Jump to content

Tom Dayspring and lipids

Recommended Posts

After having read Peter attia's strategy on lipids in his books, I wanted to listened directly to one of the sources, Tom Dayspring being one of the most respected lipidologists who teaches credit courses to medical professionals. His explanations are exceptionally clear and surely leave much less confusion than the 7-hours total podcast with Peter Attia. Maybe this material should be listened before Attia's ultra-marathon.

The main aspect is that the lipids regulating system is of course much more complex than we can believe. He also dispels some myths about cholesterol. For example, the brain does not need dietary cholesterol since it's the main producing plant of cholesterol in the body, ditto the gonads, testosterone does not need dietary cholesterol to be produced nor high amounts of dietary cholesterol for optimal T concentrations.

He also offers some guidelines on threshold levels. Main aspect, such levels are not stationary, but are a function of the general health of the subject, when various risk factors are present (smoke, T2D), the threshold is lower. When a CV event has occurred, the threshold goes further down, close to the very low levels suggested by Peter Attia.

In the following brief but info-packed video he suggests the following values for Trigs and Non-hdl, whereas in the following longer podcast with Simon hill he suggests values for ApoB (1:06 hours).

  • Triglycerides: the guidelines suggest physiological levels < 150, but he as a lipidologist suggests <100 values, optimal range being <80
  • Non-HDL cholesterol: it may constitute a proxy for ApoB. Ideal range < 130 if no CV risk factors are present. IF CV risk factors are present (insulin resistance, smoke, high blood pressure, atherosclerosis), ideal range is << 100 (well below 100), if you had a heart attack, ideal is << 70 (well below 70). If borderline values of Non-HDL chol are observed (130 mg/dL in individuals with no CV risks), then an ApoB analysis should be carried out to obtain a more precise risk indicator.
  • ApoB: best is to be in the lower quintile (20%) of the population, that is in the range 0-80 mg/dL. 80 mg/dL is good if no other risk factors are present. Values >>80 are never good and values pertaining to the upper quintile, > 115-120 mg/dL are definitely to be avoided, harbingers of CV risk.

He also comments of people with very high ApoB values who do not exhibit atherosclerosis. Such cases have been observed and the hypothetical explanation is that they enjoy some other unknown protective factors. The rule is that high ApoB statistically constitutes high (additional) risk for Atherosclerosis. And we know that when speaking statistics we also include outliers or extreme values.




Edited by mccoy
Link to comment
Share on other sites

This is a pretty concise summary, does dietary cholesterol influence plasma cholesterol? Surprisingly, the answer is little, yes and no. Little in individual who express the average amount of specific receptors in enterocytes, yes in the hyperabsorbers, no in the hypoabsorbers. Genetics govern here and with unlucky combinations of the above receptors some people may be big hyperabsobers and suck up all the dietary cholesterol they eat. Basic concept is that individual variability governs, and this is a main aspect in human biology, which is too often neglected.


Link to comment
Share on other sites

Thanks Mccoy,


I remember I already heard in some Tom's talks but forgot the details already, now I see it circa 1:21 on the second video.

I recently reread some studies from 80-90es and it seems it was clear that apoB is a part of the mosaic but there should be a (maybe genetic) nuance that made some people at higher risk with the same, relatively safe (80-100) values. Tom mentions (I think it is still not bulletproof but an educated guess based on a lot of studies) that there seems structural differences that acts as a multiplier of pure "stochastic" chance of a particle to be a trigger in the chain.




Link to comment
Share on other sites

Posted (edited)

Igor, I missed that detail, but to tell the truth I have to get to the end of that podcast, I'm hopping like crazy from one lipid-podcast to the other and now I'm re-listening to the monster 7-hours podcast with Peter Attia, which a while ago left me pretty confused. It's good to be able to see even a small clarity at last in the jungle of lipidology (and of very contrasting info in the internet).

I found the general rules expressed by Tom DAyspring very useful and I am applying them to myself and the members of my family. I am apparently in the safe zone and probably without specific need to measure ApoB. My wife instead may have problems, non-HDL-C >130, HDL in the high range, no apparent insulin resistance (from trigs and from Homa-IR estimates), maybe a mild hyperabsorber, so I just suggested to her to have a blood draw and to measure ApoB on top of the usual parameters. Surprisingly, she accepted the suggestion, it doesn't happen often .

My 19-years son is a singular case, last year exhibiting  a very low total C of 125 mg/dL, low HDL, non-HDL= 78 mg/dL, low trigs of 63 mg/dL, notwithstanding his obesity (he's autistic and on hunger-boosting psychopharmaceuticals) his cholesterol homeostasis is apparently perfect, young age probably governing the process.

It goes without saying that the situation is dynamic, so parameters must be checked regularly, especially if dietary changes or other changes in lifestyle occur.

As Tom Dayspring rightly says, individual variability governs in biology and there are the general rules and there are the outliers (who have not plaques even with TC of 400 mg/dL and high ApoB and vice-versa, those who are at risk with ideal parameters). Unless we ascertain we are the outliers, we should of course adhere to the general rules.

Edited by mccoy
Link to comment
Share on other sites

Mccoy, yes, I also found Tom's way of describing things useful because that way creates for us a kind of framework, foundation to think about these things and to assess other texts with some mechanistic and quantitative understanding, this is important because the "body of already published texts" is so big novadays that just deciding on their trustworthiness requires a lot of effort or being a working researcher/expert on own which is not possible for everyone.

Regarding your wife's nonhdl > 130 I would say - it makes sense to capture also triglicerides and do it several times. Unless values are too far from normal like they are usually showed by metabolically broken processes and this is not the case, the things are usually done this way:

1. TC,TG,HDL-C are directly measured

2. non-HDL is just TC without HDL, thus calculation

3. LDL is then assessed with Friedewald Formula: Non-HDL~=LDL+VLDL where VLDL is TG/5 in mg/dl

In my case from several observations I assumed that my lab does exactly this with cheap lipidograms, so LDL is usually 10-20 lower than non-HDL value reported. With my TG usually reported in 80-90 range I am at higher normal for LDL, but I am trying to stick to slightly undereating, thus being in the negative +-10% of daily calories spent, forcing body to save energy. If I will allow myself to move to the positive 10%, thus a bit above the daily spending I will not gain weight for relatively long time (until all the cells will stack enough spare energy and will start signaling that they are ok and brain will synchronize the "orchestra" to gain weight) but my TGs will get a bit higher and I will probably get the very similar >130 in a particular test. This is assuming approx 30% of calories coming from fat and no alcohol intake because TG values are sensitive to these things due to the way they are metabolized and formula will produce wrong estimates. So your wife could be in a completely expected way of producing the higher "core" value for LDL in the reports, thus for the sake of safety apoB could be added to the normal lipidogram taken with TG to see more detailed picture (as well as do lp(a) 1-2 times of not yet). Offcourse all the other stuff that surrounds is also has to be assessed - in the risk models there are variables that requires doctors to shift down (imho) completely normal values to lower the risks based on models, it is disputable if this is a working solution for an individual person but in country-size statistics it is a solid gain for public healthcare system so they are doing it as a part of normal practice in many countries novadays.





Link to comment
Share on other sites

Posted (edited)

Igor, my wife is apparently a case where the so called 'good cholesterol' is high, nevertheless the other parameters are not so good. Tom Daysprings goes over and over explaining why high HDL values are not very indicative of good lipids homeostasis. Her doctor is not too worried, perhaps because the values fall not far from the average values in her subgroup. But we know that medicine is presently a way to cure disease and not a way to optimize parameters not to have those diseases.

I'm detailing the values found:

TC = 244 mg/dL. This parameter, although not very indicative per se, constitute a red light for a potential condition of dyslipidemia

HDL = 73 mg/dL. On the high side. According to Dayspring, a high value may indicate sometimes hyperabsorption (overexpressed Niemann-pick C1 receptors or underexpression of ATP binding cassette (ABC) transporters  or other mechanisms).

Trigs= 95 mg/dL. Not a worrying value per se, sure not an indicator of significant insulin resistance (also, good HOMA-IR would exclude that).

Non-HDL= 171 mg/dL. Definitely a red light. With such a value, according to Dayspring it would not even be necessary to analyze ApoB, since this is not a borderline area, rather an area of potential high risk.

Calculated LDL= 152 mg/dL. That's a crude estimate by the Friedewald formula, but it is another red light.

In a few days I should have the results of the recent panel including ApoB. If I understood correctly, ApoB should theoretically be located in between Non-HDL and LDL, so in the region of 160 mg/dL in the above panel, but that's not guaranteed for several reasons. I am very curious about the forthcoming values and above all, if  ApoB confirms a red light an adequate strategy should be developed, probably including statins, perhaps after observing the results of some dietary adjustments.

By the way, I didn't hear Tom Dayspring suggesting to lower ApoB to post-natal levels to healthy people as well, which constitutes the core of Peter Attia's anti-atherogenic scheme. 


Edited by mccoy
Link to comment
Share on other sites

Aha, that is not just above 130, that is big enough to investigate the details and adjust the strategy. From the video it is clear that HDL at 70 raises a serious suspicion that hyper absorption could have place, so maybe that special analysis could be useful if available. Or as proposed a workaround - two weeks full veggie regimen and a control shot to see the difference. In my case HDL fluctuates from lower 40 to higher 50 on plants only.




Link to comment
Share on other sites

Posted (edited)

I have the latest values from my wife's lipid panel. They are as follows, units in mg/dL

  • TC=247
  • Trigs=70
  • HDL=64
  • Non-HDL=183
  • LDL=169 (as calculated from Friedewald's formula)
  • ApoB=119

My first considerations are:

  • Hi non-HDL actually is correlated to high ApoB.
  • ApoB is 65% of Non-HDL and 70% of calculated LDL.
  • ApoB seats in the upper quintile (80-100th percentile) = high atherogenic risk.
  • triglycerides are pretty modest, so there is apparently no significant insulin resistance.

Actions: according to what Tom DAyspring says, the minimum dose of Crestor (5 mg) decreases ApoB by about 38%, so it should be enough to take the values within the 20th percentile (80 mg/dL). It seems a very reasonable solution to me, low dose means low probability of side effects (myopathy and elevated liver enzymes, increase of glucose).

We'll see what the doctors propose. I would not suggest a mere lifestyle change,since my wife eats modestly and usually healthy foods. Also, she has to deal with non-optimal HbA1C values, so I would suggest a continuous glucometer monitoring to ascertain foods and combos which spike glucose and avoid them, which mathematically will bring down HbA1C. Fasting glucose is in the norm.

At the end, in her case a modest dosage of statins plus some change in dietary habits to bring down the glucose AUC should suffice to optimize metabolic parameters. Also, next time around non-HDL cholesterol may be used as a proxy for ApoB and this will allow less expensive and more frequent monitoring of lipid and HbA1C values (analyses done at the local pharmacy).

Edited by mccoy
Link to comment
Share on other sites

Hm, the absolute values are relatively high, the ratio, if studies like this https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5625702/ make sense do not indicate small ldl particles, so at least one part of known to be unwanted things seems of lesser concern. Anyway, this is to be assessed by doctors. HDL is not so low -> absorbtion could contribute a significant part, I had hdl of 60 and tc of 200 when I tried to use liquid oils as a bigger contributor to my calories, plus some small amounts of cheese and clams/sardines; going plants-only w/o liquid oils shifted me -10 for hdl and -30 for tc (constant fluctuations in my values makes me think I am also not hyper but relatively efficient absorber). So maybe a diet tweaks could also give some boost, if they are not unwanted for other reasons offcourse.





Edited by IgorF
Link to comment
Share on other sites

Igor, the article you posted is specific on LDL-C/ApoB ratio but LDL-C value has been obtained from the Friedewald's formula so it can be affected by some error. IT is strange that they did such a rigorous study but one of the basic parameters is an estimate, not a rigorous one. This may confound the results.

Anyway, apparently ratios can be influenced by some specific properties of LDL particles, which are probably subjective.

By the above, it is plausible that, in the same person and with not very different lipid panels, the ratio of Non-HDLC /ApoB remains about the same. Non-HDLC is practically a directly measured value, because it has been calculated after two actually measured values and not estimates.

The above to say that my wife's next lipid panels can be done with minimum expense at the pharmacy, using the observed ratio Non-HDLC/ApoB= 1.54 as a conversion factor from Non-HDLC to ApoB. Of course, every once in a while it is advisable to re-calibrate such ratio.

Link to comment
Share on other sites

Yes, I am doing it for myself the same way - rarely apoB tests and cheap lipidograms more often.

I am personally not so serious about absolute values of the ratios from the article, imho it is more about the way of thinking or a thing to compare. My current ratio is about 1.2x and I had up to 1.5 in the past when a bit different diet and lower calories consumed. My older parents few years ago had 1.4x and they both do have medical condition connected, so I used these ratios rather to quickly guess if there is an anomaly when the ratio is completely unexpected. But absolute values seems for 99.9% of people are the king.

Also some more data on ratios, just for curiosity https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9220033/

I think the data on their plotted graph (as 1/x to have it expressed the same) means something around 1.33 is the median and most data will hit into 1-2SD there, only those at the very extremes will indicate that there are some SNPs in action.



Edited by IgorF
Link to comment
Share on other sites

Posted (edited)

The lipid series with Simon Hill as a host is very clear, here Tom Dayspring exhibits all his educational skills. Simon Hill interrupts him rarely and poses some interesting questions, such as can phytosterols be detrimental in vegans (answer is no since 500 mg is the average ingested dose, against 2000 mg supplemental phytosterols).

I recommend all 3 episodes, they are also very recent and contain updated info. I'll have to reason about the discussions and come out with a personal strategy against CVD. A long-term one, that's the key, the temporal horizon, since atherosclerosis takes long to develop.



Edited by mccoy
Link to comment
Share on other sites

Posted (edited)

My wife's doctor prescribed to her what Dayspring calls the baby-statin, 5 mg of crestor. I'm tempted to take it as well, but am undecided since the estimate of my ApoB is in the range of 60 to 70 mg/dL, in the lower quintile, with no other risk factors.

Edited by mccoy
Link to comment
Share on other sites

Good videos, also interesting that Tom is long time doing on himself the thing he practices/proposes for others.

I think this article was somewhere in the videos https://www.jacc.org/doi/pdf/10.1016/j.jacc.2004.03.046?download=true

it is 2004, so someone who was able to read it many years ago and turned it into an actionable item probably benefited a lot in the 20 years chunk. I saw many articles from 90es where researchers were convinced regarding the connection of apob/ldl with the mechanics of the desease but much more things had to happen (in some way ressembling the anti-tobacco story) until the pressure was enough to shift enough people to do the final accord of this story. And it seems will take 10-20 more years to make it an ordinary practice (if there will be no long-term consequences that seems very unlikely). So almost a century, for the easiest to handle thing from the "grim triade".


It is also interesting that hunters-gatherers (data is in the article above) do have atherosclerosis but AFAIR relatively rarely (except inuits that do have it more often and their diet is known to be proatherogenic). So the idea that we want to have it a bit less than is available for the most of us with the best possible diet and lifestyle is plausible without learning all the 70 years long history of the research on this topic.



Edited by IgorF
Link to comment
Share on other sites

Posted (edited)

Very interesting article and yes, it seems strange that it has been written 20 years ago. The TC of hunters-gatherers is impressively low, I wonder what caused this phenotype. And the obvious question rises: how do we abate TC to the average value of 100 mg/dL with lifestyle, since hunter/gatherers took no statins. I doubt that the present-day followers of the paleo diet exhibit on the average such low values, probably the other way around. 

Edited by mccoy
Link to comment
Share on other sites

On 5/26/2023 at 10:40 PM, mccoy said:

what caused this phenotype

That is an interesting question.

I tried to connect the dots of all pieces of information I remember and came to the following hypothesys:

- modern people are under pressure of a new, almost never faced phenomena - abundance of energy (I am cutting out modern engineered food to make it less complicated, some traditionally engineered food like cheese and so on is considered as non-engineered, natural somehow). This pressure works the same way as other things from which viral infections are now the best visible - they are eliminating the hosts that can not form some mutual co-evolution strategy. The same health-related pressure re-shapes us to be more adapted to energy poisoning

- it seems now we can break the TC of 150 with lifestyle and CR, at least Fontana's study https://www.pnas.org/doi/10.1073/pnas.0308291101  gives such a figure

- to break 130 we need to either use pharmacological trick or "persuade" the body on the energy topic somehow

- it could be the case that "persuasion" is not so easy and straitforward


In other words - we were under 130 for a long time, then we moved a bit higher because a very energy expensive process https://www.sciencedirect.com/topics/medicine-and-dentistry/cholesterol-synthesis that on the other hand is fundamental to survival and reproduction drifted in this direction due to selection pressure. We can not move back easily, we already selected somehow, so we can rollback only to a previous optimum value of 150. (Some of us probably, no idea if energy poisoning from in-utero/early childhood is not raising the bar even higher)

(off course values 130 and 150 are illustrative and averages, individual distributions apply also).

There are hardly to measure things in a controlled experiments but they are widely known - those adopting westernized diet (and lifestyle) in the first generations are suffering much more from ASCVD (let's cut out other energy poisoning malfunctions for the sake of simplicity) than those already living several tens of generations in relative prosperity (mostly "global west" and some east areas also) - they "are passing the selection gate" on a population level. This was observed with (perhaps) all possible genetics - people on the far north, native americans, africa, australia and oceania, papua new guinea, india, indonesia and maybe other places I never read about.

But for the sake of curiosity I tried to find maybe some linking facts to put between far less than 130 in some studies of hunters-gatherers and far high in the first studies of e.g. Adventists (they are also interesting that they had TC 170 @2700kkal/day comparing to 200 @3000 for newyorkers in 60ies). And I found seems previously not discussed here case - Fulani



they have TC of 135 @1680kkal/day (men) normal BP and seems do not suffer extensively from ASCVD. Authors were mentioned the fact that since Fulani are seminomadic pastoralists who consume a diet rich in saturated fats and are not prone to higher (measurable?) risks then maybe protection comes from the fact of energy limit.

Another study - comparison with other nigerian people at an early stage of "westernization":


here we see - higher BP, higher TC and probably just the beginning of sophisticated "food" introduction in the city culture, so many traditional habits were also a limiting factor.

Also Fulani seems are long-term adopted to diary, they seems have something in common with caucasians in that area:




So Fulani's case could explain also a trick with saturated fat - in abundance of energy some bodies are known to shortcut on them without rebuilding the chains and just store, thus increasing the positive energy delta but when the energy is scarse - there is no considerable risk increase. Also @50% of daily energy from fats (this is definitely genetic adoption, those who are not adopted similarly will definitely have unwanted side-effects from such macro composition).


And the last part of hypothesis - how to persuade the body to produce less chole giving the case that the body is already at whole-foods diet, is doing sane CR (spending all the possible energy, no possibility to gain weight at all on a long term time chunk) but the value is still oscilates higher that 150?

If the body is already selected many generations ago then perhaps w/o pharma there is no known (to me) sustainable way. On the other hand seems some people are reaching 130 somehow. If they are not just genetically tuned for that goal (hundreds of already known genes that complement to the chole pathways and who knows how many more yet unknown) maybe the answer could come from another area but testing this part is tricky.

So, energy sensing and regulation comes not only from brain but from many neural circuits https://www.sciencedirect.com/science/article/pii/S1550413115004830

perhaps finally from some every-cell generated signal that forms information background that is detected by the brain (hypothalamus perhaps) and based on which the orchestration/distribution of energy takes place.

We know that for many things there is something that our models describe as base or tone level and waves or pulses - e.g. seratonin, dopamine etc, where the mechanism of action is not a level but rather a gradient of change in time and we do have some unconscious circuitry good at detection of such. Since it exists not one time then it could be the case that it is rather a building block that is very beneficial so could be used in the areas we have not yet discovered.

Now the 3rd thing - it was discovered that in at least some forms of addictions connected with dopamine there is an empowering factor - uncertainty. Highly addicted slotmachine gamers receive the highest reaction in their brains when the chances (as they asessing them) of the highest uncertainty.

And now connecting these dots to the hypothesys of one difference between modern people and hunters-gatherers. We do not only live in abundance of energy sources, we are certain about them. And hunters-gatherers do not only restricted in calories - they have much higher uncertainty ot that topic. So it could be the case that they are spending their energy more accurate, thus limiting more riskier and energy-demanding synthesys to the bare limit. At least in my case I can not be active @1700kcals/day - with 2 hours of daily walking (not brisk) and 3-4 on weekend plus 15minutes/day easy running - I will loose weight relatively fast. Maybe I will stop loosing it and optimize later but I dont want to drop to BMI of 17 just to get the answer on this, also hunters-gatherers are not falling so deep, they are usually 18-19 with their lifestyle and I think many of them do require to walk longer and work harder.

So the way to test this "uncertainty generation" could be unpredictable fasting periods interleaved with harder refeeding - like some hunters-gatherers doing when they are able to get big game or find honey and get 3000-3500kcals suddenly after 1200 etc.

No idea if somebody tried such a regimen but I suspect it will be hard and unpleasant (sleep disturbance will definitely have its place and it is definitely not desired).


That is my hypothesising on this really tricky to be answered question))







Edited by IgorF
Link to comment
Share on other sites

Posted (edited)

The articles on Fulani are fascinating, the Sahara was indeed a fertile and green region back during the latest glaciation and some relics of the ancient lakes are still found, for example in eastern Chad (the Ennedi region).


The low energy intake hypothesis has also been raised apropos of the Masai population.

Milk, serum cholesterol, and the Maasai. A hypothesis


The Maasai of East Africa have been found to have low serum concentrations of cholesterol and a low incidence of cardiovascular disease in spite of apparently very high milk intakes. On that basis it has been frequently suggested that milk contains a "hypocholesterolaemic factor". The hypocholesterolaemia of the Maasai had also been attributed to a genetic adaptation. We feel that the milk intakes reported for the Maasai are excessively high and that the low incidence of cardiovascular diseases and low levels of serum cholesterol may be adequately explained by their variable and generally low energy intakes.

Edited by mccoy
Link to comment
Share on other sites

While searching for something that supports energy hypothesis found a nice brief on how it was first discovered about LDL mechanics


Siddhartha Mukherjee coined his second law of medicine (“normals” teach us rules; “outliers” teach us laws) based of this story, maybe he will write a book on chole also in the future)).

Brown and Goldstein in their later works headed toward SREBP https://www.wikipathways.org/pathways/WP1982.html

It seems that SREBP activation with insulin is at least one of the 3 (or how many of them really exist) ways that can change the lipid methabolism towards unwanted scenario


SREBPs in Lipid Metabolism, Insulin
Signaling, and Beyond
Russell A. DeBose-Boyd1,* and Jin Ye1,*


(available via scihub)

In this article a lot of interesting details related to SREBP provided, describing also a possible contribution to decreased (innate) immunity and low level inflammation observed in dm2.

Also as an additional tribute to the second law mentioned - an interesting observation: unlike with dm2 in dm1 there is increased chole absorption and decreased production of it - thus mechanism is not broken - more absorbed -> less needs to be produced (in dm2 it cells do not want to absorb and produce more) but some disturbance (starting from the fact of "eagerness" to absorb), perhaps cascaded from unnatural insulin waves is observed.



I also remember on some Attia's drive a guest (unfortunatelly can't remember now, but a dedicated researcher of the topic) told that everything starts with insulin resistance.

It is a bit less usual to find a "bridging case" for transition of pre-westernized people but seems this one could be useful


Metabolic Profile and Cardiovascular Risk Patterns in an
Indigenous Population of Amazonia
Edelweiss F. Tavares, Joao P. B. Vieira-Filho, Adagmar Andriolo, Adriana Sanudo,
Suely G. A. Gimeno, Laercio J. Franco
Human Biology, Volume 75, Number 1, February 2003, pp. 31-46 (Article)
Published by Wayne State University Press
For additional information about this article
Access provided by FIOCRUZ-Fundacao Oswaldo Cruz (10 Jan 2018 17:37 GMT)

Here they do have already elevated lipids and still a very good BP, fasting glucose and acceptable HbA1c but the latter two seems at the cost of insulin @12. I have similar values (a bit higher glucose due to SNP known to do it) but my insulin is 2.5-4 to achieve the same result.

This is just one way of do it wrong, there are others, e.g.

Plasma Cholesterol, Triglyceride and Uric Acid in Urban  
and Rural Communities in Papua New Guinea  
G. B. Wyatt*, A. R. Grlewt, F. 1. R. Martin$ and D. G. Campbel

In this one they describe a transition from 1400-1500 to 2200-2400 kcals/day without increase in lipids but seems with dm2, so genetics could favor different ways in different cases.


Looking on https://pathway-viewer.toolforge.org/embed/WP1982 I am thinking about some famous story but I forgot the details - one of Oppenheimer's student, already accomplished scientist on a lecture about some complicated engeeniring thing like nuclear reactor was asked what will happen if we will block in let's say place A but do not block in B as it is expected was not able to answer because of the complexity of such a gizmo. And well, we know that Mother Nature is an an engineer we've learned a lot, so there definitely are much more backup routes to dempfer the energy and matter poisoning, maybe the main contributor ot the process is not SREBP pathway, we will learn it in the coming future. Perhaps.




in addition to SREBP there is ChREBP that is synergetically interconnected to the way liver deals with energy, helping to use lipids as a buffer to either fill the gaps in their requirement (both structural and energy reserve) or to shuttle the excess energy out into lipids since they have more destinations in the body than glucose. Perhaps when the capacities to deal with lipids are near their saturation (e.g. genetical limits on the amount of adipose cells formation in earlier life) - storage + consumption + excretion then the things are getting fishy - in addition to already not well functioning lipid part the onset of dm2 is a question of a short time.



The Regulation of ApoB Metabolism by Insulin


no idea if this 10 years old article describes the things the way they known today, Tom Dayspring mentioned in the older as well as in the newer interviews that a lot of knew knowledge gained by the researches last years but an interesting point from the article:


The synthesis and secretion of ApoB is complex. Surprisingly, most ApoB protein is degraded prior to secretion, and the amount of ApoB secreted is largely determined by the proportion of newly synthesized polypeptide that escapes degradation [6].

That is an example that highly sophisticated pictures and process descriptions which require several sentences or pages to describe them formally also have to be understood as a dynamic system of interconnected queues, with their rates, reactions on blockage or empty feeder and so on. This requires books to describe them and this is not always the full picture. Complexity fascination.

Also insulin seems really acts as an orchestrator of a large group of things and unless the queues in the model are in their (let's say) up to 90% processing capacities the whole orchestration makes it work. When there is a weak place like a queue with insufficient feed control gets overloaded and reaches its processing saturation then there are unexpected phenomenas, and there could be an effect called in the informational networks as congestion https://en.wikipedia.org/wiki/Network_congestion - other elements could be infected by slow processing queue that did not failed completely but to clean up the network from congestion it is often requires to do enormous amount of work or shutdown the whole network. That is exactly what is observed when metabolic desease is already developed and it seems similar to the effects of some poisoning (e.g. a case with longterm aftermath of beta-carotene in vita topic).




Insulin Resistance Predicts Mortality in Nondiabetic Individuals in the U.S.
Karlee J. Ausk, MD, 1 Edward J. Boyko, MD, MPH, 2 and George N. Ioannou, BMBCH, MS 1 , 3



here an interesting arrangement of data shows that despite there is a seriously increased mortality for people at borderline or worse HOMA-IR value with some known causes (it is hard to define one value for all ancestries if I understand it correct) all cause mortality for them is less increased, thus - adaptations that allowed human bodies to resist energy abundance started relatively long time ago and are beneficial somehow. This also supports the (relative) prosperity that came with agriculture -> industrialization -> modern food invention path to all the things we observe.


From queue saturation and congestion perspective one of the most suspicious candidates is IMHO some adaptation(-s) that allows adipose tissue expansion (some people can't get thick, they got dm2 before it)


What causes the insulin resistance underlying obesity?
Olga T. Hardy,a,b Michael P. Czech,a and Silvia Corveraa



Adipose cell size: importance in health and disease
Karin G. Stenkula1 and X Charlotte Erlanson-Albertsson2




This supports the fact that non-caucasian ancestries are almost always more fragile to the energy overload.

Also several hypotheses about mechanisms (perhaps not actual novadays because more data already exists) are interesting in the queue and congestion way of view on all these things

If energy influx is able to be shuttled into a major long-term storage - adipose cells in proper places - things are working and the body is able to handle the things for some time. When the capacity to channel the energy is lower - then smaller queues will be broken and health issues will happen even before the adipose reservoires saturation. So first thing to care - do not get weight too fast. The next thing is adipose tissue expansion. When it will be saturated the effects will guaranteed to happen almost everywhere - they will decline to get more fat and insulin will rise, breaking many other queues in the network. So either the energy flux will be cut at the entry side - by physical limitations or gastric surgeries or the things will be broken even worse. But it is much, uncomparabely much better not to get into such a situation at all, while some things will self-fix and improve it is unimaginable (at least for me) that the whole network will stabilize itself from semi-broken state completely.

So to CR or not is a personal choice based on persuasion but flux control to tackle the acceleration rate lower than expected max capacity of the whole network is mandatory. And here, "the second wave of energy abundance" challenge caused by engineered food called "junk" is really a challenge that will be hard to tackle, because producers learned a lot from tobacco industry case and their strategy of survival seems unbeatable now (IMHO offcourse).


Edited by IgorF
adding more info insulin's role in lipid processing
Link to comment
Share on other sites

After some thinking about chole and phenotypes I decide to look on the topic from another angle.

The hypothesys that modern people are different from chole diapason perspective due to changes caused by environment pressure required some other angle, some aggregated view. And a hint came from a bit unusual for such a topic book:

The Changing Body
Health, Nutrition, and Human Development
in the Western World since 1700
Roderick Floud
Robert W. Fogel
Bernard Harris
Sok Chul Hong

The book is very "yawn-generating" because it is all about formulas, stat, tables, graphs and so on. But authors did such a huge amount of data collection and digestion that their tables used by e.g. ourworldindata (https://ourworldindata.org/calorie-supply-sources) or other such services.

For the chole topic there are tables 5.5 (Europe 1800-1960) and 6.6 (US 1800-2004) useful to have a look on calories, the link above has this data incorporated as well as other sources into an interactive tool.

From the book's perspective it looks like the driver of phenotypical change (higher chole together with higher weight and hight) was an industrialization itself. Also based on US data exactly the same happened with farmers as an industry way to do the agriculture.

These people worked a lot and much harder than previous generations, they were able to do it because of slow process of economical changes that itself allowed to deliver more calories to the people. In other words - progress in the social organization and food storage/preparation created a possibility to consume more to do more physical work and that moved the bars, creating a newer phenotype that was not seen in the same area in the past or in other areas until something similar.

Thus, 15-20 generations in the industrialized "west" moved from "agricultural" ~130 TC to "industrial" 150-170 and towards 190 when there seems reached some balance between calories and requirements.

Here I need to say that this way of thinking cuts off chole "modifiers" - known to modulate the values foods (e.g. saturated fats) etc. They could move the bar in some directions but I am rather speculating about some median, reachable by the most people and so on. Also cutting out all the myriad of individual nuances.

So, hunters-gatherers with daily 1400kcals were long time oscilating around 100-110 for TC, those who already established agriculture with dairy were able to get more calories (1700-1900) and more available nutrients were not only able to work harder but also moved to 130. Then the next shift with 2200-3000kcals moved the values to a new normal that is itself a bit risky and the frequency of CVD allowed to start the long journey to find the answer.


And an extra - table 6.6 in the book. In the US 3200 kkals daily were all the 20th century, until 80ies where there was a jump to 3500 in the 90ies and then to 3900 in zeroes.

This perhaps creates a newer phenotype on its own - children overexposed to the calories abundance in utero, then from the earlier years and so on. They have no chances to dissiminate the extra calories into fat and inefficiencies, they are doomed to break the rate limiters in the network of queues and have serious problems from the very young ages becasue despite the idea promoted by the engineered food industries for several decades that "we don't know what causes obessity" "you need to excercise more" etc, almost 4kkals daily even on very hard physical jobs is a serious challenge to burn out, not speaking about doing it daily.

Here I am also cutting out a huge modifier that makes things worse - calories from engineered foods are in many cases immediately available, thing unimaginambe in the past. Thus some unlucky people could really damage their brakes even without overnutrition (those with glucose issues caused brain disfunctions).

So, I am stick to hypothesis that calories raised the TC bar because they created bigger and stronger body, when such a body is not really needed - we need to watch it and try to stay as low on unspent calories as possible, maybe we can get to a phenotype with normal range of TC 130 back but it will also take 15-20 generations perhaps.



Edited by IgorF
Link to comment
Share on other sites

Join the conversation

You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.

Reply to this topic...

×   Pasted as rich text.   Paste as plain text instead

  Only 75 emoji are allowed.

×   Your link has been automatically embedded.   Display as a link instead

×   Your previous content has been restored.   Clear editor

×   You cannot paste images directly. Upload or insert images from URL.


  • Create New...