Read studies about the science of heart attack and stroke prevention. You're
gonna see this term sooner or later - Mendelian randomization. Now, what the
heck is that? and why is it important? what's it used for? Well, the age of
genetics is clearly upon us and one of the things that epidemiologists study -
study authors in multiple areas, ranging from bone transplant, to drug development,
to prevention. All are beginning to discover this technique and what is it?
It's - it basically takes the fact that genes tend to be distributed at random.
So, let's say your father has one one blue-eyed gene and one brown-eyed gene.
So he's got brown eyes and your mother has blue-eyed genes, so she's got two
blue-eyed genes. Your father's got one blue-eyed gene, one brown-eyed gene. So at -
both his eyes are brown because brown is dominant. Your mother - it has two
blue-eyed genes, so both eyes are blue. What will the kids be? Well, we know brown
is dominant. So, half the kids have brown eyes, half the kids will have blue
because half of them will have gotten the father's brown-eyed gene, and the
mother's blue-eyed gene. So, they'll be brown-eyed. Half of (them)will have gotten the
father's blue-eyed gene and the mother's blue-eyed gene, and they will be
blue-eyed. Here's what we don't know - which half. And
so, that's what we mean by a random distribution of genes - Genetics. What
researchers have begun to realize is they can take that randomization and, in
many ways, use that to replace some of the function that we see in randomized
clinical trials. Let me give you an example - Does being obese cause a heart
attack or is the same something else that's causing obesity all
cause that heart attack? Well, they've actually done studies on that and that's
how this came up in our - in our channel. I'll talk about those studies in just a
minute, but let's go back. Again, a little bit more into the history of Mendelian
randomization. It's credited to these two authors Gray and Wheatley. And as you can
see, they're not so much epidemiologists as they are bone marrow transplant guys
and they came up with this idea on how to avoid bias when comparing bone marrow
transplant - transplantation with chemotherapy. Now, actually there was an
author before that - Katan. He was in more of the prevention area. He was
talking about apolipoprotein E isoforms and cholesterol and cancer.
Again, I'm not going to go into either of those studies. Right now, I'm gonna talk a
little bit more, just about - though, the whole concept of Mendelian randomization.
Now, we again - we first talked about it as we were going through the obesity
paradox when thinner means sicker and heavier means healthier. I'm
not going to get deep into those studies or those concepts other than to say that
as we studied that, we found that this was very much related to the issue of
lethal sarcopenia and, again, we had several videos that covered those issues.
We're not going to spend any time on those. We're going to go straight to the
article that brought up Mendelian randomization for us and that had to do
with obesity in cardiovascular outcomes. So I just mentioned that a few
minutes ago. There was a study in JAMA cardiology - the network, open network
group where they did a meta-analysis. You know... the Cochran studies where you take
multiple studies and you pull them together to see what they show. But these
were a unique type of study and they only found 5 of them, it's a
study where you do this. You take a large population. These were called GWAS -
Genetic - Genome Wide Association Studies. So they
took a large population, each of these studies did that. They looked at genes
that are associated that appeared to cause obesity and there are some - if you
didn't know that - yes, obesity does have, clearly, a genetic component. So they
separated those out here and looked at the - the race of heart disease. They
compared that in the race of the heart disease in the control group. The people
that did not have the genes for obesity. Here's what they found:
Yes, the people that had the genes for obesity had increased risk for not only
heart attack but diabetes as well. So, very interesting and in many ways not
surprising. There was one surprise twist which I don't think we can explain. If
you want to - if you want to bottom line on that, I think the bottom line is still
a mystery. In that same study that - they did not find that relationship with stroke.
You saw the same amount of strokes in both of these populations. The study
population and the control. Now, were these big studies? Yes, the total was
almost a million. So, statistically - very powerful studies. And, again, it over - Now,
why did they have to use this technique and, again, as we began to
discuss it, I think it becomes clearer what Mendelian randomization is about.
Let's say we wanted to find out - Does obesity cause heart attack and stroke?
Well, if you're gonna do a randomized clinical trial, first you have to get a
large group and you have to randomly assign obesity to one group and not to
another. You can't do that. How are you going to say "Okay, we've picked a 100,000
people and this 50,000 is going to be - is going
to become obese. You can't do that. Obesity and its relationship to
something like heart attack - it's always going to be what we call an
observational study. But let's go on. Let's just humor us - humor ourselves here
and say "There's a way that we can randomly assign and make somebody obese."
You know there's a thing called blinding as well. In other words, you have to blind
the patient and the healthcare provider - the doctor, to the fact that this person
has the exposure and this one doesn't. In other words, how are you going to blind
the patient and the doc to the fact that you've made them obese? Again, just will
not happen. That's why we get into this question of randomization and bias and
confounding and using - since you can't use randomized clinical trials, use the
randomization of genetic distribution. So if that's still making your head feel
kind of hurting and turning inside out, trying to link those two - you're not the
only one. There's whole textbooks on how to do this. I will also share - there's a
Mendelian randomization Bootcamp at Columbia University later on in 2019, if
you really want to go. You can spend a few days talking about exactly how to do
that but it might be helpful if I go back and - and use another example of
Mendelian randomization in prevention and it has to do with C reactive protein.
Now, those of you who've seen any of my - well, have seen many of my videos, will
remember C reactive protein. I've got several videos on it and if you
don't know what it is, take the inflammation course. In the inflammation
course, I tell you how to find out whether or not you have cardiovascular
inflammation. One of the key studies for cardiovascular inflammation - one of the
key labs is CRP (C reactive protein). C reactive protein is made by the liver
when there is inflammation going on in the body. The guy that came up with this
whole idea that cardiovascular inflammation causes heart attack and
stroke, Paul Ridker, a very smart guy at Harvard - that's really all he uses. I
tend to use more than c-reactive protein. I also use microbium and creatinine ratio, MPO,
Lp(a). But, let's go back to CRP and Mendelian randomization. So there are
genes that are, as we said before - excuse me,
randomly distributed genes which cause high CRP so let's ask the question: Does
having an elevated c-reactive protein cause heart attack or is there a
confounder? Something that biases the study for people that have elevated CRP?
Well, since we know there are genes that will create elevated CRP in people, there
are genes that - for example, slow down the breakdown of c-reactive protein. If we
can look at those, find those genes and - what we can do is this: Again, take a
large population. Find those that have genetic elevated CRP. Now, if that group
has higher heart attack and stroke risk, then we know that CRP actually
causes it. If it doesn't have a higher heart attack and stroke risk, it's the
same as the group that does not have genetically elevated CRP then it's not
the CRP that's causing it because you got a higher CRP in the genetic risk
group. So, again, that risk group - if the CRP were causing it, should have more
heart attacks and strokes. And here's exactly what you see on the - on the image
behind me. When we do random - when we do testing, if your CRP begins to elevate -
Yes, you are much more likely to have a heart attack or stroke. However, if
you do... Again, a genome - why does GWAS or if you just do a genetic study, you pull
these groups and you look at it. The groups that have genetically elevated
CRP do not have an increase in heart attack and stroke. Their relative risk is
one. So what we know is that CRP - elevated CRP is a marker, not a cause of heart
attack and stroke. So, for those of you that have made it this far, as usual and
this time especially, we did some mind-bending stuff. I'm not the greatest
public speaker as I get reminded routinely on in the comments section but
I do have a passion for helping people understand the science behind prevention.
I hope this has been helpful and maybe even just a little bit eye opening in
terms of the science and what's happening out there today. Thank you for
your interest.