
LDL-C Does Not Cause Cardiovascular Disease: A Comprehensive Review (2018) - harshreality
https://doi.org/10.1080/17512433.2018.1519391
======
et2o
Cardiovascular geneticist/statistician and physician-in-training here: This is
a completely bogus and scientifically illiterate review. This small group of
people in Sweden keep publishing crap like this and it's frankly kind of
annoying.

It's hard to even know where to start with the overwhelming amount of evidence
that elevated levels of LDL cholesterol causes cardiovascular disease.

Since I'm a geneticist, I'll point out just a handful of strong genetics-
guided experiments:

1) Familial hypercholesterolemia - Mutations in the LDLR Gene causing
basically only elevated LDL lead to 10x increased odds for coronary artery
disease

2) PCSK9 inhibitors - essentially only reduce LDL concentration, dramatically
reduce risk

3) Mendelian randomization techniques - statistical causal inference in
massive datasets shows pretty conclusively LDL increases CVD

Yes, LDL cholesterol causes CVD. Yes, there are other factors as well
(especially hemodynamics and chronic inflammation).

~~~
AstralStorm
No, everything you mentioned says that LDL-C levels correlates with
cardiovascular disease rather than causes.

Mutation in LDLR gene is a cause. LDL-C level is a correlate. The mutation may
or may not have additional repercussions other than just higher level of
LDL-C. Like with many metabolic issues - the problem sometimes truly is the
high level of (toxic) product, sometimes overload of the compensatory
mechanism (competitive inhibition etc.), sometimes the product is innocent but
the mutation has other effects.

PCSK9 inhibitors... I would be very careful. These might be just as
inconsistent as statins with equivocal evidence. For now, Cochrane agrees.
(Cochrane cancelled 2018 rereview of statins due to methodology update, the
2013 one is somewhat suspect. Later fluvastatin review shows it's not potent
enough etc. But this is all tangential.)

At least they will shine more light on the LDL-C hypothesis than statins which
have more complex effects. They are still not sensitive enough to rule out
other mechanisms. The drugs only recently exited phase III trials.

To accurately conclude LDL-C causes cardiovascular disease you will have to
figure out a way to increase LDL-C in absence of other relevant factors. Or
perhaps strongly control for those factors. This is actually hard. (among
them: obesity, smoking, diet and excercise, gene variants)

This should be quite possible to verify in animal model by pumping them with
relevant lipids regularly. Not entirely sure how to extend this to human
trials, but a way can be found.

If you have such results, I'd like to read them.

~~~
et2o
There are literally hundreds to thousands of papers where they have done
exactly this: Feed animals a high-cholesterol diet and compare the results to
control animals fed a normal diet. Usually they will also compare different
drugs in separate experimental arms. The LDL diet is a positive control, the
normal diet is a negative control, and the drug arms are usually the
intervention being tested. How much evidence do you want? This (molecular
imaging of atherosclerosis) is an entire subfield of medicine with tons of
work.

I myself have done this in rabbits, followed by by molecular imaging (Tc-99m
bound to various ligands) which __directly image __atherosclerosis in the
animal. We use single photon emission computed tomography (SPECT) as well as
position emission tomography (PET) to quantitatively measure atherosclerotic
burden. We also sacrifice the animals and remove their arteries–upon
unmagnified visual inspection of the plaques in the arteries, I can tell you
which animals get which diet.

I'm not going to debate all of your points. Sure, it's possible there are
other potential explanations for FH or PCSK9. However, they are not likely.
Also, mendelian randomization studies are use a __causal inference __strategy
via instrumental variable analysis, getting around the idea that we are
measuring only correlations. It 's a very nice technique which mimics a
randomized controlled trial via the random assignment of genetic material
during gametogenesis. So I don't agree with you.

Last thing: The equivocal evidence of statin therapy is only in primary
prevention, not in secondary prevention. No one is really challenging that
statins work, the question is what population is of high enough risk that they
should get statins. This is widely misreported in the popular media and pretty
harmful to patients who see a headline and stop taking their drugs.

~~~
AstralStorm
High cholesterol diet is not the same as high blood level of lipids. There are
many steps inbetween. It is additionally not the same as the high occurence of
atheroma. Even more steps.

You've introduced an additional super complex variable (diet) where there
should be none (blood level of LDL-C). I do not dispute accuracy of atheroma
measurements at all. This is easy enough technicality.

What is this "LDL diet" anyway? Do you feed animals with lipids?

If you mean high saturated fat diet, then that's a different beast. It does
many more things than just increase LDL-C levels - it also increases TG
levels, LDL levels in total, places metabolic burden on liver and more
interesting things.

Even there, the trials are rightly calling these levels _correlates_. Not
causes. And it is not a pedantic point, it is critical and informs the way we
should be dealing with related CVD.

Secondary prevention wrt statins, hmm, I see one good USPTF study. It includes
primary prevention too and has well defined results which are mildly positive.

It actually says you're not allowed to attribute statin results to LDL-C
levels as LDL-C dose/response strategies were not superior to plain fixed
dose. More importantly, this area has not been evaluated with enough power.

[https://jamanetwork.com/journals/jama/fullarticle/2584057](https://jamanetwork.com/journals/jama/fullarticle/2584057)

Key point 1b. No dose response, likely no direct causation. Suspected
mechanism is thus different from direct LDL-C levels. Most importantly:
"Benefits of statins did not appear to be restricted to patients with severely
elevated lipid levels, because similar effects were observed in subgroups
stratified according to baseline levels."

We have barely enough statistical power to say they're superior, not even
figure out the dosage in 3 levels.

Interesting fact there being that biggest trials reported smallest relative
risk reduction. (~15% with pretty big error bars on this.) Absolute risk
values are even more funny, like ~0.5% reduction... in high risk groups.

~~~
et2o
We feed the animals regular chow mixed with a percentage of pure cholesterol
(0.5% by mass, if I recall, but I might be wrong). I do not mean a high
saturated fat diet.

This is not the introduction of complex "diet" variables as in humans
whatsoever. I am quite aware of the differences in various lipids. Feeding
animals pure cholesterol is about as close as we can get. There might be
studies that have literally infused LDL in animals, I am not exactly sure. It
sounds like a huge pain to do experimentally since we would need to obtain
vascular access at least each day and risk infection, stress and pain in the
animals, etc.

We measure animal blood using the same machines used on humans and see
primarily increases in total cholesterol and LDL cholesterol following the
diet.

There is not "one good" study for secondary prevention of statins, there are
dozens.

There is very good evidence for the effectiveness of dose-response in statins.
Again, I don't even know where exactly to start with this body of literature.
Look up "high intensity statin therapy." This review for primary prevention,
which is probably why it was underpowered in this meta-analysis of 19 trials
in primary prevention (where I said the evidence was more equivocal; this
study actually shows pretty good evidence for the effectiveness of statins. in
1° prevention). A RR of 0.86 in only 1-6 years is pretty damn good for a
chronic disease.

Finally, I think you misunderstand statistics when you say that this review
(in which there were only three studies which could be used to analyze dose-
response) implies there is no dose response.

When they analyze dose-response (which is done through increasing statin
dosage until the LDL-C levels are low enough), I quote: "RR for cardiovascular
mortality, 0.61 [95% CI, 0.37 to 1.02]" Yes, this is underpowered because the
CI includes 1 but the point estimate of 0.6 is pretty impressive. This is a
poor conclusion by the authors via incorrect application of the NHST
framework, and not evidence that there is no dose-response effect. The best
evidence is actually pretty strong (RR of 0.6 is big!). I personally doubt
it's even that big.

Furthermore, RR for composite cardiovascular outcomes, 0.63 [95% CI, 0.53 to
0.76] was very statistically significant and again with a pretty strong
signal. So I don't think this paper says what you say it does.

You didn't feel the need to address mendelian randomization studies in 500,000
plus people?

~~~
AstralStorm
I'm not disputing effectiveness of statins one bit. They're effective, though
not as hugely effective as we're led to believe by marketing. (15% RRR is
probably worthwhile even if we don't know how these work.)

I'm disputing that the effect is related to LDL-C. There were no important
differences in trials that titrated based on LDL-C or used fixed dose. Compare
RR 0.63 vs 0.71 and full error bar overlap. There were also no relevant
differences of outcome based on stratification by LDL-C levels.

I did not feel the need to address "genetic"/"metabolomic" studies. (Also
known as data sifting.)

Standard MR is essentially n-D crosscorrelation of LDL-C levels with LDLR
genetic variant and CHD occurences. We know that beforehand. It doesn't tell
us anything of causation nor anything we don't know. The authors like to
misuse R as "explains".

The stronger MR variant results suggest adiposity causes LDL-C levels. Which
we already know, again, does not give us a clear treatment target.

The other advanced studies pinpoint specific lipids as the cause of CHD, but
cannot say where they are from. And no, they're not quite LDL-C.

[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816855/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816855/)

I'm not entirely sure how the authors got the rationale from what they're
writing about.

The better MR-like methods as mentioned are like stepwise crosscorrelation and
median clustering. Not entirely sure how they can actually show causality.

When the statistical guesswork method (MR is one kind of) does not match the
observations... it is likely that either the method is incorrect or that our
treatment is misapplied and reality does not match it. MR suggests RRR 3.5 for
all LDL-C lowering drugs. We see 1.15 on statins and none on PCSK9 inhibitors
vs CVD mortality.

I'd bet on MR being invalid/confused.

~~~
et2o
You misunderstand what mendelian randomization and instrumental variable
estimation are.

I'm not even sure what the methods you propose are, they're definitely not
popular ways to do causal inference in medicine or epidemiology.

~~~
AstralStorm
Sorry, but I actually understand precisely what mendelian randomization and
instrumental variable estimation are.

You apply nonlinear least squares estimation to every selected suspected
variable which is a bunch of linearization/polynomial approximating cross
correlations with normalized by estimated covariances. That is nonlinear IV
method.

MR is this based on an assumption that genomes are random fields of genes with
equal independent probabilities of occurence (known to be false, partly
corrected by population statistics which is not enough) giving direct results
on marker conditions/correlates but not on endpoints (known to be false,
partial attempts to correct for it are made to check for pleiotropy but those
checks are weak and linear) which markers are nonlinearly covariate with
endpoints (hope you used the right mapping) and that highest magnitudes of the
"correlations" say something about causation related to certain endpoints.
(not in general) MR shines as a negative method to rule out genetic causation
or susceptibility, not positive method to confirm it. It can be used to
confirm internal validity of a marker - invariance of it vs genetics.

The choice of variables (dimensions) is an educated guess too.

The assumptions that are verified is that genetic sequence is not
heterogenous, heteroskedastic, there are no hidden linkages etc.

The assumptions are not typically met or verified for complex system such as
lipid metabolism alone, much less endpoints such as CVD. Polygenetic
phenotypes are common and typical, not to say anything about epigenetics.

Nothing is said about the choice of the checked variables which is critical,
and trying too many gives the problem of multiple measurement reducing power.

The strongest assumption is that the variables are not covariant with
estimation error. This is not possible to check with MR statistics alone
unless you can somehow check those variants experimentally directly. (e.g. via
gene splicing or mutation) Good luck with that.

~~~
et2o
No, I don't think you have a clue.

You wrote a completely wrong thing, edited it when I pointed out it was
incorrect, and then 4 hours later you read up about MR on wikipedia or
something and came back here and posted a partially correct answer with a lot
of buzzwords and nice-sounding phrases, but with even more straw-man arguments
and outright errors.

Peace out, I'm done with you.

------
fedups
Does this claim apply equally to the relationship of LDL-P measurements to CVD
as well?

~~~
et2o
LDL particle size is less studied but probably an even better indicator for
CVD than LDL-C serum concentration.

