1/ New video by @NutritionMadeS3 which I'd like to retweet for added discussion.

There's a layperson-friendly section in it that does a great job of illustrating the existing expectation of:

(1) LDL/ApoB Exposure Size
X
(2) Time
=
Rate of Plaque Development
2/ Using "mg-years" (much like "pack years" with cigs), one can quickly figure out what state of cumulative exposure they'd be at.

Gil's graph in video was similar to the one I tweeted on last week 👇

And indeed, this is the convention of exposure x time
3/ To be sure, I'd echo @NutritionMadeS3's qualifier in the video that this is expected at a population level. So the exceptions don't prove the rule (in either direction).

Hence the enormous importance of studying those with extremely high LDL/ApoB at a population level...
4/ Naturally, this is where I again emphasize the importance of studying plaque emergence and development in #LMHRs

Using the above equation, we should certainly see a lot of plaque at a population level for even short term LMHRs compared to healthy likewise cohorts of avg LDL..
5/ Here's an example using the equation above:

Someone has a mean LDL-C of 125 up to their 40th birthday, but then goes #keto and becomes a LMHR with an LDL of 500 for the next 3 years.
Their "mg-years" are
125 x 40 -> 5000 (age 0-40)
+
500 x 3 -> 1500 (age 40-43)
=
6500
6/ Per the equation above-> in 3 years at an LDL of 500, they will have added the equivalent of 12 years at LDL-C of 125.

So at 43, given the equation, this person should have comparable likelihood of plaque development for a 52 year old (again, speaking to population averages).
7/ If adding an additional 3 years, that 46 year should have comparable likelihood of plaque development for a 64 year old. (8000 mg-years)

Certainly I'm hoping this isn't the case, but I don't know (nor does anyone else)...
8/ But we're getting this specific data on #LMHRs right now (see LMHRstudy.com)

While I'm sure most will be at lower than levels comparable to 500, I likewise know there are many who are (or even higher). Hence the need to collect this population data soon!

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More from @realDaveFeldman

Jun 5
1/ I'd love to take an opportunity to expand on this important topic, and if I may, suggest something important to watch for with some newly emerging data.

To @MichaelMindrum point, I too believe the #ApoB will demonstrate higher association with #ASCVD than #LDL #Cholesterol..
2/ But to be sure, ApoB can be best represented as:

(1) Non-LDL ApoB lipoproteins
- and -
(2) LDL ApoB lipoproteins

The first category is predominantly chylomicrons, VLDL, and IDL -- which associate very highly with ASCVD.
3/ You can think of category (1) as "Triglyceride Rich Lipoproteins" (TRL, aka "remnants") and category (2) as "Triglyceride Poor Lipoproteins" (TPL)

The population of #LMHRs have extremely high levels of ApoB. But this pattern is a mix of very *low* TRL and very high TPL.
Read 6 tweets
Jun 4
Design a VLC diet that is low in fiber with the goal toward reaching a low respiratory exchange ratio on a cohort of lean, fit athletes (but no other exercise confounding like resistance training or diet confounding like meds/sups, etc).

I’d likewise bet big majority = #LMHRs
Full disclosure - @DrNadolsky and I took to some of this discussion via direct texting. However, it did lead me to a good question that I decided to turn into a poll out of curiosity...
1/2 Another great prop bet @DrNadolsky and I were discussing:

He proposed he could emulate the #LMHR phenotype by consuming a lot of butter and coconut oil while not keto and fat-adapted (thus, high RER). I'd predict the opposite.
Read 4 tweets
Jun 4
1/ Two weeks ago we released our paper on the #LipidEnergyModel (#LEM) along with our video abstract for it. I'm pleased to say it has led to many great connections and expanded discussion.

I'm going to recap on a lot of these in this thread. 🧵 ...

2/ First and foremost, thanks to everyone for their extraordinary support in retweeting our announcement, sharing our paper, and letting researchers know of this model.
3/ As we state many times (including within the video abstract), this model doesn't describe all possible influences on cholesterol levels. For example, other things can impact LDL-C such as M/PUFA-to-saturated fat composition, fiber, genetics, medication, etc.
Read 9 tweets
Jun 3
1/ Cool thread via @DrNadolsky

FWIW, I think I've figured out the perfect experiment via weight loss alone.

If I were to lose, say, 10-15lbs but keep diet composition as identical as possible (thus no increase in sat fat), the LEM would predict increased LDL/ApoB independently
2/ This is a great design given there are now other food items that would change other than possibly a net reduction in overall calories to maintain at the lower weight (but if anything, that would mean less sat fat in the overall, ofc).
3/ Given how strikingly different each model would predict the outcome, it seems like a given I'm going to need to do this experiment.

There's even a chance I line it up before the fiber experiment. (Working out scheduling right now...)
Read 4 tweets
May 25
1/ Listening to @theproof's podcast with @NutritionMadeS3 as I work. I'm really enjoying it thus far and I again commend Gil on his ability for distilling complex scientific discussion effectively in his YouTube videos.
2/ I just got through the part at 47:51 that had me stopping to write a couple thoughts... (the queued spot in the video linked here👇)

@theproof brings up one's individual need to want to feel a "part of a community" (very big deal in the diet space)...
3/ ... And that "...it can challenge our identity if we come across information that is directly challenging one of these very strongly held views from within that community that our fellow community members also hold..."
Read 7 tweets
May 23
1/ I had the debate between @NutritionMadeS3 & @ifixhearts on in the background while working. Really enjoyed it

First and foremost, both gentlemen were very cordial and professional. No ridicule, name-calling, or any other emotive personal attacks, etc..
2/ Which -- as you all know -- I'm a strong advocate for.

@NutritionMadeS3 represented the pro-LDL/ApoB lowering position well. (Note I've linked/tweeted his videos several times)

@ifixhearts brought forward the importance of metabolic health, and fault in it getting ignored...
3/ One important difference I was especially interested in-> do we have enough data in hand to feel confident high LDL/ApoB is a strong independent risk factor regardless of metabolic health. Generally @NutritionMadeS3 appears to favor "yes", @ifixhearts favors "unsure" to "no"
Read 5 tweets

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