Genetic testing for risk of Heart Disease: fact or fiction? (23 Feb 2012)

Genetic testing for risk of Heart Disease: fact or fiction? (23 Feb 2012)


>>Professor Humphries: Well,
thanks very much, Audrey. And thanks for the
opportunity to present some of our work to you today. So you’ve seen up here on the slide the talk
is divided into 4 parts. I’m going to first of all
describe to you about the causes and the mechanisms
of heart disease. And then I imagine there’s
plenty of people in the audience who are not from a
genetic background, so I’ll tell you what a gene is
or remind you on how it works. And what is this SNP thing? You’ll find out by the end. And can we use DNA tests
to identify patients. So if you like the topic of
the talk is genetic testing for risk of heart disease. Are we talking fact or
are we talking fiction? A number of people
who are in my group, only some of them are mentioned
up here, who have contributed to the work and the work
is funded almost entirely over the last 25 years by
the British Heart Foundation. So I’ll be giving
them quite a few plugs as we go through the talk. So what are the common risk
factors for heart disease? Someone give me some
ideas please.>>Blood pressure.>>Professor Humphries: Yep. High blood pressure is
very bad for you, yep.>>Obesity.>>Professor Humphries: Obesity. Yes.>>Family history.>>Professor Humphries:
Family history. Yes, that’s, of course, the important one we’re
going to talk about today. Yeah.>>Smoking.>>Professor Humphries: Smoking. Very bad. Terrible. No one here smokes I’m sure. Yeah. Anything else? Yes. In the lay press there’s
bad cholesterol which is — which from a clinical point
of view is called low density or LDL, LDL cholesterol. And there’s good cholesterol
which is called high density like — high density
like for rating so good and bad, bad cholesterol. I mean high levels of
lipids is a problem. Anything else? Yeah. Lack of exercise. You’ve missed the two big ones.>>[ Inaudible ]>>Professor Humphries:
Yes and no. That’s not one of the —
what are the big ones?>>[ Inaudible ]>>Professor Humphries: Yeah. That’s on the list. Yeah. You’re right.>>[ Inaudible ]>>Professor Humphries: Diet. Healthy diet is important. But what am I? Major risk factor. And what am I as opposed to most
of the students in the audience? Age. So these are the list. These are the main ones. You got almost all of them. Well done. Now, some are modifiable
and some are not. Some have got a very
strong genetic contribution and some are mostly
environmental. Most of these risk factors
have got bits of genes and bits of environment in them. Okay. So let’s talk about
what are the processes of heart disease. In some of the slides,
you’ll see it as CHD an abbreviation
coronary heart disease. So it means that the arteries
in the heart are diseased. You may have seen a couple of years ago this very
challenging advert by the British Heart Foundation. For every cigarette we smoke
makes fatty deposits stick in our arteries. That’s a very nice graphic. And that, of course,
is one of the problems and that’s both genes
and environment. So here we’ve got an artery
of maybe quite a young man, young man or woman, opened up
post mortem along its length. And what you can see here
is there are these little yellow streaks. They’re called fatty streaks. They’ve got fat in them. You can see they’re oriented in
the direction of the blood flow. They seem to be very much
downstream of the branches. That’s a little blood
vessel going off. These are the very first
signs of atherosclerosis. You can find these
in young people in their teens or
their twenties. And what we hope is
and what we know is if you lower your cholesterol,
you can get rid of these. But they are the
precursors of this. This is an artery from maybe a
50 year old taken post mortem and now cut across. You can see interestingly this
part of the artery wall is fine. It looks nice and thin but
what you’ve got here is a big cholesterol laden plague,
an atherosclerotic plague, that’s more — that’s blocking
at least half of the lumen here. That’s an advanced lesion. And this is what
something looks really bad. This is a genetic disease
that we do a lot of work on called familial
hypercholesterolemia. It’s a 45 year old smoker. The whole of the artery from this individual is
just completely stuffed with this cholesterol. Obviously bad news. Here’s again, cut-in section,
an intact advanced lesion. Again, part of the
blood vessel looks fine; here is the plaque here. Here it’s no longer cellular. Cholesterol has killed the
cells and they’ve died. So there’s what’s
called a necrotic core. But there’s lots of
muscle cells, there’s lots of smooth muscle cells, epithelial cells
keeping this happy. This one’s not a problem yet. But if you were open that up,
you’d see this sort of thing, a bit like a fried egg. Some — maybe some blood
clotting has gone on here. You can see it’s sort of
ulcerated, there’s little holes. It’s leading to trouble. It’s not looking clever. And this is what happens when
one of these lesions ruptures. You get a clot. This, again, in section, this
is maybe a platelet rich clot covered with protein, the
fibrin that’s made the fibers that forms the clot. And if you would open that
up, that’s what you’d see. So here you’ve got an
atherosclerotic lesion, a bit like this. It’s ruptured and this
clot has formed on top and blocked the blood flow. Now you can see atherosclerosis
in the arteries in the heart using — of a living person using a
technique called angiography. An x-ray of opaque dyes injected into the bloodstream
via a catheter. And what you can see here — and you can take a
series of x-ray pictures. You can see that some of these
blood vessels are really nice. The blood flow is going
through very happily. And others are looking
really bad. This lesion looks
pretty terrible. There’s almost no blood
getting through there at all. And of course the problem
is when that happens, if the blockage is complete, the clot completely
prevents oxygen flowing, then no oxygen will get through. That tissue will die. And that’s what causes
a heart attack. So what you’ve got to think of that heart disease
is an ongoing process. So we’re born with very nice
clean arteries here, and the 20s or 30s, we get the fatty streaks
leading to this sort of thing. And this is clinically silent. No one knows they’ve got this. Maybe by the 50s or so,
people might get chest pains when they run for a bus. In other words, there’s enough
blood and oxygen flowing when they’re sitting down, not doing anything,
there’s no demand. But when the heart
needs to pump more, there’s not enough
oxygen getting through and you get chest pains. A big sign. Go to your doctor. Try to see what’s going on. Then you get the plaque
rupture, the clot forms, and you get a heart attack. And then this is the
Heart Foundation campaign. The main problem from people
dying from heart disease that we can fix is not
calling 9-9-9 early enough. Oh, I’ve got angina. No, you’re not, you’re dying. And so when you get this
or when your husband or someone else starts feeling
this crushing chest pain which is visualized by this very
nice poster, call the ambulance, take an aspirin, get to the
hospital as quick as you can. So understanding this
gives us some clues about the genes we should be
thinking about when we’re trying to work out a genetic test. The thing to remember is that heart disease
risk is multifactorial as we already showed
in an earlier slide. So what you’ve got is,
some people by luck, have inherited very
few risk raising genes, risk raising alleles. And others have inherited
lots of cholesterol genes, blood pressure genes, clotting
genes, things like this. But equally we inherit
different environments. Some of us choose to
maintain a healthy environment and others don’t and
by all these thesis of things that we discussed. But really heart — the risk of
early heart disease only occurs when you’ve got a bit of both. It’s this overlap when you’ve
got a number of high risk genes, a number of high
risk environments. And the thing to remember
is that nature loads the gun and nurture pulls the trigger. You have to have both
to get an explosion which in this case
is the heart attack. So the research that
we’re doing is try to find the genes involved,
the way they interact with each other and with diet, and we use this for
patient benefit. Okay. So if we’re going to
try to develop a genetic test, what are the criteria we need
to set out before we do this? It’s got to be predictive over and above the established risk
factors we talked about earlier. It’s clearly got to take
environment interactions into account. It may be that a particular
risk gene is only important if you smoke. Doesn’t matter if
you don’t smoke. It’s only important if your
— high blood pressure. So that’s really
quite important. Clearly it’s got to be accurate
and not to be associated with negative psychological
impact. And if I’ve got time at the end,
I’ll come into that question. But why are these predictive
tests going to be helpful? Well, in the U.K., if
an individual has a more than 20 percent risk of
developing heart disease over the next ten years,
NICHE, the National Institute of Clinical Health
and Excellence, says you can give him a statin. Who is currently taking
statins in the audience? At least a half dozen people. Good. Excellent. Well done. And what are the statins doing? Why are you doing it? To lower the LDL cholesterol,
to lower the bad cholesterol. And they do it very well. They lower LDL cholesterol
and they lower heart disease. Wonderful. But they cost money and
clearly you want to give it to the people who are
going to benefit most. So here’s the typical
U.K. punter. You can see his age,
his LDL cholesterol, his HDL, blood pressure. He’s a smoker; he
has a family history. If we stick that
into a risk algorithm which the government
says we should use, his 10 year risk
comes out at 21%. So great. No problems. The doctor doesn’t have a
problem giving him a statin. Here’s his colleague at work. He maybe goes to the gym
a couple times a week. You can see he’s not overweight. His lipid profile’s
a bit better. But he’s got smoker, blood
pressure, family history. You put that into the algorithm,
his 10 year risk is only 18%. You tell him to stop smoking. You’re not really officially
allowed to give him a statin. Now it maybe that this man here
has actually inherited lots of the bad risk alleles, his genetic makeup means
his risk is much higher than this individual so what we
really want to do is try to work out tests that would allow us
to distinguish people who are at this intermediate risk into
those who are genetically high or genetically low risk. So how do we currently
estimate an individual’s risk? There are a number of algorithms
that are used very widely. There’s one called Pro
Cam, one called F’Ham, there’s one called Q Risk,
there’s one called Score. They all basically
work the same way. Just focus here on
this F’Ham one. So they stratify by a risk
factor and give you points for high blood pressure,
whether you smoke, whether your HDL is low,
whether your LDL is low, whether you’ve got diabetes. And in this case,
points don’t mean prizes. Points mean risk
of heart disease. So what you can do if you
took a large group of men, the distribution of their
risk would look like this, and their distribution of
score would look like this, and their risk would go
up something like that. So let’s see how it works. This is a study that we’ve
done a lot of work on. It’s just over 3000 healthy
middle-aged men recruited from 9 general practices
throughout the U.K. They were all free of heart
disease on entry. And then in the first 10 years, 200 of these individuals
have an event. These are the baseline
characteristics and if you look at the event group
compared to the event free, the ones who went on to have a
heart attack were a bit older, a bit fatter. Their blood pressure
was a bit higher, their cholesterol was a bit
higher, more of them smoked. So very much the sort of risk
profile that you would expect. Okay. So what percentage
of the events that actually occurred do
the risk algorithms predict? I’d like to be able to
tell you that they pick up 60,70,80,90%, they don’t. This, in cartoon form, is the
risk score distribution in those who didn’t have an event. This, in red, is the
score of those who did. If we set a cutoff here so that
we pick up a false positive of 5% of the men who
don’t have an event, we correctly identify
14% of those who did which means we’ve
missed 86% of the events that actually occurred. It’s a rotten test. It’s the best we’ve got. And it’s being used by doctors
all over the place to decide if you’re going to
get a statin or not. In other words, these folks up here get a statin
and these don’t. The problem is most events occur in people who’ve got
average levels of risk, sort of by definition. So looks like there’s plenty
of room to improve on this if we can find some useful
individual genetic information. Okay. That’s the
heart disease bit. Let’s go on to the genes bit. Now each chromosome
is the storage unit for thousands of genes. We now know we’ve got
about 25,000 gene pairs and they make us who we are. You, they come in
22 matching pairs, one from mom and one from dad. Here they are spread out in
what we call a cario type. And this individual has 2 copies
of the X chromosome so this is from a female individual. Male has an X and
an Y. Genes are made up of 4 chemical codes
known as DNA of course. Adenine, Cytosine, Guanine, and Thymine in the classic what
someone crypt, the double helix. A gene can be many
thousands of these bases long. And the information is a code. It contains what you need
to make a whole human being. The cell reads this and
is told what to make, when to make it, and
how much to make. When a change occurs
in the DNA sequence, the genetic instructions
are no longer correct. It’s like having a
typo in the manual. One base is changed to another. For example, CAT becomes TAT. It means the cell makes
a part that doesn’t work, sometimes bases get missed out,
or are copied too many times and the cell makes too
few or too many parts. Imagine the manual tells
how to make an umbrella. So here’s the gene and the
gene says, when it rains, I’m going to make some proteins
that will protect the cell. Let’s make some umbrellas. Okay. So here’s a gene
that’s got a mutation, a single based change, and
it could be that instead of making lots of
umbrellas, it only makes one. Obviously not protective enough. Or it could make an umbrella
that doesn’t work quite right. It opens and closes again. Okay. Or it could be
that it makes the protein at the wrong time. You can see how using
this simple analogy, that mutations either mean that the gene doesn’t
make enough protein, doesn’t work right —
well, or is not made in the right time
or the right place. Genes make proteins that
are important for health. Mutations stop them working. There are 3 different
types of genetic disease. Chromosomal disease. You can think of Down’s Syndrome where an individual has
3 entire copies of one of the small chromosomes,
chromosome 21. Single gene defects,
like Huntington’s or cystic fibrosis
or haemophilia. But what we’re interested
in, of course, is multifactorial
diseases where there’s lot of different genes involved. Hypertension, obesity,
diabetes, and heart disease. Again, I just make this point,
the clinical consequence of all genetic disorders
is modified by environment. You would think, of course,
that hair color is genetic, but many of us in the room
are modifying our gene type by using some sort of chemicals. And clearly, tall parents
have tall children. But if those children are not
fed well, they will be shorter. So all of these different
traits, there’s both genes
and environment. So how can we look
at a person’s genes? So what we need — what we
use is something called the polymerase chain reaction
and I’ll just spend a couple of minutes telling you about
this because it’s so clever. What you need is the gene
sequence that you’re interested in and from that you design
what are called primers. They’re homologous to a short
region of the DNA, the sequence of that gene, 20 or so bases. You’ll then need an
enzyme that will copy DNA, and it’s useful if
it’s thermastable. I’ll explain why then. You need the denaturise
buffer energy and you need a machine
called a thermocycler. Because what you’re
going to do first of all is take the DNA here and
denaturate it, so you raise it to 94 degrees, almost boiling. And the 2 strands fall apart. You then lower the
temperature to about 54. And what happens then is
these primers come along and find the place in the genome
that they are equivalent to. And they form what’s
[inaudible] as double strand. And then this enzyme takes these and copies them using
all the nucleotides. So what happens is you start off
with template DNA with 2 copies of the gene, you then
have 4, 8, 16, 32 copies. You keep on doing this
35 times and you end up with 68 billion copies
of just the fragment of DNA that you’re interested in. So you can see why just with
a nuclear chain reaction, this is a polymerase
chain reaction. So then you’ve got loads of
DNA, absolutely bucket loads and you can sequence it, you
can digest it, you can clone it. You can do all sorts of things. Now many of you know that the — there’s been a lot
of fuss in the press about the human genome sequence. This is the press
conference — Clinton — this is Francis Collins
who’s the director of National Institute of Health in the U.S. This is a venture
capitalist called Craig Venter. And they were announcing
the completion of the first draft
of the human genome. 10 years work, cost
$2.7 billion, and you can see the quote there. And our glorious
leader at the time, never one for missing an
opportunity for hyperbole said, “It’s a revolution
in medical science. A breakthrough, it opens
the way for massive advances in the treatment of cancer
and hereditary disease and that’s only the beginning.” In this instance, he was right. You can believe him. It has revolutionized
our research. Back in the days in the 70s,
I won’t go into the details, but we could work
out one individual — we could work out a
single based chain in 20 individuals,
it took us a week. At the Steam Age in the
80s, we could do maybe 200 to 2000 individuals in a week. In the 1990s, we were up to 3000
to 5000, and for Star Trek fans, we are now in the warp drive
where we can do 100,000 a day. I mean we’ve got databases,
tons of information. There is a bioinformatic
gold mine out there. We can now capture DNA from the
whole genome in one experiment. Okay. So what’s a SNP? SNP stands for Single
Nucleotide Polymorphism. It means one base in
the DNA is changed. Polymorphism is from Greek. It means many shapes. So it means the difference in
DNA sequence found commonly in the population, but we define
it as more than 1% of people. So here’s the sequence, it’s
there and then in the other — in another individual, there’s
an A instead of a T. Clearly if it occurs in the
coding region of the gene, it’s going to affect
a number of umbrellas. Most of them occur outside
the gene and are of unknown or of no effect but we can still
use them as genetic markers. And they’re all given a unique
ID; it’s called a RS number. So SNP would be called
RS #237… And we’re all getting very used
to recognizing 7 or 8 numbers and keeping them in our heads. How do we choose
the genes to study? Well, clearly, because of what
we know about the pathology, we can think of genes involved
in lipid metabolism, clotting and hypertension, and we
can start looking at these. These are very easy
studies to set up. But most of them
were underpowered. There were too many —
because we were limited by the technology. We could look at — it
took us months to look at 200 patients and
200 controls. And many of the results didn’t
stand up to the test of time. What we need is a
hypothesis free approach and with the technology,
we can now do this. So what we do is we
take 2000 cases and — with heart disease,
2000 controls. And companies now make gene
chip devices which have 300,000 or a million of these
SNPs spread throughout the entire genome. We can cover the entire genome
with one little chip like that. So what we do is for each
of these SNPs we look to see if the frequency is different
in the cases and the controls. If the frequency of
this SNP, this allele, is base change is higher in
the cases than the controls, significantly, then we say
Ah, this gene is marking — this SNP is marking a gene
that increases your risk of developing heart disease. Now, of course, if
you’ve got a million SNPs, you have done a lot
of contrasts and many of these will be statistically
significantly different by chance alone. So what you have to do
is set a very low P value as your threshold. And what you have to
do, more importantly, is to replicate it
in the second study. That’s what people have
been beavering away doing for many years now. And if you look on this website,
in the middle of last year, there were more than 237 traits that had been mapped
to the human genome. And they’re for all
sorts of things. Some of them are very
interesting and some of them are very
weird and wonderful. It’s amazing what you
can do with genetics. You can find the gene
causing restless leg syndrome. But some of these, of course,
are very important genes and we want to know about them. The way that the
data is presented is in what’s called
a Manhattan plot. You present it along
the X chromosome here as the chromosomes and up
here, in fact, it’s the log — minus the log with the P value
so what you want is to find lots of different P values that are
statistically significant being associated with your trait. In 2007, there were
3 GWA studies, genome wide association studies for heart disease
published at once. All 3 of them looked like this. There was one hit and one
hit only on chromosome 9. It’s not really a
Manhattan skyline, it’s more of a Oxford skyline. Now, replicating many
independent data sets, a major breakthrough. What the heck is this gene? It wasn’t anything that
we’ve ever thought of. It occurs in a gene desert. The nearest gene or codes
or proteins that we know about are 58,000 bases
away, miles away. The common SNPs are, however,
strongly associated with risk and compared to the AA, to
people who’ve got 2 alleles, if you’ve got one gene allele,
your risk is 30% higher. Two G alleles, 60% higher. But interestingly, these
GG people weren’t — the fact that they didn’t
have high cholesterol, they didn’t have
high blood pressure, we still don’t really know
what the mechanism of this is. But it’s certainly —
I’m going to skip this because we’re running
out of time. But it certainly looks like it’s
going to be of clinical utility and you can actually buy it now. You can actually go
online at 23andMe. If you send them $399 they will
test you for this single SNP and that’s its RS number. If you go to deCODE,
they will also do it and they will just send a SNP. Now is it worth $399? Might be. Let’s see. So we looked — went back to Northwood Park
[assumed spelling] and found exactly the
same results compared to the AA group. Let’s see if you had 1 G allele,
your risk was 38% higher; 2 G alleles, it was
about 60% higher. This is adjusted for age,
cholesterol, triglycerides, BMI. It certainly looks
like it’s working well. So the question is, is
it going to add over and above the Framingham score? The one I showed you earlier. So we went back to [inaudible]
again and we looked at it and we got a 3% improvement. That curve was shifted
slightly to the right but they still overlapped. It wasn’t significantly better. The two — when we did tests, that wasn’t better
than the other. We’re getting there. But one single SNP
is not enough. Just as you wouldn’t
predict an individual’s risk by simply measuring cholesterol. You’d put them all together. Simply looking at
one gene won’t do it. It’s because heart
disease is multifactorial. You’ve got to have lots
of different genes. So here’s the chromosome 9 SNP
and we’re very quickly able to find by looking at data,
a whole bunch of others. And then earlier,
about a year ago now, a whole bunch of
others were found. We are now doing GWAs
by combining data in 100,000 individuals
and it gives you the power to find very small effects. But we now have over 50
heart disease risk genes. The alleles are common but they’re all having
this modest effect. They’re increasing
your risk by 10%, 20%, the chromosome 9 one
is the biggest one. That’s why we’re able
to find it first. So what are we going to do? Well, what we want to do
is put them all together. We would need to combine them in
what we would call a gene score. So we put together a
number of genes involved in lipid metabolism, clotting,
and endothelial function. So 13 SNPs in these genes. 7 of these, GWAs SNPs,
the earlier ones, and we look at the
frequency distribution. Now, we’ve simply used
an additive model. We say at each SNP if
you’ve got no risk alleles, we’ll score you 0. We’ll score you 1
if you’re a carrier. And 2 if you’ve got 2. It’s very simple. It assumes equal
and additive effect. We can do much better than that,
but this is a simple first-go. And we went back to
the Northwood Park map. This is the distribution
in Northwood Park. This is the distribution in
U.K. Caucasian individuals. Median number is 15. What you can see
there’s a group of people that have got 12 or fewer. We imagine they should
be protected. A group who’ve got 18 or more, our guess is they’re
going to have higher risk. How does it actually work out? This is how it looks. It looks just what we wanted. So compared to this
group in the middle here, we’ve got average risk, we
can identify that these people who are in the lower,
the lower three tenths of the risk, they’re protected. The average risk is
about half of this group. And this group here, in
the top three tenths, their risk is almost 2, 2 1/2. Just to put that in context, a
risk of 2 is about what smoking, lifetime risk of smoking is. If you smoke, it roughly
doubles your risk. So what we can do with
this score is identify men, maybe 20% of men who have
a genetic risk as high as if they were smoking. We all know doctors try
to stop you from smoking so this really just
puts this into context. So can we go home? Are we all done? No. The heritability of
heart disease are 45 to 50% so roughly half the causes
of heart disease are genetic and roughly half of
them are environmental which is pretty much
what we’d expect. So here’s a pie chart,
half environment. We have maybe found 10% of the
genetic cause of heart disease with the SNPs we’re looking at. The problem we’ve got is
we’ve only found this bit. We’ve still got to
find all that lot. There’s a number of
possible reasons why, I won’t go through
them in great detail, but we’ve still got
a lot to learn. Can we find more by sequencing
an individual’s genome? Now you may remember the first
genome cost how much was it? $2.7 billion — oh,
it’s got a lot cheaper. You can now sequence
a whole genome for an individual for $5000. You can sequence just
the part that codes for proteins for about $1000. You can just take these 40 genes
that I’ve been talking about and you could probably get
them sequenced for $500. This sounds like good value. This sounds like it
would really be useful. Now the problem is
the bioinformatics. We are drowning in data and we
don’t know what to do with it. One of the projects I’m
working with is funded by the Wellcome Trust and it’s
called The U.K. 10,000 Genomes Project and they’re
doing just that. They’re finding the genome, they’re sequencing
the entire genome of about 6000 individuals. And just the exomes,
the part that codes for proteins, in about 4000. And we’re providing samples from
people with this disease, FH, this inherited high
cholesterol disease. Here’s the results for the
first 22 of these samples. Each part — each coding part
is covered more than 74 times, we get 30 million bits
of DNA information. This is what’s startling. So for every patient, and for
everybody in this room as well, we got about 42,000 SNPs. And about 1100 of them have
never been seen before. They aren’t in any
of the databases. They’re completely novel. And we use could bioinformatics
and predict that about 350 of them are likely to
affect the protein and 10 of them are likely to
make the protein shorter than it should be,
to truncate it. So we could guess
that each individual, everyone in the room, has
got about 350 variants that are going to
affect the protein. This is why you shouldn’t
marry your cousin because it’s very likely
that there will be — any children will have 2 copies
of this, one of these genes, and that could really
affect disease. So we’re in the needle
in the haystack business and it’s a big challenge. So yes, we can do
it technically; we can’t actually
analyze the data yet. So these are the criteria that
I set out in the beginning. Criteria for useful
heart disease tests. I’m quite certain with several
genes, we’re going to get there. We certainly are not taking
interactions into account. I told you the model
is additive. Work to do. I hope I’ve persuaded you
that we do have accurate and reproducible risk estimates. But all the studies almost
so far have been in white, Caucasian, middle
class aged men. We don’t know anything
about women. And we certainly
don’t know anything about different ethnic groups. And then what we don’t have —
maybe I’ll have to skip this — I’ve got 5 minutes; okay. Let me just explain to you
about the psychological impact. What’s the concern? The concern is that is if about
— what we call genetic fatalism or forced reassurance. There are, of course,
issues of confidentiality but let’s not worry
about those right now. This is a cartoon
illustrating this and here’s Freda and his Fanny. They’ve just been given
their genetic test results. They’ve gone home. They’ve lit up cigarettes;
they’re drinking martinis. And Freda says, “I haven’t got
the genes so it’s fine for me to smoke” and Fanny says,
“I’ve got the genes. So I guess I’m doomed anyway.” So all out technology
is to no avail. And there was a lot of concern
about both of these aspects. And it really seems now
we’ve got more data, that these are unjustified. Studies actually suggest that DNA risk information
doesn’t increase fatalism and it actually may motivate
people to change behavior, to actually take their
medication and things like this. So I think this is an issue that we probably don’t
need to worry about yet. So heart disease risk test,
I think it is possible. We need to use several genes. It’s got to be based on
good data and currently, there are some gaps in that. Don’t bother buying over the
internet because without use — without having the information about your other risk
factors, it’s not valuable. It will help us to risk stratify
those 2 men that I talked about and the idea would be that
before you come for a clinic, we would ask you to send us
a saliva through the post and we could then test it. We could test 20 SNPs,
40 SNPs, a thousand SNPs. And we would then present
you your risk information, your 10 year risk information, based both on your
classical risk factors and your genetic risk factors,
and then we would work with you to try to reduce
your overall risk. We still need to compile
how to best present the data for maximum understanding. So yes, heart disease
DNA testing is ready now. And finally, the
take home message is that small differences in your
genes make big differences to how you look, but
also to your health. And, Audrey, I’ll stop there. Thank you. [ Applause ]>>Audrey: Thank you very much. That was a tremendous talk. We have 5 minutes for questions. Would anybody like
to raise a — yeah.>>Professor Humphries:
Microphone’s coming. Just wait.>>Hi. Thanks for a
really interesting talk. I was just wondering do you
think doctors are well equipped at the moment to give
that information?>>Professor Humphries: Not
in the slightest I’m afraid. I know of a number of colleagues
in the medical school, people are — having the tests. They’re getting 23andMe
reams of information. They’re going to their
cardiologists and saying, look I’ve got this and
that and the other. I’ve got this chromosome 9 SNP. And it’s a bit — one of my
jobs is to educate doctors. We need to be doing continued
professional development so they know about
this sort of thing. And as always, it’s
about the balance between hype, fact and fiction. In other words, to what
extent is this information clinically useful? I mean I think it
is, but 23andMe and deCODE don’t present
it to you in a way that you can understand or
in a way that the doctor can. I can but that’s a bit
different, isn’t it? So these are the things
that we need to be doing.>>Audrey: We have
2 final questions.>>Professor Humphries:
One right here.>>Excuse my voice. It’s gone a bit. I’m afraid I missed the first
few minutes of your lecture so you may have covered this. This is anecdotal but all
my family, for as far back as medical records go, have
suffered from only one thing which is high cholesterol. No high blood pressure,
no cancer, anything. And it’s always scared me out of
my wits that that might transfer over to cancer, but
nobody’s ever had cancer. We don’t smoke; we
don’t eat animals, and we don’t drink, so –>>Professor Humphries: Are
you taking a statin or –>>I don’t want to take a statin
because I’m — somebody I knew, one of teachers from I think
it was University of — College School, a math teacher
took statins for a while and then he threw
himself under a train. It struck me that I
stood more chance away from the railway lines.>>Professor Humphries: One of
the things that I just touched on very briefly is that inherited disease called
familial hypercholesterolemia. High cholesterol runs
through families. I don’t know. It sounds like that’s what’s
happening in your family. It’s a single — it’s a
mutation in a single gene. It knocks out this gene and it prevents you removing
cholesterol from the blood. So you have high cholesterol
and early atherosclerosis. People who’ve got this disease
have maybe ten-fold higher risk of early heart disease. And if we find them and give
them a statin, that risk reduces to the same as the
general population. We have shown that these
individuals, people with FH, don’t have a high risk of
cancer and when they’re treated with statin, they
actually are — I guess you could
say paradoxically, they’re actually
carrying less cancer than the general population
because we tell them not to smoke and they don’t smoke. So they’re not dying of lung
cancer or other cancers. Statins are in general
remarkably safe. We’re very lucky to have such a
powerful and such a safe drug. There are some side effects. There are some muscle pains. But my recommendation to
you is that you do get a — you ask a GP for a
referral to a lipid clinic. We’ve got a very good
lipid clinic at UCL and get a proper diagnosis. And then you really should
consider taking a statin.>>I feel confident –>>Professor Humphries:
You know what? I think we better stop.>>It’s just that –>>Professor Humphries:
I’m happy to talk to you afterwards but –>>Audrey: I think that’s
actually all we have time for today. Quite a day. Join me in thanking Professor
Humphries for a great lecture. [ Clapping ]