1/ ☠️ Thread ☠️
Looking at Heart Disease vs All Cause Mortality
Let's start with a poll. Would you prefer: 1. Being less likely to die of heart disease 2. Being more likely to die of something that isn’t heart disease
2/ The “how” you die is important, but probably not as important to you as “when” you die.
But could we just look at the "how" and "when" of one kind of mortality and know whether it will truly extend lifespan?
3/ If I hold an experiment and my intervention group died 50% less by heart disease than my control.
Can I conclude this intervention group must necessarily live longer than the control group on average – particularly given heart disease is our number one killer?
4/ It cannot. We don't have enough information when looking at only one kind of mortality. What we *want* to infer is that heart disease went down and all other risk factors remained the same.
That's very intuitive. That's how we think of it like the poll answer in (1) above.
5/ What if something makes you more vulnerable to another mortal illness that isn't heart disease?
Technically speaking, that will reduce your risk of dying of heart disease.
For a hyperbolic example, consuming cyanide would reduce your risk of dying by heart disease 100%
6/ Which brings us to genetically high and low LDL cholesterol (LDL-C). There is a known association between LDL-C and heart disease, and this includes genetics.
So an obvious question comes to mind, do those with naturally lower LDL-C live longer?
7/ That was actually the very first question I wanted to find out at the very beginning of my research in Nov' 2015.
It seemed relatively simple -- if people with genetically low LDL-C were blessed with longer lifespans, then the case was made, full stop.
8/ There are actually many different genetic ways one gets to low/no LDL-C/-P with technical names like abetalipoproteinemia, familial hypobetalipoproteinemia, and PCSK9 LOF.
Do they live longer?
They don't.
Why?
9/ This brings us back to the beginning. Three scenarios:
1. Less heart disease risk, all else the same 2. Less heart disease risk, one or more risk factors worsen (trade off) 3. Heart disease same, one or more risk factors worsen (net loss)
10/ In all three of the above scenarios we get less death by heart disease and more death by something else.
There's just one way to help understand the trade off -- you have to track mortality by non-heart disease as well.
You need All Cause Mortality (ACM)
11/ A couple weeks ago @JakeKushnerMD brought this up regarding the podcast @ethanjweiss had with @skathire. (I only just now listened to the podcast today) Here's Jake's tweet:
@JakeKushnerMD@ethanjweiss@skathire@mvholmes@mrbase2 13/ To be sure, I was hoping for LDL-C vs simply "Age at Death". I found later that this endpoint actually does exist and ran the data for myself. Finally seeing
Genetically higher LDL-C
vs
"Age at Death"
...
@JakeKushnerMD@ethanjweiss@skathire@mvholmes@mrbase2 14/ But I'm not going to link the graphic yet. Yes, I'll hint that it doesn't look good for pro-lipid lowerers, but I'm going to take more time to better understand from their position why they'd say it is.
That's why I wanted to understand @mvholmes position and a few others...
To @JakeKushnerMD's point, we can only know when good scientists like @skathire can take these massive population analyses beyond heart disease and apply them to all cause mortality as well.
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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...