MY REVIEW OF ATTIA'S SUMMATION ON FELDMAN'S THEORY

My comments in purple

From

PETER ATTIA MD PODCAST LINK

October 8, 2018

PODCAST

Ultimately Peter found Dave’s model unconvincing
for three reasons, and provided them in the intro of the podcast:

1. “Dave was unable to explain the mass balance,
2. meaning how does one account for the greater amount of cholesterol in, and the greater number of, LDL particles.

No one, including Dave,
is disputing that the phenotype of interest
has more LDL-C and more LDL-P.

There are only 3 ways this can happen
(these are [collectively exhaustive,
but not [mutually exclusive]):
make more, clear less, transfer from other pools
that we can’t see (e.g., cell membranes).

Hyperabsorption of cholesterol from Gut?

I think the data make the first of these
by far the most likely driver,
but Dave seemed unable to address this
and could not explain, to me at least,
what could account for this increase in LDL-P/C.

So on first principles,
my doubt of this model has gone up from
the start of this discussion,
as the person who developed the model
could not actually explain the mass balance.

This is one of the most fundamental requirements
of any model.
And to be clear,
even if this fundamental condition were met,
it would not be sufficient to make the case that
[lean mass hyper-responders or LMHRs]
are not at risk.

IMO, Dave's major blind spot is not looking at lifetime risk. He doesn't have CAC's or CIMT's on his LMHRs
(which may be negative before 40 yo), he ignores the risk of residence time of LDLp greater than 1500 for 30 to 40 years.

It’s a [necessary but not sufficient] criteria that, in my mind,
has failed.”

2. “Dave argues that VLDL production
3. is driving the LDL concentration, but the fact remains
4. that in insulin-sensitive people
5. (which presumably the LMHRs are),
6. the opposite is true: there are fewer, not more,
7. TG being exported from the liver
8. and there is less, not more, apoC-III on the VLDL,
9. thereby reducing, not increasing, their residence time.

In other words,
LMHR would have less VLDL to LDL conversion
than, say, someone with T2D.

So again, I can see no evidence whatsoever
that his energy model,
which can’t be explained on mass balance,
and can’t be explained on what is known
about the physiology of VLDL and LDL, is plausible.”

3. “Even if you ignore the points above—
4. which you can’t—
5. I am more un-convinced than ever at the notion
6. that we should exclude the roughly
7. 2,000 genetic mutations
8. known to produce a phenotype of
9. high LDL-C, high HDL-C, and low TG.

We have 2,000 natural experiments.

Surely at least some of these cases (e.g., PCSK9 gain of function) are excellent proxies
for the key features of LMHR.

I am concerned most of these LMHRs have FH or polygenic genetic hypercholesterolemia.

Larry Huston article link

Yet to ignore them for imaginary reasons (e.g., having gain of function PCSK9 is somehow toxic to endothelial cells because it impairs their ability to take up cholesterol despite there being no evidence that endothelial cells require PCSK9 to uptake LDL in a receptor-mediated fashion) is to say, in my opinion, one does not want to know the answer to this question.”

Peter emphasizes that probabilities play a very important role
in diseases like atherosclerosis,
and this nuance is often missing when discussing this disease.

Atherosclerosis is impacted by many things beyond the lipoproteins,
but that doesn’t
diminish their role in the causality of atherosclerosis,
Peter argues.

Note from Peter: Some low carb enthusiasts argue
that as long as they are insulin sensitive,
have high HDL-C and low TG,
their LDL-C (or LDL-P or apoB) is irrelevant.

Their data seems to be based on old low number trials. TG/HDL is supreme marker link

Further, many confuse imaging tests like
calcium scans (CACs) as biomarkers and argue that
as long as CAC = 0, there is no need to treat,
despite the risk predicted by biomarkers.

Fatty streaks don't show up on CAC.

A more sensitive test is CIMT. I had 11 patients with CAC zero but high CIMT. My 200 patient data link

If you are confused by all of the noise on this topic,
consider this example:
A biomarker like LDL-P or apoB is predictive.

It’s like saying you live in a neighborhood with a lot of break-ins.
A CAC is a backward-looking assessment
of damage that has already taken place.

Peter you make a very important point here.
ASHD is present with CAC greater than 1.
If nonHDLc kept less than 80 for rest of life with meds there should be no further build up of plaque (assuming other risk factors under control.)

So it’s more like an investigation
into a break-in
that already happened.

In my opinion,
waiting until there is grossly visible
(i.e., no longer just microscopic)
evidence of disease in the artery
to decide to treat
for risk already predicted by biomarkers
is like saying you won’t get a lock on your door—
even if you live in a high-risk neighborhood—
until you’ve suffered a break-in.

This is bad risk management.
As the saying goes, “When did Noah build the ark?”

Allen Sniderman has pushed for treating LDLc early. Multiplier effect link

Ultimately, it’s up to the individual,
who’s LDL-P and LDL-C
are very high while consuming a low-carb high-fat (LCHF)
or ketogenic diet (KD),
to make a decision:
the hope is that the following discussion
(and related references and material in the show notes)
can help people think through the issues and
make a more informed decision.