2/ At about eight minutes in Dayspring discusses how there is new emerging data on various things in the last couple years, particularly triglycerides and how they have taken center stage in relation to atherogenicity of an ApoB particle.
3/ About 10m in @PeterAttiaMD brings up the importance in distinguishing the difference between what ApB and LDL-P — of course, if you followed me for a while, you know this is a distinction of crucial importance for me (see cholesterolcode.com/thoughts-regar… )
4/ So I have some thoughts around the discussion following the 15:45 mark, but it’s not super Twitter friendly and I want to just keep going. I’m a double back with the thread of its own at some point...
5/ Wow — at around 23m in @PeterAttiaMD describes a (what I assume is) a hyper-responder case. (Possibly a LMHR...?)
6/ Full disclosure -- I had to pause the podcast to ruminate on these discussions, and now I need to take care of some business.
I'll restart this #ListeningThread later at my next bloc of convenience...
7/ At 35m in they are discussing the Vasa Vasorum.
@PeterAttiaMD differentiates the environments of the arterial lumen vs the VV with regard to insulin, glucose, sheer stress, etc. and why that should be considered a stronger suspect given potential risk of damage.
8/ At around 37m in they start talking HDL cholesterol, expanding on our drug targeting of this marker has it yielded positive effects, along with a brief mention on Mendelian randomization studies as well.
9/ Talk about timing. At about halfway through – around the 60 minute mark — @drlipid talks about OxLP_ApoB test and its value (particularly in the context of Lp(a))
11/ At about 74m @drlipid points out that if one were only allowed to look at one metric to be cost effective, he would recommend LDL triglycerides (tho they concede that discreet assay isn’t commercially available). But I definitely agree that LDL-TG should be very meaningful.
12/ I'll concede the pharmacological topic isn't as interesting to me so I'll button up here.
Again, this podcast has definitely been very interesting for many reasons I've outlined above. (I don't think I'll re-cover the ground of ApoB vs LDL; see blog post for details on that)
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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...