The Future of Genomic Medicine – Anne Wojcicki, Richard Lifton and Eric Green

The Future of Genomic Medicine – Anne Wojcicki, Richard Lifton and Eric Green

Eric Green:
So I now want to introduce to you two very special guests that I’m delighted were able
to come here and join us for this conversation. The first is Anne Wojcicki. And for those
of you who don’t know Anne, I’ll tell you a little bit about her. And then she’s
going to tell about herself a little in her own voice. Anne got a B.S. degree at Yale
University, and then worked in the health care investing area for about a decade, focusing
on biotechnology companies. But then she decided to found a company, a company you’ve probably
heard of called 23andMe, where she’s a co-founder and now CEO. And 23andMe is really a key part
of this personal genomics revolution, one with really — focusing on amassing now a
large database of individual genomic information and doing all sorts of things with it that
she’s going to tell you about. And then in fact, in November of last year she was
named the most daring CEO by Fast Company Magazine. So this is what Anne had to say about herself. Anne Wojcicki:
Being on Wall Street and learning about finance and how health care works is really fundamental
to everything that I’ve done because I learned the mechanics, essentially, of the system.
So I did it for about 10 years. And then after 10 years I said, look, like I — “One, I
don’t think I’m going to learn anything else; and two, like, this is not the system
that I really want to be part of.” Being surrounded by an environment where people
were really just pursuing money really started to conflict with my ethics and my values. And I spent a lot of time volunteering in
Bellevue Hospital in New York and then at San Francisco General out here. And I almost
did that as a detox where I’d be on Wall Street, and I’d spend all days, like, trying
to monetize, you know, obesity. And then I’d go into San Francisco General and it was tragic.
The idea of just thinking of these people coming in — sort of crisis situation, or
being sick, and seeing people with their families and thinking that — I’m just thinking about
you as a dollar amount. Like how do I monetize the situation? And it became pretty disgusting
to me. So again, I ended up having — feeling like Wall Street did not reconcile with my
values, and I had to leave. And 23andMe really evolved out of that frustration
that, I think, one of the ways that you can circumvent this — essentially, this whole
system is through the individual — is that the individual owns their data. And if I can
empower you to make a difference in your own health, we can potentially really change health
care. Eric Green:
So please welcome the — please help me in welcoming Anne Wojcicki to the stage. Anne,
come up, take a seat. [applause] Eric Green:
Middle seat. The hot seat. So the second — the second and other member of this panel that
will join me for this discussion is Rick Lifton. Rick graduated from Dartmouth with an undergraduate
degree, went on to get an M.D. and Ph.D. degree from Stanford University, and has just had
a meteoric rise, if you will, of a successful research career. He’s now a Sterling Professor
and Chair of the Department of Genetics at Yale University. He’s also an investigator,
for actually many years, in the Howard Hughes Medical Institute. And he is a recipient of
many awards and accolades, a small subset of which is shown here. And you can see the
American Heart Association, the American Society of Nephrology, and the American Society of
Hypertension have all honored him because of major advances he has made. In particular,
doing the genetics of disorders related to blood pressure, cardiovascular disease, and
bone density with multiple, wonderful successes credited to Rick and his laboratory. And this is what Rick had to say about his
circumstances. Rick Lifton:
I’m Rick Lifton. I’m Chair of the Genetics Department at Yale and an investigator of
the Howard Hughes Medical Institute, and we do human genetics of cardiovascular, kidney,
bone, and several other diseases. My favorite applications of genetics are to
reveal mechanisms of disease that we’ve known about the disease forever, but have
had almost no insight into their underlying, core biology. And when we think about where
we make our greatest advances in medical therapeutics, it typically starts with understanding what
the underlying biology is. And that allows you to target the, you know, what is the real
core disease process as opposed to the secondary pathways that revolve around there. And so
I think that’s what’s so beautiful about genetics and the ability to understand complex
traits — is the opportunity for the first time to really get to the core, underlying,
primary abnormalities, and understand those. Now, of course, those will not necessarily
tell you everything you need to know about the disease, but they are incredibly strong
starting points for unraveling the pathophysiology. And, of course, we expect that these will
define what the therapeutic opportunities will be. And we can’t predict with any certainty
what those therapies will be until we really understand the basic biology. Eric Green:
So please help me in welcoming Rick Lifton to the stage. [applause] Eric Green:
Thank you so much. Good to see you guys. Anne Wojcicki:
Good to see you. Eric Green:
So let me lay some ground rules here — what we’re going to do. We’re having a conversation.
I’m going to kick it off with a question, and both Anne and Rick prepared just a few
slides to sort of help answer that opening question and provide a little bit of background.
We’re going to talk for a little bit, but then we’re also going to take questions
from the audience. And there will be index cards that will be passed around at some point
during this and you can feel free to write questions out for one or both of them. If
you have a really easy question, I’ll take it. If it’s really hard, make sure it goes
to them. [laughter] Eric Green:
And then we will get — we probably won’t get to all the questions, but my staff over
there is going to sort through and try to find the best questions and pass them on to
me. And we will have some of the questions then from the audience put before our two
wonderful speakers. So what we want to start with — which, actually,
I think is a great way to think about it — I think about this a lot — is, you know, we
sort of in this decade of incredible advances; and we’re almost at halftime — 2015 will
be about halftime. And we knew when the decade began that this was going to be an exciting
one. And we sort of see 2020 now — really now only about six years away or something.
Soon it will be five years away. So I’m curious to hear from each of you — we’re
going to start with Anne — and sort of — in the year 2020 what is going to be the role
of genomics in medicine? I tantalized everyone with some of the early examples. But one of
the big questions is, how quick will this happen? And over the next, you know, five,
six years, what is this going to look like when we’re celebrating the January 1 of
2020 or something like that? So, Anne, you can advance your slides. Anne Wojcicki:
[unintelligible] it up? Eric Green:
Yep. Anne Wojcicki:
Okay. So I will start getting to that question towards the end, but I will — I’ll go through
a little bit on 23andMe and that will sort of touch in here. How many of you actually
have your genome or have been sequenced or — okay. Eric Green:
About 10 or 12. Anne Wojcicki:
Yeah. Yeah. It’s less than I thought. So part of the whole purpose for me of 23andMe
is — I grew up as a child of a scientist. And that science in my opinion should be more
in touch with the consumer. And that you actually want to — like, you should all be participating.
There’s billions of dollars that come from your institution and that we should all be
following it. Like there’s nothing more exciting than actually following science and
watching it progress. So 23andMe was sort of born out of that idea
of, like, how can I actually engage you, the consumer, with this. And one of the things
that we do is we, you know, like we said, it started out as a $3 billion venture. And
we’ve made it affordable and accessible. So it’s direct to consumer; it’s something
that you can actually afford. It’s $99. It’s something that you can get access to.
And the idea is, like, then you should be able to explore it. And what we have now is
750,000 people who have actually done this. So what’s amazing here is in a pretty short
time period it’s now become accessible, and large numbers of people actually have
experimented and played with their own genome. And what we’ve also learned is that people
actually want this information. Is that science — when you actually empower people with it
— that it’s actually — people can understand it. And so when I think about the future — one,
there’s a big question out there — is how much can actually people understand the science.
What we find is that the average individual actually can be empowered with this information
and they can make sense of it. And so here’s some of the areas, Dr. Green
already touched on these, you know, things that you can actually learn from your DNA:
you know, medication response, disease risks, inherited conditions like cystic fibrosis;
and then interesting traits, things like, you know, lactose intolerance or caffeine
metabolism. And then things like ancestry, and ancestry includes other fun things like
your Neanderthal status. Which again, is part of the things that we’ve done because it’s
science that’s coming out. It talks about you. That you’re not — just as much as
we’re talking here about disease and wellness, you’re not just about a disease. You know,
you have your whole — I mean the fascinating thing with your ancestry is that it’s, you
know, it’s your whole history of you. It’s your personal history. And that’s so cool.
Like how much Neanderthal do you have? And then comparing that to other people. It tells
your own personal story. So what we’ve also learned with this information
is that people get their genetic information, and that it does motivate them to change.
And so this a study by Robert Green that — more of it’s coming out soon — but people are
getting their genetic information and they’re actually showing up to their physician, and
they actually want to make a change. And I think one of things that we’re seeing genetic
information do is that it gets people interested in their health before they’re sick. And
for all of you, if you raised your hand and you say, well I’d actually rather, you know,
treat my diabetes than prevent it, well then you’re part of the old system. But for me,
personally, like I’d rather actually prevent my diabetes. And if I know that I’m at risk
for something, how is that I can actually, you know, prevent it? And I think more and
more you’re starting to see these trends like Walmart and your convenience stores getting
involved in health care, which is where you go to regularly. So more and more there’s
going to be more support for a preventive kind of society that’s probably going to
be outside of the existing medical system. So again, one of the things that we’re doing
is we’re actually getting people excited about genetic information. And I think the
more — one of the best things I think that we can do is to help people like Dr. Lifton
and all of NHGRI. Is if the entire world gets excited about the genetics research coming
out and participates, you’ll help clinical trials go faster. We’ll all be more excited
about funding going to this area. And I think we’ll uncover what the genome means much
faster. So as we see this — this is a slide that’s
probably shown all the time. That shows Moore’s Law and how, you know, costs of computing
is going down. And you can see that the costs of actually getting their genetic information
has dropped dramatically. And so this sort of leads to the conclusion — oops, we have
one slide I missed — is that at some point genetic information is going to be free. And
to me that’s actually one of the bigger questions when we think about 2020 and beyond.
Is that so much of population health today is based on the fact that, you know, is it
actually — is it cost-effective for you to get this information? So you look at things
like the Angelina Jolie effect, you know, and the BROCA testing. Right now people are
get — the BROCA test if they have a history of breast cancer or if they’re Ashkenazi
descent. But at some point, if the information’s free, everyone’s just going to have this
information. And so then how does that actually change
some of our population health guidelines? And how does that then change when people
are coming into you and they don’t necessarily have a history of, you know, something like
sudden cardiac death and they’re walking in saying I have this genetic variant, what
do you start to do? So I think that’s going to be actually one of the interesting issues. One of the other areas — the obstacles is
going to be how is this actually all going to become regulated? So what is going to be
the path forward to actually get all this information out? And what you’re starting
to see is there’s all kinds of countries — you know, the U.K. has a massive genome
— 100,000 Genomes Project. Beijing actually has the largest sequencing shop in the world
called Beijing Genome Institute. There’s tons of other countries. The whole Middle
East is actually launching these big sequencing initiatives. So how are we going to keep up?
And how is that we’re going get through all the ethical, legal, social debates about
how to use genetic information? But because the genie’s out of the bottle, the rest
of the world is engaging in this, what is our role? And what is the role that the U.S.
wants to be playing? So with that I’ll pass it on. Eric Green:
Yes. Pass it on and — Richard Lifton:
Great. Thanks, Anne. So just to continue framing the discussion a bit. To emphasize the pace
at which this work is progressing — if we think about humans as a species — a 500,000
year history of Homo sapiens, give or take a hundred thousand years or so — it’s only
in the last 50 years that we’ve really begun having the faintest ideas about how the well-known
principle of like begets like, which is where genetics really starts, to understanding the
fundamental contributions of individual variation to health and disease. We only learned about
the structure of DNA in 1953. We unlocked the genetic code in the 1960s. In the 1970s,
we just began to be able to get our hands on individual pieces of individual genes.
And then this led to the beginning of the Human Genome Project in the late 1980s. I have to say, having started in this area
in 1975 as a graduate student — I think if you had asked anyone involved in genetics
and genomics in 1975 when would we be able to sequence human genomes essentially at will,
I don’t think anyone would have imagined that that would have happened within — certainly
within my lifetime or the lifetimes of just about anybody else who was engaged in the
activity now. So the pace at which this has happened is really stunning. And if you think
about the eras that we’ve been through in human genetics, it was only in the late 1980s
that we really began being able to get our hands on individual disease genes and find
these to begin with. And that’s been taken over in just the last five years by this dramatic
reduction in cost of DNA sequencing, which now allows us to literally identify an individual
with a particular disease and be able to think about the question, can we figure out what
that person’s — the cause of that person’s disease might be just from studying his DNA
and perhaps several other individuals. Now we’ve talked for — at great length
over the years about the impact of what this work is going to have on human health. And
I’ll just give a couple of examples of this. So in the case — Eric mentioned cancer as
a particular beneficiary of genomics research, because there we know that there are somatic
mutations in the cancers that are not present in the patient’s germline that occur in
single cells that initiate the cancer. And those single mutations with large effect are
terrific targets for new therapeutics. And in the case of cancer, we now have specific
treatments that are aimed at the specific genetic abnormalities in individual cancers.
So if you have chronic myelogenous leukemia, there’s a specific mutation that is found
in nearly all patients with this disease; and there’s a specific drug that has transformed
the history of this disease from one that is uniformly fatal to one that is now highly
treatable with a specific drug that inhibits the specific molecular mechanism that is mutated
in this cancer. And there are a number of other such oncogenes that cause malignant
melanoma, lung cancer, and glioblastoma multiforme, the most lethal form of brain cancer, that
have specific treatments that are coming from this. Further, the study of rare patients frequently
gives us information about the pathogenesis of common disease. And these suggest particular
targets that will be beneficial for therapeutics. So for — one of my favorite examples of this
is if you’re missing a sodium channel that is in the dorsal root ganglia in your spine,
you’re completely impervious to sensory pain. Now those patients don’t need a drug
for pain relief. However, our current treatment of pain is very ineffective and has a number
of side effects. If you are able to develop a specific inhibitor of that sodium channel,
you wouldn’t even need that drug to get into the brain in order to have effective
treatment for pain. And there are many other examples where rare mutations found in extremely
outliers in the population have suggested therapeutic targets. And these are becoming
the norm in the pharmaceutical industry; to use human genetics to identify what are the
best targets where we’re going to have therapeutic efficacy. And this is rapidly emerging as
these drugs are coming on. And looking down this list, one that I’m
particularly enthusiastic about is the treatment of Alzheimer’s disease. Currently an intractable
disease of the aging population. And the best targets that we’re likely to get for the
next decade have come from rare mutations with early onset Alzheimer’s disease that
have pointed to a specific pathway for which drugs are currently in development. And we’ll
have to see whether these will prevent the development of Alzheimer’s disease in the
population. But as both Anne and Eric have indicated,
the last several years have led to spectacular ability to rapidly and efficiently sequence
large numbers of human genomes. And this is unlocking problems that have heretofore been
unapproachable. And one reason that they’ve been unapproachable is that there are some
diseases that are caused almost exclusively by de novo mutations. Not necessarily exclusively,
but there are many patients with these diseases where mutations that are absent in the mother
and father occur and cause a severe disease in the offspring. One example of this is congenital heart disease;
where we’ve now sequenced a large number of unaffected parents with a severely affected
child, where the plumbing that is required for the oxygenation of blood and its distribution
to the tissues doesn’t work properly. And we’ve identified a number of mutations that
drive this process and have identified an underlying pathway involved in modification
of the proteins around which DNA in the nucleus is wrapped. And perturbation in that — in
those pathways are driving this disease in a significant fraction of cases. So this is
one example of the kinds of discoveries that are happening now. And I want to make a point that when we ask
what remains to be done — the answer is almost everything. So they’re 21,000 protein-coding
genes in the genome. We know what happens when humans have mutation in about 3,000 of
those genes. So you don’t need to put a very fine point on it to say there’s much
more discovery that lies ahead than lies behind. And that just encompasses the 1 percent of
the genome that codes for proteins. When we get outside the part of the genome that codes
for these 21,000 proteins, it’s really terra incognita. We don’t understand the language
of genomes at all. If I were to give everyone in this room the sequence of the genome of
a mouse, an elephant, and a human and said tell me which one is which, we would be completely
incapable without other knowledge of determining which is which. Our genomes are very similar
to one another. We all share the — generally the same — when we say we all — all in the
animal kingdom share the same core set of genes. And it’s how those genes are used
that make the difference. We don’t understand that language hardly at all. The last point that Eric alluded to was the
ability to use this technology in the clinic. And I want to give one recent, quite dramatic
example from our work at Yale. So we were presented with a case of a 15 day old boy
who had severe diarrhea and fever, who was progressing in an unexpected clinical course
that the physicians taking care of him in the intensive care unit were concerned that
he was not going to survive. He was developing coagulopathy, blood clotting, and loss of
red cells and white cells. And the physicians were very concerned about his health. And
he had been seen by every patient — every consult service in the hospital, and nobody
knew what the diagnosis was. So in five days we turned around the sequence
and analysis of all of the protein-coding genes in his genome and his parents. And surprisingly
we did not find a new mutation that described his disease. But we obtained the hint that
there might be a mutation causing his disease that caused an auto-inflammatory disorder.
A disease in which the normal inflammatory response pathway was activated in the absence
of the normal stimuli for that. Unfortunately, the day before we obtained our complete analysis,
the boy died of pulmonary hemorrhage. However, it came as a matter of great surprise when
the next day we learned that his father had been hospitalized at the same outside hospital
with high fever and was intubated with respiratory distress. He turned out to have the same disease
that had been undiagnosed his entire life, despite the fact that he had been hospitalized
in a hospital his first month of life with a syndrome very similar to his deceased child. Because of this mutation that was identified,
we ultimately made the diagnosis of a new previously undescribed auto-inflammatory disorder
and he was put on high-dose immunosuppression and recovered. And he then revealed that throughout
the course of his life, he had had periodic fevers that were up to 104 to 106. They were
always triggered by emotional or physical stress. He recognized that with the stress
of his son’s death that he was kicking off another of these inflammatory episodes, but
thought he would ride it out the way he had every other one that he had had, but ended
up with this near fatal disorder in the hospital. So this is one dramatic example where sequencing
both defined a new disease and led to treatment of individuals in the family, and has suggested
preventive therapy that can be offered these individuals. I think that’s one of the last points that
I’ll add now. Is that frequently the discovery of the fundamental pathogenesis of disease
not only suggests the mutations and treatment, but frequently will suggest prevention. Eric
mentioned that we’ve had a long interest in high blood pressure, a disease that affects
a billion people worldwide and contributes to 17 million deaths from cardiovascular disease
around the world every year. Well, the mutations that cause this trait converge on how the
kidney handles salt, which immediately suggests an environmental interaction with dietary
salt intake and blood pressure. And this has led to a recognition that we ought to be able
to reduce blood pressure in the population by reducing dietary salt. And there are now
32 countries around the world that have public health programs to reduce morbidity from cardiovascular
disease by reducing dietary salt intake with the scientific fundamentals coming from these
rare patients with extreme forms of high and low blood pressure. So if we look forward to 2020 and beyond,
where are we going to be and what are we going to be able to do? The things that seem most
obvious are — we are certainly going to be sequencing virtually every cancer in patients
because those are going to drive the therapies that we’re going to give these patients
as we move forward. Similarly, we’re not going to waste too much sleep wondering whether
we ought to be sequencing patients who are in the intensive care unit and critically
ill in order to try to make what might be unexpected diagnoses. And there are multiple
examples of this happening now. The bigger questions, I think, going forward
will be to what extent will the sequence of every individual in the population contribute
to their health care? And that’s a research question at this point in my view. There are
relatively few examples where identification of a specific mutation today we will be able
to say, aye, we know what treatment you ought to have as a consequence. The BRCA1 and 2
mutations are wonderful examples; where if you have these disease-causing mutations,
this has very strong implications for how your diagnosis — your future diagnoses and
susceptibility to disease, and we don’t yet know how frequently that will, in fact,
be the case. I think it will be relatively modest impact if we tell our patients have
your genome sequenced and we can tell you whether you have a 1 percent or a 2 percent
risk of developing schizophrenia. That’s not the kind of information that we’re likely
to be going to our physicians for. What we want to find are those mutations that are
going to be driving disease. And for that reason, I think quite conservatively one can
imagine that we’ll be starting in the clinic with diseases that — with patients who have
disease or are at high risk for disease. And then newborn screening, I think, is an
open question. We now screen in most states in the country every newborn for a handful
of diseases ranging from 20 to 40 different diseases. We might do much better than that
with genome sequencing rather than the current screening tests that we perform. But these
are questions that we’ll have to settle as we go forward. So I’ll stop there. Thanks. Eric Green:
So that was great. So what I want to drill down a little bit because I think what you
touched on, and actually each of you sort of put out something to think about, really
I think relates to prediction. Because, I mean — first I want to talk about what’s
truth, not that we know it, but let’s talk about what truth might be. And then we should
think about some of these implementation things because I think there’s relevant — I know
both of you are very interested in those. But let’s focus on truth because we don’t
know what truth is. And when we try to use genomics as a tool, as a predictive tool,
that’s where I know there’s disagreement in the scientific community. So Anne, you
made a passing reference to you want to know things to prevent your diabetes. And the question
is whether it’s diabetes or hypertension — something that Rick is passionate about.
The question is what do we know now that is predictive if handed somebody’s sequence
or handed the kind of data that a 23andMe test might reveal? And, you know, what do
we know now? But also, where do you think we’re going to be in 2020? Of course, we
don’t know the answer. But where do you think we’re going to be? And does that tend
to influence, sort of, how we try to set up the system for — the medical system for dealing
with this information? Because I think as Rick says, it’s going to be a no-brainer
for cancer, a no-brainer for rare diseases, probably for some examples of pharmaceutical
genomics. But what — I know it gets more, shall we say, spicy and debate-y — Anne Wojcicki:
[laughs] Eric Green:
— out in the community is really when you get into these complicated diseases like diabetes
and hypertension — there’s an environmental component — and many genomic contributions.
Will we have something predictive enough to really tell us something that can be used
for clinical care, especially in the prevention realm? So Anne, what do you think? Anne Wojcicki:
Sure. So I would say for 23andMe one of the things that we were doing — and again, just
for disclosure, we’re not selling our health reports today as we’re working with the
FDA. But historically, what we did is we had two sets of information; information that
was what we call sort of the four-star reports that was clinically actionable. So BROCA,
for the BRCA1 and 2, cystic fibrosis, associations with pseudo-cholinesterase inhibitors, for
instance, about drug response. So we had that kind of information that — it was sort of
unrefuted — that was known to be — to have meaning in the clinic. And that if you walked
into most physicians that they should know what to do with it. And then there was sort of this grey area
of disease-risk prediction. And that’s where there’s been the most controversy. And type-2
diabetes is a good example where you can say there’s good data; there’s interesting
science that is being done here that — that again, I’ve always felt strongly that you,
the consumer, the taxpayer, since you’re paying for this research, you should have
the ability to go and look at it yourself since you’ve paid for it. And so can 23andMe
engage you in the science? And we’re never going to know how to actually predict disease
risk unless we have massive sums of data. And so one of the reasons why 23andMe has
a huge research component is that what we’re looking for is how can we actually create
this community of tens of millions of individuals and understand which of them actually go on
to develop disease; what are the genetic risk factors that they have, and can we actually
really develop a risk prediction modeling system that’s based on tens and tens of
millions of individuals — the genetic information, taking in environmental information, and looking
at this longitudinally. Because I think that it is a grey science right now, but in the
future, there should be able to be pretty good risk predictions. And again, cholesterol
is sort of an example of that. Cholesterol doesn’t mean that you’re going to get
a heart attack. It means that you have a risk factor for it. And I think the genetic — this risk prediction
— you might have a thousand genes that put you at elevated risk. We might be able to
calculate a score. And with that information, it’s another risk factor that gets totaled
up with your environmental factors, your family history, et cetera, so that you know these
are the areas that you’re higher risk for that you might want to actually — there might
be something that you can do about. And these are things that you’re — you know, that
you’re not as high risk for and potentially you don’t need to be as concerned about. So it’s definitely one of those grey zones.
But again, part of the reason why we’ve had this massive research initiative is that
you’re never going to get to that solution about how — what actually is the meaning
of all this information until you’ve actually can do these kinds of massive, million types
of person studies. Eric Green:
But 2020 — you think by the time we’re there, do you think for most of these diseases
that we’re talking about — hyperlipidemia, cholesterol, high cholesterol, hypertension,
diabetes — do you think we’re going to be mostly able to predict based on genomic
testing? Or you think we’re going to be just barely up the curve in being able to
predict? Don’t worry about it. We’ll save the video, so we want to make sure don’t
[inaudible] — [laughter] Anne Wojcicki:
[laughs] I would actually say it’s dependent upon how quickly we can grow. I mean 23andMe
last year was on a mission to get to a million individuals. If I could hit 10 million people
I think in five years, I think we can actually have pretty spectacular risk prediction algorithms. Eric Green:
So that’s — so your prediction is that that knowledge can actually be gained if the
right study is done? Anne Wojcicki:
I think — completely. I think if you can do — if we could get 10 to 20 million individuals
engaged in research, filling out surveys, we could actually understand genetics and
what it’s going to mean for your disease risk. Eric Green:
Okay. Rick, I have a feeling you’re going to have thoughts about this. Richard Lifton:
Well, so, I’m an optimist. And I want to see the experiments done. And the question
is, what are the experiments that one wants to do? There’s been a huge effort associating
common variants with common disease, and we clearly have associations. Sometimes they’ve
been pivotal in giving us insight into disease where we didn’t have any previously. But
in general, these have small effect on disease risk and so our ability to predict who is
going to get disease from these — the assembly of common variants across the genome has been
rather modest. And so I think the question going forward
is, will rare variation prove to be of sufficient importance to give us better ability to predict?
And that’s an experiment that has not yet really been done in a comprehensive way for
any common disease. And this is — these are experiments that are going to be done over
the next five years for, I would expect, for virtually every common disease as you go down
the list. We’re going to be sequencing large numbers of individuals, and the key question
is how large is large? What is the number that we’re going to need to — in order
to actually believe that we have tested the hypothesis? And the current estimates are
probably that it’s going to require in the tens of thousands of individuals for each
disease that we’re interested in. And that’s going to require a lot of work around the
world to collect the cohorts, study them, and make conclusions. So I think it’s a very open question as
to where we’re going to be by 2020. Because, as you noted, that’s a short time from now
and we’re barely scratching the surface in most disease areas right now. And that
presupposes that we’re sequencing just the protein-coding parts of genomes. And we, as
I indicated earlier, we really don’t understand the language outside the protein-coding parts,
so I’m not sure we’re going to be able to digest that part [inaudible] — Eric Green:
Nor do we know the balance between. Of all the things that happen in the genome that
cause disease, we don’t even know is — what the fraction is happening in the genes themselves
versus those happening outside the genes. Richard Lifton:
Exactly so. And so for that reason, you know, I think we don’t know much more than we
do know at this point. And it is a long way to go before we are capable of making confident
predictions. Eric Green:
So what was your reaction to the INOVA health care ad that I showed in my talk? What was
your immediate gut reaction? Richard Lifton:
Well, so, I think the field of genomics has always been fraught with optimism that frequently
is not tempered by reality. And I think my immediate reaction to that ad fell squarely
into that. I don’t think we’re ready to be making those kinds of predictions for most
people. I’ll give an example. So when exome sequencing became — came online and suddenly
people could do this, I must have reviewed one paper a week from a high-profile journal
that ran as follows. We sequenced 50 healthy year olds [spelled phonetically] and identified
variants in known disease genes. We then spent x number of dollars working them up for those
diseases, and were surprised to find that they in fact did not have those diseases.
And of course, this reflects a lack of knowledge of Bayes’ theorem; that if the prior likelihood
of a healthy 50 year old having a lethal genetic disease is extremely low, if you find a variant
in that gene, the likelihood that that’s a disease-causing variant is probably very
unlikely. And so you can spend a lot of money chasing these kinds of diagnoses. And this, I think, is a major problem that
we have as we try to interpret genome-level sequence. Is — for example, in BRCA1 today,
we know a lot of mutations that clearly cause — are causally-related to the risk of breast
cancer. There are other variants that change the protein-coding sequence, but do not predispose
to breast cancer. And the bane of our genetic existence today, in many cases, is the variant
of unknown significance. We find a variant that we’ve never seen before in any of the
people who have been sequenced around the world. And the geneticists are left with a
puzzle. There’s a variant there; we haven’t seen it before. How do we know whether it’s
functionally important or not? And there are approaches to try to address all variation
in every gene in the genome. And these are the kinds of things that we’re going to
need to have the kinds of diagnostic certainty that’s going to increase the power of our
tests ; so that we’ll know which variants have an effect on the encoded protein and
which — or the genome function — and which don’t. But we’re very, you know, the first
papers in this are just being published literally now. Eric Green:
Anne, what was your reaction to that ad? You’re the — you’re an optimist, I know. Anne Wojcicki:
I’m definitely an optimist. I mean, I think the ad was non-specific enough that it can
mean anything. Eric Green:
Yeah. Anne Wojcicki:
I mean, some of the things that I am excited about is that I do think that sort of this
general population health that — you know, I just turned — I’m 41, so should I get
a mammogram? So are all 40 year olds the same? And I look at other associations like — I’m
actually curious to ask you this question — there’s associations with macular degeneration
that actually are discovered out of Yale. And that falls in the grey zone. But if you
were homozygous for that high-risk variant, would you show up at your ophthalmologist
sooner to check for macular degeneration? And — so would you? Richard Lifton:
So — [laughter] Eric Green:
You don’t have to tell your age. Just because she’s bragging — [laughter] Eric Green:
You don’t have to do that. Because we were both once 41, weren’t we? Richard Lifton:
So this is actually not a theoretical question. My father had retinitis pigmentosa. And he
was from — his parents were from the same small village in Russia. And it was no surprise
that he was — probably his parents had distant relationship to one another, and he was homozygous
for one of the genes causing retinal degeneration. And I was actually faced with that question
of do you want to know? And my father went — had a productive life.
Had to retire early because of his blindness. It progressed to complete inability to see
in his 70s. And I made the conclusion that — drew the conclusion that he had a productive
life and I — would you — how differently would you want to behave if you knew? And
for me, the question was, is there something that you would do about it today? And I’m
very enthusiastic about things that you have some ability to change. At that time, there
was no treatment for the disease other than laser zapping of the lesions to try to prevent
them from progressing. And I decided that I didn’t want to have eye exams at that
point. So I think individuals will vary in how they
respond to that. APOE4 in Alzheimer’s disease today is a very practical example of this.
Allele frequency around the world is about 17 percent. And about 4 percent of the population
will have two mutant copies of this gene. And if you have one copy you’ll get Alzheimer’s
disease on average eight years earlier; and if you have two, 16 years earlier. And practical
question — do you want to know? And currently there are no useful treatments that we know
of that will prevent progression if you are an APOE4 carrier. And I think individuals
will vary in their response to that. And in general, in my experience as a physician,
patients really want to know if there’s something that can be done. And if there’s
not, it’s a very mixed impression. Anne Wojcicki:
Right. But one of the things I think that will be interesting is with population health
guidelines. So things like macular degeneration or with breast cancer, can I actually get
more specific guidelines for me that are based on my genome? And that’s when I start to
look at like some of these new, you know, prevention diagnostics that are coming out
that are very expensive. You know, if all women didn’t have to get a mammogram — one,
that’s great for me, but two, that’s a big cost savings. And so I look at things as well, like macular
degeneration. Where it’s in that grey zone now — still of information — but I can see
that actually being a really valuable risk prediction tool. To say this group of individuals
— not everybody actually has coverage with an ophthalmologist — but if I could actually
send these people at 50 to go and get screened, and there is now a treatment for delaying
and actually stopping the progression of macular degeneration — the cost to society of blindness
is very expensive. So can I find those individuals who are homozygous and actually get them involved
in front of a physician much sooner? And I think that is like — as much as that information
is the grey, that’s the kind of thing, I think that 23andMe could actually start to
validate by having this community-based research project. And then start doing these types
of population health studies to say yes, like, I can get these people in ahead of time and
actually try and prevent the disease before it actually really becomes costly to society. Eric Green:
One of the things I worry about a lot in these situations is managing expectations. And I,
of course, like the idea of getting community-based research involvement the way you describe
it. But do you — are we convinced people see the distinction between being involved
in research and actually having what they perceive as getting as truth? I mean, my reaction
to the commercial when I first saw it was at first was like, oh my gosh. They’re talking
about genomics. Isn’t this fantastic? And then by the end of it, oh my gosh, they are
really subliminally implying some things that many people may not, sort of, appreciate as
not really here and now. It’s the promise, but it’s not reality. I worry a little bit
about getting people involved. Will they interpret, sort of, the excitement of doing a study as
being the new way that you should make life decisions? How do we — Anne Wojcicki:
So I think those are two — Eric Green:
— strike that balance? Anne Wojcicki:
I think it’s two different questions. So one thing for us is getting our customers
to understand how much we just tested them for. So for instance, if I just tested you
on 50 different carrier statuses — so including cystic fibrosis and a whole host of others.
How do I get you to appreciate the fact that we actually just screened you for all of this
and that we did not find any variance there? So one is like getting you to realize there’s
all this information. One of the things that we have done is we
include this whole section on traits. Is that — traits are actually really fun for people.
So if I can tell you what your likely eye color is; or I can do things like caffeine
metabolism. Every one of our customers gets something. And they love that. Like, they
love thinking about lactose intolerance or caffeine metabolism — Eric Green:
Everybody loves thinking about lactose intolerance. Anne Wojcicki:
— ancestry. [laughter] Anne Wojcicki:
Well, but it’s actually interesting. So like I look at things like my child, who,
you know, was having stomach pain and then I looked into the genome. I was like, oh,
you’re genetically likely to be lactose intolerant; like I’ll just try out that
lactose-free milk. It’s a relatively — it’s cheaper than going to the doctor. So like
— and it seemed to work. [laughs] So I think those are things like — it just
— it kind of just fits in with your life. And I think that’s part of it — is I think
part of the reason for the success of 23andMe is that we can give everyone some kind of
piece of information. And I think that the research — I think one of the things we have
found is that people — you know, you look at Susan G. Komen and Livestrong. And there’s
this, like, goodwill sense where people want to contribute to the world. But we kind of
make it hard. And in part, one of the insulting factors
that I found on Wall Street is how we treat people like a human subject. And again, you
have the Henrietta Lacks up here. Like, it’s kind of insulting how you are in a clinical
trial, we get as much from you as we can, and then you are deemed too complicated to
ever return any results for. There’s not a single federally-funded study that returns
the data back to the — the genetic data back to the subject. And I find it kind of insulting
even just to be treated as a subject. So part of what 23andMe has tried to do is
humanize it. And we do all kinds of research studies. Like, we did a big study on — we’ve
done now the largest study on human sexuality. And no one else — like, it’s going to be
tough for me to get an NIH grant for that. But it’s one of the things –consumers actually
wanted that. And if you don’t want to participate, you just don’t take the survey. And if you
want to participate, you take the survey. And you look at the success of this ALS ice
bucket challenge. And you imagine, like, if you had a family member with Parkinson’s
disease and you could email out to all your friends and say, “Take this Parkinson’s
survey, you’re going to contribute to real research.” That’s like — then you can
really make a difference. And I think that’s part of what we’ve done. So the customers like — they have their information.
That’s their — like, their information of their genetic data, what they should do,
and then these surveys about, like, what is it — like, how can I answer the questions?
What are the genetic associations with type-2 diabetes? Why is it that it says I have this
genetic risk factor, but I don’t have a family history? How can we actually understand
that? And that’s the responsibility of 23andMe to keep innovating on that and make sure it’s
clear to customers that we don’t know everything. There’s this fascinating world of gene and
environment. And the more environmental information we can learn, the more we can understand of
how your genes interact with your environment; and then we should be able to give you better
information about actually how to manage your health. Eric Green:
So this is all about what truth is going to be, as I said earlier. What we’re really
going to learn through whatever means, whatever studies of the interaction of genomic variation,
and diseases, and traits, and the environment, and so forth. And I want to talk a little bit about implementation
— the real world. And I’m going to start with Rick. As a practicing physician, geneticist,
and someone who deals — in some cases with rare diseases, but much of your career has
also been looking very complicated common diseases such as hypertension. But you encounter
patients and you don’t have hours with them, but — you know, project to 2020. You’re
seeing patients in the clinic. When they come in with their particular circumstance, whether
it be hypertension or whether it be some other renal disorder, and they come with a lot of
genomic information. What’s that encounter going to be like? How certain are you going
to be to be able to give an answer? And how certain are you going to be that they’re
going to understand what you’re about to tell them? Because it’s not going to be
black and white. It’s going to be some shades of grey. Richard Lifton:
Yeah. I think in the long run both physicians and patients are enormously practical. If
things make a difference to patients’ individual health, patients and physicians will want
the information. And I think BRCA1 and 2 are perfect examples of that. When the tests became
available, there was a paternalistic strain in the community that said, “Well, we’re
not ready for this testing. We need time to figure everything out.” And patients and
physicians in the community said, “Wait a minute. My patient — or as a patient, I’ve
got a family history of early onset breast and/or ovarian cancer. I believe I’m at
risk. I want this information now. And because I’m going to do things with it.” And physicians,
I think, were pretty quick to pick that up. And a few more daring ones said, “Yeah.
Of course we’re going to start” — Eric Green:
It was pretty black and white. Right? Those examples are pretty black and white. Richard Lifton:
So I think the — so I think the black and white examples are the ones that in the long
run — and it’s the getting from where we are now to the long run. Because in the long
run I think it’s going to distill down to a manageable number of things that matter.
And physicians and patients will coalesce around — here are things that really matter
for your health in the long run, and these are the things that we ought to be measuring
in everybody. We have a rather shaky period going from where we are today to that point
where there is going to be a lot of uncertainty as to what individual variants mean in individual
patients. And this, of course, comes right back to Eric because his job is to get as
many people sequenced for as many diseases as rapidly as possible to settle which variants
actually matter so that Anne can put on her diagnostic list; here are the things that
we’re testing now because these are the things that we’re certain really will matter
to patients. And we’ll be able to hopefully use this to improve public health. But I think we will have a very — a period
in the near term where we will have a lot of variants of uncertain significance where
— Eric Green:
Which is why I’m picking on 2020. Because I think, you know, I share a lot of the optimism
that will eventually understand a lot of this. But it will be an awkward phase. So in 2020
though, think about in our medical colleagues, and our pharmacist colleagues, and our nursing
colleagues, and genetic counselor colleagues — you know, they’re either in training
now or they’re out there in practice. And it’s just this tsunami of uncertainty. I
think the BRCA1 is an easy example, but I purposely pointed to hypertension, — Richard Lifton:
Yeah. Eric Green:
— diabetes. I know it’s going to be grey for a while, and yet, some of it will start
percolating in. And what is that going to look like — and both from the patient point
of view and for this busy health care professional point of view? Richard Lifton:
Yeah. I think it’s going to be quite taxing in many instances, and I think we need to
be prepared for uncertainty. We’re going to be dealing with a fair degree of uncertainty
in many cases about what the significance. And for this reason, this is where I come
back to my earlier comment. I’m most enthusiastic about using this technology for people who
either — we have good reason to think they are at risk or they are presenting with a
particular disease. And the element that you and I have discussed previously is — we’ve
got a long list of genes to figure out what they do and what they mean in the context
of humans. And more rapidly we populate that space, the better opportunity we’re going
to have to understand when a patient comes to us, what disease they actually have, if
it is genetic; and if it’s genetic, which gene is mutated, and how that’s driving
disease. Another element that we haven’t touched
on yet is the potential impact of all the information coming from electronic medical
records and the ability to do very large amalgamations of that data with genomic data. And this again
poses both opportunity as well as enormous challenge for trying to make all of this coalesce
onto — into new knowledge pathways that will benefit public health. Eric Green:
As you know, we’re very interested in that, and research going on actively to try to see
what that future is going to bring. So Anne, I think you alluded to this. I mean, are the
great discoveries the next five years going to be in the United States? Or are we at risk
of losing our lead on this? Anne Wojcicki:
See, I definitely — there’s two things. So one, I’ll answer that and then I wanted
to go back to your last question. Eric Green:
Sure. Anne Wojcicki:
So I do — I do really fear that the U.S. is going to be falling behind because there
are major initiatives going in a lot of other countries. So the U.K. has their 100,000 Genomes
Project. Like I said, Beijing Genome Institute has just a massive — it’s the world’s
largest sequencing shop. You look at other countries like the Netherlands where they
actually have some of these massive, half-a-million person studies where the medical records already
are integrated. And I think that’s where we have this dream and this fantasy of actually
having all electronic medical records integrate. But I actually have — I mean, raise your
hand here if you’ve ever downloaded your medical record or if you’ve ever used — oh,
some of you. Anyone ever use Blue Button? Oh, we’ve been looking for you. [laughs] [laughter] Anne Wojcicki:
So I mean that’s part of it — is that trying to find people who are actually getting this
data is hard because medical records are not really integrated. And that’s part of the
problem with not having a single patient identifier in this country, and actually really being
able to get all this data. But there is massive potential for doing these types of studies.
And I look in the — Europe — I mean, the U.K. they have, like, this million women study
where it’s just like this one woman who runs the study and they just have amazing
amounts of data. So I do worry that at this time because we don’t have a clear path
for actually how we’re going to do these types of massive research studies. And there has actually recently been a hold
on some of these research studies. Like, there’s BabySeq [spelled phonetically], for instance.
There’s this big sequencing program where they want to, sort of, you know, understand
the approval — the regulatory process before they’re going to return all this data back
to the individuals. So I think that right now, we’re really kind of stuck because
we don’t know the right way to deliver all this information back. So the second thing I was going to say on
the variants of unknown significance — I do see that as actually one of the biggest
challenges. Is that you get tons of this data and you don’t know what it means. And so
this is actually a project that Rick and I ironically ended up working on. Where somebody
came to Rick where they had three generations of pancreatic cancer. Rick did the sequencing.
We found that there is a mutation in MLH1, which is associated with hereditary colorectal
cancer, and we thought this is the likely mutation. So it was a variance of unknown
significance that had a high probability of being this mutation. And what 23andMe did
is we took that mutation and we looked back in our database, and we said, oh, we have
a 157 other people with that same mutation. If this is really the highly penetrant mutation,
those 157 individuals also should have had hereditary cancers. And so we ran a survey.
We got 12,000 people to respond in 12 hours. And we could see almost instantaneously that
this mutation had — that those individuals with that mutation had nothing above baseline.
And so we could conclude than with a high degree of probability that this variance of
unknown significance was likely not the cause of the mutation for this hereditary pancreatic
cancer. And so this is something that 23andMe is looking
to do more and more; is that it’s not our job to mine all the data. We want to be, sort
of, representing the consumer. So we are looking at ways that we can actually make our entire
database accessible to people like Rick, to you, to all researchers in the world; where
they can run a query in the database and they can instantaneously see is this variance of
unknown significance. What is being found in other individuals like this? And that’s,
I think, part of how you, the individuals, are actually going to be able to contribute
to research like us decoding the genome really fast. And if we have that ability in five
years — if we have massive numbers of people, we really could decode a massive amount of
this genome. Richard Lifton:
So I want to completely agree with this point. If we sequenced our individual genomes today,
the best annotation tool that we could possibly have for understanding what is interesting
or potentially actionable in it, is to know the sequence of — not just everybody else
in this room, but a million other people. And today the largest publicly available database
— you could put together maybe 20,000 people from available databases. And I know NHGRI
is passionate about trying to get this data available. And, of course, it raises many
issues with regulatory authorities. And I think it is one of these — will be one of
these individual responsibilities where we will need individuals to be willing to make
their data in some way accessible. Because we all will benefit to the extent that everyone
makes their data accessible to be able to correlate genotypes with phenotypes. I think
that’s critical. Getting back to your question about a — you
know, how the U.S. is fairing. It — we’re in a somewhat ironic time, when having spent
enormous taxpayer dollars since the end of World War II for basic biomedical research
that has led to this point where we are today. That we are now in the throes of cutting back
on our investment — on our public investment in research just at the time when the fruits
are most likely to benefit the public. And I think this is a poor decision to be making
at this time. Eric Green:
And we need to reverse it. Anne Wojcicki:
[affirmative] Eric Green:
So changing topics slightly, one of the things to be careful about is making sure then the
process of using genomics in a productive way to improve how we can practice medicine,
we don’t leave behind certain elements of the population. So health disparities — is
— think genomics is going to exacerbate or reduce health disparities in America and elsewhere
in the world? Anne Wojcicki:
[affirmative] Eric Green:
Not an easy topic, I realize. Anne Wojcicki:
It’s not an easy topic. I mean, it’s a couple things that we’ve done. I mean, part
of the whole mission for 23andMe was the accessibility and the democratization. So at $99, there’s
a massive difference between us and the entire genetic testing field. So we’ve tried very
hard to make this information accessible for individuals. And we’re trying very hard
to make it so it’s understandable, that it’s easy for people, that it’s — you
know, you just go online and you order it. I do think that one of the differentiating
factors is going to be when you get your information you show up to your physician and if your
physician doesn’t know what to do with it, then it’s a challenge. So I think there’s
two things. One, it’s part of the reason why 23andMe has a community — is that people
are learning a lot because genetics is still so new, they need to have a community resource
to ask questions. And then we find those community members are pointing each other to other resources.
And we also have a list of resources for our customers. I think second, I think you’re
going to have to have things like tele-medicine where you’re going to have — you know,
we have a partnership with InformedDNA, a group of genetic counselors that are trained
on all this genetic information. So it’s, again, relatively inexpensive, but then someone
from their home can then go and get this information. But I think it’s a challenge. And it’s
part of the reason why we’ve put in — we’re starting to put in significant resources into
the education. Because most of the medical community is not educated about genetics.
And I do believe it’s part of our responsibility to make sure that we are at least supporting
the physician as much as possible. And I was an investor in the days of WebMD when it first
came out. And it was hated. You know, it was just wreaking havoc on the world. And so I’ve
at least learned from that in that I want to be able to enable customers to get a report
on Factor V Leiden printed out and actually have the basic information on it where they
can walk to a physician, and the physician feels capable and competent at actually answering
those questions. So that’s our goal and that’s going to be the direction that we’re
going. Eric Green:
Rick? Richard Lifton:
I’ll take a somewhat different tack on the question. When I was a medical student, the
first time I walked into a dialysis unit was in Palo Alto, California and I was astounded
to see that most of the patients in the dialysis unit were of African American ancestry. Because
Palo Alto at that time — African Americans constituted a small fraction of the population,
and yet they dominated the dialysis population. And I asked the attending physician, what’s
the explanation for this? “Yeah. Socio-economics, access to health care — don’t know.”
Wave of the hands and that was the end of the conversation. But it was something that
was persistent and stuck with me over the years. And just recently in 2011, a really remarkable
study came out that provided an explanation that this major health disparity is actually
genetic in origin. And it turns out that if you have one copy of the particular variant
in a gene called APOL1, and you live in Africa, and are exposed to trypanosomes, you are protected
from development of trypanosomiasis. And that’s a very beneficial thing to have. But if you
have two copies of the allele, you — of that variant in APOL1 — you are likely to end
up on dialysis at age 50 or 60. This was a mystery that was completely unknown and people
dealt with — what’s the origin of this health disparity — for a very long time until
this genetic explanation came forward. So I think there’s a path forward there
to actually address one of these health disparities. And, of course, the challenge now is to understand
the pathogenesis, how this variant APOL1 translates to this predisposition to end-stage kidney
failure. But is a nice example of — where in genetic discoveries have the opportunity
to reduce a health care disparity in a rather dramatic way. Anne Wojcicki:
So do people get screened for that now? Richard Lifton:
Well, so right now it’s in that grey zone — Eric Green:
Grey zone. Richard Lifton:
— of we don’t really know what to do. And it’s a very recent finding. But it clearly
has a very large — unlike many common variant studies, this has quite a large effect on
risk of disease and clearly is of importance. Eric Green:
I just looked down. One of the questions — Anne, I don’t know if you want to extend any more,
but specifically related to this — where they wanted to ask you what do you envision
23andMe can contribute to discussions on health disparities for various populations? Anne Wojcicki:
What can we –? Eric Green:
What can you contribute to discussions on health disparities? In other words, is any
— are there — I would imagine some of the studies you’re doing or whether you’re
doing enough population collections to be able to answer some of the questions like
what Rick was giving examples about. Anne Wojcicki:
Yeah. So — so one of things that we have found is in — I mean, you guys certainly
know, is that most genetic studies are done on European populations. So I think it was
three or four years ago we actually launched an initiative called Roots Into the Future,
where we gave away — we partnered with Skip Gates, and we gave away 10,000 free kits to
African Americans because we wanted to see — could we do sort of a massive replication
study? So could we find, you know, this, you know, this type 2 diabetes or Factor V — like
all these genetic variants that are found in European populations, do they replicate
in the African-American populations? So 23andMe, I think, has — recognizes that
genetic studies are not done in all populations. And again, I think it’s part of where we
— we tried to rectify it at least a little bit there by having this, sort of, major initiative.
And when we gave away 10,000 free kits, we found then that each family member then goes
and they get other family members to start — to sign up as well. So then it actually
expanded it quite a bit. But that it’s important for us to make sure that the genetic information
is relevant and meaningful to all populations. And today it is decidedly not. So it’s one of the things that’s definitely
on our mind. It’s some of the things that we think about. We’ve put — you know, as
an early non-profitable start-up, we’ve put pretty substantial resources into this
already. And we try to advocate for this. Like Southeast Asians as well are routinely
not part of these big genomic consortiums. So that’s again something that we’re very
aware of, and that we think actually needs to be remedied. So we are thinking about that
and we try to recruit potentially certain populations. But it’s a problem in the industry. Eric Green:
So one of the members of the audience pointed out that we’re talking a lot about prediction.
But let’s also maybe explore a little bit about therapeutics and what is now possible.
And they gave us an example, which is one that I know Rick — you probably hear about
frequently. You know, the examples where we’ve known the genomic base of a disease like sickle
cell for many years, and yet we really haven’t been able to come up with good therapeutic
or improved therapeutic options. So what — when you look in the crystal ball, you know, what
do you sort of see? Is genomics going to be mostly a diagnostic and predictive tool? Or
is this going to lead to new therapeutics including, obviously, gene therapy, drug development,
and so forth? Richard Lifton:
Yeah. So key question. I think the starting point from my perspective is always the biology
is going to tell you what your options are. And sickle cell anemia is a good example of
how difficult it can be to go from understanding biology to developing a new therapeutic. We’ve
known the molecular cause of sickle cell anemia since 1953, and yet we still don’t have
effective therapy for that. And part of this gets to the nature of what the gene is, and
what the specific mutation is, and what would be the path forward. So some of the examples that I gave in cancer,
where we’ve gone in stunningly short time from identifying a mutation that’s driving
a particular form of cancer to a new therapeutic, has occurred specifically because the nature
of the mutation suggested an immediate path to therapy. The genes in cancer that I illustrated
were types of mutations that cause increased activity of a particular pathway and suggested
immediately that we could turn off that particular pathway and have a beneficial effect on the
development of that cancer. Much more difficult are situations where you have lost the function
of a particular gene or protein, and then are trying to figure out how to reactivate
that gene or some downstream pathway. And that’s frequently much more vexing. Similarly,
structural proteins are very difficult to figure out how to deal with their replacement. So thinking about potential magic bullets
going forward, there — gene therapy is always, you know, it’s one of those areas that the
future is always just around the corner. And I think that we haven’t really cracked that
nut yet. For trying to correct genetic mutations there are, I think, quite promising technologies
that, you know — as you know, just over the last year the development of general approaches
for either knocking out gene function or potentially replacing — correcting specific mutations
with technology called CRISPR technology, which came from basic biomedical research
identifying fundamental pathway used in bacteria to ward off invaders has really quickly caught
on in the biomedical community and is being widely used. And there are potential therapeutic
approaches using this that clearly are not likely to happen immediately, but are of the
sort that are clearly getting a lot of interest in the public. So I think the bottom line is we don’t know
what we’re dealing with until we understand the biology. And as I always tell my students
and fellows, the surest path to therapy is understanding the biology. It’s just not
the case that every time you understand the biology, it’s going to immediately suggest
a therapeutic. Eric Green:
So Anne, one of the people in the audience is asking questions about privacy issues.
I am quite sure you’ve thought about this. Sort of, what are some of the — do you think
we’re properly situated in the United States to deal with a lot of genomic information
on a lot of patients in their electronic health records? Do you think this is something that’s
going to come and backfire? Or do you think we need a better framework for putting that
future together? Anne Wojcicki:
I mean, I think in electronic medical records it’s — I wouldn’t say as much of an expert
in that. But I think that in general, genetic information is sensitive information. And
I think it’s — in some ways the consumer just needs to be really informed of the fact
that it’s impossible to de-identify you from your genetic information. So — so it’s part of where there’s a
responsibility; you need to understand what it means when you share your genetic information
and what those risks are. One of the things 23andMe has tried to do is — what we have
found, is that most consumers — actually most of our customers at least are comfortable
with sharing their genetic information, but they want to be in charge of that. So they
want to know, am I sharing this with my mother? Am I sharing this with a stranger? You potentially
want to share different levels of information. I might want to share more information with
my physician, less information with my sister, less information with random people on Ancestry. So I think it’s important that the privacy
controls — you know, when we spent early — in the early days when we met with all
the privacy experts, one of the things that they said is that, like, look, the definition
of privacy is giving individuals that choice of maintaining whatever level of privacy they
want. And so 23andMe — you can join us. There’s no legal chain of custody that we have. If
you’ve ordered a kit, I don’t necessarily know that that kit actually was spat in by
you. So we don’t’ have that direct chain of custody. And we do everything we can to
protect that privacy of your genome. At the same time, we give you those controls if you
want to share it with individuals that you can. If you don’t want to share it, you
can’t. But I think it’s the reality for this country
is that we need to make sure that people understand that there is always a risk with this information
and when you’re sharing it. And I would advocate that there is a reasonable risk-benefit
reward. You know, what Rick was saying is that we’re all going to learn from each
other if we can all get over this. But we all need to understand what those risks are.
And I think that there does — like, GINA is in place here. I think — GINA is the Genetic
Information Non-Discrimination Act — so there is federal legislation now that’s going
to protect you from having your employer and your insurance company from discriminating
against you. It could be made stronger. It could include life insurance. And I think
what we’re going to wait to see is some severe penalties. If there are breaches of
privacy, there needs to be sort of that severe penalties coming after those individuals. Richard Lifton:
I do think — just to follow onto that — I think we have placed enormous weight on theoretical
harms that are rarely met, and have placed almost zero weight on practical benefits that
will come from data sharing of the sort that Anne is alluding to that is really necessary
to make full utility of the information that’s available. Anne Wojcicki:
I mean, it’s one of the things that when we get asked these questions, I look at all
of you in the room and — could I hack into your genome or would I rather hack into your
bank account? [laughter] Anne Wojcicki:
And the reality is, like, I’m sure your email or your bank account is much more interesting. Eric Green:
And a lot of these are federal employees. Our bank accounts are really boring. [laughter] Anne Wojcicki:
You never know. [laughs] So — so it’s still that there’s more than incentive. And there
is a lot of really great sophisticated technology that’s evolved that we’re able to copy;
and we’re able to, sort of, understand what is it that they do in the banking industry
with your mail, other things, that we can then emulate with 23andMe. And actually the
team that originally built the infrastructure for 23andMe was a group that had come from
PayPal that were specifically from that banking industry and brought that kind of security
obsession. So it’s clearly important, and again, I
would agree with Rick. Like, it’s that risk-benefit. We worry so much about the theoretical. But
there’s a massive benefit to society if we actually all can pool our data together.
And I think that’s also part of the reason why we have 750,000 people pretty quickly
that have all come together, and 80 percent of them are consenting to research and sharing
information. Eric Green:
So Rick, another question came in. This is a person who is clearly going to be recruited
to be one of your reviewers next time you’re up for a Hughes evaluation [spelled phonetically],
which I know is a very stressful evaluation that comes in. So they said hypertension,
which you’ve spent much of your life studying, is a challenging example. But we can easily
and cheaply see if a person is suffering from it and there are large numbers of effective
drugs. So why do we need genomics at all to study hypertension? Richard Lifton:
Terrific. [laughter] Richard Lifton:
So when I started working on hypertension, I chose to work on it specifically because
it was one of the common diseases that, as I said, affects a billion people. And when
we started our research on it, it was passionately debated as to whether hypertension was a primary
disease of the heart, brain, kidney, adrenal gland, or vasculature. And as a consequence
of that inexact understanding, two-thirds of patients with hypertension are inadequately
treated and we continue to have 17 and a half million deaths annually around the world from
cardiovascular disease –remains the leading cause of death worldwide. The rare outliers that we studied with extremely
high and extremely low blood pressure settled the question that probably only the salt lobby
really wanted not to be answered. [laughter] Richard Lifton:
Which is the kidney is a central regulator of long-term blood pressure by determining
how much salt is reabsorbed by the kidney. And the impact of this is it is immediately
suggested how you might want to try to attenuate the age-dependent rise in blood pressure that
occurs in western societies by modest reduction of salt intake. And as I mentioned, 32 countries
now — as an accumulation of knowledge implicating renal salt reabsorption — now have modest
reductions in salt intake as a uniform goal for the entire population, which is modeled
to — and in the U.K. there’s evidence — has reduced cardiovascular morbidity and mortality. Eric Green:
So if I combine a couple of questions related to education, I want to ask each of you — do
you think the bigger challenge is going to be in educating and preparing the health care
professionals for this future? Or is the bigger challenge going to be preparing the patients
and the general public for genomics and its use in medical care? Or is it going to be
a tie? Anne, I’ll let you go first. Anne Wojcicki:
I think it’s going to be the physicians. Eric Green:
Are going to be harder? Anne Wojcicki:
Yeah. I know, I think the physicians are harder. And I had — Eric Green:
And other health care professionals — Anne Wojcicki:
And other health care professionals. And I think part of it is that, you know, we had
— at one of our early conferences we had a physician stand up and say, “Look, the
biggest problem with 23andMe is that you generate non-billable questions.” And I think that
that’s actually true. It’s because there’s not, you know — we’ve seen doctors make
lots of changes when there’s a massive reimbursement incentive. So Lasik was one example. You know,
when everyone was getting their eyes cut, people made a ton of money off that so everyone
learned that new technology. There’s not a lot of money to be made off genetics. So
it’s hard to justify with such a busy world that you already have. Why is it that you’re
going to learn all this information? And I think the physicians have been generally,
you know — it just hasn’t been taught. It’s not really taught that much in medical
school, or it’s taught just about things like cystic fibrosis. So this — it’s a
whole new class of information to learn. And what we find is that no one cares, you know,
from the consumer perspective — no one cares more about your health than you. And if your
genetic information is all about you — and you’re worried about how you can stay as
healthy as possible, and you see your family has a history of one thing or a history of
other, you’re really motivated to learn as much as you can about you. And that’s
— that’s where I think what we’re seeing is. Like, our customers are really — get
educated. You know, we have these videos that — called Genetics 101. It’s a YouTube series.
And we have over a million views on these videos collectively. So people are — people
want to understand this. And so I do think that you have more of an
incentive because it’s about you; versus the physician, where it’s part of your workload
and there’s not a reimbursement structure to really support that right now. Eric Green:
So Rick, are all the Yale first-year medical students watching these videos and getting
educated about — [laughter] Eric Green:
No? Seriously — Anne Wojcicki:
[laughs] I can trace them back. Eric Green:
I’m curious what you think about what’s going to be — where is the bigger challenge
going to be: the public or health care professionals? Richard Lifton:
I think they evolve just about in parallel in my experience. And I go back to BRCA1 where
I think patients and physicians — patients were a little bit ahead because of exactly
Anne’s point — that it’s me, it’s my family, and I really want to know. But physicians
were pretty quick to pick up that this was practical and important and made a difference.
And surely, physicians currently in medical care don’t have huge amounts of time to
spend with each individual patient. And so they’re going to be focusing on main effects.
Right? What are the things that actually are going to matter most to long-term health of
patients? And I think to the extent that things matter, people will be paying appropriate
attention to that. Certainly, in the first-year Yale medical
school curriculum, we teach a lot of genetics now. Genetics is — you know, there is no
better framework for understanding human biology today than focusing on the diseases of every
organ system from what happens when you have a specific mutation. And you take one, you
know, essentially one piece out of this working organ, what happens? It’s a wonderful way
to organize a curriculum. Eric Green:
And how much has that changed in the last decade — that curriculum? Richard Lifton:
So I think in medical schools around the country, it’s quite common now to have aspects of
genetics and genomics tie into almost every organ system; because it provides such a special
way of understanding the biology of what happens when you mutate this gene and why does, you
know, all the secondary consequences evolve from this primary abnormality. Eric Green:
Okay. We’re winding down and we want to end at an appropriate time to have a break
before the next panel. So I’m going to ask each of you one more question. The question
is, when thinking about everything we’ve discussed, what keeps you up at night? And
Anne, your answer can’t be the FDA. [laughter] Eric Green:
You have to come up with something other than the FDA. [laughter] Eric Green:
So we’ll let Rick start and then we’ll come to you. Anne Wojcicki:
Yeah, I have to think about it. [laughs] Richard Lifton:
Well, so I think we’ve already touched on the part that keeps me up at night, which
is how do we get from here to there? You know, we can see over the event horizon to see to
— once we’ve got a million people sequenced, maybe more than that million genomes, we’re
going to have ideas of what variants are highly — most strongly predictive of particular
diseases or their outcomes. And trying to get from where we are today to that point
I think is going to be — have a lot of challenges because a lot of genomes are going to be sequenced.
And just as Anne articulated, people are going to show up and say, I’ve got this variant.
What does it mean? And right now we’re not going to know with nearly the precision that
we want in many cases what those variants actually mean. And I’ll add the FDA part for [laughs] — for
Anne so she doesn’t have to answer that. I think there’s huge opportunity for innovation
in health care. And I do have serious concerns that if we over regulate — I think the FDA
has a completely appropriate role in making sure that tests are being done well and appropriately
and the information is accurate. But I do have reservations that — about if we go down
a path where we insist that these are the only tests that people can offer at any one
time, that that will really stifle development and innovation in this area. Eric Green:
Anne. Although now I realize your answer’s going to be your young children keep you up
at night. [laughter] Anne Wojcicki:
My young children do keep me up — they wake me up early rather. I mean, there’s things
that I lose the most sleep about is that the most rewarding part of 23andMe is — I always
wanted to be a doctor and help people. And I get an email almost on a weekly basis of
somebody who says, “Like, oh, you know, you saved my life because I learned this information.”
Or, you know, there’s a man who came up to me recently who said, “You know, my son
hated sugar. I couldn’t figure out why. We took him to all these specialists. And
then my sister was pregnant and she did 23andMe. She found out she’s a carrier for fructose
intolerance. Lo and behold, I go to another five physicians. I get my son tested and he’s
homozygous for fructose intolerance. He can’t absorb fructose and that’s’ why he hates
sugar.” It’s normally only detected in their twenties, once they actually have severe
disease. And so this little boy, like, we’ve just impacted his life. We prevented him from
actually having this disease. And, you know, information, you know, significant
percent of the 23andMe customers really learn something that influences their life. And
it could be that, you know, it could be on their ancestry. It could be that they find
a relative. It could be that they, you know, actually have Jewish ancestry and they didn’t
know about it, or they didn’t know whether they were adopted. Or it could be on the medical
side. And so it keeps me up at night that people
can’t get this information right now. And I think more than that, I’m impatient like
I am — I’m 41, which is young, but it’s also sort of old — Eric Green:
It’s actually disgusting, but that’s okay. [laughter] Anne Wojcicki:
[laughs] But I really — like I feel this, you know, this pressure. And I was looking
back for this talk — I was actually looking back at where were cellphones 10 years ago
— just to look at that delta. And, you know, it was like the old flip phone. Like that
was really hot, like having one of those StarTACs — Eric Green:
I just got rid of my flip phone like six months ago. Anne Wojcicki:
[laughs] I know. Don’t admit that. Eric Green:
[laughs] Anne Wojcicki:
So — and then I compare that to the iPhone 6, which just came out. And then I think about,
well, we want that same kind of evolution to happen in genetics. And so how are we going
to get there? And at this current pace of funding individual little studies, it is not
going to happen, frankly. And so we need a massive community of individuals to help us
decipher what this genome means. And I am definitely the big believer. I mean, I spend
every single day doing this because I believe that if we can have the world’s information
combined with genetic data, you really will be — have a much better path for making drug
discovery, you’ll have much better diagnostics, you’ll have just a much better way of living
your life. So how can we get there faster? And I don’t
want 23andMe being the only one sitting on this data. I want to enable every researcher
in the world to get access to our data. So when I think about what keeps me at night,
like, I want to empower this revolution. It’s so — like it is so exciting right now. Like
it’s the most exciting time in science. And I just — like, we’re on the cusp. We’re
just slowly getting there. And I want to see it happen faster because I’m impatient. Eric Green:
So — [applause] Anne Wojcicki:
Thanks. [laughs] Eric Green:
So I would say, in case anybody’s interested, what would keep me up at night — actually
in some ways is exactly what you were just saying but brings a different dimension. Is
that — this incredible, enthusiastic opportunity — but also knowing that not only we have
to do a lot of things right to make this happen, here in the U.S. in particular. We also have
to convince the next generation that being part of this revolution, at many different
levels whether it’s as a health care professional, as a researcher, whether it’s a data science
expert, we need them to come into this and embrace this as part of their professional
career. And I’m just — what I lose sleep about is then seeing them being discouraged
because of a decaying support for biomedical research in the United States, and seeing
other opportunities that seem much more exciting to them. I really worry about the workforce and the
next generation, because I think without the — well, some of us on this panel aren’t
as young as you, and the next generation are going to be needed to really see us through
some of the things we talked about today. Anne Wojcicki:
Yeah. Eric Green:
So we need to change the course and make sure they get enthusiastic. And some of your infectious
enthusiasm needs to be part of what they bring into their profession, so. So we will — please thank Anne and Rick for
a wonderful conversation. [applause] Eric Green:
And thank the audience for some terrific questions. Please — you get a 15 minute break now. Do
not wander far because the next panel’s going to be just as good as this one. I promise.
Thank you very much. [end of transcript]


11 thoughts on “The Future of Genomic Medicine – Anne Wojcicki, Richard Lifton and Eric Green”

  • On St Elsewhere and Chicago Hope tackle this subject of monetary system trumps medical considerations. Those programs were 20 sum years ago! Nothing has changed.

  • Let us get the FDA out of most health care such as companies that help with DNA.
    In the case of 23andME FDA overstepped their authority,

  • The panel have not talked about the side-effects of pharmicuticals on the genes. Also,The is a great site that can combine genomics and medical records, A person can download different DNA results from say and 23andME.

  • This is so dumb, why don't they release medical info for internationals. That way it would be easy to set up an outside service that you send your dna to and have them collect the data and send it to you ………….

  • The cost of sequencing a person's genome is now $1000 and dropping fast. 23andMe's less comprehensive service is $100. In 5 or 10 years, genome sequencing will surely be standard medical procedure.

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