2/ Ha! When @IanCramer has me give a little background on how I got into this space, I give one of the clumsier setups I think I've given in an interview. Not the best intro for the energy model either- but you can always check out the general poster here: CholesterolCode.com/model
3/ @IanCramer asks me for a "50,000 foot view of my thesis" where I walk it into the "high LDL where metabolically induced" context.
4/ @IanCramer: "I think if you take someone who is, as you put it, metabolically unhealthy and put them on a ketogenic diet and all of these markers improve -- except for the LDL -- I think this is absolutely a good thing."
5/ "... But I'd caveat that by saying, I think that the LDL cholesterol, LDL particles [being high] is still a risk factor... why not take that additional step and say, 'hey, let's try to bring this down a little bit.'"
6/ About 25 minutes in I give a decent setup for Lipid Profile vs Lipoprotein-centric view points.
But that said, I know I need to do a larger article, video, or both to really unpack it.
7/ At around 41 minutes we get into genetics. I brought up my interest in genetic abnormalities with regard to immune cells, but ironically, I hadn't yet read this paper at the point of recording- which happens to fall in line with what I was discussing pubmed.ncbi.nlm.nih.gov/27680891/
8/ Really, really love the last 20m of this podcast.
@IanCramer and I had some deep discussion on the importance of civility and respectful discourse with people of differing opinions.
Naturally, I have to again applaud his efforts in being such a strong example of this himself
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🧵 My thoughts on the Baseline Piece of the Puzzle
-- That everyone keeps missing... 1/10
A week ago today the longitudinal paper for our KETO-CTA study dropped (jacc.org/doi/10.1016/j.…) and there's been a lot of positive feedback, but also critiques worth discussing. I'd like to zero in on the topic of NCPV and PAV change.
First and foremost, I’m looking to be respectful of lead author Dr. Adrian Soto-Mota (@AdrianSotoMota) and Principal Investigator Dr. Matthew Budoff (@BudoffMd) regarding the complexity and relevance the heterogeneity of the cohort with regard to our findings. The coming paper expanding on this for both classification and clinical use is already under submission for review.
However, waiting for the publication of the new paper seems very untenable given how long these things take and interest in discussing the overall change in NCPV and PAV for the KETO-CTA study.
This can be challenging on my end as I want to represent this study effectively. And that’s difficult right now when I not as versed to delve deeper into both the heterogeneity relevance statistics like Dr. Soto-Mota or the issues with looking to changes in NCPV or PAV at low baseline levels like Dr. Budoff.
However, here’s what I can speak to…
I can speak to my own personal challenges in looking to the change of NCPV and PAV overall and why this hasn’t made sense to me. Not from a standpoint of discouragement, such as — this makes the study look bad. No, I mean it actually doesn’t fit any model I’m aware of save present plaque being predictive of future plaque change.
Let me unpack what I’m talking about…
Our baseline scans from the study showed this was a low risk population. Again, if looking at this from a population level.
But then, we were able to do a match analysis with Miami Heart. Matching up age, sex, ethnicity and risk factors quite tightly, but with our cohort having an average LDL-C of 272 mg/dL, and the matched Miami Heart cohort having average LDL-C of 123 mg/dL. And what did we find? They were nearly identical. In fact, for the semi-quantitative data ours was trending slightly better. jacc.org/doi/10.1016/j.…
2/10 - Moreover, while unpublished, I was cleared to present a preliminary quantitative match analysis with Miami Heart last year at a conference. These would make use of Cleerly scan data for both our cohort and Miami Heart. So it had both overall plaque volume and non calcified plaque volume (NCPV).
3/10 - But even better, there was a subgroup analysis that excluded those taking cholesterol lowering medication on Miami Heart to match again with ours...
First, let me say that data on this has been a bit limited. But *IF* we do ultimately confirm there are more ApoB-48 (B48) than ApoB-100 (B100) in ASCVD plaque, it would be a very big deal.
Let's unpack...
2/ First, thanks to @TuckerGoodrich for pinging me on these pubs and pressing the discussion.
But also credit to @CaloriesProper on tweeting this a couple years ago (I missed it then)
To understand why this would be so important if true, some review...
3/ B48 and B100s are the major proteins on chylomicrons (CMs) and VLDLs, respectively.
CMs mostly carry lipids from the small intestine to the bloodstream (lipids consumed), VLDL mostly carry lipids from storage; predominantly from adipose stores.
#Me: Why would triglyceride rich LDL particles be more atherogenic than triglyceride poor LDL particles?
#ChatGPT: Triglyceride-rich LDL (low-density lipoprotein) particles are more atherogenic (i.e., more likely to contribute to the… twitter.com/i/web/status/1…
2/
#Me: Couldn’t it also be possible that triglyceride rich LDL are ultimately the result of metabolic dysfunction and that better explains its association with atherosclerosis?
#Me: Is it possible that almost the entire amount of atherogenesis associated with high triglyceride rich LDL is due to dysfunctional lipid metabolism and the diseases that result in these profiles rather than the LDL particles themselves?
1/🧵 I'm definitely a fan of both @DominicDAgosti2 and @DrRagnar (obviously), so I was excited to see them chatting about #lipids, #LMHRs, and Dom's consideration of increasing carbs to lower his #ApoB
3/ When chatting with Dom in SD last year for dinner, he mentioned focusing less on maintaining such a sizable muscle mass as he typically does, and I predicted he'd likely see his LDL/ApoB as considerably higher with this change if still #keto. This podcast appears to confirm...