Please wait while the transcript is being prepared...
0:00
Today, I'm going to talk about using genetics
to determine causality
of a biomarker
in cardiovascular disease
using an approach known
as Mendelian randomization.
0:13
I'm going to touch on a
number of points in this talk,
including why we need
to use this approach
and what exactly is
Mendelian randomization.
I will then go on to
discuss in more detail
the different components
of this approach,
including the biomarker-disease
association and the selection
of the most appropriate SNPs
to use as our genetic instrument.
I will then go on to give some
examples where this approach is
being used to infer causality, as
well as to examine drug targets.
Finally, I will end with some of
the limitations of this approach.
First, let's start
with why we should
use Mendelian randomization
in cardiovascular disease.
0:53
Cardiovascular disease
is a complex disease.
There are many contributing
aetiological factors and risk
factors with several interacting
pathological pathways where
risk factors tend
to cluster together.
This makes it difficult to tease
apart which factors are causal
or which pathway should
be targeted for treatment.
Therefore, better
evidence for causality
is required since this can lead to
delays in potential new therapies.
One approach to infer causality
is to use Mendelian randomization.
1:29
We can use this approach to
answer two types of questions.
Firstly, is the relationship between
a biomarker and disease causal?
And secondly, to
examine drug targets.
What are the consequences for
biomarkers or disease risk
when you specifically
modulate the drug target?
