JANE PICKERING: Good
evening, everyone.
My name is Jane Pickering.
I'm the executive director of
the Harvard Museums of Science
and Culture and that
includes the Harvard
Museum of Natural
History which is
the sponsor for tonight's event.
And this is actually
the final installment
of our Evolution
Matters lecture series.
And so we've had three
wonderful lectures
all on the topic exploring the
various aspects of evolution
through natural selection.
And this is our final talk
with Steve Stearns from Yale.
And I think it's going to be
just as marvelous as the others
so I'm very excited.
We do have a complete list
of our spring programs
online for the
whole of HMSC and I
would encourage
you to also pick up
a few of our
brochures and things
that are to my
right on the table.
And you can also
join our email list
and so you get regular updates
for all the programs going on
here.
And you can also find out
how to become a member
and help support all the
wonderful programs that we do.
And I would like to acknowledge,
although I haven't actually
seen them here yet, Doctors
Herman and Joan Suit.
Since no one is
standing up and waving,
I assume they weren't
able to be here.
But Herman and Joan
have very generously
supported the Evolution
Matters lecture
series for a number
of years now.
We couldn't do it without them.
And so I'd actually
like to acknowledge them
in their absence if
that's OK with everybody.
[APPLAUSE]
And thanks to their support,
tonight's talk is being videoed
and will be posted along with
the other Evolution Matters
lectures on our website.
And finally, I'd
like to just mention
that we have another
lecture on Tuesday,
April the 29th supported by the
Peabody Museum, which is called
Between the Caves: Landscape
Archaeology of the Palaeolithic
in the French Central Pyrenees.
So we can all come and look
at wonderful photographs
of the French Central Pyrenees
and wish we were there.
Anyhow, I am actually once
again delighted to introduce
a Harvard faculty member
who will introduce
tonight's speaker,
Peter Ellison.
And Dr. Ellison is the
John Cowles Professor
of Anthropology and Human
Evolutionary Biology
here at Harvard in a position
he's held since 2003.
And he was also for his sins
dean of the Graduate School
of Arts and Sciences
from 2000 to 2005.
And has taught here
at Harvard since 1983.
He is a member of the
National Academy of Sciences
and a fellow of the
American Association
for the Advancement of Science.
And he currently serves
on the Scientific Advisory
Board for the National
Evolutionary Synthesis Center,
is the co-editor in chief of the
Annual Review of Anthropology
and editor in chief
of the American
Journal of Human Biology.
And as with many
Harvard professors,
I could go on for a lot
longer, but actually I'd
like to bring him up to
introduce our speaker.
Thank you.
[APPLAUSE]
PETER ELLISON: Thank you Jane.
It's a distinct pleasure to
introduce Professor Stearns.
Professor Stearns I think
of as a force of nature
in evolutionary biology.
He certainly has been a
positive selective force,
if I can say that, on the
field for his entire career.
He was, he's currently
the Edward Bass professor
of ecology and evolutionary
biology at Yale.
But his career has
been rather meteoric.
He burst on the scene
while still a postdoc,
I believe, after finishing
his degree at Reed?
STEPHEN STEARNS: No.
British Columbia.
PETER ELLISON: That's right.
But then was on the
faculty at Reed.
STEPHEN STEARNS: Yeah.
PETER ELLISON: Early on.
But burst on the
scene by publishing
what was an extremely
influential review
in a quarterly review of biology
on life history theory, which
was an area of evolutionary
ecology that was just
burgeoning.
Which then led onto his
very important book,
The Evolution of Life Histories.
He left the US for a
period and was the director
of the Institute of Zoology
and professor of zoology
at the University of
Basel in Switzerland
for a number of years,
from 1983 to 2000.
And while there, he started
the European Society
for the Study of Evolution,
for Evolutionary Biology.
He edited the journal of
that society for some time
and he began the
collection of what
is a very distinguished
wine cellar.
[LAUGHTER]
He has received any
number of accolades,
including the DeVane
Medal for distinction
in undergraduate teaching.
In addition to the
book I mentioned
on the evolution
of life histories,
he's published perhaps one of
the most widely used textbooks
on evolution, Evolution:
An Introduction together
with his co-author
Rolf Hoekstra.
And also edited a
very important volume
on evolution in
health and disease
which was one of the
major starting points
for what has become a rapidly
growing field of evolutionary,
or Darwinian, medicine.
As payment for
his sins he is now
the editor of a new journal,
Evolution Medicine and Public
Health, which is perhaps the
flagship of that burgeoning
field.
He has served as the vice
president for the Society
for the Study of Evolution.
He is a fellow of the American
Association for Advancement
of Science, and the
accolades go on and on.
But I won't take any
more of your time.
Instead, I will introduce
Professor Stearns.
Welcome him.
[APPLAUSE]
STEPHEN STEARNS: Well.
Jane, thank you
for the invitation.
And Peter, thank you
for the introduction.
And thank all of you for coming.
How many of you are
from Framingham?
[LAUGHTER]
Not too many.
Well, I had been hoping.
About seven years ago, the chief
geneticist in the Framingham
Heart Study walked into my
office in New Haven and said,
I know you work on
evolution and I've
got my hands on all this
data from Framingham.
Do you think we could
do anything with it?
And I looked at it
and I thought, well,
if there was one
thing that I would
like to do with the
human population,
it would be to demonstrate that
evolution is still going on.
And that's not a point
that would surprise
any evolutionary biologist
but as early as 1869,
an Irish doctor wrote the
paper saying that, oh, this guy
Darwin, well, OK,
he's got some ideas
but we all know that
evolution has stopped
in humans because
of modern medicine.
Now that's just not true.
And in a minute we'll
do a little exercise
that will convince you
of why it hasn't stopped.
So what I'm going
to talk about today
is our measurement of a burst
of selection in Framingham.
Actually, for many of
the traits, the people
were experiencing
selection, say for those
born between about
1919 and 1940.
And then on traits like
cholesterol and blood pressure,
that went away for
interesting reasons.
It continued, however,
for age at first birth.
So the age at which women mature
and have their first child.
I'm going to talk a bit about
intersexual constraints, what
evidence for cost
of reproduction,
and then I'm going
to switch to a study
that we did in
the Gambia to show
a few ideas on the impact of
the demographic transition
on human evolution
and what it means
for the degenerative diseases
that we are now increasingly
encountering, heart
disease, cancer, diabetes,
and things like that.
So our aims first were to see
whether natural selection is
operating on
contemporary humans.
It is.
So we have not been able to
demonstrate a genetic response.
Had we been able to, that
would've been astonishing
because we really only have
one generation of grandchildren
in which we could've seen it.
Then we also wanted to ask
whether selection on males
constrains responses in females
and selection on females
constrains responses in males.
And we can show that it did.
I'll explain why that happens.
But it has the knock-on
effect that you can always
blame the other sex for
whatever your problem is.
[LAUGHTER]
Since I started out
life history evolution,
I'm quite interested in
the cost of reproduction
because they play a big role
in the evolution of aging
and then the evolutionary
explanation of why
it is that we must
grow old and die.
And I wanted to see if
they exist in Framingham,
and they do.
And they are in part
genetically-based.
And we have some hints at the
genes that might be involved.
And then to place these
results in the general context
of the demographic
transition, I'll
take a look at the demographic
transition in the Gambia.
And this is a
worldwide phenomenon
that really changes selection
pressures on humans.
It's one of the
biggest things that's
happened to us in the
last 250,000 years.
And basically what it
does is it reveals costs
that we did not
previously have to pay
because we were dying
for other reasons.
We used to die from infectious
disease, and from childbirth,
and things like that, and
that's mostly been eliminated.
And now we live
long enough to see
what happens when
you go on the buy
now, pay later plan in biology.
[LAUGHTER]
OK.
Framingham Heart Study.
This is the gold standard
of multicore cohort medical
studies.
It was started in
Framingham in 1948
and it enrolled people who had
been born as early as 1890.
It has three cohorts
that are being followed
and they total
about 14,500 people.
They had been given
exams every two years
for the original cohort
and then about every four
years for the offspring cohort.
And the third generation
cohort has actually now
had its second exam,
it just had had one
by the time we got
the initial data.
So we measured
selection intensity
as the correlation of
the trait with lifetime
reproductive success
or family size.
And here is an important point.
Herbert Spencer coined this
motto in the 19th century
that evolution was about
the survival of the fittest.
But it's not.
It's about the
increased representation
of the reproductively
successful.
And survival is only
important to the extent
that it contributes to
reproduction, which gets genes
into the next generation.
Now when I get near
the end of the talk
and you see how selection
intensities have changed
on the human population through
the demographic transition,
you'll see that the
mortality selection
has fallen very close to zero.
But fertility selection
remains strong.
And here's the
illustration of it.
Would everyone in the room
who comes from a family of one
please raise their hand.
Only children.
Two.
Look around.
Three.
Look around.
Four.
Look around.
Five and more.
OK.
There is a lot of variation
in reproductive success
in contemporary
human populations
and that is what is driving
contemporary selection.
OK?
And the evidence is irrefutable.
OK, we measured the potential
to respond to selection
by estimating genetic
variation and co
variation from
pedigrees, and then we
projected the responses.
A lot of this work was
done by Sean Byars.
He grew up on a
farm in New Zealand
and got trained in Melbourne
and came to me as a postdoc.
And he's now back
in Melbourne working
on cardiovascular disease.
So there are some issues
with this kind of data.
Here is on the x-axis, we go
from 1890 out to about 1960.
And on the y-axis we have
lifetime reproductive success.
So this is completed
family size.
And the dots are the
averages and the bars
are the standard deviations.
And basically what
we decided that we
were going to represent
fitness as the deviation
of an individual from the
average for a period of time.
And the lines mark
the period of time.
This is the baby boom.
It's where the
Boomers came from.
This is the baby crash.
OK?
This is what happened as
we entered the 20th century
and went through
the first World War.
So when you're dealing with that
kind of demographic history,
you have to make some
adjustments to try
to estimate what might be a
reasonable relative fitness,
and that's how we did it.
And then there is this
issue of the traits, OK?
So this looks kind of
complicated but basically we've
got women over here
and men over here.
And on this axis, we have
how old they are, OK?
On this axis we have what
year were they measured in.
What you can see,
if you just look
at the age axis for
example, and over here
we have total cholesterol.
So these are both measures
of total cholesterol.
And you can see that
if you measure men,
that their cholesterol tends
to go up as they get older
and then it goes down.
And with women, it's
even more dramatic.
And the question is, how
are you going to estimate,
if you want one sample,
what that person's
total cholesterol is?
So we estimated the surface
for the whole population.
And for women we have
nearly 45,000 measures
and for men we had about 37,000.
These dots here are repeated
measures for one individual,
OK?
So that's one
individual there, this
is another individual
over here similarly.
And we took their average
distance from the surface
as their relative
cholesterol measure.
So some of them would be above,
some of them would be below.
And that averaged out their
tendency for their lifetime
and for their period
of history as well.
OK, so these are the
traits we looked at.
We looked at total cholesterol,
height weight, blood pressure,
blood glucose, ages at first
birth, menopause and death.
Now the Framingham
Study was set up
to look at risk factors
for heart disease
and that's why they were so
careful to look at cholesterol,
height and weight,
and blood pressure.
And the Framingham
Study gave us two things
that are very, very important
worldwide for health.
One is cholesterol
as a risk factor
for heart disease
and other things.
And the other is that
smoking is a risk
factor for all kinds of stuff.
That came from
Framingham and the people
of Framingham who still
participate in this program
are very proud of
the fact that that's
something they
gave to the world.
And they learned from
it and that actually
changed the selection pressures.
So I'll talk about that
a little bit later.
These are the
selection gradients
in the Framingham Heart Study.
This is a bunch of numbers
so let me just take
a minute to parse them for you.
So here are the traits.
Total cholesterol, height,
weight, and so forth,
going down this column.
These are the sample sizes.
So we couldn't use everybody
for various reasons
but the sample sizes
were pretty good.
This beta here is the
selection gradient.
OK, so that shows
you if it's negative,
it means that
selection is pushing,
in this case
cholesterol, downward.
If it's positive, as
it is in this case,
it's pushing weight upward.
And then these are the
statistical P values.
And this is in a, for those of
you who are into statistics,
this is in the
general linear model.
This is like a
multiple regression
where lots of other
factors are taken account
of before these
estimates are made.
Similarly for the men, sample
size, selection gradient,
P value.
So if you look at
that, basically it's
saying that for this
population, this is mostly
people born between
1900 and 1940.
It's not everybody.
Selection is acting to
decrease total cholesterol,
to decrease height,
to increase weight,
to decrease blood pressure,
this is systolic blood pressure.
To decrease blood glucose.
To decrease age at first birth,
to increase age at menopause.
And for women, no
selection on age at death.
For men, selection for
them to die younger.
OK.
And selection for men also to
have their first child earlier,
which isn't surprising
because people
tend to marry people
of similar age.
Otherwise the selection
wasn't so significant on men.
I'm going to take that
apart in a minute.
OK, so at this level, it
doesn't look so significant.
Now my dear friend and chief
publicity and press adviser
is in the audience.
She is my wife.
And when this hit the
press and it said,
hey, women are getting shorter
and they're getting heavier,
she said, don't say fat.
Say pleasingly plump.
Now in a minute I'll get to why
we think that's happening, OK?
Then to see whether or not
we could expect a response
to selection, we
needed information
on genetic variation because
without genetic response,
there is no real evolution.
Genetic variation
is the fuel that
runs the engine of evolution.
So we used quantitative
genetic techniques,
for those of you
who are into it,
we used the animal model to
estimate genetic components
on seven traits in 2,655 males
and a bit over 2,200 females.
They were in 1,538 families.
That gave us a fair amount
of statistical power
for this kind of thing.
We stuck in a random
effect for maternal ID.
OK, that was more or less
to take care of anything
like the difference between
Italian and Irish cooking.
That was significant in
about 11% of the analyses.
And then we also controlled
for smoking, education level
and country of origin.
And those were significant
in about 3% of the analyses.
But whether they were
significant or not,
we controlled for them.
Since I'm at Harvard
I have to tell you
that natural selection
was operating
to decrease education
level in Framingham.
Basically all that says is that
women that had less education
had more kids, OK?
So these are the projected
responses to selection
for women and men.
So if you go out about
10 generations, what
these numbers mean is that you
would expect total cholesterol
to go from 223.9 to 215.9.
OK, so it's going to decrease.
It's about a 3.6% change.
There's a lot of
numbers here and I'm
going to summarize the main
points in a little bit.
But we translate
those into haldanes.
And that means,
this is an estimate
of how many standard
deviations this trait
is changing per generation.
And we do that so we can
compare it with other species.
This is for men
down here and you
can see that, basically the
take home point on this,
if you look down
at these numbers,
is that, oh, evolution
is continuing
but it looks like it's
going to be kind of slow.
OK?
There's nothing astonishingly
fast about these numbers.
So the rates of projected
evolution in haldanes
ranged from about 0.03
for height in women
to less than 0.001
for glucose in men.
OK.
That's slower than
Galapagos finches.
It's slower than
Trinidadian guppies
but it's about like New
Zealand Chinook salmon
or Hawaiian mosquitofish.
And if you take the
rates of evolution here,
and then this is over how
long a period the study went,
this is a summary
from 1999 of all
of the studies of
rates of evolution.
There are a whole bunch of
Hawaiian mosquitofish in here
which I like because I got
those estimates myself.
This is where the people are.
OK?
They're right in the middle.
People are evolving
at kind of the lower
end of the natural range of
other plants and animals.
At least that's what
they're projected to do.
Remember I said we didn't
have a response to selection.
We're just projecting
what we think
would happen if things
kept going like they are.
OK, so, now a little bit
about secular change.
Culture is really important.
And the one trait that was
consistently under selection
was age at first birth in women.
And it was to reduce it.
Now this is for
the period, this is
for the birth dates
between 1892 and 1913.
This is up through the
middle of the Depression.
This is from the Depression
through the middle of the '50s.
Very similar negative selection
to reduce age at first birth.
And I've often been asked
how can that possibly be?
Because most of the
women who are asking me
that are well educated,
ambitious women
from two-career families
who have delayed
having their first
child until they're 35.
And how is it that
selection could
be operating the
other direction?
Well, this is, first, this
is the whole population.
It's not just all the
two-career families.
And it is showing you that
throughout this period
in Framingham,
there were women who
had more children
in their lifetime
because they began sooner, OK?
However what it's
doing is it is changing
the biological structure
of the population.
Layered on top of that
is cultural evolution
which is saying, no.
Wait.
Delay the kid.
Have a happy career.
Get your PH.D. And then
have your children.
And what that's doing
is it's increasing
the tension between
biology and culture.
And so if you in
your heart of hearts
feel like you are being
torn, you really you are.
Biology is pushing one way and
culture is pushing another.
So why is this happening?
Well, I was involved in a
piece of life history theory
about 25 years ago that
connects this shift in selection
to the demographic transition.
And let me walk you
through this slide a bit.
This is a slide
from a paper in 1986
and it was the first prediction
of what the optimal reaction
norm for age and size
of maturity should be.
So this is size on the y-axis,
this is age on the x-axis.
These dotted lines
are growth curves.
And there are various
forces that would say, well,
it would be better
to mature earlier.
You could have a
shorter generation time.
You'd have less risk
of getting killed
before you had your first kid.
There are other forces
which are saying,
oh you want to mature later
because if you mature later,
you are bigger, you're more
physiologically competent,
you can have more offspring.
And this line shows where the
balance between those forces
is.
OK?
So it's sort of the best
compromise you can make.
And what it says is, for this
particular set of assumptions,
if you're growing fast,
mature young and big.
And if you're growing
slow, mature old and small.
That's what the optimal
reaction norm prediction is.
Well, we have fairly good
data on the difference
in ages of maturity of women
in England and Scotland
in the 19th century and women
living on farms in the US
in the 20th century with
similar genetic background.
These women were stressed.
They were working in the
Industrial Revolution.
And as Peter and his
colleague will tell you,
stress has a big impact
on female reproduction.
They were growing more slowly
and they matured later.
The women who were living on
farms in the United States
in the 1930s and '40s
were growing faster.
They were bigger at a given
age and they matured younger.
The difference was about
somewhere between five
and six years.
And if we put in these
effects into that model,
it predicts just
about that change.
Now you'll see that there
are two lines here, OK?
One of them is
lower than the other
and shifts over to
the left a little bit.
This is what we predicted
25 years ago, 28 years ago,
if infant mortality
rates remained low
because of modern medicine.
So we have clean water,
hygiene, vaccines, antibiotics
and better health care.
And as a result of that,
infant mortality rates
from infectious
disease have dropped.
What that means basically
is that you can get away
with having a kid earlier.
You don't have to have
it in such great shape
because we've removed
a lot of the threats.
And that would shift the whole
curve down and to the left.
In other words, it
predicts that when
you go through the demographic
transition in the Industrial
Revolution, women will
be selected to be smaller
and to have their
first child earlier.
Exactly what we
saw in Framingham.
This is, by the way, a useful
way of looking at the world
because it shows you
that this change here
along this axis, that's nurture.
OK, that's the effect of
less stress and better food.
This shift here, that's genetic.
That's nature.
That's shifting the whole curve.
So you should think of evolution
as designing a flexible rule
of thumb to deal
with a wide range
of environmental conditions.
And it allows you
to think, I think,
in a much more nuanced way
about the whole nature-nurture
question.
That's a broader issue than
what I'm talking about today
but this is a useful tool.
OK, so what is actually the cost
of earlier age at first birth?
OK, as I've mentioned, the
age and size at maturation
are by trade offs,
by cost and benefits
on either side of the picture.
And its offspring of
younger first-time mothers
whose are suffering
higher mortality rates.
So these are the infant
mortality rate per thousand
for all the births in the
United States in 1960 and 1961.
And these are the ages
of the mothers who
were giving birth
for the first time.
This is very
probably a point that
is determined almost entirely
by rape within families
because these are
eight-year-old girls.
And they have very
high mortality rates
in their offspring.
It drops off real fast.
It seems to hit a nice
low point around 18 to 28.
That would be the peak time
to start having babies,
biologically.
And then, as you all
know, the biological clock
starts ticking.
Interesting things happen to the
maintenance of the female germ
line.
And the probability that a child
will die if the mother is older
starts to go up.
So what happened in the
demographic transition
is this whole curve got
shifted down and to the left
and it made it cheaper
to have a child earlier.
And that is what shifted that
optimal age at first birth down
towards, or the
neighborhood of 20 or 18
or something like that.
So what's going on
here is that culture
is influencing
demographic rates.
It's influencing
fertility and mortality.
But that is what is
driving selection.
And in this case, they
reduce the evolutionary cost
of earlier maturation but
the benefits remain the same
and that's why women were
selected to mature earlier.
OK, so first summary.
Women in Framingham born
between 1900 and 1940
were predicted to evolve to
become shorter and plumper
with lower values for total
cholesterol and systolic blood
pressure, and to reach
for first birth earlier
and menopause later.
By the way, this is an
interesting observation.
They're getting their
first child earlier,
they could have their
last child later.
Selection has shifted from being
driven primarily by mortality
to being driven primarily
by fertility and the window
for having children
is getting longer.
In other words, you
concentrate on fertility,
you get more opportunities
to have babies.
Males were also predicted
to father their first child
earlier and to die earlier.
We'll come back to that point.
Selection in these
populations is driven mostly
by variation in
infertility, it's
broadening the fertility window.
And these are modest,
gradual, evolutionary changes.
Nothing is happening too fast.
Now during the 20th
century, selection
decreased in intensity.
It didn't change direction
but it decreased in intensity.
It actually, we can't detect
any more significant selection
on blood product
pressure and cholesterol
operating in the 1980s,
1990s and this millennium.
That's because it was
the Framingham study that
showed that cholesterol
and smoking are
bad for your health.
And like everybody else in the
world, the people of Framingham
adopted a healthier lifestyle.
They cut their smoking.
They started jogging.
We can actually see a blip
in body mass index in 1977
when everybody starts jogging.
And that cultural
feedback, right?
The Framingham study is
culture, it's medical culture,
put information out,
culturally transmitted,
that caused people to change
their lifestyles in ways
the changed natural
selection on their biology.
I think that's
probably the biggest
take home message of
the Framingham study
is that culture has become
the most important selected
agent acting on
further human evolution
and the primary
driver is medicine.
It's changes in medical
practice and public health.
OK, so culture has not
stopped evolution in humans,
instead become the major factor.
So medicine and public health
are playing leading role.
That was our first message.
However when we did
that initial study,
we didn't really
yet have our hands
adequately on the issue of
the following important fact.
Every autosomal
gene in your body,
that means every one that's
not on a Y chromosome,
it would include
the X chromosomes.
Spends half its time in males
and half its time in females.
That means that if you look
at it from the point of view
of the gene, it's got to be able
to function, to make babies,
both when it's sitting
in a male and when
it's sitting in a female.
Well, that constrains
things because it's
got to try to do two things
rather than just one.
So the traits that these
genes influence also
experience different selection
pressures in the two sexes.
So selection might be acting
one way on height in males
and another way on height
in females, for example.
So this fact means that there
are genetic correlations
between the sexes
and they're going
to be interacting with sexually
conflicting selection pressures
and that will generate
constraints on response.
So the question is, did
it happen in Framingham?
Well, here are the
Framingham pedigrees.
So blue is a connection
from a father to a child.
Red is from a mother to a child.
Gray means they're
not on the correlation
analysis for one
reason or another.
And I give that to
you just to show you
the depth of the
number of generations
and the amount of data that
went into the following numbers.
OK, there were significant
cross-sex correlations.
This is kind of a hard
table to parse, OK?
But basically this is the
additive genetic variants
covariance matrix, the G matrix.
And this part over here is
just showing you, OK, this
is total cholesterol
here in a row.
And is the total
cholesterol in a column.
And this number here
is the genetic variants
for total cholesterol
for both men and women.
And this would be the, this
number going down the diagonal,
is the genetic variants for
weight in men and women.
It's not heritability,
this is genetic variants.
Now, the off-diagonal
elements are the covariances.
So this would be, for example,
this negative number here
between total cholesterol
and height means
that as height goes
up, total cholesterol
goes down genetically.
That's the genetic
component of that.
So that's a little bit about
how to read the numbers.
The numbers that are
in bold, the dark ones,
have a P value which
is less than 0.0001.
OK, so they're
highly significant.
This is for males.
Excuse me, that's for males.
This is for females.
This is between the sexes.
Now I see the colors
didn't come out
quite so well here
but basically we
call the genetic correlation
of total cholesterol in females
with total cholesterol in
males the direct correlation.
And these would be the direct
correlations between the sexes.
But if you see something off
the diagonal, that means,
for example, that
systolic blood pressure
has a significant
genetic correlation
between the sexes with
diastolic blood pressure.
Systolic blood pressure has
a significant correlation
between the sexes with glucose.
This one means that there's a
significant genetic correlation
between the weight of the female
and the height of the male.
Not necessarily in a marriage.
This isn't the whole population.
In other words, the
expression of these genes
in the different
sexes is leading
to these genetic correlations.
And that means that the
evolution of the two sexes
is linked together.
This is not sexual
selection, OK?
This is all stemming
from the fact
that all autosomal genes
spend half their time in males
and half the time in females.
And they are involved usually
in building similar sorts
of traits, but in
somewhat different ways.
And some of these things
are really kind of curious.
And one would wonder why is it
that maybe female height might
be correlated with
something crazy in males?
And vice versa.
And the way I think
about it is this.
Evolution proceeds by tinkering.
And a gene will
only get selected
if it's available
in the population
and if it has a net
positive effect.
It might have some
disadvantages,
but if it has a
net positive effect
it will get selected at
the time that it comes in.
It doesn't mean
it's the best one.
It's just whichever had
one what happened to occur.
And this process starts
layering upon layer
of genetic interaction until
you build a genome that's
connected in many
different ways.
And then we come along
millions of years
later and do a study
like this and what
we see are some connections
between the sexes that
look kind of arbitrary and
why did that ever happen?
Well, it's a trace of history in
the genetic structure of males
and females.
Ah, all I had to do was click
and I would get the colors.
I forgot.
So these are the direct.
These are the indirect.
And yes, the answer is yes.
There are genetic correlations
between males and females
and they are both direct
in the same traits
and they are indirect
where one trait in a female
is affecting another
trait in a male.
Now what difference did
that make to selection?
Well, what we have here, this
may be a little confusing
so I'm going to try to
be real clear about.
In this graph, black is
females and white is males.
These are selection intensities.
So this would be positive.
This would be negative.
The asterisk tell you
how significant it is.
The more asterisks, the more
highly significant it is.
For example, take a look
at selection on height.
OK, black is female.
Selection is very
strong in females
to decrease height
and very weak in males
and not significant at all.
That's what the difference
between those two bars means.
And if you look
across that you can
get an overall
picture showing you
that selection is not only
different on different traits,
but it differs by sex as
you go across the traits.
Now, now we change the
meaning of black and white.
Black now means you've got
the genetic correlations
I showed you between
the sexes in there
and white means we pulled
them out artificially, OK?
And we then wanted
to project what
would be the
response to selection
with and without the genetic
linkage between the sexes.
So if you see a difference
between the black
and the white bar, what
this one is saying,
this is for total
cholesterol, OK?
And this is in males.
And it's saying that
almost all of the selection
on total cholesterol
in males is coming
through its genetic
correlations with females.
And if you take
that out, there's
almost no selection on
total cholesterol in males.
And if you look across
that for males and females,
you can see that the response
to selection that you expect
depends critically on the degree
of linkage with the other sex,
OK?
So that is the little
mental exercise
we carried out to
try to dissect out
this genetic connection
between the two sexes.
So selection on
males is constraining
responses in females
and vice versa.
And it happens both because
selection intensities differ
between the two sexes and
because traits are genetically
correlated across the two sexes.
And that gives us, you
know, I would advise you not
to use it in family argument.
But it's an interesting
observation about our nature.
And it leads me to
a modest suggestion.
So do a mental experiment.
So substitute genes
for mate preference
for genes for total
cholesterol and blood pressure.
We don't know what they are.
We don't even know
if they exist.
But let us suppose
that they might exist.
Would a similar effect explain
the evolution of homosexuality?
I think it might, OK?
So this, other people have
tried to analyze this.
There's a paper by a
group of Italians, Chiani
and some others.
Other evolutionary
alternatives, but the existence
of homosexuality, where
people are at least
before modern
reproductive medicine,
they were deciding that they
weren't going to reproduce.
That was a very puzzling
evolutionary problem.
And I think that if we see
that the two sexes are really
linked together
like this, you can
begin to see that
maybe it's a spillover
effect from the other sex.
Of course it's also modulated
by lots of other things
like having older brothers
and stuff like that.
So it's not genetically
straightforwardly determined
by any means.
Now, back to my
life history roots,
are there costs of
reproduction in humans?
So this is an important idea
because if there is a trade
off between reproduction
and survival
as posited by
George Williams back
in the 1950s, that
would be a key reason
for the evolution of aging.
And also for the evolution of
the whole reproductive schedule
while one is still alive.
That's been detected
experimentally
in flies and worms.
I did some of the work on flies.
Lots of people did it.
And some of the genes
there are known.
And previous work on
people has demonstrated
some phenotypic trade offs,
OK, but without really getting
at the genetic bases of them.
So the people involved in this
study, this time it was mostly
Susan Wong, who is a wonderful
grad student in stats at Yale.
And she's decided she wants to
teach in a liberal arts college
and is starting at
Amherst in the fall.
And Sean Byars, who was
involved in the other part
of the Framingham study,
kind of guided Susan
through the complexities
of the Framingham data set.
They are so complex
that for this study,
downloading the genomic
data took a week.
It was 756 gigabytes.
And if Susan did one run,
even on a fast computer,
it would often
take hours or days.
So there were phenotypic
costs of reproduction.
So if you just took the
people who had already
died in Framingham, there were
680 women who had already died,
the phenotypic correlation of
their reproductive success,
which is called, the
demographers call it children
ever born, by
lifespan was negative.
That was highly significant.
And each additional child cost
about 3/4 of year of life.
Now actually what
was going on is
that it was good to have the
first one and the second one
so that your lifespan
actually increased.
Your mortality decreased
if you had one or two kids.
But three, four,
five, six, seven, it
just started climbing like that.
Which won't surprise parents
getting up late at night,
right?
David can go on about
that later if you want.
So in a larger sample
where we allowed
for right censoring,
which you can
do with these kinds
of sample sizes
and using something which
is called Cox regression.
Increases in family size
were significantly related
to increases in risk of
death from heart attack,
stroke and cancer in both
women and men in Framingham.
so we had not only
the general pattern,
we had some indications
of the kinds
of mechanisms that
might be in play.
Did they have a genetic basis?
So we looked at
genetic correlations
from a lot of pedigrees,
you saw the pedigree study.
There is a whopping huge
negative genetic correlation
between number of children
per lifetime and age
at death in women.
Highly significant.
And there is a significant
genetic correlation
between the number of
children and age at menarche.
In other words, if
you increase age
at menarche, which
actually is decreasing
the reproductive window, there
was a genetic effect on it.
OK, this is not phenotype,
this is genetic effect.
So these things are
controlled for stuff
like smoking and
education and so forth,
like the other estimates were.
So we then used the genetic
data available in Framingham
to look across
the entire genome.
We have genetic data about
9,500 people in Framingham.
And we were looking for
chromosomal regions that
had little markers planted on
them like little flags, OK?
And we could see whether they
had a red flag or a green flag
basically.
And that would associate that
chunk of genome with an effect
that we could measure.
One of those markers
was close to robust
to changes in the model.
And now what I'm
doing here is I'm
hedging because
this whole aspect
of modern genomic
science is fraught
with statistical difficulty.
And you can change the
assumptions of the models,
an effect will go away
and they'll come back.
We tried many different
ways of doing this estimate
and it was really
quite robust, OK?
So this region of the
genome is near a gene
called EOMES, which is
a master regulator gene.
It's implicated
in bladder cancer
and in multiple sclerosis.
Now if you were looking, if
you were just a priori looking
for things that caused
trade offs between traits,
it would make sense
to concentrate
on genes that controled
entire genetic networks
because they're controlling
lots of interactions.
One of which might hit one
trait and another of which
might hit another trait.
OK, so maybe it's not surprising
that the strongest signal
we got was from a
master regulator.
However, when we put in
major causes of mortality,
whether they're smokers,
their total cholesterol, stuff
like that, that marker
dropped below the significance
threshold if you're doing
440,000 statistical tests.
OK, so this is a
conservative way of doing it
that probably misses
some significant signals
and we think that we
have a signal here,
which is interesting and
deserves further exploration.
There was another one that
was almost significant.
It's close to a gene
that's associated
with brain development
and with vaccine response.
Now, interestingly,
and now I'm getting
into the demographic transition
into degenerative disease,
others have found
genes that increase
fertility early in
life while increasing
risk of cancer late in life.
P53 is a famous cancer gene.
You get a mutation in
this in your germ line
and you get, it's called,
LiFraumen Syndrome.
One I may not be
pronouncing it correctly
but a whole set of
childhood cancers.
This is a gene that controls
both cell cycle and DNA repair
and it controls whether or not
a cell will listen to a signal
to commit suicide if
it's got damage in it.
OK?
So the worst thing that
can happen in a cancer
is that a damaged cell will
not listen to the immune system
and will say, no, I
will not commit suicide
for the good of the
rest of my body.
I'm going to go ahead and
I'm going to make more cells.
And that's what
starts a cancer off.
Often that it is because of
a mutation of the P53 gene.
Well, that allele that raises
that risk helps the embryo
to implant into the endometrium
right at the start of life.
That's an incredible trade off.
I mean, that's about as
early as you can go in life.
So this is a trade
off between something
very early and then
a risk much later.
The evidence for that I
think is a little bit better
than the evidence for the
early-onset breast cancer gene
but there are
interesting correlations.
The alleles in early
onset breast cancer
gene that raise the risk of
breast cancer in younger women
also increase the
number of children,
reduce birth
intervals, and extend
the period of child bearing.
So if you're scratching your
head and you're wondering,
why in the heck do
we have mutations
floating around in our
population that put us
at risk of getting cancer,
it looks like maybe
we're starting to get
some insight into that.
Maybe in the past
when cancer was
unlikely to be the
cause of death,
these things were
actually increasing
reproductive success.
So into the
demographic transition,
prior to the
demographic transition,
and it started occurring
in France in about 1700
and it's still going on in
parts of the developed world,
very few people died of
cancer or heart disease.
So genes that
increased fertility
at the cost of risking such
deaths had low cost or no cost.
When we shift the
causes of mortality
with modern hygiene in vaccines,
that allows us to live longer
but then reveals
genetic effects that
had previously been concealed.
So here's a picture of
the demographic transition
in England.
This runs from 1541 over
here to 2001 over here.
The black line is the
total fertility rate.
So this point here means that
in 1541, the average woman had
about 3.3 kids and it
fluctuated through history
and then it dropped very
suddenly and steeply.
That's the demographic
transition.
And now it's at less than two.
So it's at less than
replacement in England
as it is in most countries
of the developed world.
These other lines are
the selection intensities
that are due to the variation
in mortality rates and fertility
rates among individuals.
The total selection
intensity is in yellow.
The mortality
contribution is in blue
and the fertility
contribution is in pink.
And the thing I
want you to notice
is that right about
here, right about 1900,
the blue and the
pink lines cross
and the mortality contribution
to the potential contribution
to selection goes down and
down and just about disappears.
And the pink contribution
to selection,
which is from fertility
variation, which
is what happened when you
guys raised all your hands,
stay significant and
is not disappearing.
So that's a picture of
the demographic transition
and it's one of the
biggest things that's
happened in human populations
really in our life
as a species.
So we decided to take a
look at it in the Gambia.
Peter does some
work in the Gambia.
And the people who did it
were Ian Rickard and Alex
[? Corteal ?] and a
bunch of us others.
They were the lead on that.
It was kind of a hard study
to do because we wanted
to get an estimate every
year so that, you know,
people don't live one year.
People live 70 or 80 years.
So we had to come up with
a method of estimating
yearly contributions to fitness
and associate them with traits.
OK, so this is the total
variance in fitness each year
and look at what happens to
early survival, variation
in early survival,
in 1974, 1975.
That's when the British
Medical establishment
went into these villages,
instituted a program of hygiene
and malaria control, and
brought infant mortality
rates way down.
So this was a very sudden
demographic transition.
And when that happened, the
variation in fertility, which
had been substantial before,
it took a little bit of dip
and then it went up.
And the selection on height,
total selection on height,
looks kind of
scattered over there,
but if you break it
down into its components
you can see that the
mortality selection on height
is quite different from the
fertility selection on height.
And when you look at it that
way, you come to the conclusion
that unlike Framingham,
in the Gambia when
that population went through
demographic transition,
women got selected to
be taller and thinner.
And the Daily Mail in London
picked that up and said,
natural selection
for fashion models.
OK?
Which was nicer than saying
the women of Framingham
are getting plumper and shorter.
It's the other way
around in the Gambia
and that means that
we are just beginning
our understanding of what
selection pressures are
like on contemporary
human populations,
it depends a lot on whether
they're in a developed country
where the patterns are pretty
consistent between Framingham,
and Finland, and Australia.
Or if you are in a
quite different country,
like the Gambia, where
the sources of mortality
are very different,
infectious disease
was still quite important,
people are suffering from worm.
Nutrition is a whole
different picture.
And that means differences
in selection pressure.
If we look at what's
going on in Utah where
we have magnificent data
that Jake Morad has analyzed
and we look from
1830 through 1890,
we see that the selection being
caused by survival or variation
in mortality rates is dropping.
And the selection being caused
by variation reproductive rates
is rising.
So this is actually a
very similar pictures
to what we saw with that picture
from England and the exercise
that I led you through
with respect to Framingham.
Variation in fertility
is now really driving
modern human evolution
in developed countries.
So my conclusions are
that we're still evolving.
We have documented an
episode of intense selection
that later eased off because
of cultural evolution.
And I think that change
is very interesting.
Women in Framingham
are under selection
to have their first
child earlier in life.
Also in Finland.
Also in Australia.
That amplifies an already
developing conflict
between biology and culture.
So that one kind of
grabs us in the gut.
Selection in each
sex is constraining
responses in the other sex.
That might explain some of the
paradoxes of human sexuality
and it certainly explains
some of our imperfections.
We are, as Shakespeare
noted, rather imperfect.
There are genetically-based
cost of reproduction in humans
and some of the genes
have been identified
and deserve a bit
more examination.
And I think the take
home there is that
If you are thinking
in a science fiction
fashion about the long term
consequences of germ line
therapy in humans to
get rid of cancer,
you'd better know what other
things those cancer genes are
doing because there is no
such thing as a cancer gene.
There's no gene that has ever
selected for cancer, right?
It's the deregulation
of a normal gene
that has other functions.
In this case, improving
reproductive success.
The demographic transition
is a major recent shift
in selection.
It uncovered costs
that previously did not
have to be paid, at least
not to the current extent.
And those costs now burden
our aging population
and are causing the
cost of health care
to skyrocket all over
the developed world.
Thank you.
[APPLAUSE]
STEPHEN STEARNS: So
Jane told me we're
going to break up by 7:15.
We have time for
questions and I'll
be happy to field them myself.
So just raise your hand if
you want to ask something.
In the back, yeah.
AUDIENCE: [INAUDIBLE].
STEPHEN STEARNS:
I can't hear that.
Could you speak up?
AUDIENCE: What do you think of
the impact of all these health
monitors and things like that
that people are wearing now
[INAUDIBLE]?
STEPHEN STEARNS: Jane,
do we have a mic?
Or can you walk down
here and ask me?
I'm wearing hearing aids and
when people go out the door
and they rustle, it
covers up your voice.
AUDIENCE: What do you think
are the effects of Fitbits
and other health monitors that
people are beginning to wear
and how that's going
to affect evolution?
STEPHEN STEARNS: Oh,
do I think that Fitbits
and other things that people
wear will affect evolution?
Well, you know, to
the extent that it's
going to have a marginal
impact on mortality from things
like heart disease and
cancer than it probably
will have something.
But I think more realistically,
a big impact on evolution
comes from NSAIDs.
So people who are
taking statins,
naproxin and aspirin are
lowering the inflammatory level
of their entire body and
they are reducing the risk,
not only of heart disease,
but of cancer and Alzheimer's.
So I think those are
probably also going
to be changing mortality
patterns and therefore
selection pressures.
But they do so mostly
in older people
so it's kind of a weak effect.
It's things that happen
to young people that
have a big impact
on gene frequencies.
AUDIENCE: What about
obesity in young population,
how's that going to affect?
STEPHEN STEARNS: How will
obesity in the young population
affect evolution?
Well, obesity in
the young population
has an impact on
reproductive success.
And kids who are obese
are likely to have
fewer children for a
variety of reasons.
Some of them having to do with
disease, some with behavior.
Being a little bit overweight
is good for your reproduction
but being a lot overweight is
very bad for your reproduction.
So it's complicated.
It's not it's not a linear
relationship by any means.
But I think that what
you're getting at
is a cultural trend that popped
up pretty quickly, right?
And was noticed and which
is now being combated
by Michelle Obama and
lots of other people
which is having some effect.
And I think the
take home on that
is that culture is
really hard to predict.
And evolution is slow
and culture is fast.
And culture can be
doing this and evolution
is running to keep up but it's
tracking a moving target that's
changing all the time.
And so I think that we're
probably always going
to be locked into this tortoise
and the hare kind of race
where biology is the tortoise
and culture is the hare.
And the hare is fickle and
it changes direction a lot.
Back there.
AUDIENCE: Yeah, so the
correlation between the gene
that helps to implant
embryo and cancer,
does that mean that a woman
who is fertile or gets pregnant
easily is more
[INAUDIBLE] to get cancer?
Or is that a bad--
STEPHEN STEARNS: Well, like a
lot of things in these studies,
one has to be careful
about quantifying risk, OK?
You can get statistical
significant associations
on small effects.
So I've just done this in
another study for autism
and schizophrenia in Denmark.
And I can show you
that if you have
a child who is very heavy, so
maybe a nine or 10 pounder,
that they are at an
increased risk of autism.
But the absolute risk
is 0.65% and when
you add in that extra
risk, it becomes 1%.
So it's still a
one in 100 chance.
So one has to be careful
about thinking quantitatively
when we say things
like that and it's just
like that for implantation
in the P53 gene.
But in that case, I
don't have the numbers
in my head to quote to you.
But the effect is
significant but small.
AUDIENCE: Thank you
very much for your talk.
I would like to ask
if you would comment
on the impact of the efforts
of Planned Parenthood
and those people
making decisions
but they're not going to have
[INAUDIBLE] straight away.
According to what
I've read, every age
of female in the United
States with their first baby
has gone up very strikingly.
The last figure I
read, it was about 26.
It seems to me that
there is major change
in [INAUDIBLE] without
having children.
I know that as a youngster,
I lived in Houston Texas
in an economically
disadvantaged area.
And all the chums
that I had either had
no siblings or one or two.
And there grandparents
had many, many more.
My grandmother had 12.
That was anything
uncommon around 1900.
And it just seems to me as
though those men and women
were not less fertile if
they're making decisions.
And it seems to
me as though this
would impact your conclusion.
STEPHEN STEARNS: It does.
And what basically you're
calling attention to
is the very important
role of culture
in starting to change
selection pressures on humans.
And it's a bit complicated.
So for example, if a woman
decides at the age of 22
to freeze some eggs
because she's not
planning to have our
first child until she's 38
and she doesn't want to have
trisome or something like that,
how does evolution, how does
the blind judge of selection
look at her age at maturity?
Is it 22 or is it 38?
Well, genetically, it's 22.
Demographically, it's 38.
We probably have to
keep track both ways
if we want to really
understand the consequences.
I have a colleague who is
a reproductive doctor who
does in vitro
fertilizations and who
was very interested
in the question of
whether or not IVF babies
would be more likely to have
genetic defects because
they wouldn't have passed
through the marvelous
screening procedure
that the natural female
reproductive tract has.
Which is a very
impressive screen
and produces pretty
high quality babies.
It make some mistakes,
more as it gets older,
but it's a very
impressive screen.
And Roger Gosden was not
able to find very much effect
in in vitro fertilization.
But we have to remember that
the way in vitro fertilization
works is you harvest
a bunch of eggs
and you put them in a Petri
dish and you inseminate them
with the sperm.
And then you get a lot more
than you implant and they
check to see which ones
are developing properly
before they implant them.
And then they always implant
extras and they often fail.
So there is a selection
step there as well.
So the fact that Roger
wasn't getting a big bump
in genetic defects in IVF babies
is at least partially accounted
for by the fact
that there's still
a selection filter in IVF.
AUDIENCE: Yeah, the
use of technology
on human development over the
next hundred years, people
are not using, not walking as
much as they were in the past
and not communicating
with other humans.
STEPHEN STEARNS: Like what
is the impact of Facebook
and Twitter on
natural selection?
[LAUGHTER]
Well, as Yogi Berra
said, prediction
is very difficult, especially
about the future, right?
But we do know this
about technology
and human reproduction.
Prior to the introduction
of the bicycle,
the average distance
between the birthplaces
of a husband and a wife was on
the order of one to five miles.
It was how far you could walk.
The introduction of the bicycle
bumped it up to 10 to 20 miles.
The introduction of the train
bumped it up even further.
My son is married to
a woman whose father
was born on Mount Kilimanjaro.
He was born in San Francisco.
And that's going to
happen more and more.
So one of the things
that technology is doing
and globalization
is doing is it's
causing the merging of
the total human gene pool.
It's going to take
a while, there
are all kinds of
cultural traditions
that are going to push
against it and whatnot.
I got quoted once on this issue
by saying, oh, in the future,
we're all going to
look like Brazilians
and I got a call from
Brazilian journalist who said,
hey, I'm looking
out at the street
and everybody looks different.
[LAUGHTER]
Well, that's not
necessarily unexpected.
There's this phenomenon,
when you make a genetic cross
that you get an F2, the
second, the grandchildren
have tremendous variation.
But one of the
impacts of technology
is going to be that we're
all going to look more alike
1,000 years from
now than we do now.
And that will have
various consequences.
One of them will be that we'll
probably have more resistance
genes and I'll bet the record
in the 10o-yard dash goes down.
AUDIENCE: Would you be
willing to explain again
how this model
explains homosexuality?
STEPHEN STEARNS: Oh,
well, I'm not sure
that it does because it makes
an assumption that there
are genes for mate choice, OK?
But the idea would be that
women are being selected
to choose men who have
certain characteristics
and men are being
selected to choose
women who have certain
characteristics.
And that when the genes
for mate selection in women
get expressed in men,
sometimes it's not perfect
and the men then
are selecting men
who have the characteristics it
had misselected in the women.
Got it?
So would you like
to go out to dinner?
[LAUGHTER]
AUDIENCE: That trade off
with the alleles and P53
that reduced the risk of
implantation early in life
and then caused--
STEPHEN STEARNS: Increased the
risk of cancer later, yeah.
AUDIENCE: On average,
if women lived
health-wise optimal
lives, health-wise.
Like you know, they eat
only whole grains, very
little wheat--
STEPHEN STEARNS: Kale
for breakfast, yeah.
[LAUGHTER]
AUDIENCE: Do you
think that would
reduce the risk,
in your opinion?
STEPHEN STEARNS: Oh sure.
There are strong environment,
genetic gene environment
interactions in all
of these things.
So normally, the
risk goes way up
when you're doing bad
things environmentally
and you got bad genes.
It doesn't mean you
always get cancer
but the risks will go up.
But if you have bad genes
and you do good things
environmentally, you definitely
will have lower risk.
There's no question about it.
AUDIENCE: You know
that curve when
you showed that
older women have more
mortality in their offspring?
How much of that is due to older
males that are their partners?
STEPHEN STEARNS: That's
very interesting.
The question is, how much of
the increase in infant mortality
in older women is due to the
fact that those women are
having children by older males?
90% of the mutations
in the human germ line
have come in through
older males and that's
because of the
profound difference
in the biology of
eggs and sperm.
Sperm have gone through
many more cell divisions
by the time an
older male uses one.
And each cell division
is an opportunity
to pick up a mutation.
Jim Crow did a really
nice analysis of that.
So my answer to that is that
I think that's part of it.
And I think the
other part of it is
this wonderful
quality-control screen that
is the human female
reproductive tract also ages.
It gets leakier
is it gets older.
It's not as precise
in picking up
the trisomes and the biochemical
defects and stuff like that.
So it gets leakier
but also I remember
I had a graduate
student in Switzerland,
a woman who was a
behavioral ecologist.
And I pointed out this
observation about older men
having defective sperm and
younger men having healthier
ones and she said,
oh, women have
known that for a long time.
That's why we marry the old
ones and we have the babies
with the young ones.
[LAUGHTER]
AUDIENCE: So as we went through
the demographic transition
and we started to dive things
like breast cancer, P53-related
cancers, were those genes
always there in the same amounts
or did we start selecting
for them if we were selecting
for fertility to basically
give ourselves these cancers?
STEPHEN STEARNS: Well, I think
the way I see it Michael,
is that there was selection for
fertility before the transition
and it didn't result in
cancers because people
died of infectious disease and
in childbirth and in things
like that.
So the costs were low and
there was some benefit.
There were lots of other things
that selected for fertility
and these genes
were not that, it's
not like everybody had them.
They're at fairly
low, they're not
at strikingly high
frequency in the population
but if cancer was the
main thing that they did,
they are at surprisingly
high frequency.
There is a paradox
to be explained,
a quantitative paradox
to be explained.
So yeah, I doubt that we any
longer selecting for them, OK?
Just the whole impact of modern
medicine and breast cancer
screening, and all kinds of
things leads me to believe that
we probably aren't.
But I can't prove that.
And of the things that
I've learned in science
is that as we get
older, we all want
to be able to come to some
kind of profound conclusion
about something.
But in fact, the data
won't let us do it yet.
And so we have to
learn to be kind
of firm in our agnosticism.
So my answer to you is that
on that point, I'm agnostic.
OK that's it.
[APPLAUSE]
