Carlos Bustamante: Well, it's a real pleasure to be here, and
I want to thank you for sticking for the last talk after not having much of a break, so
-- and also want to thank my co-presenters in the session, it's a very exciting session.
Hopefully, the slides will come up in a moment.
So if we take a step back and think about the last, say, five to six years of complex
trait genetics, one can say that they've been extraordinarily successful in identifying
common genetic variants that are associated with some amount of disease risk in populations,
largely of Northern European descent.
And so hopefully, is that -- it's not coming on?
Okay.
That's your guy's laptop, that's not my laptop, so if you pass me my laptop there.
Okay.
Not sure if that's -- not mirroring [spelled phonetically], is it?
Okay.
Now we're good.
Okay, thank you.
So, as I was saying, if we take a step back and think about the last, say, five to six
years of complex trait genetics, they have been extraordinarily successful in identifying
common genetic variants that are associated some amount of disease risk, largely in populations
of Northern European descent.
And this is kind of a quintessential example of the so-called genome wide association studies.
This is a study by my former post-doctoral advisor, Peter Donnelly at Oxford, which was
really a watershed moment in complex trait genetics.
This was published in 2007, where they took 14,000 cases, so 2,000 cases for each of seven
different disorders: bipolar disorder, coronary artery disease, Crohn's disease, hypertension,
rheumatoid arthritis, type one and type two diabetes, as well as a set of 3,000 controls,
and produced so-called Manhattan plots, so the y-axis here is the strength of p-value
of association between a particular genetic marker and disease outcome, and the x-axis
is positional on the genome.
They're supposed to remind you of the Manhattan skyline, and each of these towering skyscrapers
is a region of association with each of these different phenotypes.
And this is really fantastic and wonderful if you're British and born between the months
of March and April in 1958, or a British blood donor.
Then the Welcome Trust has invested millions and millions of pounds, which is more in dollars,
to figure out why you have a particular set of genetic variants, that may or may not be
associated with disease outcome.
But what if you happen to be born in Cairo, or Caracas, Karachi, or Washington, D.C.;
are any of these relevant -- are any of these variants relevant to your population, or to
why you may have a particular disease, and may you or your population harbor a different
set of variants that won't be characterized by this kind of a study?
And as Esteban mentioned, you know, one of the things that we're particularly concerned
about is the, you know, really lopsided investment in populations of European descent and the
consequences that that might have.
And, you know, I'm happy to report that we're actually now -- we and others -- are part
of large endeavors to do multi- and trans-ethnic studies that try to, you know, get at these
issues and understand the contribution of both common and rare genetic variants to disease,
and that's what I hope to tell you a little bit about today.
But really, we need to understand some very fundamental questions about the structure
of human genetic variation at this scale in order to be successful in this enterprise.
So we need to understand to what degree are human populations that are going to be enrolled
in such medical genetic studies substruction and different from one another.
What are accurate models, statistical models for describing this sort of variation within
the confines of doing medical genetic studies?
How should we, or can we, use these kinds of genetic data to reconstruct personal genetic
history, and why might that be important in this context, and what does it tell us about
the design of future medical genetic studies?
So, one of the projects we've been particularly involved with and been very happy to be involved
with is the 1,000 Genomes project.
Aravinda's also been involved with this, and Esteban as well.
Esteban and I, in particular, worked on some of the collections in the Americas.
And thinking, in particular, about the impact that admixture has on patterns of variation.
And I just want to give you one result from this study that I think is really important
in our thinking about the next, say, five to 10 years of medical genetic studies.
Okay?
And this is the only bit of population genetics in most of the talk; this is an esoteric summary
of genetic variation known as the joint allele frequency spectrum.
So if you hold on for a minute, hopefully you'll see why this is important.
So on this axis, we have the frequency of genetic variants in the Yoruba, from Ibadan,
Nigeria.
On this axis, we have the frequency of genetic variants in the Chinese and Japanese sample.
And all we've done is cross-tabulate and ask, "When we find a genetic variant, what box
does it fall into?"
And the summary of this slide is that the vast majority of genetic variants, that is,
individual genetic changes in the human genome are, one, exceedingly rare, and you actually
predict this from population genetic theory.
So most genetic variation is actually not common.
Common variants are rare, and rare common variants are very common.
And, when we're thinking about variants in this frequency spectrum, that is, those that
are between 1 to 10 percent, and, in fact, even below 1 percent, they tend to be extraordinarily
population-private.
So what does this mean?
If we're now delving into these sort of variants, this is where a tremendous amount of the effort
is going, to catalog associations between genetic variation and disease, it really,
really matters what study -- what populations are enrolled, because we have an a priori
expectation that associations found at this scale will not translate across ethnic groups.
And Esteban and I had a commentary on this in Nature which basically asked a very simple
question: If you take a pair of populations, say European -- a pair of European populations,
or a European and a Chinese population, or a European and an African population, within
the 1,000 Genomes paradigm, and ask to what degree are they exchangeable in the sense
that they'll -- you know, you'll find matched individuals, well, for common genetic variants,
populations are extraordinarily exchangeable, right?
These are mutations that have been around for tens of thousands of years.
You're going to find them all over the world.
Pairs of European populations look indistinguishable, and you expect replication across Chinese
and European populations, or European and African populations.
When we're talking about rare variants, and again, this is the bulk of human genetic variation.
Most mutations are extraordinarily rare and population-private; you have no such expectation.
So now the underrepresentation of ethnic minority groups in the United States in such studies
in an extraordinary problem that needs to be addressed, because if we do not participate,
we will not benefit.
I will repeat that: If we do not participate, we will not benefit.
Okay, and let me give you one concrete example of rare genetic variation and why it may be
medically important.
And this is really the pioneering work of Helen Hobbs and Jonathan Cohen.
This is an extraordinarily important gene called PCSK9.
And what Hobbs and Cohen did is resequence this gene in the Dallas Heart Study, and they
found an extraordinary result.
This gene, when knocked out, reduces your baseline levels of LDL, or so-called bad cholesterol.
So they took 3,000 subjects in this case, and for those individuals that had mutations
in this gene, about 3 percent of them carried knockout mutations of this gene, they had
a 28 percent natural reduction in LDL.
Okay, these are not people on medication; they naturally have a lower LDL.
Here's the distribution of LDL, and here is the shift in LDL for individuals, this is
particularly for black subjects, and this is true in black subjects as well as white
subjects.
These variants, again, are population private; the effect is the same, the biology is the
same, but the set of variants are going to be different across the two.
What's actually most important about this result -- and, I mean, it's an absolutely
result -- is that these mutations not only lower your LDL, but they have a noticeable
impact on coronary heart disease.
So it, number one, establishes a direct causal link between this gene and the adverse medical
phenotype, and it establishes that there are going to be differences across population
in the actual set of variants that are involved.
Now, we're all going to benefit in the sense that now, five different drug companies are
making monoclonal antibodies to knock down this gene so that we can all benefit by taking
a PCSK9 inhibitor, and some will argue that, much like statins, you probably, you know,
they should just put this in the water, right, because it'll reduce our LDL.
And here's sort of the biology that leads them in this direction.
So it's a very nice example about rare genetic variations, causality, you know, differences
in terms of the distribution of the genetic variants, and the need to really think in
terms of, you know, broad representation in medical genetics.
Okay, so, you know, the upshot of this is that, you know, I really believe, and, you
know, have been working towards trying to document examples of where these sort of rare
genetic variants may be common somewhere, and, you know, this is sort of a map of places
where we've been involved in projects and sort of active field work, and, you know,
I want to sort of take us -- and I'm not actually going to tell you about ancestry, and, you
know, I really sort of took the remit of focusing on phenotype, but one of the, you know, very,
you know, consistent messages that has come out is that if you look here, for example,
these blue pinpoints are all the pop red samples, which gave us such exquisite resolution within
Europe.
And some of you know, we're involved in an ancient DNA project with a guy named Utzi
[spelled phonetically], and we can pinpoint Utzi's ancestry to Sardinia, you know, within
tens of kilometers, here's this 5,000-year-old mummy, and we could tell him exactly where
he's from, but for most of us in this room, we can't get anywhere near that kind of resolution.
So I'll ascribe to something called the Utzi rule, which is that we should be able to do
for everybody what we could do for Utzi.
Okay?
And that's -- and I'll just, you know, sort of my aside on that.
And the story I want to close with is actually this issue of why these rare genetic variants
may have phenotypic impact, and if we really think hard about phenotype and about sampling,
how we can actually learn some pretty cool biology.
And to me, it's actually a very fun project we were involved with, and some of you who
were in the exhibit, this actually -- in the exhibit two floors up, and it's the case of
blonde hair in Melanesia.
Okay, so this is a project that I was sort of unwittingly involved with, in that, you
know, this post doc in my lab, Sean Myles, came to me with this photo, and he said, "Carlos,
I want to study the genetic basis of the blonde hair in the Solomon Islands."
And I will admit, when I first talked to Sean, I had no idea where the Solomon Islands are.
For those of you who don't know either, the Solomon Islands are a sovereign nation off
the coast of Papua New Guinea.
And when he showed me this picture, I said, "Well, Sean, you know, look at this kid's
U.S. Servicemen's jacket, you know, I can probably tell you the genetic basis of the
blonde hair, right?
His dad had blonde hair, and, you know, it's a sort of Captain Cook allele."
And he said, "No, no, no, no, I think it's a different -- it could be potentially a different
gene."
I said, "Oh, God, you know, we've really studied blonde hair a lot," so I said, "Okay, but,
you know, if you get a grant and can the samples, then we'll think about it."
So Sean went out and he got some funding, and went out to the Solomon Islands, and here's
Sean with spectrophotometric, taking spectrophotometric measures of kids in the Solomon Islands.
We -- this is a project we did while I was back at Cornell, we collected about 1,000
subjects and measured their hair, and there's, you know, there's actually a lot of interest
in the Solomons, that if you look at the Lonely Planet Guide, there's actually a blonde Melanesian
kid who's featured on the cover.
So -- and I actually had no idea why the genetic basis of blonde hair, you know, they have
all kinds of different theories about it, and so we were interested in thinking about
the problem.
So then he came back to the lab at Stanford and said, "I'd like to do a genome-wide association
study."
And I said, "Well, you know, at this point, Sean, this is really, really expensive.
We don't have, you know, thousands of arrays that we can throw at this."
And he said, "No, you know, I think if we did it with 100, it would work."
And I sort of looked at him and said, "Okay, clearly, you've never taken either a course
in statistics, or looked at a general, you know, issue of Nature Genetics, you know,
these were, you know, the one that I told you about had 2,000 cases and controls."
And, you know, Sean here, then, had a very good insight, which is, let's focus on the
extremes of the distribution, which is exactly what Helen Hobbs, and Jonathan Cohen had done.
They had initially sequenced individuals from the tails of the distribution.
So they said, "Fine, let's genotype these kids with blonde hair, these kids with dark
hair," and then I said, "You know, when this doesn't work, Sean, you really need to go
work on your other project, and, you know, so you can sort of get out of the lab."
Okay, so these are the results, so this is what we like to call our Dubai plot, not our
Manhattan plot, because there's a single towering peak of association.
It's on chromosome 9, in a region called P-23.
And, in fact, we got extraordinarily lucky.
Within this region there's actually a single gene that is associated.
And it's not some predicted hypothetical gene, it's an actual real gene with honest-to-goodness
research that people have done on this gene.
And, in fact, the association has an odds ratio of 30, which I challenge anyone out
there -- I think it's still the largest odds ratio with a GWAS.
So when you delve into it further, in fact, it's a gene called TERP-1, tyrosinase-related
protein 1, which is expressed in the melanocytes, which is in the cell types which produce melanin.
It's involved in melanin synthesis in the maintenance of the melanosomal structure.
It affects cell death and proliferation.
And, fascinatingly, there are cases of people with knockouts of this gene that have a form
of albinism called OCA3, or rufous albinism, or albinos of dark skin.
The first family that was described with this was actually a South African family who were
essentially dark-skinned parents with albino children.
At this point, as a good PI, I became very interested in this project, and green-lighted
that we do some additional sequencing.
And we sequenced the gene, figuring that, you know, we're going to have a ton of markers
that we're going to then have to delve into.
It's probably going to be some non-coding element that's involved, you know, these GWAS
events are never clear.
But, you know, again, sort of we were extraordinarily lucky.
We had one, and only one, mutation.
And it turned out to be not just any mutation, it was an amino acid change.
It's a change from the amino acid arginine to the amino acid cystine at an extraordinarily
conserved position.
So here's the protein sequence, and these are all Rs, which stand for arginine, and
I'll just read these out to you for, you know, dramatic effect.
This is human, rhesus, dog, elephant, possum, out to chicken and zebrafish.
So all of them have an arginine at this position, and our kids with blonde hair are walking
around with a cystine.
Furthermore, we have 1,000 kids, so we could actually test directly for association, and
here is the distribution of hair pigmentation.
Here are kids that are homozygous arginine.
Here are the kids who are heterozygous.
These two distributions are the same.
And then our kids who are homozygous for the cystine mutation are two standard deviations
out.
Okay?
So here's a phenotype, blonde hair.
There are two populations in the world that have blonde hair, Melanesians and Europeans.
So we can now ask, "Is it the same set of genetic variants?"
And the answer is, "No."
This is what one might call chemically-induced blonde hair variation.
[laughter]
But if you're European and have blonde hair, then you would tend to have a mutation in
OCA2, or, you know, perhaps kit-ligand.
You don't not have this TERP-1 B mutation unless you have Melanesian ancestry.
Okay?
So, you know, in my mind, I think it's a very, perhaps, representative example of what we
would learn if we broaden ethnic representation in such studies, and focus on phenotypes -- I
mean, it's easy to, you know, phenotypically identify a blonde Melanesian, so they make
a ton of sense.
But if you imagine being able to better phenotype, you could then dissect the genetic basis of
these complex traits, with far, perhaps, smaller sample sizes.
So the conclusions here is that, you know, even traits like hair and skin pigmentation
that are, you know, highly heritable, we've yet to identify all the genes involved.
We do not know whether, for example, the dark skin pigmentation in these individuals from
Melanesia has the same genetic basis as dark skin pigmentation in other parts of the world.
Other complex traits may similarly be amenable.
We need to undertake, in my mind, phenotyping across diverse human populations.
To me, it breaks down any simple notions of race, you know, the alleles are geographically
distributed and confuted to phenotypic differences.
And I think in this regard, you know, I -- I'm in, you know, violent agreement with Aravinda
that this isn't about race and classification.
This is about the distribution of alleles that have impacts on biomedical traits.
And, you know, it's our, you know, I think it's really, really important that we characterize
this.
I'll leave you with two final thoughts, which is that this gene, number one, has a mouse
knockout, so we actually, you know, have good biological, you know, sort of proof that this
is the gene that's going to be involved.
And secondly, it is the gene that is most overexpressed in metastatic melanoma.
Right?
So there could be a direct potential medical link there.
So with that, I'd like to thank you all.
Thank the people of the Solomon Islands; it's a privilege and pleasure to be able to work
with them.
And I'm happy to take any questions you may have.
[applause]