The American Journal of Medicine, 94(5), 515–519. doi:10.1016/0002-9343(93)90087-6

7 Baillie, E. E., & Orr, C. W. (1979). Lowered high-density-lipoprotein cholesterol in viral illness. Clinical Chemistry, 25(5), 817–818. https://doi.org/10.1093/clinchem/25.5.817

8 Fensterl, V., Chattopadhyay, S., & Sen, G. C. (2015). No Love Lost Between Viruses and Interferons. Annual Review of Virology, 2(1), 549–572. https://doi.org/10.1146/annurev-virology-100114-055249
 
9 Wang, X., Hinson, E. R., & Cresswell, P. (2007). The interferon-inducible protein viperin inhibits influenza virus release by perturbing lipid rafts. Cell Host & Microbe, 2(2), 96–105. https://doi.org/10.1016/j.chom.2007.06.009
 
10 Nasr, N., Maddocks, S., Turville, S. G., Harman, A. N., Woolger, N., Helbig, K. J., Wilkinson, J., Bye, C. R., Wright, T. K., Rambukwelle, D., Donaghy, H., Beard, M. R., & Cunningham, A. L. (2012). HIV-1 infection of human macrophages directly induces viperin which inhibits viral production. Blood, 120(4), 778–788. https://doi.org/10.1182/blood-2012-01-407395
 
11 Duschene, K. S., & Broderick, J. B. (2012). Viperin: A radical response to viral infection. Biomolecular Concepts, 3(3), 255–266. https://doi.org/10.1515/bmc-2011-0057

12 Bukrinsky, M. I., Mukhamedova, N., & Sviridov, D. (2019). Lipid Rafts and Pathogens: The Art of Deception and Exploitation. Journal of Lipid Research. https://doi.org/10.1194/jlr.TR119000391

13 González-Aldaco, K., Torres-Reyes, L. A., Ojeda-Granados, C., José-Ábrego, A., Fierro, N. A., & Román, S. (2018). Immunometabolic Effect of Cholesterol in Hepatitis C Infection: Implications in Clinical Management and Antiviral Therapy. Annals of Hepatology, 17(6), 908–919. https://doi.org/10.5604/01.3001.0012.7191

14 Thaker, S. K., Ch’ng, J., & Christofk, H. R. (2019). Viral hijacking of cellular metabolism. BMC Biology, 17. https://doi.org/10.1186/s12915-019-0678-9

15 Wang, L. W., Wang, Z., Ersing, I., Nobre, L., Guo, R., Jiang, S., Trudeau, S., Zhao, B., Weekes, M. P., & Gewurz, B. E. (2019). Epstein-Barr virus subverts mevalonate and fatty acid pathways to promote infected B-cell proliferation and survival. PLoS Pathogens, 15(9). https://doi.org/10.1371/journal.ppat.1008030

16 Fritsch, S. D., & Weichhart, T. (2016). Effects of Interferons and Viruses on Metabolism. Frontiers in Immunology, 7. https://doi.org/10.3389/fimmu.2016.00630

17 York, A. G., Williams, K. J., Argus, J. P., Zhou, Q. D., Brar, G., Vergnes, L., Gray, E. E., Zhen, A., Wu, N. C., Yamada, D. H., Cunningham, C. R., Tarling, E. J., Wilks, M. Q., Casero, D., Gray, D. H., Yu, A. K., Wang, E. S., Brooks, D. G., Sun, R., … Bensinger, S. J. (2015). Limiting Cholesterol Biosynthetic Flux Spontaneously Engages Type I IFN Signaling. Cell, 163(7), 1716–1729. https://doi.org/10.1016/j.cell.2015.11.045

18 Finkelshtein, D., Werman, A., Novick, D., Barak, S., & Rubinstein, M. (2013). LDL receptor and its family members serve as the cellular receptors for vesicular stomatitis virus. Proceedings of the National Academy of Sciences of the United States of America, 110(18), 7306–7311. https://doi.org/10.1073/pnas.1214441110

19 Hofer, F., Gruenberger, M., Kowalski, H., Machat, H., Huettinger, M., Kuechler, E., & Blaas, D. (1994). Members of the low density lipoprotein receptor family mediate cell entry of a minor-group common cold virus. Proceedings of the National Academy of Sciences of the United States of America, 91(5), 1839–1842. https://doi.org/10.1073/pnas.91.5.1839

20 Agnello, V., Ábel, G., Elfahal, M., Knight, G. B., & Zhang, Q.-X. (1999). Hepatitis C virus and other Flaviviridae viruses enter cells via low density lipoprotein receptor. Proceedings of the National Academy of Sciences of the United States of America, 96(22), 12766–12771.

21 Huemer, H. P., Menzel, H. J., Potratz, D., Brake, B., Falke, D., Utermann, G., & Dierich, M. P. (1988). Herpes simplex virus binds to human serum lipoprotein. Intervirology, 29(2), 68–76. https://doi.org/10.1159/000150031

22 Activity of human serum lipoproteins on the infectivity of rhabdoviruses. – Abstract—Europe PMC. (n.d.). Retrieved March 31, 2020, from https://europepmc.org/article/med/6306404

23 Singh, I. P., Chopra, A. K., Coppenhaver, D. H., Ananatharamaiah, G. M., & Baron, S. (1999). Lipoproteins account for part of the broad non-specific antiviral activity of human serum. Antiviral Research, 42(3), 211–218. https://doi.org/10.1016/s0166-3542(99)00032-7

24 Srinivas, R. V., Rui, Z., Owens, R. J., Compans, R. W., Venkatachalapathi, Y. V., Gupta, K. B., Srinivas, S. K., Anantharamaiah, G. M., & Segrest, J. P. (1991). Inhibition of virus-induced cell fusion by apolipoprotein A-I and its amphipathic peptide analogs. Journal of Cellular Biochemistry, 45(2), 224–237. https://doi.org/10.1002/jcb.240450214

25 Eklund, K. K., Niemi, K., & Kovanen, P. T. (2012). Immune functions of serum amyloid A. Critical Reviews in Immunology, 32(4), 335–348. https://doi.org/10.1615/critrevimmunol.v32.i4.40

26 Dubrovsky, L., Ward, A., Choi, S.-H., Pushkarsky, T., Brichacek, B., Vanpouille, C., Adzhubei, A. A., Mukhamedova, N., Sviridov, D., Margolis, L., Jones, R. B., Miller, Y. I., & Bukrinsky, M. (2020). Inhibition of HIV Replication by Apolipoprotein A-I Binding Protein Targeting the Lipid Rafts. MBio, 11(1). https://doi.org/10.1128/mBio.02956-19

27 Lavie, M., Voisset, C., Vu-Dac, N., Zurawski, V., Duverlie, G., Wychowski, C., & Dubuisson, J. (2006). Serum amyloid A has antiviral activity against hepatitis C virus by inhibiting virus entry in a cell culture system. Hepatology (Baltimore, Md.), 44(6), 1626–1634. https://doi.org/10.1002/hep.21406

28 Oliveira, C., Fournier, C., Descamps, V., Morel, V., Scipione, C. A., Romagnuolo, R., Koschinsky, M. L., Boullier, A., Marcelo, P., Domon, J.-M., Brochot, E., Duverlie, G., Francois, C., Castelain, S., & Helle, F. (2017). Apolipoprotein(a) inhibits hepatitis C virus entry through interaction with infectious particles. Hepatology, 65(6), 1851–1864. https://doi.org/10.1002/hep.29096
 
29 Li, Y., Kakinami, C., Li, Q., Yang, B., & Li, H. (2013). Human Apolipoprotein A-I Is Associated with Dengue Virus and Enhances Virus Infection through SR-BI. PLOS ONE, 8(7), e70390. https://doi.org/10.1371/journal.pone.0070390
 
30 Qiao, L., & Luo, G. G. (2019). Human apolipoprotein E promotes hepatitis B virus infection and production. PLoS Pathogens, 15(8), e1007874. https://doi.org/10.1371/journal.ppat.1007874
 
31 Gondar, V., Molina-Jiménez, F., Hishiki, T., García-Buey, L., Koutsoudakis, G., Shimotohno, K., Benedicto, I., & Majano, P. L. (2015). Apolipoprotein E, but Not Apolipoprotein B, Is Essential for Efficient Cell-to-Cell Transmission of Hepatitis C Virus. Journal of Virology, 89(19), 9962–9973. https://doi.org/10.1128/JVI.00577-15

Apr 14

A Dialog on the Lipid Triad with Sigma Nutrition Radio

A while ago a podcast aired (episode 317) from Sigma Nutrition Radio that referenced concern of low carbers having high LDL cholesterol (LDL). But in particular, that they shouldn’t take comfort in having high HDL cholesterol (HDL) and low Triglycerides (TG). This was meaningful to me as it was referencing the “Lipid Triad” (high LDL, high HDL, low TG) that is of keen interest in my research.

I reached out to the host, Danny Lennon, and asked if they’d be up for having me on to talk about it, which he worked out with the original lipid guest, Alan Flanagan. We squeezed it in while I was traveling and shooting the CC documentary, so I was a little sleep deprived, but all-in-all I think it went really well (Episode 321, which you can listen to here). In fact, I went further and did a #ListenThread on Twitter which you can read here.

Response Article

Yesterday morning, Danny was kind enough to let me know an article dropped at Sigma Nutrition that sought to answer key points I brought up in the podcast. I was quite excited about this, actually. As you know, I’m very keen to explore this topic, particularly as it relates to not only cardiovascular disease risk, but all cause mortality itself.

The goal of this article is to zero in on some specific points made in the podcast episode with Dave. So rather than go into every individual point made in that discussion, this article will focus in on points Dave made in relation to four concepts:

1. The ‘Lipid Profile-Centric Model’

2. Atherogenic Dyslipidemia and the ‘Lipid Triad’

3. Remnant Lipoproteins

4. Inflammation

The article then takes each of these proposed areas in segments, which I’ll do likewise with responses below.

Segment 1) The ‘Lipid Profile-Centric Model’

In this first section I’m quoted here from the podcast:

Dave Feldman [10:37]: “I think conventional medicine, especially in lipidology has a kind of lipoprotein centric viewpoint which is to say that lipoproteins are themselves pathogenic or in particular at least Apo B containing lipoproteins, LDL particles especially that they themselves at a certain concentration level will drive atherosclerosis. And what I sort of want to put on the table is something that I would call a kind of lipid profile centric model, which is to say that I want to distinguish how much it is that a lipid profile drives the disease especially of atherosclerosis or whether or not it’s the disease that drives the lipid profile…”

Which is responded in the article with:

The first key point to note here is Dave’s suggestion that conventional medicine has a “viewpoint” that ApoB-containing lipoproteins (especially LDL) “at a certain concentration will drive atherosclerosis.” This phrasing suggests that the causal role of ApoB (and LDL) in driving atherosclerosis is simply a competing hypothesis, with as much claim to be correct as others. But this is just not the case. Within the lipidology and cardiovascular sciences community, that LDL-C and ApoB-containing lipoproteins drive atherosclerosis is not considered a mere “viewpoint”, but rather an established fact with sufficient proof to deem LDL-C causal.

What follows for the remainder of the segment are a series of studies that look at LDL-C alone (not in combination with HDL-C and/or TG). This is counter to my proposition with the “Lipid Triad” to begin with, and why I had called attention to a lipid profile-centric comparison.

Applying Bradford Hill for Causality

Interestingly, they bring up three of the Bradford Hill criteria, Temporality, Biological Gradient, and Reversibility. I’m actually a big fan of Bradford Hill, and to be sure, he has nine criteria. There are many that are important here, but one missing that is of particular importance (indeed, it is argued as the most important): Consistency. This is especially relevant to the examination of the Lipid Triad.

Consistency of findings.
Have the same findings must be observed among different populations, in different study designs and different times?

https://www.healthknowledge.org.uk/e-learning/epidemiology/practitioners/causation-epidemiology-association-causation

In other words, high LDL should result in high atherosclerosis consistently across the variety of lipid profiles we see in the populations of interest.

There shouldn’t be a sizable population we can find with generally high levels of LDL, yet low levels of atherosclerosis, even if they have high HDL and low TG.

The Low Carb Cholesterol Challenge

And indeed, this is why I developed the “Low Carb Cholesterol Challenge” two years ago in the attempt to collect evidence on this very key criteria:

I even have a “finder’s fee” of $1,000 for anyone who can help us get a study that meets or beats the existing Lipid Triad studies showing low CVD instead.

Segment 1 Conclusion

In the conclusion, it states:

Feldman’s Claim: The disease drives the lipid profile (i.e., reverse causality).

Again, this isn’t my claim. Reverse causality assumes atherosclerosis itself is the cause and high LDL is the effect, specifically. Rather, I’m pointing to the lipid profile as a result of a disease, potentially several — such as Type 2 Diabetes. And these diseases can likewise associate with higher cardiovascular disease.

Example: Type 2 Diabetes and Its Associated Lipid Profile

For example, we already know Type 2 Diabetes can result in a specific lipid profile and likewise have a strong association with heart disease risk.

Type 2 diabetes is associated with a cluster of interrelated plasma lipid and lipoprotein abnormalities, including reduced HDL cholesterol, a predominance of small dense LDL particles, and elevated triglycerides (1). These abnormalities occur in many patients despite normal LDL cholesterol levels. These changes are also a feature of the insulin resistance syndrome (also known as the metabolic syndrome), which underlies many cases of type 2 diabetes.

https://care.diabetesjournals.org/content/27/6/1496

Note that second sentence, “These abnormalities occur in many patients despite normal LDL cholesterol levels.” So high or normal LDL, we still get greater risk with T2D alongside low HDL and high TG.

Dyslipidemia is a major underlying risk factor contributing to the excess CVD risk, and is usually more atherogenic in the presence of diabetes. It is uniquely manifested by raised levels of triglycerides, low levels of high-density lipoprotein cholesterol, and smaller, denser, and more atherogenic low-density lipoprotein particles.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2941780/

“More atherogenic in the presence of diabetes” can likewise be read in the reverse, “less atherogenic in the absence of diabetes”.

Again, if we know a disease (in this case T2D) associates with a particular lipid profile and that disease likewise associated with increased CVD (even where LDL appears normal), why not remove both? Why not look at high LDL where HDL is high and TG low?

Consistency is indeed relevant. We should apply this criterion of Bradford Hill.

Segment 2) Atherogenic Dyslipidemia and the ‘Lipid Triad’

This segment more specifically aims at HDL and TG individually and classifies these markers as “systems biomarkers”.

Systems biomarker: biomarker which provides indications of underlying cardio-metabolic processes, but are not causal independently.

I’m actually quite happy with this distinction as it is a roundabout way of agreeing with the lipid profile-centric standpoint. Indeed, I think it something systemic that typically influences the levels of these markers.

However, the segment goes on to say:

Thus, while LDL particles do possess varying degrees of atherogenicity, the fact remains that all LDL particles are atherogenic. To argue that in the context of high-HDL/low-TGs, LDL-C is not atherogenic, implies a causal role for HDL and TGs, which is not established on the basis of the current evidence.

Not at all. It doesn’t imply a causal role for the levels of these markers, it implies a causal role for that which results in the levels for these markers.

Are there diseases that can drive these lipid profiles that likewise drive the cardiovascular disease they become associated with? And again — if this is so — why wouldn’t we want to subtract this confounder to test the hypothesis?

In this context, for the ‘lipid triad’ to be true, it must demonstrate that high LDL-C alone is not a risk factor for CVD, independent of its relationship to other correlated biomarkers. <More studies provided that look at LDL in isolation>

This rounds us back to LDL in isolation. Because we keep coming back to this point regarding study quantity, I think I’ll take some time to illustrate this problem with an analogy…

Analogy: BMI Study Quantity vs non-BMI Study Quality

BMI stands for Body Mass Index. The equation is BMI = kg/m2. It is used widely in studies as a very simple measurement that tends to correlate loosely with being under, normal, or overweight.

Obviously, it has problems given many people who are muscular would be considered as a “high BMI” and one can have lots of, say, visceral fat with a pot belly, yet a “normal BMI”.

Generally, having higher BMI will likewise associate with a greater risk of cardiovascular disease. And generally, those with higher BMI going on a diet to bring it down to “normal” levels with reduce their cardiovascular risk.

Of course, if BMI were the only measurement we had, then it might be the best one. But we have others that are more accurate to assess if you’re actually overweight that are clearly better.

Yet what if we had 100,000 studies using BMI, and this was a couple orders of magnitude greater than studies around any other measurement? Would that make BMI the best marker given the volume of studies, regardless of its lower quality when compared to other metrics? If other studies came forward showing, say, DXA scans were much more accurate in assessing this same risk, could it be countered that these studies were too few in number next to the wealth of existing BMI data?

Ironically, this is already happened many times over with the lipid hypothesis. For example, at the point LDL cholesterol was isolated for examination there were many more studies using total cholesterol. And at the point LDL particles were gaining focus, there were many more studies on LDL cholesterol, and so on.

Segments 3 and 4, Remnants Lipoproteins and Inflammation

I’m not going to spend much time on these segments as they were actually discussed in secondary fashion. See context of the quotes mentioned in the transcript to better understand.

All Cause Mortality?

Throughout the discussion I bring up All Cause Mortality (ACM) frequently. Between all of us the phrase is mentioned 18 times.

ACM is extremely relevant to this discussion given there is a great deal of literature regarding lipoproteins/cholesterol and the immune response (here’s one of our articles on it). We need to see the complete balance on outcomes to determine a benefit.

For example, lower LDL is associated with greater risk of cancer. This doesn’t mean low LDL causes cancer, it could be in many cases the cancer caused the low LDL. But either way, if we look at populations with low LDL and they end up dying proportionately more by cancer, that means they will be dying proportionately less by non-cancer diseases (such as CVD, of course).

When talking about mortality, we care much more about “the when” (ACM) than the “what” (specific cause). The what only tells us useful information when we know the when as well. Otherwise, you could correctly say that rock climbing without safety equipment “reduces risk of dying by a heart attack substantially”.

The Unanswered Question

There are two underlying interests I have in the “Lipid Triad”:

  1. Do we see low levels of cardiovascular disease in populations of normal, untreated people who have the combination of high LDL Cholesterol, high HDL Cholesterol, and low Triglycerides?
  2. Do we see low all cause mortality (greater longevity) in populations of normal, untreated people who have the combination of high LDL Cholesterol, high HDL Cholesterol, and low Triglycerides?

I believe the answer to both of these questions is “yes”, but I don’t know for sure. I’ve sought to connect with experts who would answer “no” and how they come to this conclusion.

Many of these people I’m friends with and appreciate their interest. But if I may speak plainly, this direct question continues to get anything but a direct answer.

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