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0:00
I'm Jenny Barrett, Professor
of Statistical Genetics
at the University of Leeds
in the UK.
And in this talk, I'm going
to give An Introduction
to Genetic Association Analysis.
0:12
Genetic association
simply refers
to the statistical association
between the genetic variant
and the trait.
The trait could be categorical,
such as whether or not
someone has diabetes
or continuous, like height.
So for a disease trait,
genetic association is seen
if the disease frequency varies
according to genotype,
or equivalently,
if particular genotypes
are more common in disease cases
than in controls
from the same population.
Here, if we look
at the three genotypes
AA, AG, GG,
defined by one particular
A-G single nucleotide
polymorphism or SNP,
we see the frequency
of a common disease in people
with the three genotypes varies
from 515 per 10,000 adults
in those with the AA genotype
to 712 per 10,000 adults
with the GG genotype.
Similarly,
for a quantitative trait,
we might see
a slightly different
distribution of trait values
according to genotype
illustrated here
by height in adult males
where we can see
the mean height is highest
in those with the AA genotype.
1:26
Tests for genetic association
with a single genetic variant
are very simple.
We'll begin by
considering binary traits,
typically a comparison
between cases
with a particular disease
and controls.
Note that most of the examples
in this talk will be about SNPs,
although, there are other types
of genetic variants
such as simple indoles
that could be analyzed
in a similar manner.
A simple test for association
is the chi-squared test.
So a chi-squared test
on this 3 x 2 table
shows very strong evidence
for association,
where we can see the difference
in genotype frequencies
between cases and controls.
The GG genotype,
and to a lesser extent,
the AG genotype
is much more frequent in cases.
Furthermore,
we'd probably be interested
in estimating the relative risk
associated with each genotype.
Assuming the data
from a case control study,
we could do this
by calculating an odds ratio
to estimate risk to individuals
with the AG or GG genotypes,
compared with AA as baseline.
If the disease is rare,
this gives a good approximation
to the relative risk.
So we see, in this case,
that the heterozygotes
with the AG genotype are at
about 30 percent increased risk
with an odds ratio 1.29,
and the rare homozygotes
are about twice the risk
compared with the baseline.
Note that this test
of the 3 x 2 table of genotypes
versus disease status
is a very general test.
No assumptions are made about
the nature or pattern of risk.
This has advantages.
It's good
not to make assumptions,
but also disadvantages in terms
of likely loss of power.
If instead, we're prepared
to make assumptions
about the genetic model,
then other more specific tests
can be used.
