1/5 This is BIG & I've really been looking forward to it. @DrNadolsky will be looking to see if he can reach a #LMHR phenotype while not being low carb or keto (or at a minimum, increase LDL-C to 200)
In short, can high consumption of saturated fat w/o being fat-adapted = #LMHR?
3/5 But more importantly, this gets to a very common assumption regarding #LMHRs -- that their phenotype can be mostly explained by higher consumption of saturated fat.
4/5 Ofc, it's worth repeating myself (and @nicknorwitz et al) agree saturated fat can impact LDL-C levels. But while we agree wrt additional component influences, we posit (and are exploring) the #LEM likelihood as the predominant influence for the #LMHR profile.
5/5 Which is why this is a powerful experiment. If one can demonstrate consistent #LMHR cut points while *not* being fat adapted (as confirmed by high RER, thus in contradiction with #LEM), that would be a very meaningful finding.
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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...
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.
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).
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.
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. 𧡠...
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.
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...)