1/ I want to give huge props to @DrNadolsky for doing this #MakingLMHR experiment!

Yes, I know some of my followers may be blocked -- so I'm including an image as well.

If you're interested in how this experiment came about -- read on... 🧵 Image
2/ We've had an ongoing debate on how much (or little) #saturated fat consumption is responsible for high #LDL #cholesterol levels we typically see for #LMHRs.

Whereas I (we) believe #LEM to have greater relevance overall.

Which led to the experiment👇
3/ Could @DrNadolsky emulate the #LMHR phenotype while *not* being fat adapted? (or at least, to get his #LDL #cholesterol that high?)

He consumed two sticks of butter a day to test this! 🧈🧈

Yes, the experiment went more toward my prediction, so alas, I won't be flying there.
4/ However, @DrNadolsky is now doing another experiment on the heals of this one where he's going keto with some added elements you may find interesting. But I'm leaving it to him to share.

(Not as excited about this 2nd one, but still very much interested in the data)
5/ Again, my sincerest thanks to @DrNadolsky for performing this experiment and contributing his share of #CitizenScience. 🙏🙏🙏

Lastly, if you want to read more on the #LEM I was speaking to above, be sure to see our recent paper on it here:
@DrNadolsky -- question from @LowCarbEyeDoc:

"What were the Lumen readings on the last day of lipid testing?"
Image

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More from @realDaveFeldman

Jun 29
1/ 🚨New N=1 Experiment: #IsItSaturatedFat🚨
🙏retweet🙏

Yes, I'm doing a new N=1 -- and it's going to be a biggie!

My good friend and colleague, @DrNadolsky completed his recent #MakingLMHR experiment concluding the added 2 sticks of butter as the reason for his LDL increase. Image
2/ He's already conceded he's left out all the context on aiming for #LMHR profile, the relevance of RER, and the #LEM (so no need for people to keep pinging me on the IG video). I've chatted with him privately and we'll leave it at that. 👍

3/ However -- this actually affords us a huge new opportunity.

@DrNadolsky's claim isn't just his own, it's just about everyone else's outside the low carb community.

Simply stated: high #LDL #cholesterol seen in #LMHRs is predominantly due to high consumption of saturated fat.
Read 6 tweets
Jun 18
1/ It begins...

Naturally, the #LEM would be a bit suggestive of this outcome where a diet is mid to moderately higher carb for this context.

Low TG typical of metabolic health.
Lower turnover of VLDL-TG = lower total cholesterol, lower LDL cholesterol, and lower HDL...
2/ If replacing M/PUFA with SFA but keeping all else equal (including -- importantly -- carbs) for this exact context, this might have a marginal impact on TC/LDL/HDL. But would it command a higher magnitude of increase? I'd be doubtful...

However, if replacing carbs with fat...
3/ ... Thus going lower carb, we get closer to the model around LEM and its explanation regarding TC/LDL-C/HDL-C changes toward the outcome magnitude of the LMHR phenotype.

Hence the value of looking to RER for this experiment to confirm/disconfirm fat-adaptation.
Read 4 tweets
Jun 15
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?
2/5 There's a bit of back-and-forth that originated this experiment which you can read about here 👇

And yes, this could literally result in my flying to him to confirm results directly with advanced bloodwork & RER (Respiratory Exchange Ratio)

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.
Read 5 tweets
Jun 13
📣📣📣Big #diabetes #bundle drop for @ownyourlabs

🏷Introductory Sale for 5% until June 20th!

👇 👇 👇 👇 👇 👇
OwnYourLabs.com/diabetes
👆 👆 👆 👆 👆 👆

After much research, we decided on 4 variations of the bundle (see below)...
Basics Bundle

✅ Basic Metabolic Panel (8)
✅ Fructosamine
✅ Hemoglobin A1c
✅ Insulin

Diabetes Plus Bundle

✅ Comprehensive Metabolic Panel (14)
✅ Fructosamine
✅ Hemoglobin A1c
✅ Insulin and C-Peptide, Serum
✅ GGT
✅ Lipid Panel
Advanced Bundle

✅ Comprehensive Metabolic Panel (14)
✅ Fructosamine
✅ Hemoglobin A1c
✅ Insulin and C-Peptide, Serum
✅ GGT
✅ Uric Acid, Serum
✅ C-Reactive Protein, Cardiac
✅ NMR Lipoprofile
✅ Urinalysis, Complete
Read 5 tweets
Jun 7
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...
Read 8 tweets
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

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