[Rhonda]: But if someone were to have their lipid panel done by their physician, and it
was 150, let's say they didn't know they were ApoE4.
Their physician would look at them and go, "Whoa, that's really high."
[Ron]: Right.
And I think, you know, it's not just on the LDL, but there's a range.
If you want to actually pick a number, the sort of consensus number that the lipid community,
the cardiology community has accepted as mandating attention for genetic reasons is an LDL actually
at 190.
So it's even higher than that.
So I'll start with that.
If your LDL is 190 and greater, the particle measurement probably isn't going to affect
the treatment decision because in almost all cases, those patients have genetic abnormalities.
ApoE may be part of it, but not the cause of those very high levels, that's usually
an LDL receptor abnormality.
Those patients are at, sufficiently, a high life-long risk of heart disease that they
are candidates for statin therapy almost in all cases.
It's very difficult to achieve a significant approach towards optimizing LDL levels in
those patients.
So that's 190.
One-fifty, sort of halfway in between.
So that's a gray zone.
And so it depends not just on the LDL, but the overall risk, blood pressure, diabetes,
family history.
[Rhonda]: Triglycerides?
[Ron]: And triglycerides have not entered into the equation.
So, you know, there's epidemiologists that do all this number crunching, and they come
up with risk assessment tools.
Triglyceride hasn't entered into it because it's so tightly related to everything else.
And so it's a very bouncy measurement.
It's much less stable over time, even from day-to-day, as LDL cholesterol and HDL cholesterol.
So it sort of falls out of these equations.
But it's part of this atherogenic dyslipidemia phenotype, it's part of that trait.
It's important.
But as a measurement, it doesn't stand up to the LDL particles in terms of its association
with risk or even HDL.
So, anyway, this risk assessment is done, and then you decide, "Well, is this patient
at sufficiently high risk using these," you know, if you're in the swing of things with
the guidelines, you do these assessments of likelihood of having a heart attack over the
next few years, and if it's high enough, then you jump in with aggressive treatment.
And I think if the risk was high enough, you'd probably use statins.
You need to use statins for those patients, as well, but it's not an automatic decision.
That's where the particle measurement hasn't yet achieved the level of acceptance to enter
into those risk calculation formulas, partly because the risk assessment tools that we
have work pretty well by themselves.
And this is actually a very interesting point from sort of a, how should I say, a conceptual
standpoint.
So I'm just going to say this because that's maybe a little bit complicated.
But when you have some very strong predictors of heart disease risk, blood pressure, diabetes,
even LDL cholesterol, HDL cholesterol, use standard measurements.
And you throw them into a risk formula and you add in age and sex, you can explain a
lot of risk that way.
We can argue what that explanatory number is, whether it's 50% or 70%, it's very high.
So if you add LDL particles or these more refined measurements of particle concentrations
into those formulas, you don't get much additional explanation of risk, because a lot of these
things are interrelated with one another.
And so there is a confusion between the magnitude by which you can improve risk prediction by
these measurements versus what's really important biologically that you should be treating.
And so people think, "Well, because the particle measurements don't add that much to the risk
assessment," but it adds to the measurable amount, it's not just a lot, people say, "Well,
let's not worry about that."
But from a biological standpoint, that may be the driving factor.
So if you turn that whole process around, and you throw out the standard factors, and
you just use the particle concentrations and maybe a few other things like age and sex,
you can also explain a lot of the risk.
So you can choose your weapon, but don't confuse the ability to predict risk with what you
should be treating, because those are not always the same.
I hope that's not too complicated, but that, to me, is a very interesting point.
[Rhonda]: It is very interesting.
It is very interesting.
It is a little complicated.
[Ron]: It is complicated, so we may not want to get too far into that.