Pathology Grand Rounds, April 30, 2026: Eric Green, MD, PhD

Transcript

• 00:01Welcome to,
• 00:02Grand Rounds for the Department
• 00:03of Pathology.
• 00:04Today, we have a very
• 00:06unusual speaker,
• 00:07and then it's it's nearly
• 00:08a childhood friend of mine,
• 00:10but not exactly. We didn't
• 00:11meet until college, And then
• 00:13we helped each other get
• 00:14to where we are now.
• 00:16And he was,
• 00:18in the undergraduate program with
• 00:19me at University of Wisconsin,
• 00:21and we had probably eighty
• 00:23percent of our classes were
• 00:24the same. And then and,
• 00:26then he went off to
• 00:27do an MD PhD at
• 00:28WashU when I went off
• 00:29to Johns Hopkins. And we
• 00:31kinda kept in touch a
• 00:32little bit, and then he
• 00:33did, MD after his MD,
• 00:35he did laboratory medicine only,
• 00:37didn't do and I did
• 00:38AP only. So we're kinda
• 00:40little contradicting in that way
• 00:41as well. Yin and yang.
• 00:43Yeah.
• 00:44And then,
• 00:45after that, he became faculty
• 00:47at WashU for a couple
• 00:48years, and then he moved
• 00:49to the NIH, and that's
• 00:50the story he's gonna tell
• 00:51you about today along with,
• 00:54the whole world of genomics,
• 00:55which Eric is a main
• 00:56lead major leader in. So
• 00:58without further ado, we'll bring
• 01:00Eric up to tell you
• 01:00the story.
• 01:06Well, thanks, Dave. It's a
• 01:08pleasure to be here. I,
• 01:10I'm I'm I'm always delighted
• 01:12to see Dave. We we
• 01:13we catch up with each
• 01:13other every handful of years,
• 01:16and,
• 01:17like you said, we started
• 01:18to know each other a
• 01:19lot by sharing a lot
• 01:20of classes and having a
• 01:21similar professional journey.
• 01:23And, it's always great to
• 01:25see him, but it's also
• 01:26always, this is, I think,
• 01:27my second or third time,
• 01:29coming to to Yale. Actually,
• 01:31I couldn't I didn't remember
• 01:32exactly the year, and I
• 01:33didn't have chance to look
• 01:34it up. But the last
• 01:35time I was here was
• 01:36also for for pathology lecture.
• 01:37I gave the Don King
• 01:39lecture, and I think it
• 01:40was maybe about ten years
• 01:41ago or twelve years ago,
• 01:42something like that.
• 01:43But, it is going to
• 01:45be an unusual talk. This
• 01:46is probably I guarantee you
• 01:47it's not a traditional,
• 01:49grand rounds.
• 01:51But I am here to
• 01:52really tell you about,
• 01:54a story, a journey, if
• 01:55you will,
• 01:56about genomics.
• 01:58One that you'll see has,
• 02:00elements that are scientific, some
• 02:02are medical, some are societal.
• 02:04It's also completely intertwined with
• 02:06my, my professional life.
• 02:08And so I will anecdotally
• 02:10explain to you how I've
• 02:11been woven into this, for
• 02:13now, multiple decades.
• 02:15The other thing I really
• 02:16enjoy,
• 02:17really enjoy about talks like
• 02:18this, and I'm looking out
• 02:19of the audience,
• 02:20is that it's really fun
• 02:22to tell the story I'm
• 02:23about to tell you to
• 02:24heterogeneous audiences. And in particularly
• 02:26heterogeneous with respect to age,
• 02:28And I'm not gonna call
• 02:29anyone out, but I always
• 02:30like when I can give
• 02:32talks that include people that
• 02:33are like Dave's and my
• 02:34age, and then people that
• 02:36are somewhat younger. And then
• 02:37in particular, when I see
• 02:39young trainees here as well.
• 02:40Because for some of us,
• 02:42it's gonna be a walk
• 02:43down memory lane, and for
• 02:45others of you, it's gonna
• 02:46be a history lesson. And
• 02:48so it is a challenge
• 02:49to prepare a talk like
• 02:50this because it means you
• 02:52really have to have
• 02:53pieces of your story
• 02:55that are interesting,
• 02:57to all members of the
• 02:58audience.
• 02:59And, so some people
• 03:01have told me that my
• 03:03talks tend to remind them
• 03:05of, Pixar movies where you
• 03:07have to have something for
• 03:09everybody. Otherwise, the parents don't
• 03:10really wanna watch it and
• 03:11the kids love it. You
• 03:11have to have something that
• 03:12entertains everybody. And so it
• 03:14really is true. And I
• 03:15my talk will follow some
• 03:17very prominent Pixar movies such
• 03:19as Genome Story,
• 03:20Finding Genome, and my personal
• 03:22favorite, genomes dot inc. So
• 03:24hopefully, I will live up
• 03:26to this by the end
• 03:27and hopefully,
• 03:28you will agree that there's
• 03:29a little bit of something
• 03:30for everybody.
• 03:31The other reason it's getting
• 03:33even more fun now for
• 03:34me to tell stories the
• 03:35way I'm gonna tell the
• 03:36story is
• 03:38because I've been able to
• 03:40exist, not totally by choice,
• 03:43but mostly by choice,
• 03:44in really three different and
• 03:46major major parts of the
• 03:48biomedical ecosystem.
• 03:50So as you heard,
• 03:51after being an undergraduate with
• 03:53Dave University of Wisconsin, I
• 03:54went into the MD PhD
• 03:55program at Washington University.
• 03:57In nineteen eighty seven, I
• 03:58graduated. That's my graduation picture.
• 04:00But that's about the halfway
• 04:02point of my thirteen years
• 04:03there. I then trained in
• 04:04pathology.
• 04:05By the way, we will
• 04:06come back to the year
• 04:07nineteen eighty seven in a
• 04:08minute. But but when I
• 04:10graduated
• 04:11there and I chose to
• 04:12stay there in part, because
• 04:13my wife was a medical
• 04:14student then,
• 04:15I,
• 04:16therefore
• 04:18trained in pathology, which or
• 04:19lab medicine, which gave me
• 04:20a chance to go back
• 04:21to the lab. That was
• 04:22at a critical juncture because
• 04:24it was right and especially
• 04:25at WashU because this new
• 04:26thing called genomics was pretty
• 04:28hot at WashU back then,
• 04:30and that's how I jumped
• 04:31into genomics as for the
• 04:32very first time as a
• 04:33postdoctoral
• 04:35fellow.
• 04:35And then I was fortunate
• 04:36enough to be get involved
• 04:37in the Human Genome Project
• 04:38literally on day one. And
• 04:40even as an assistant professor
• 04:41for two years, I was
• 04:42working on the Human Genome
• 04:43Project. But then an opportunity
• 04:45came when Francis Collins,
• 04:47recruited me to the National
• 04:49Institutes of Health, specifically to
• 04:51the Genome Institute, now called
• 04:52the National Human Genome Research
• 04:54Institute. That was the institute
• 04:56that was created by the
• 04:57US Congress to lead the
• 04:58US's effort in the Human
• 05:00Genome Project. And I and
• 05:02and and Francis became the
• 05:03second director after Jim Watson,
• 05:05and then he recruited me
• 05:06there as a junior investigator.
• 05:08And then over my thirty
• 05:09one years there, I accumulated
• 05:11various leadership positions. And then
• 05:13eventually, when Francis became the
• 05:15NIH director, I can I
• 05:17applied to become the Genome
• 05:18Institute director, which I got?
• 05:20And then for my last
• 05:21fifteen years
• 05:23at NHGRI, I was the
• 05:24institute director. Last time, I
• 05:25think, I was here, I
• 05:26was already the NHGRI director.
• 05:29I retired from federal service
• 05:31about thirteen months ago.
• 05:33It wasn't totally by choice.
• 05:35I won't go there. But
• 05:36let's just say I was
• 05:37retirement eligible, and so I
• 05:39retired from federal service with
• 05:41zero intention of retiring.
• 05:44And, and after looking and
• 05:46exploring options for this next
• 05:48stage of my career, I
• 05:49was very fortunate
• 05:50that,
• 05:51eighty seven days ago, and
• 05:53when I was still counting
• 05:54days, I went into the
• 05:55private sector. So I started
• 05:56in academia,
• 05:58then the public sector and
• 05:59the government, and now I'm
• 06:00in the private sector where
• 06:01I am the chief medical
• 06:02officer for a company that
• 06:03probably many of you have
• 06:04heard of called Illumina.
• 06:05And I'm in by eighty
• 06:07seventh day. So you can
• 06:08see there's an imbalance of
• 06:09time across these three domains,
• 06:11but I've learned a lot
• 06:12of my first eighty but
• 06:13I bring a perspective
• 06:14of someone who's lived in
• 06:15three places, although only eighty
• 06:17seven days in the private
• 06:18sector.
• 06:19One of the things that's
• 06:20really cool though about being
• 06:22at Illumina,
• 06:23because especially in my thirty
• 06:24one years in the federal
• 06:25government is when you're in
• 06:27the federal government, especially when
• 06:29you're in a leadership position,
• 06:30you are overwhelmingly
• 06:31boring because of ethics rules
• 06:33that don't allow you to
• 06:34do anything worth disclosing. But
• 06:36now at Illumina, I get
• 06:37to actually use a disclosure
• 06:39slide, which I've never been
• 06:40able to do except for
• 06:41eighty seven days ago. So
• 06:42I have to disclose this,
• 06:44and I'm so excited that
• 06:45I get to add a
• 06:46slide to my slide deck.
• 06:47So that's been one of
• 06:48the fun learning experiences.
• 06:51So I bring to this
• 06:52storytelling
• 06:53talk,
• 06:54basically, a very broad perspective
• 06:56of someone who got involved
• 06:58in genomics at its inception.
• 06:59But I actually wanna take
• 07:00a step back and set
• 07:01a broader context for you.
• 07:03I'm gonna make the claim
• 07:04that it's so fun to
• 07:05talk to a group of
• 07:06pathologists because you're so much
• 07:07in the crosshairs of this
• 07:09revolution or this transition or
• 07:10this transformation, whatever word you
• 07:12wanna use. I'm gonna contend
• 07:14that there are two interrelated
• 07:15scientific fields,
• 07:16both launched last century, that
• 07:18I think are changing medicine
• 07:19this century.
• 07:20The first of which is
• 07:22this field of genetics,
• 07:23by the way, which didn't
• 07:25exist as a word until
• 07:26nineteen o seven, wasn't appearing
• 07:28the word never appeared in
• 07:29the scientific press until this
• 07:31publication
• 07:32in nineteen o seven. And
• 07:33of course, genetics is the
• 07:34study of inheritance.
• 07:36And the word was invented
• 07:38before we even know what
• 07:39the information of inher molecule
• 07:41of inheritance was, of course,
• 07:42DNA, but they knew there
• 07:44was things that were transmitted
• 07:46through
• 07:47the inheritance process.
• 07:49Well, things happened after nineteen
• 07:51o seven, eventually figured out
• 07:52that not we. I wasn't
• 07:53alive. Others figured out that
• 07:55DNA was the molecule of
• 07:56heredity. A lot of attention
• 07:58went to DNA, and at
• 07:59halftime of last century came
• 08:01that famous discovery,
• 08:03of the double helical structure
• 08:04of DNA,
• 08:06which gave a key insight
• 08:08about how it was that
• 08:09DNA was the information molecule.
• 08:10And then a lot happened
• 08:12between the fifties and the
• 08:13sixties and the seventies and
• 08:15the eighties that then led
• 08:17to the coining of a
• 08:18new word, genomics, genome being
• 08:21all the DNA of an
• 08:22organism, and the launching of
• 08:23a new field of genomics,
• 08:25which happened in nineteen eighty
• 08:27seven. And I told you,
• 08:28that was the year I
• 08:29graduated
• 08:30medical school and graduate school,
• 08:32which means never once as
• 08:33an MD PhD student did
• 08:34I hear the word genomics
• 08:35because it didn't exist until
• 08:36eighty seven.
• 08:38And, of course, all of
• 08:39this was being discussed because
• 08:41of this idea that the
• 08:42tools for studying DNA were
• 08:44getting so so good. And
• 08:46that's really what made this
• 08:47progression happen was technological innovation
• 08:50be between when we discovered
• 08:52the double helical structure of
• 08:53DNA that led to the
• 08:55recognition that we needed a
• 08:56whole new discipline or at
• 08:57least the name of a
• 08:58discipline. And that progression
• 09:00really does reflect technical innovation.
• 09:02And it was a series
• 09:03of important discoveries
• 09:05such as going from our,
• 09:08a complete lack of understanding
• 09:09of how it was that
• 09:10the four letters of DNA
• 09:11could encode biological information, actually
• 09:13figuring out the genetic code,
• 09:15which took place in the
• 09:16nineteen sixties.
• 09:17Of course, then by the
• 09:18nineteen seventies, when Dave and
• 09:20I graduated high school, roughly
• 09:21that time, was when the
• 09:23first methods for sequencing DNA,
• 09:24reading out the g's, a's,
• 09:25t's, and c's were invented.
• 09:27But then, of course, the
• 09:28latter seventies and and into
• 09:30the eighties with the molecular
• 09:32biology revolution brought all the
• 09:34tools of molecular biology for
• 09:35cloning DNA, manipulating DNA, doing
• 09:37recombinant DNA, eventually inventing PCR
• 09:40for amplifying DNA and so
• 09:42forth.
• 09:43This created an increasingly powerful
• 09:46tool belt for those who
• 09:47are interested in studying DNA.
• 09:49And what that led to
• 09:51was the idea of could
• 09:52we, should we, might we
• 09:54be able to start to
• 09:55think comprehensively
• 09:57about organisms' DNA,
• 09:59all of their genome.
• 10:01So that led to a
• 10:02drumbeat of discussions
• 10:03that ended up leading to
• 10:05the human genome project. So,
• 10:07you know, the first as
• 10:08possible real serious discussion
• 10:11came about in a very
• 10:12famous meeting that took place
• 10:13in nineteen eighty four. It
• 10:14was called the Alta Summit
• 10:16where a group of scientists
• 10:17got together and for the
• 10:18very first time said, what
• 10:19might that look like if
• 10:20we were actually gonna map
• 10:21and sequence the human genome
• 10:23and maybe some other genomes?
• 10:26Then oops. Then nineteen eighty
• 10:28six,
• 10:28a prominent,
• 10:30cancer biologist, Renato Del Beco,
• 10:32wrote a very pivotal,
• 10:34editorial perspective
• 10:36where he talked about the
• 10:37fact that if we were
• 10:38ever gonna truly understand cancer,
• 10:40we needed to sequence the
• 10:41human genome.
• 10:42It was that kind of
• 10:43discussion and drum increasing drum
• 10:46beats that led to nineteen
• 10:47eighty seven, the launching of
• 10:48the field, the coining of
• 10:49the word, the first journal
• 10:50called Genomics.
• 10:52And then scientists got really
• 10:53serious because then they said,
• 10:55we really do think we
• 10:56wanna operationalize this. There were
• 10:58then two important
• 11:00studies
• 11:01that were conducted. One under
• 11:02the auspices of the National
• 11:04Research Council, one under the
• 11:05offices the auspices of the
• 11:07office of science and technology
• 11:09policy in the White House,
• 11:10both of which brought scientists
• 11:11together and fleshed out the
• 11:13idea of how we would
• 11:14go about mapping and sequencing
• 11:16the human genome, launching a
• 11:17big project like the Human
• 11:18Genome Project and so forth.
• 11:20Of course, that required funders
• 11:22around the world committing to
• 11:24actually having the money to
• 11:25actually do this and then
• 11:26organize it in some way.
• 11:28In the United States, the
• 11:29instrumental hearing took place in
• 11:31the senate
• 11:32at at a particular hearing
• 11:34that took place in nineteen
• 11:35eighty nine,
• 11:36presided, including senators like senator
• 11:39Al Gore and senator Ted
• 11:41Kennedy, who are big proponents
• 11:43of genomics and the Human
• 11:44Genome Project. And they then
• 11:46authorized that the Human Genome
• 11:48Project begin, created an entity
• 11:50at NIH to do it,
• 11:51and most importantly, wrote a
• 11:53check to get the Human
• 11:54Genome Project off the ground
• 11:56in the subsequent year. Other
• 11:57funders came in from other
• 11:58countries and particularly the UK,
• 12:00and therefore, it was all
• 12:02teed up to start the
• 12:03Human Genome Project.
• 12:05I think that nineteen oh,
• 12:07you can't quite see it,
• 12:07but you'll see it in
• 12:08a second. Nineteen eighty nine,
• 12:10it'll always be regarded as
• 12:11a pivotal year where sort
• 12:13of the world just seemed
• 12:14to change in nineteen eighty
• 12:15nine as everything was was
• 12:17moving towards these incredible things.
• 12:19So so I will make
• 12:21the strong argument that the
• 12:23world changed in eighty nine.
• 12:25You know, first of all,
• 12:26we should appreciate that eighty
• 12:27nine is when Taylor Swift
• 12:28was born. Okay? So, you
• 12:29know, you could say whatever
• 12:30you want, but the world
• 12:31has never been the same
• 12:32after that. So appreciate it.
• 12:34But I also think that
• 12:35we will look back, especially
• 12:37as physicians and scientists and
• 12:38biologists, as eighty nine being
• 12:40in a pivotal year because
• 12:42eighty nine was when the
• 12:43Human Genome Project was about
• 12:44to be born. And so
• 12:46there you are, eighty nine,
• 12:47gonna be blazoned into the
• 12:49history books for two very
• 12:50important reasons.
• 12:52But that, of course, led
• 12:53to the launching of the
• 12:54human genome project in nineteen
• 12:55ninety.
• 12:57It was really as its
• 12:58signature goal was about reading
• 13:00the human blueprint, other genomes
• 13:01were sweet sequenced smaller organisms,
• 13:03smaller genomes.
• 13:04But the signature goal was
• 13:06to read out for the
• 13:07very first time the three
• 13:08billion letters that represents one
• 13:10copy of the human genome.
• 13:12And this will forever be
• 13:14regarded as biology's
• 13:16most ambitious or at least
• 13:17its very first incredibly ambitious,
• 13:20endeavor. Now for those who
• 13:21don't, especially the younger folks,
• 13:23don't appreciate, the Human Genome
• 13:25Project was very unusual.
• 13:27It was it was not
• 13:29typical for biologists to do
• 13:30big organized projects involving thousands
• 13:32of scientists, multiple countries. It
• 13:34was not typical to have
• 13:36it be highly managed.
• 13:38It had a lot of,
• 13:40individuals in the scientific community
• 13:42who were against it, who
• 13:43didn't believe it was a
• 13:44good idea. And so there
• 13:45was just not a simp
• 13:47a single aspect of the
• 13:47Human Genome Project that was
• 13:49conventional.
• 13:50But despite headwinds, lots of
• 13:51concerns about whether it'd be
• 13:53successful, etcetera, etcetera, at the
• 13:55end of the day, thirteen
• 13:56years later, the Human Genome
• 13:57Project was completed and by
• 13:59any criteria was regarded as
• 14:01a successful endeavor.
• 14:03And so what happened, literally
• 14:05now, I think we're getting
• 14:07yeah. It's like twenty six
• 14:08years ago.
• 14:09And in fact, we're just
• 14:10over twenty six years ago.
• 14:11I'm gonna be sorry. Twenty
• 14:12three years ago, almost exactly
• 14:14the Genome Project was declared
• 14:15completed. There were some incredibly
• 14:17good parties and celebrations that
• 14:19that took place around that
• 14:20time. And it's important to
• 14:23recognize that what the Genome
• 14:24Project delivered to humanity
• 14:27was the order of the
• 14:28roughly three billion letters in
• 14:29the human genome.
• 14:31Of course, that just gave
• 14:32us the ordered letters. It
• 14:34didn't give us an interpretation.
• 14:35We knew that was gonna
• 14:36follow, but at least it
• 14:37gave us a framework that
• 14:39everything could then be built
• 14:40on. And so one important
• 14:42thing to appreciate about where
• 14:43we were twenty three years
• 14:44ago is that we had
• 14:46just crossed the initial finish
• 14:48line in the journey of
• 14:49human genomics, and that will
• 14:51forever be a historic,
• 14:53of of historic significance.
• 14:55However,
• 14:56as all of you can
• 14:56appreciate,
• 14:57that's just when everything began
• 14:59because that finish line immediately
• 15:00became a starting line. It's
• 15:02this classic example that you
• 15:03finish one thing and you
• 15:04immediately are gonna start another.
• 15:06And so a lot happened
• 15:08when the Genome Project ended.
• 15:09The different funders had different
• 15:11reasons for being there. For
• 15:12example, the other major funder
• 15:13in the United States was
• 15:15the Department of Energy. They
• 15:16had a whole other reason
• 15:17for wanting to sequence the
• 15:18human genome. They went off
• 15:20in a different direction. But
• 15:21and but and various other
• 15:22funders around the world, they
• 15:24did different things in genomics
• 15:25subsequently. But back at the
• 15:26National Institutes of Health, as
• 15:28you might imagine, the focus
• 15:30was gonna be on human
• 15:31health, and that's why the
• 15:32NIH played such a major
• 15:33role in the Human Genome
• 15:34Project.
• 15:36And the reason this became
• 15:37so important went back to
• 15:39one of the premises
• 15:40that was stated in any
• 15:41of the things written about
• 15:42that led up to the
• 15:43Human Genome Project, and that
• 15:45and which I think was
• 15:45a very compelling argument, including
• 15:47to the senators who ultimately
• 15:49approved this, was that we
• 15:50can go in and say
• 15:51that virtually everything that Dave
• 15:53and I were taught in
• 15:54medical school was based on
• 15:56the average patient. But no
• 15:58patient is average. Every patient
• 15:59is unique. They bring with
• 16:00them their unique physical and
• 16:02social
• 16:03environments. They also bring a
• 16:04unique blueprint because every two
• 16:06people are different unless they're
• 16:07twins, identical twins. But bottom
• 16:09line is no patient is
• 16:11average. Every patient is unique,
• 16:13and yet we are blind
• 16:14to the uniqueness in their
• 16:16DNA, but we don't have
• 16:17to be if we could
• 16:18have the ability to query
• 16:20people's DNA and use information
• 16:21about their differences
• 16:23in order to improve the
• 16:24practice of medicine.
• 16:26So there we were at
• 16:27a new starting line, and
• 16:28it was pretty obvious what
• 16:29was gonna happen. We were
• 16:30gonna use genomics in medicine.
• 16:32So none of us were
• 16:33surprised that either the popular
• 16:35press or the scientific press
• 16:37juxtaposed the two words. Of
• 16:38course, they're gonna juxtapose the
• 16:40two words. They're gonna put
• 16:41the words together and come
• 16:42up with a phrase like
• 16:42genomic medicine.
• 16:44There was only one problem
• 16:45with twenty three years ago,
• 16:46is that we could spell
• 16:47genomic medicine and we could
• 16:48juxtapose the words, but it
• 16:49was a very blurry concept.
• 16:51We really had no idea
• 16:52what that was gonna look
• 16:53like nor how we were
• 16:54gonna actually get there.
• 16:56Now we appreciated what it
• 16:58might involve in terms of
• 17:00from a definitional point of
• 17:01view, and it was basically
• 17:03get genomic information about patients
• 17:05and use that information in
• 17:06some way to either prevent
• 17:08disease or to diagnose disease
• 17:09or maybe even perhaps even
• 17:11to help treat disease.
• 17:12So that was where we
• 17:14were heading,
• 17:15and we now had to
• 17:17pivot. So twenty three years
• 17:18ago, the Genome Institute and
• 17:20much of the field of
• 17:21human genomics pivoted. They didn't
• 17:23abandon. They just pivoted to
• 17:25include a larger
• 17:27next journey
• 17:28that had a new starting
• 17:29line of the human genome
• 17:30project and had as its
• 17:31finish line,
• 17:32even more audacious,
• 17:34goal that is realizing genomic
• 17:36medicine.
• 17:37And just like the Genome
• 17:38Project, it was gonna be
• 17:39a long journey. And just
• 17:41like the Genome Project, we
• 17:42didn't know what all the
• 17:42steps were gonna be, but
• 17:43we knew what some of
• 17:44the steps were gonna be.
• 17:45And just like the Human
• 17:47Genome Project, it was not
• 17:48gonna be completed by one
• 17:50scientist, one institution, one funder,
• 17:52one country, one discipline, and
• 17:53it was not gonna be
• 17:54a sprint. It was gonna
• 17:55be a marathon.
• 17:57Lots of different disciplines coming
• 17:58together, running shoulder to shoulder
• 18:00for a very long time
• 18:01and just figuring out what
• 18:02were the steps that were
• 18:03gonna be needed, what were
• 18:04the obstacles, knock them down,
• 18:06and keep inching your way
• 18:07closer and closer to get
• 18:08into the realization of genomic
• 18:10medicine.
• 18:11So how do you do
• 18:12that? Well, I was fortunate
• 18:14enough to have a front
• 18:15row seat. I was, at
• 18:15that point, already in a
• 18:16leadership position
• 18:18at NHGRI.
• 18:20And I was the director
• 18:21of the intramural program when
• 18:22the Genome Project ended two
• 18:24thousand three. Now the Genome
• 18:26Institute,
• 18:26just as a representative example
• 18:28of what had to happen,
• 18:29they had to pivot, and
• 18:30they had to develop a
• 18:31vision to how to get
• 18:32us to genomic medicine.
• 18:34Well, the way we did
• 18:35it, I can tell you,
• 18:36is that we took sort
• 18:37of, a routine that we
• 18:39had developed during the Genome
• 18:40Project of gathering the scientific
• 18:42community together and updating the
• 18:44idea of how you're gonna
• 18:45accomplish the goals in front
• 18:46of you. We're shown here
• 18:47sort of three classic documents
• 18:49that were published at at
• 18:51different stages of the Human
• 18:52Genome Project
• 18:53that that that basically iterated
• 18:55and then reiterated how to
• 18:56complete the Human Genome Project.
• 18:58And so the day the
• 18:59Human Genome Project ended, NHGRI
• 19:01had finished a two year
• 19:02strategic planning process that laid
• 19:04out a new blueprint for
• 19:05what needed to happen in
• 19:06genomics. And then eight years
• 19:08later, it was time to
• 19:09publish a new one. And
• 19:10and and, and then shortly
• 19:12nine years later, it was
• 19:13in during the pandemic,
• 19:15we published the most recent
• 19:16one, which the institute is
• 19:17still going on. These basically
• 19:19became road maps or blueprints,
• 19:21whatever metaphor you wanna use,
• 19:22not only for the institute,
• 19:24but more broadly for the
• 19:25community of what were the
• 19:26steps that we're gonna need
• 19:27in order to get us
• 19:28towards,
• 19:29improving the practice of medicine
• 19:31through genomics.
• 19:32And so twenty three years
• 19:34of progress have been basically,
• 19:36represented by these three strategic
• 19:38visions, and I don't have
• 19:39time to go through all
• 19:41twenty three years nor do
• 19:42I have time to go
• 19:42through all of them. Knowing
• 19:44I was given a clinical
• 19:45grand rounds, I thought I
• 19:47would would just briefly summarize
• 19:49the more proximal steps so
• 19:51that I could emphasize the
• 19:52more clinical ones. And it
• 19:53but it's not to say
• 19:54that the more proximal basic
• 19:55science and translational science is
• 19:56not important. It's just I
• 19:58was just trying to figure
• 19:58out how to best allocate
• 19:59the time to an audience
• 20:00like this. So what are
• 20:02the more proximal accomplishments? What
• 20:04was the very first step
• 20:06that needed to be accomplished?
• 20:07Well, the first step is
• 20:08probably the most remarkable.
• 20:10The fact is when we
• 20:11sequenced the human genome for
• 20:13the very first time and
• 20:14finished it twenty three years
• 20:15ago, it was successful, but
• 20:17it was expensive. Cost about
• 20:18a billion dollars to sequence
• 20:20that first human genome.
• 20:21Well, I was trained as
• 20:23a laboratory medicine physician, and
• 20:24I knew that a billion
• 20:25dollars was too high of
• 20:26a price tag for a
• 20:27clinical test. And I knew
• 20:29that we needed to lop
• 20:30off a lot of zeros
• 20:31to get it down to
• 20:32something that seemed reasonable, and
• 20:33the figure we came up
• 20:34with was a thousand. So
• 20:36it was in in two
• 20:37thousand three where the genome
• 20:38institute said, we need to
• 20:39figure out how we're gonna
• 20:40sequence a human genome for
• 20:41less than a thousand dollars,
• 20:43and the rest is history.
• 20:44We've now reduced the cost
• 20:45of sequencing a human genome
• 20:46by more than a million
• 20:47fold. It is less than
• 20:48a thousand dollars. Companies like
• 20:50Illumina, where I now work,
• 20:51were involved with this, but
• 20:52the Genome Institute was instrumental
• 20:54in putting out grants that
• 20:55helped get us there. Other
• 20:56companies have bought been involved
• 20:58incredibly
• 20:59successful.
• 21:00The fact that in twenty
• 21:01three years, we were able
• 21:02to reduce the cost of
• 21:03saying to make it now
• 21:03a diagnostic test.
• 21:06That has allowed us to
• 21:06go out and not just
• 21:07be happy with one human
• 21:09genome sequence. Now we have
• 21:10millions. In fact, we don't
• 21:11even know how many millions
• 21:12we have because there's publicly
• 21:13available data, and then there's
• 21:15lots of private data out
• 21:16there, that that we don't
• 21:17even know about at at
• 21:19companies and so forth in
• 21:20other countries.
• 21:21And that has given us
• 21:22a lot of information about
• 21:23how we differ. We now
• 21:25have a very precise estimate.
• 21:26We now know that we
• 21:27are, you know, ninety
• 21:29nine point four percent identical
• 21:32between any two people. And
• 21:33that sounds incredibly identical, which
• 21:35it is, but it also
• 21:36means that there's about three
• 21:37to five million
• 21:39spelling differences between any two
• 21:40of our genomes. And and
• 21:42buried within those three to
• 21:43five million different differences in
• 21:45our spelling are some variants
• 21:47that are biologically important, some
• 21:49that are biologically irrelevant, and
• 21:51then a subset of the
• 21:52biologically important ones that are
• 21:53clinically important. And we need
• 21:55to figure out what all
• 21:56that means, and we have
• 21:57incredibly deep catalogs all now
• 21:59publicly available about all the
• 22:01places in the human genome
• 22:02where we know so far
• 22:03people vary what those variants
• 22:05are, and the grand challenge
• 22:07is to figure out which
• 22:08of those variants are biologically
• 22:09and medically important.
• 22:11In order to do that,
• 22:12you need to know how
• 22:13a variant changes genome function.
• 22:15In order to know that,
• 22:16you need to know how
• 22:17the genome works. Well, where
• 22:18are we? Well, we have
• 22:20profoundly advanced in twenty three
• 22:22years of studying those three
• 22:23billion letters
• 22:24of understanding of how the
• 22:26genome works. We know a
• 22:27lot about our twenty thousand
• 22:28genes, roughly twenty thousand. Although
• 22:31we still don't know what
• 22:32the vast majority of those
• 22:33genes actually do. We now
• 22:35know there's an incredible complexity
• 22:37out in the noncoding parts
• 22:38of the human genome that
• 22:39choreograph how all these genes
• 22:41work. We know a lot
• 22:42about that, but we still
• 22:43have a long way to
• 22:44go. In the twenty three
• 22:45years, we've learned that RNA
• 22:47is really complicated. Lots of
• 22:49different kinds of RNAs are
• 22:50doing lots of things that
• 22:51we had never any idea
• 22:52they were actually doing.
• 22:53So the there's good news
• 22:55and bad news. The good
• 22:55news is that we've come
• 22:57a long way in twenty
• 22:57three years. The bad news
• 22:59is we have a still
• 22:59a long way to go.
• 23:00And I often will say
• 23:02that my I'd skip over
• 23:03my children and grandchildren and
• 23:05great grandchildren. You'll all still
• 23:06be interpreting the three billion
• 23:08letters. This is a multigenerational
• 23:10challenge,
• 23:10but we have all the
• 23:11tools in front of us.
• 23:12Technologies are coming on board.
• 23:14We'll get better all the
• 23:14time. And we have a
• 23:16we've learned a lot about
• 23:17genomic variation, genome function, and,
• 23:20of course, what did that
• 23:21lead us to? Well, as
• 23:22as as people interested in
• 23:23human biology, human health and
• 23:25disease, it has significantly
• 23:27advanced our ability to understand
• 23:28the genomic basis of human
• 23:30disease.
• 23:31This has come about most
• 23:32fruitfully with rare genetic diseases,
• 23:34which I'm gonna tell you
• 23:35a little bit more about,
• 23:36but increasingly we're learning about
• 23:38the complexity of more common
• 23:39diseases and where multiple genomic
• 23:42variants are involved, greater contribution
• 23:44of the physical and social
• 23:44environment are involved, and so
• 23:46forth. But significant
• 23:48work has been accomplished.
• 23:50Lots more work has to
• 23:51be done to fully gain
• 23:52gain a a full understanding
• 23:54of the genomic basis of
• 23:55human disease. But But still,
• 23:56we're on a good glide
• 23:57path, and better technologies will
• 23:59improve it all the time.
• 24:00What I really wanted to
• 24:02emphasize, though, which is where
• 24:03I'm gonna pivot now to,
• 24:05is the fact that, you
• 24:06know, even if you go
• 24:07back sixteen years ago or
• 24:09something when I first became
• 24:10the NHGRI director,
• 24:11we really didn't have examples
• 24:13of genomic medicine that were
• 24:15truly being implemented at any
• 24:16sort of scale, and that
• 24:18just is not true anymore.
• 24:20It really has we've really
• 24:21seen
• 24:22some vivid examples emerge that
• 24:24I think is really, really
• 24:26exciting and I think has
• 24:27injected a lot of optimism
• 24:28about what still is left
• 24:29to come. How has this
• 24:30come about? Well, it's come
• 24:31about because of all things
• 24:32I sort of mentioned. We
• 24:34can now sequence a patient's
• 24:35genome for less than a
• 24:36thousand dollars. We can compare
• 24:37it to a reference sequence.
• 24:38We can make a big
• 24:39list of all the genomic
• 24:41variants that person has, got
• 24:42put out a DNA report,
• 24:44and off we go to
• 24:44practice genomic medicine.
• 24:46Now I know there's clinicians
• 24:48and others in the audience
• 24:49that know that this is
• 24:50an oversimplification.
• 24:51I will admit that. I'll
• 24:52come back to the slide
• 24:53later. But
• 24:55sometimes this works. It does
• 24:56and and and the sometimes
• 24:58is enough times to make
• 25:00it really impressive of predicting
• 25:01where we're gonna be as
• 25:02we get better and better
• 25:03at this. But even this
• 25:05cursory simple scheme
• 25:07has allowed us to move
• 25:08forward and come up with
• 25:09what I think are at
• 25:10least five areas where genomic
• 25:12medicine is here and now.
• 25:14And so this is sort
• 25:15of my examples,
• 25:16and I'm only I'm gonna
• 25:17dig a little deeper to
• 25:18some of them than others
• 25:19because I don't have time
• 25:20to dig in all of
• 25:20them, but so I cherry
• 25:21picked. The first of which
• 25:23is I'm just gonna give
• 25:24a shout out to Del
• 25:25Becco and just say he
• 25:27was right. He was absolutely
• 25:28right. I am looking at
• 25:29the well, I know in
• 25:30the audience are people that
• 25:31are far smarter than me
• 25:32in cancer genomics, so I
• 25:34won't even talk anymore about
• 25:35cancer genomics except to say
• 25:37that
• 25:38I believe that in the
• 25:39long run, the greatest area
• 25:41of impact
• 25:42across all of medicine
• 25:44in the long run with
• 25:45respect to genomics is gonna
• 25:47be in the cancer realm.
• 25:47Cancer is a disease of
• 25:48the genome. I think by
• 25:49the time we figure this
• 25:50all out, we're gonna have
• 25:52incredible stories to tell. We
• 25:53already have some pretty incredible
• 25:54stories. I would contend, in
• 25:55the last twenty three years,
• 25:57a lot of aspects of
• 25:58clinic of cancer research, oncology
• 26:00practice has been greatly influenced
• 26:02by genomics,
• 26:03and and and therefore is
• 26:04why I conclude DelBacco was
• 26:05simply right. I thought I'd
• 26:07go a little bit more
• 26:08into rare genetic disease diagnostics,
• 26:11because I think there there's
• 26:12something that maybe people don't
• 26:13fully appreciate, and I really
• 26:15wanna make sure you can
• 26:16see where some of the
• 26:17early successes have really come.
• 26:20In order to fully appreciate
• 26:21it, though, I wanna take
• 26:22you back in time. So
• 26:23remember, rare genetic diseases are
• 26:25diseases
• 26:26where it's almost always a
• 26:28single gene that is broken
• 26:30that leads with a high
• 26:31likelihood of leading to disease,
• 26:33you know. And but if
• 26:34I wanna take and and
• 26:35it's thought that there's something
• 26:37like ten thousand,
• 26:39rare genetic diseases.
• 26:40By the way, they're individually
• 26:42rare, but, you know, one
• 26:44out of ten of us
• 26:45in this room probably have
• 26:46a rare genetic disease. So
• 26:47I don't know what that
• 26:48number would be. There might
• 26:49you know, there may be
• 26:50ten or fifteen of us
• 26:50in this room who have
• 26:51a rare genetic disease. There's
• 26:53thirty million people in America
• 26:55with a a known,
• 26:56rare a rare disease, eighty
• 26:58percent of which are thought
• 26:59to be genetic, and that
• 27:00if you do that worldwide,
• 27:01about three hundred million people
• 27:02on this earth have a
• 27:03rare genetic disease.
• 27:05But let me take you
• 27:05back in time. The day
• 27:07the human genome project
• 27:08started in October of nineteen
• 27:11ninety,
• 27:12there were sixty one rare
• 27:13diseases
• 27:14for which we knew what
• 27:15the mutated gene was. Classic
• 27:17example was sickle cell. Cystic
• 27:19fibrosis got in by a
• 27:20year under the wire, just
• 27:21barely. But sixty one out
• 27:23of ten thousand.
• 27:24But now with cheap methods
• 27:26for sequencing DNA, understanding about
• 27:28genomic variation, increasing understanding about
• 27:31the genome function,
• 27:32and major programs to try
• 27:34to get at the remaining
• 27:36tenth of the ten thousand,
• 27:38we have made tremendous strides.
• 27:39We're over six thousand. Still
• 27:41shy of ten thousand, but
• 27:42we're over six we've gone
• 27:43from sixty one to six
• 27:45thousand. And that has just
• 27:46been unbelievably game changing for
• 27:48lots of families and game
• 27:50changing with regard to understanding
• 27:51the genomic basis of a
• 27:52lot of rare genetic diseases.
• 27:54What this means,
• 27:55it is it is now
• 27:57routine, and I'm sure it
• 27:58is taking place here in
• 27:59pediatrics department in particular where
• 28:02a patient will come in
• 28:03with something like a developmental
• 28:05delay or a cardiac abnormality.
• 28:07And, yes, they will get
• 28:08a traditional clinical workup, but
• 28:10very early on, that clinician
• 28:11suspects a genetic disease, a
• 28:13tube of blood goes off,
• 28:14they will sequence that patient's
• 28:15genome. It'll cost less than
• 28:17a thousand dollars. Maybe they'll
• 28:18even sequence both patient parents'
• 28:20genomes. They will come out
• 28:21with a report, and they
• 28:22will quite frequently come up
• 28:24with a diagnosis.
• 28:25All as quick as you
• 28:26could imagine compared to a
• 28:28long
• 28:29Odyssey that typically would be,
• 28:30seen with those many patients
• 28:32with rare genetic diseases. What's
• 28:34the frequency of it? There's
• 28:35lots of articles I could
• 28:36point you to. This just
• 28:37happens to be one that
• 28:38I will where they talk
• 28:39about how the yield, at
• 28:40least in the hands of
• 28:41the people involved in this,
• 28:42is about fifty percent.
• 28:44Just, you know, thirty to
• 28:45fifty percent.
• 28:46And and but this never
• 28:47will increase over time for
• 28:49lots of reasons,
• 28:51including the fact that the
• 28:52better we get at interpreting
• 28:53the human genome and the
• 28:54better we get at understanding
• 28:55how the variance influence genome
• 28:57function,
• 28:58we're gonna get better and
• 28:58better at this. And there's
• 28:59other reasons to believe we're
• 29:00only gonna get better and
• 29:01better at this. And what's
• 29:03really gratifying, especially for someone
• 29:04like me who's always worried
• 29:06about would this get implemented,
• 29:07would this get implemented,
• 29:09now we start to see
• 29:10review articles that talk about
• 29:12how this is the state
• 29:13of implementation across dozens and
• 29:15dozens of studies where genome
• 29:17sequencing is being used as
• 29:18a frontline diagnostic tool in
• 29:20the for working up working
• 29:22up patients with rare diseases.
• 29:24And so we are absolutely
• 29:25seeing this,
• 29:26play out over and over
• 29:27again. In fact, it's it's,
• 29:28you know, thousands and thousands
• 29:29of times every single month
• 29:31around the world. Patients with
• 29:32rare diseases are getting, diagnosed
• 29:34using genome sequencing as a
• 29:36frontline tool. There are also
• 29:38some niche areas that I
• 29:39wanted to point out. One
• 29:41is
• 29:42is in the undiagnosed diseases
• 29:43space. You you should remember
• 29:45and I actually don't know,
• 29:46Dave, if you have this
• 29:46at at at Hopkins, but
• 29:48I know we have this
• 29:49at WashU that you you
• 29:50there'd be clinics at WashU.
• 29:52They'd call them Fasanoma clinics
• 29:54back then. And these and
• 29:55they definitely had them at
• 29:56NIH for years where basically,
• 29:58when there were patients, oftentimes
• 30:00into adulthood,
• 30:02where they had gone from
• 30:03specialist to specialist to specialist,
• 30:04nobody could figure out what's
• 30:05wrong with them. They would
• 30:06bring them to what's called
• 30:07a fascinoma clinic where they'd
• 30:09have multiple disciplines come and
• 30:10take one critical last look.
• 30:12Can we figure out what's
• 30:13wrong with this person?
• 30:14Now under the leadership of
• 30:16Bill Gall, when he when
• 30:17I were both, at NHGRI,
• 30:20and he's shown in the
• 30:21center, was our clinical director
• 30:22for many years, Came up
• 30:23with this idea of undiagnosed
• 30:24diseases programs
• 30:26and just called it that
• 30:27and in particular,
• 30:28used genomics as a frontline
• 30:30tool for sort of one
• 30:31last workup of a patient,
• 30:32but now using genomics.
• 30:34And this has now taken
• 30:35off. We're at an undiagnosed
• 30:37diseases network across the United
• 30:38States, and dozens and dozens
• 30:40of countries have now implemented
• 30:42undiagnosed diseases programs. They bring
• 30:44them together, big clinical workup,
• 30:45genome sequencing,
• 30:46and this is now becoming
• 30:48sort of mainstream in a
• 30:49lot of places,
• 30:50and really has
• 30:52importantly
• 30:53given diagnoses
• 30:54to many people who for
• 30:56decades have gone on through
• 30:57life without knowing diagnosis. In
• 30:58some cases, it actually has
• 30:59changed their management. And it's
• 31:01been very important. It's also
• 31:02led to discovery of many
• 31:03new, genetic diseases.
• 31:06Another niche area is in
• 31:08the setting of acutely ill
• 31:09newborns.
• 31:10In the setting of, of
• 31:12any given NICU, neonatal intensive
• 31:14care unit, you will often
• 31:15have babies
• 31:17where you have stumped the
• 31:18neonatologist,
• 31:19and they simply have no
• 31:20idea what is going on.
• 31:21In many cases, they can
• 31:22predict that the child probably
• 31:23has a few days before
• 31:24the they their child will
• 31:26expire.
• 31:26Well, through a program that
• 31:28I helped launch and NHGRI
• 31:29funded that has now become
• 31:31sort of now standard in
• 31:32many places
• 31:33is the idea when you
• 31:34have a patient like that
• 31:35in NICU, don't just get
• 31:36a genome sequence. Get it
• 31:37fast. And so technologies and
• 31:39approaches have been now implemented
• 31:41to be able to get
• 31:42a very rapid genome sequence.
• 31:44And in about thirty to
• 31:45fifty percent of the time,
• 31:46you get a diagnosis. And
• 31:47in many cases, it changes
• 31:48the management. You get the
• 31:49kids the patient out of
• 31:50the NICU into a specialist
• 31:51care, and it has saved
• 31:53lives and has resulted in,
• 31:56a savings of a lot
• 31:56of money. And, again, what
• 31:58makes me really happy is
• 31:59to see the uptake of
• 32:00this in the NICU
• 32:02increasingly in the pediatric
• 32:03the PICU, the pediatric intensive
• 32:05care unit. And then they
• 32:07actually do review articles, which
• 32:08means its uptake is significant
• 32:10if they can actually study
• 32:11this. This was a review
• 32:12article from a couple years
• 32:13ago. And just read the
• 32:15first paragraph in particular. They
• 32:16looked at forty four studies
• 32:18where this was being done
• 32:19in ICUs
• 32:20in with in the pediatric,
• 32:23area.
• 32:24And thirty seven percent of
• 32:25the time, they got a
• 32:26genetic diagnosis, and twenty six
• 32:28percent had consequent changes in
• 32:30management leading to net health
• 32:31care costs,
• 32:32reduction or savings.
• 32:34The point is every one
• 32:35of these numbers will get
• 32:36better because we'll get better
• 32:38at interpreting the data, better
• 32:39understanding about the genetic basis
• 32:40of rare diseases and so
• 32:42forth, which gives great optimism,
• 32:44exactly why this is now
• 32:46being implemented more and more
• 32:47in pediatric intensive care units.
• 32:50I was particularly impressed at
• 32:52this paper that I saw,
• 32:53because I always wonder, well,
• 32:54what about other intensive care
• 32:56units? And the people at
• 32:57Penn also thought about this.
• 32:59And last summer, they published
• 33:00this paper, which I thought
• 33:01is pretty cool, where they
• 33:02basically said, let's take a
• 33:04bunch of patients, hundreds of
• 33:05patients that came into the
• 33:06adult ICU.
• 33:08They ruled out they they
• 33:09excluded from the study those
• 33:10that were there for trauma
• 33:11or for poisoning
• 33:13or for, you know, known
• 33:14condition like cancer. They were
• 33:15having, you know, problems related
• 33:17to their treatment, leaving just
• 33:19a lot of patients that
• 33:20all of us know about
• 33:21that are just they're they're
• 33:22they're they're just fragile that
• 33:23they that you're surprised they
• 33:25have to be in the
• 33:25ICU, and they just end
• 33:26up landing in the ICU.
• 33:28And they're otherwise adult in
• 33:29some cases, being otherwise healthy
• 33:31until of a sudden onset
• 33:32of some symptoms that land
• 33:33them in the ICU.
• 33:34And they sequenced their genomes,
• 33:36and they found that a
• 33:37quarter of them had an
• 33:38undiagnosed rare genetic disease.
• 33:40So, again, that number will
• 33:42get bigger, but it also
• 33:43starts pointing to the fact
• 33:44that many people, including people
• 33:46who just seem to be
• 33:47fragile, have rare genetic diseases
• 33:49that are going on undiagnosed,
• 33:50and we're in a position
• 33:51now to increasingly be able
• 33:52to diagnose them.
• 33:54So I, you could tell
• 33:55I'm very enthusiastic about the
• 33:56progress in this area. And
• 33:58if you wanna read more,
• 33:59I would just point you
• 34:00to to two very short
• 34:02perspective pieces that came out
• 34:04just in the last few
• 34:05weeks, actually,
• 34:06in two different journals. And
• 34:07I would just point you
• 34:08to those because it really,
• 34:10I think, very nicely underscores
• 34:11the point that I am
• 34:12making. And I I just
• 34:13like the very last paragraph,
• 34:15what actually, Harry is a
• 34:17good friend of mine, and
• 34:17he wrote, I just thought
• 34:18so eloquently what he just
• 34:20said. As professional societies codify
• 34:22universal standards
• 34:23and laboratories deliver rapid variant
• 34:26specific insights, clinicians must transition
• 34:28from reactive
• 34:29watchful waiting to proactive phenotype
• 34:32and genotype informed management.
• 34:35In other words, when you
• 34:36don't just sit and watch
• 34:37a patient. Get the damn
• 34:38genotype. And increasingly,
• 34:40that's a heck of a
• 34:40lot cheaper than a lot
• 34:41of other things you're doing.
• 34:42And if you had all
• 34:43of the suspicion of a
• 34:44rare genetic disease,
• 34:46you should absolutely be doing
• 34:47that.
• 34:48And part of the reason
• 34:49I wanna point out that
• 34:51I think it's only gonna
• 34:52get better is I'm a
• 34:53genomics guy, so I'm all
• 34:55enthusiastic about changes in DNA
• 34:56sequence. But I also realize
• 34:59biology is more complicated,
• 35:00and there'll be other technologies
• 35:02that will deliver other types
• 35:04of data that will enhance
• 35:06what we are doing in
• 35:07genomics.
• 35:08And one way to think
• 35:09about it is that, you
• 35:09know, genomics has just seen
• 35:11this wave of technology that's
• 35:12given us insights above the
• 35:14waterline,
• 35:15about DNA sequence and DNA
• 35:17sequence variation.
• 35:18But there's all these other
• 35:19things going on, and increasing
• 35:21the same technologies
• 35:22can be adapted
• 35:23to give readouts on transcriptomics
• 35:25and proteomics
• 35:27and epigenomic changes and so
• 35:28on and so forth. And
• 35:30increasingly and I will have
• 35:31to change my vocabulary because
• 35:32I will always say genomics,
• 35:34but that's gonna almost be
• 35:35something that's gonna be about
• 35:37multiomics.
• 35:38And increasingly,
• 35:39you're gonna start to see
• 35:40datasets
• 35:41that are gonna be delivered
• 35:42on patients as part of
• 35:43diagnostic workups for rare genetic
• 35:45disease. Maybe that accounts for
• 35:46some of the ones we
• 35:47can't diagnose. These other modalities
• 35:49will give us clues. You'll
• 35:50see this all across research.
• 35:52You're gonna hear a lot
• 35:53about data integration represented by
• 35:55the middle panel, and you're
• 35:56gonna start to see how
• 35:57we can extract insights
• 35:58from the data analysis
• 36:00of these integrated datasets.
• 36:02And so
• 36:03if you just look at
• 36:05rare genetic diseases,
• 36:07I it sounds great and
• 36:08it hypothetical,
• 36:09but it's actually real. And
• 36:10it's all once again, I
• 36:11love when I see review
• 36:12articles or major articles. Across
• 36:14the board, you're hearing more
• 36:16and more publication. You're seeing
• 36:17more and more publications
• 36:19talking about the use of
• 36:20multi omics as part of
• 36:22rare genetic diseases with respect
• 36:24to the study of the
• 36:25diseases and also the diagnostics
• 36:27associated with working this up.
• 36:29And so as a result
• 36:30of this, people are beginning
• 36:31to prioritize multi omics
• 36:33beyond just genomics.
• 36:35In fact, one of the
• 36:36very last
• 36:37programs I stood up as
• 36:38the NHGRI director is a
• 36:40program that's now in its
• 36:41third year called Multi Omics
• 36:43for Health and Disease or
• 36:44Mode, where it it's exactly
• 36:46as the name implies, and
• 36:47it supports this consortium where
• 36:49they're taking a series of
• 36:50diseases, and they're using multiple
• 36:52omics
• 36:52to see how they can
• 36:54operationalize
• 36:54those analyses
• 36:55to be able to gain
• 36:56new insights about these about
• 36:58the those diseases that are
• 36:59being studied.
• 37:00And then in my new
• 37:02hat at Illumina, I can
• 37:03tell you Illumina is serious
• 37:04about this. They think there's
• 37:06more to see, more to
• 37:07understand, more with multi omics,
• 37:09and they're not only delivering
• 37:11platform the same boxes that
• 37:12are used for sequencing are
• 37:14now being adapted for getting
• 37:15methylation data and getting other
• 37:17types of data, certainly transcriptomic
• 37:19data, increasingly spatial genomics data,
• 37:22other types of data, all
• 37:23with software platforms to help
• 37:25support the data analysis.
• 37:26So the public sector supporting
• 37:28research in this area and
• 37:30and companies like Illumina supporting
• 37:32research in this area as
• 37:33well.
• 37:35So with respect to genetic
• 37:36rare genetic diseases, I introduced
• 37:39you to the idea of
• 37:39just routine diagnostic workup of
• 37:42these, of patients.
• 37:44I mentioned rapid genome sequencing
• 37:46in the case of of
• 37:47of newborns. I didn't really
• 37:49talk much about reproductive
• 37:50carrier screening, but I could,
• 37:52and there's certainly a very
• 37:53interesting area to keep an
• 37:55eye on. And later in
• 37:56my talk, I'm gonna come
• 37:57to the idea of screening
• 37:58newborns by genome sequencing. But
• 38:00before I get to
• 38:01that, there is this important
• 38:02point in life called birth.
• 38:05And just before birth has
• 38:06been one of the most
• 38:07fertile areas of genomics actually,
• 38:09fertile area. That's actually sort
• 38:10of a cute little metaphor.
• 38:11I've never said that before.
• 38:12It's a very productive area
• 38:14because it turns out
• 38:16that the most used genomic
• 38:18test today
• 38:20is noninvasive
• 38:21prenatal genomic testing. You may
• 38:23not realize this, but let
• 38:24me just remind you that
• 38:26in the old days, meaning
• 38:27before genomics,
• 38:28lots of couples, not all
• 38:29couples, but lot of couples
• 38:30were interested in getting genomic
• 38:32information
• 38:33about their unborn child.
• 38:35And they would typically,
• 38:37through an invasive procedure like
• 38:38what my wife went through
• 38:39for our two kids, an
• 38:41amniocentesis, which is unpleasant.
• 38:43It is expensive, and it's
• 38:44actually a little dangerous.
• 38:46But you get out a
• 38:47carrier type, and you could
• 38:48look for any employees, like
• 38:50three copies of chromosome twenty
• 38:51one. This doesn't have to
• 38:53be done this way anymore.
• 38:53In fact, it's not being
• 38:54done this way anymore routinely.
• 38:56The frontline diagnostic tool takes
• 38:58advantage of the fact that
• 39:01that mothers and fetuses and
• 39:03the placenta naturally shed DNA
• 39:05into the bloodstream of a
• 39:06pregnant individual,
• 39:07and that DNA can is
• 39:09cell free DNA, and it
• 39:10can be analyzed.
• 39:12And you can analyze it
• 39:13not through an invasive procedure,
• 39:14but through a simple blood
• 39:15draw. Well, pregnant individuals getting
• 39:17lots of blood draws. Just
• 39:18one extra tube off it
• 39:19goes. Actually, most typically to
• 39:21a company now because companies
• 39:22have just sprung up to
• 39:24do this noninvasive
• 39:25prenatal testing.
• 39:27Insurance companies are paying for
• 39:28it. That catalyzed it as
• 39:29well. And all they're doing
• 39:31is counting and assigning
• 39:33read counts to chromosomes. And
• 39:35if they see an abnormal
• 39:36ratio, like too many going
• 39:37to twenty one, it signals
• 39:39they need a follow-up test
• 39:40to see if there's an
• 39:41aneuploidy.
• 39:42Guess what? It's now the
• 39:43number one genomic test worldwide.
• 39:45Eight million pregnant individuals that
• 39:47is estimated around the world
• 39:49will get this noninvasive genetic
• 39:51test done, making it the
• 39:52number one genomic test. It's
• 39:53completely
• 39:54changed how prenatal genetic testing
• 39:56has been done.
• 39:58So that's that so fourth
• 40:00area,
• 40:01which I'm only gonna mention
• 40:02but not talk about is
• 40:03pharmacogenomics,
• 40:04two big words put together.
• 40:06But bottom line is people
• 40:07respond to medications differently. We've
• 40:09always been perplexed by it,
• 40:10and we've always done sort
• 40:11of in a hit and
• 40:12miss way picking the best
• 40:14medication. We are increasingly
• 40:16learning that variants in genes
• 40:18involved in drug metabolism
• 40:20are are have a a
• 40:21large effect on why people
• 40:23respond to certain medications better
• 40:25or worse or why they
• 40:26need their dosage adjusted.
• 40:27We are learning more and
• 40:28more about what those variants
• 40:29are. We're figuring out how
• 40:31to be able to read
• 40:31them out efficiently.
• 40:33It turns out it hasn't
• 40:34hit as much mainstream because
• 40:36physicians are difficult to change
• 40:37their behavior, and they don't
• 40:39like a test beam between
• 40:40them and and and the
• 40:41other patients getting the drug
• 40:43they want. So there's there's
• 40:45implementation
• 40:45issues. There's lots of reasons
• 40:47I think this will change.
• 40:47At some institutions, this absolutely
• 40:49is changing,
• 40:51partially through the implementation of
• 40:52clinical decision support tools and
• 40:54the electronic record and blah
• 40:55blah blah. There's lots we
• 40:56could talk about. Needless to
• 40:57say, this is still an
• 40:58evolving area. It's been a
• 41:00little disappointing for some of
• 41:01us that it hasn't happened
• 41:02sooner, but trust me. It
• 41:03has happened in cancer. So
• 41:05in pharmacogenomics
• 41:06and cancer has been much
• 41:07more heavily used than in
• 41:08in other types of medicine,
• 41:09but more will come.
• 41:11I also wanted to immediately
• 41:13also point out that sometimes
• 41:14it was, oh, you talk
• 41:14about medicine. What about prevention?
• 41:16Is genomics helping there? Absolutely.
• 41:18Genomics absolutely having to play
• 41:20a major role in prevention,
• 41:21but be careful what type
• 41:23of of of tools you're
• 41:24talking about and what types
• 41:26of diseases you're talking about.
• 41:27There really is a bifurcation
• 41:29because when it comes to
• 41:30rare genetic diseases,
• 41:32prevention,
• 41:32genomics,
• 41:33here and now. And it
• 41:35happens for this gentleman right
• 41:36here. Maybe he's,
• 41:38just had a sister who
• 41:39in her thirties was diagnosed
• 41:41with, colon cancer. When that
• 41:43happens,
• 41:44people will jump in and
• 41:45immediately say, boy, you know,
• 41:46you may have something like
• 41:47Lynch syndrome. We should test
• 41:48for the known genes that
• 41:50give to a cancer predisposition
• 41:51at a young age, and
• 41:52you should get tested, and
• 41:53your other siblings should get
• 41:54tested. Cascade
• 41:56testing, and boom, all of
• 41:57a sudden you find out
• 41:58which members of the family
• 41:59have the the mutation and
• 42:01then screen them more proactively,
• 42:03surveil them more proactively, catch
• 42:05any cancer earlier. That's absolutely
• 42:07here and now for b
• 42:08a c r BRCA one
• 42:10and breast and ovarian cancer,
• 42:11for Lynch Syndrome and so
• 42:12forth. But we also have
• 42:14prevention for youngsters, and I'm
• 42:15gonna talk in a bit
• 42:16about prenatal not prenatal,
• 42:18newborn screening.
• 42:20But this little girl may
• 42:21have been picked up at
• 42:22a at a very at
• 42:22birth or shortly after birth
• 42:24through genetic screening and found
• 42:26to have a mutation in
• 42:27a gene that is really
• 42:28important for how she digest
• 42:29food, and she would get
• 42:31have cognitive delay if we
• 42:32didn't change her diet, but
• 42:33we could change her diet.
• 42:34And so there's other increasing
• 42:36numbers of these circumstances where
• 42:38simple interventions
• 42:39truly do prevent disease. And
• 42:40so prevention and gen in
• 42:42genomics here and now.
• 42:44Where it gets a little
• 42:45tricky and we're at an
• 42:46awkward phase right now is
• 42:48when it comes to common
• 42:50diseases. Because for common diseases,
• 42:52we don't really have a
• 42:53lot of examples where we
• 42:54can point to specific variants.
• 42:57But rather,
• 42:58what we have is the
• 42:59ability to do a flyover
• 43:01over a person's genome and
• 43:02collect information about what variants
• 43:05they have and then correlate
• 43:07their set of three to
• 43:08five billion variants
• 43:09with other people who either
• 43:11have or don't have a
• 43:12disease like sudden cardiac death
• 43:15or hyperlipidemia
• 43:16or so on and so
• 43:17forth. And that has led
• 43:18to the ability to do
• 43:19distributions
• 43:20of of risk
• 43:22based on correlations of people's
• 43:24set of genomic variance. This
• 43:25has led to the idea
• 43:26of a polygenic risk score,
• 43:28and there's some pretty cool
• 43:30data out there.
• 43:31And the problem is it's
• 43:33still under construction. It's still
• 43:34under study. It's still not
• 43:36quite ready for prime time.
• 43:38And it's something that NIH
• 43:40is funding in a big
• 43:41way to try to explore
• 43:42because it has a lot
• 43:43of potential to be able
• 43:44to
• 43:45find out who's at greatest
• 43:46risk and maybe able to
• 43:48do some interventions to try
• 43:49to dampen that risk. And
• 43:51so this is one of
• 43:52these areas where immediately what
• 43:54happens in a country like
• 43:55the United States is that
• 43:57there seems to be some
• 43:58excitement.
• 43:59There absolutely is some good
• 44:01effective examples
• 44:02seemingly, but we need to
• 44:03have clinical trials to do
• 44:04it. But that doesn't stop
• 44:07companies going to direct to
• 44:09consumers
• 44:09and selling things to consumers
• 44:11that therefore may or may
• 44:13not be warranted based on
• 44:14the clinical data. So this
• 44:15is where I put in
• 44:16some caution. What's my caution?
• 44:17Well, any of you could
• 44:18do this, and I do
• 44:19this every once in a
• 44:20while. Just start doing Google
• 44:21searches for polygenic risk scores,
• 44:23and you see lovely websites
• 44:24that are completely convincing that,
• 44:26yeah, maybe I should get
• 44:27that test and maybe the
• 44:28doctor doesn't wanna order it.
• 44:29I'll just get it myself
• 44:30and see what I'm at
• 44:31risk for. And that seems
• 44:32so good, and at first
• 44:33you say, oh, yeah, that's
• 44:34really good for two hundred
• 44:35and fifty nine dollars. But
• 44:36then you realize, it's just
• 44:38like Amazon. When you click
• 44:39there, they say, if you
• 44:41want that, maybe you also
• 44:42wanna get tested for other
• 44:44things, like whether you have
• 44:45your healthy weight or your
• 44:47nutrition or your personality type
• 44:48or your etcetera etcetera.
• 44:51Or here's another one. Looks
• 44:53great. Certainly very innocent until
• 44:55you see what else they're
• 44:56offering including
• 44:57finding your superpowers through DNA
• 44:59and perfecting your skin.
• 45:01This risks undermining the whole
• 45:04endeavor which is what makes
• 45:05me nervous. I think there's
• 45:06one more. Yeah. This I
• 45:07like. They even have a
• 45:08good metaphor to explain single
• 45:10gene disorders and polygenic risk.
• 45:11I love it. They're teaching.
• 45:13And then but you click
• 45:14through and you find out
• 45:15that they're talking about all
• 45:16sorts of crazy things, including
• 45:18DNA mindfulness. I don't even
• 45:20know what the hell that
• 45:21means.
• 45:22This risks undermining the enterprise
• 45:24completely, and I don't want
• 45:26that to happen by people
• 45:27clicking all this. And then
• 45:28eventually, when their clinician talks
• 45:29to them, they're gonna say,
• 45:30I didn't learn any mindfulness
• 45:32from the test. Forget this.
• 45:33I don't want my polygenic
• 45:34risk assessed.
• 45:36However, there is some optimism
• 45:38is that if we could
• 45:39just try to dampen out
• 45:40that that commercial noise
• 45:43that when you start to
• 45:44see a place that you
• 45:45actually could trust, and then
• 45:46you could start to build
• 45:47on that with some could
• 45:48very cautiously,
• 45:50then maybe we'll see this
• 45:51come to be. And I
• 45:52I Broad the Broad Clinical
• 45:53Labs, I have great respect
• 45:54for the people there. And
• 45:55very recently, they launched a
• 45:57test that they are now
• 45:58selling, for polygenic respites just
• 46:00for eight cardiovascular
• 46:01conditions.
• 46:02And as a result, we're
• 46:04starting to see people stick
• 46:05their toe in the water
• 46:06just around this domain. They
• 46:07said a lot of people
• 46:08are starting to order this.
• 46:09And then I thought this
• 46:10was pretty cool, and it's
• 46:11what we've been waiting for.
• 46:13And I think it signals
• 46:14a first step towards progress.
• 46:15In breaking news, very recently,
• 46:18the American College of Cardiology
• 46:20and the American Heart Association,
• 46:21who periodically put out the
• 46:24the the clinical guidelines,
• 46:26for working up patients with
• 46:28hyperlipidemia,
• 46:29put one out last month,
• 46:30and here's the paper,
• 46:32that where it's described. And
• 46:33it's very detailed if any
• 46:35of you have looked at
• 46:36this and lots and lots
• 46:36of things. But if you
• 46:38dig a little deeper into
• 46:39that paper, there is this
• 46:40table here where they actually
• 46:42start to talk about,
• 46:44I mean, high polygenic risk.
• 46:46And what I thought was
• 46:47even more exciting, and it
• 46:48was it's really a light
• 46:49touch. It's just you may
• 46:50wanna think about it and
• 46:51they gave some examples. It
• 46:52really wasn't a heavy guideline.
• 46:54But more importantly in my
• 46:55mind is they had a
• 46:56paragraph in the text where
• 46:58they actually talked about polygenic
• 47:00risk scores, which is the
• 47:01first step towards educating busy
• 47:03practicing physicians that in practice
• 47:05guidelines, we're gonna start to
• 47:06hear about polygenic risk.
• 47:08So I'm not overstating this
• 47:10as being the end all.
• 47:11I'm just saying it's the
• 47:12beginning of what I think
• 47:13is a very important progression
• 47:15as maybe we're gonna start
• 47:16to see the idea polygenic
• 47:18risk,
• 47:19come into clinical guidelines increasingly
• 47:21across different medical disciplines.
• 47:24So what I've told you
• 47:26about so far is what's
• 47:28going on in the last
• 47:28twenty three years with this
• 47:30vaguest idea of what genomic
• 47:31medicine was gonna be,
• 47:34to now actually bringing clarity.
• 47:36We don't have a comprehensive
• 47:37list. If you invite me
• 47:38back here ten years from
• 47:39now, I'm sure we'll have
• 47:40a bigger list. But at
• 47:41least for some of the
• 47:42early examples, it is in
• 47:44focus. We know what we
• 47:45are doing. And we we've
• 47:46we're learning so much from
• 47:48these earliest examples, good, bad,
• 47:49and other.
• 47:50That does lead to a
• 47:52question that I am frequently
• 47:53asked, and so I will
• 47:55just, right now, put it
• 47:56as part of my talk.
• 47:57What do I think is
• 47:58the next big thing in
• 47:59genomic medicine?
• 48:01And my views on this
• 48:02have actually changed over the
• 48:03last year, year and a
• 48:04half. And I would say
• 48:06that my number one answer
• 48:07now is that it's a
• 48:08seismic expansion of an established
• 48:10thing. What do I mean
• 48:11by that? Well, let me
• 48:12remind you, and I hinted
• 48:13at it earlier,
• 48:14is if we go back
• 48:15sixty years, there is a
• 48:17very rich history starting here
• 48:18in the US, but now
• 48:19around the world of prenatal
• 48:21genetic screening. And it started
• 48:23in the sixties, but it's
• 48:24progressed throughout. For those of
• 48:25you who don't know the
• 48:26details,
• 48:27just let me just remind
• 48:28you that at about day
• 48:29one or two in every
• 48:31state in the United States,
• 48:33a mean nurse comes into
• 48:35the nursery
• 48:36and nicely cleans off the
• 48:38heel of an of a
• 48:39newly born, infant
• 48:41and and sticks it with
• 48:43a little needle and then
• 48:44gets a little wipe there
• 48:45and then takes a drop
• 48:47several drops of blood and
• 48:49puts it on a piece
• 48:50of filter paper called a
• 48:51Guthrie card that gets sent
• 48:53off to the state lab
• 48:54in the United States. It's
• 48:55done state by state in
• 48:56the public health lab where
• 48:58they are screened for anywhere
• 49:00between forty and sixty
• 49:02rare genetic diseases, single gene
• 49:04disorders. Usually, I try to
• 49:05I does anybody know what
• 49:06Connecticut is? Usually, when I
• 49:07come somewhere, I always try
• 49:08to look up. Does anybody
• 49:09know what every state has
• 49:11a different number. I don't
• 49:12know if Connecticut's more like
• 49:13seventy or Connecticut's more like
• 49:15sixty or fifty. But in
• 49:16any case, it's somewhere in
• 49:17that range.
• 49:17And, of course, now you're
• 49:19thinking you're screening for fifty
• 49:20or sixty, but we know
• 49:21about six thousand. You could
• 49:22see that the mismatch is.
• 49:24So the idea is, why
• 49:25are we just doing sixty?
• 49:26Why don't we just do
• 49:26them all? Well, I can
• 49:28tell you that there always
• 49:29was early talk about just
• 49:31sequencing every newborn.
• 49:32And in fact, I can
• 49:33tell you that when the
• 49:34Genome Project in fact, I
• 49:35actually think of the congressional
• 49:36hearings in eighty nine. They
• 49:38talked about the ideas that
• 49:39if we could learn how
• 49:39to sequence the human genome,
• 49:41maybe one day, maybe one
• 49:43day, we would sequence every
• 49:45baby's genome at birth and
• 49:46we would make it part
• 49:47of their electronic record. It
• 49:49was very funny to say
• 49:50that back in nineteen ninety
• 49:51when the Human Genome Project
• 49:52began because Dave and I
• 49:54remember that back in nineteen
• 49:55ninety, the electronic record was
• 49:56all done handwritten
• 49:58paper was not electronic.
• 49:59The the the idea of
• 50:00sequencing a genome and having
• 50:01the genome sequence be carried
• 50:03forward with a patient for
• 50:04their life before electronic records
• 50:06was a bit of a
• 50:07joke. But by the time
• 50:08the Genome Project ended, it
• 50:09started to get serious attention
• 50:11with electronic health records, it
• 50:12became quite viable. And we
• 50:14already have the infrastructure for
• 50:15doing it. And so it's
• 50:16beginning to get a lot
• 50:17of attention right now.
• 50:19And I'm not the only
• 50:21one thinking it's getting a
• 50:22lot of attention. You know,
• 50:23even the popular press has
• 50:24thought about this idea.
• 50:26Time magazine got really audacious
• 50:28about twelve years ago. They
• 50:29had one of their futuristic
• 50:30issues where they talked about
• 50:32a series of domains, what
• 50:33was gonna happen in the
• 50:34future. And they made a
• 50:35claim in twenty fourteen
• 50:37that by twenty twenty five,
• 50:39which meant last year, everyone
• 50:41would get their DNA mapped.
• 50:42I wish I could have
• 50:43edited that. I would have
• 50:44said sequenced
• 50:45at birth.
• 50:46We didn't make that. Okay?
• 50:48But I like their audacity
• 50:49that they thought that was
• 50:50happening. But maybe they were
• 50:51off by some number of
• 50:52years because things are really
• 50:54starting to heat up now
• 50:56in this arena. And there
• 50:57is a lot of activity
• 50:58and a lot of research
• 50:59going on. And all you
• 51:01have to do is is
• 51:02and that's why I put
• 51:03it on my watch list
• 51:04of what I think is
• 51:04happening. There is just so
• 51:06many publications coming out where
• 51:08they are doing pilots
• 51:09all around the world of
• 51:11sequencing healthy newborns, not this
• 51:13the ill ones, the healthy
• 51:14ones, seeing what they could
• 51:15learn, seeing how you could
• 51:16operational, dealing with all the
• 51:17logistics.
• 51:18In fact, there are so
• 51:19many worldwide studies going on
• 51:22that a few years ago
• 51:23an international organization called ICONS,
• 51:26International Consortium of Newborn Sequencing
• 51:28got established, and every one
• 51:29of those little black dots
• 51:30are where a major study
• 51:31is going on of of
• 51:33of of healthy newborn sequencing.
• 51:35Some of the most prominent
• 51:36of these, there's multiple prominent
• 51:38ones, but you may have
• 51:39heard of the generation study
• 51:40in the UK or the
• 51:41guardian study here in the
• 51:43United States.
• 51:44The generation study in the
• 51:45UK has so far along
• 51:47and they're so excited about
• 51:48it that last year,
• 51:51the UK declared that by
• 51:53twenty thirty five, they're gonna
• 51:54sequence every baby born in
• 51:56the UK. And other countries
• 51:57are now starting to talk
• 51:58in a similar way. So
• 51:59they've really put down the
• 52:01marker. And as a result
• 52:02of that, even here in
• 52:03the United States,
• 52:05more attention is being spent.
• 52:07And the project that I
• 52:08tweaked a little before I
• 52:09left and finally,
• 52:11it got launched after I
• 52:12left NIH. It's a brand
• 52:13oh, I'm sorry. Before I
• 52:14get to that one, other
• 52:15breaking stories. Thailand has a
• 52:16major program. Denmark has a
• 52:18major program of newborn sequencing.
• 52:20But then I was telling
• 52:21you about the program that
• 52:22just got launched earlier this
• 52:24year at NIH called the
• 52:25Beacon study, where they are
• 52:28specifically working with the state
• 52:29health labs to try to
• 52:31move forward at making that
• 52:33transition from forty to fifty,
• 52:35diseases to be screened for.
• 52:36But what would it look
• 52:37like if a state lab
• 52:38started to do genome sequencing?
• 52:40So a big consortium funded
• 52:41by the NIH.
• 52:42Oh, and then there's politics
• 52:44getting involved in it. In
• 52:46fact, if if any of
• 52:47you said, what is the
• 52:48most progressive state when it
• 52:50comes to committing to genome
• 52:52sequencing of newborns,
• 52:54you would never think that
• 52:56I would say the word
• 52:57Florida.
• 52:58But it turns out that
• 52:59it's Florida. Why? Because one
• 53:02member of the state legislature
• 53:04had a child who died
• 53:05of Tay Sachs disease. His
• 53:07name is Adam Anderson. You
• 53:08can read about him or
• 53:08see interviews in the news.
• 53:10He they died he was
• 53:11not Ashkenazi Jewish nor was
• 53:13his wife. And the child
• 53:14died
• 53:15of Tay Sachs disease at
• 53:17age four, and they went
• 53:18under a three year diagnostic
• 53:20odyssey missing every opportunity to
• 53:22enroll in clinical trials because
• 53:23you had to be much
• 53:24younger to be in a
• 53:25clinical trial for Tay Sachs.
• 53:26And he just said, why
• 53:27are parents not being given
• 53:28the ability to sequence their
• 53:30patient their child's genome at
• 53:31birth? We should figure out
• 53:32a way to do this
• 53:33and at least give them
• 53:34the option. They got passed
• 53:35in Florida, the Florida Genetic
• 53:37Sunshine Act,
• 53:38passed in Florida by a
• 53:40unanimous vote of the state
• 53:41legislature, signed into law by
• 53:43by governor DeSantis and is
• 53:45the most progressive ambition. They
• 53:47haven't committed fully, but they
• 53:48are now doing a pilot.
• 53:49It's the most ambitious pilot
• 53:51of any given state. So
• 53:52Florida's leading kind of embarrasses
• 53:54Connecticut as far as I'm
• 53:55concerned, but I say that
• 53:56every state I visit.
• 53:58There's a lot of momentum
• 53:59in this arena,
• 54:01and I I I'd also
• 54:02just like to share a
• 54:03clip. So there's another green
• 54:05in the genomics world called
• 54:06Robert Green. We're not related.
• 54:08We we we,
• 54:09he he I just like
• 54:10a lot of the things
• 54:11he says and how he
• 54:11says it. He is the
• 54:12leader of the beacons program
• 54:14that I just told you
• 54:15about, and I just like
• 54:16how he brings us into
• 54:17the future in this TED
• 54:18Talk. If you wanna listen
• 54:19to the whole thing, it's
• 54:20fifteen minutes. I'm just gonna
• 54:21show you a one minute
• 54:22clip. But if we really
• 54:23want to invent the future,
• 54:24we've gotta do something different.
• 54:26We really want to invent
• 54:27the future, we've gotta realize
• 54:29that a child's DNA
• 54:31doesn't change over time,
• 54:34but the science
• 54:35is changing all the time.
• 54:37And so what that means
• 54:38is we should sequence your
• 54:40child's DNA, and we should
• 54:42revisit and reanalyze
• 54:43that DNA
• 54:45over and over again to
• 54:47truly
• 54:48create the dream of genome
• 54:50informed medicine.
• 54:52Because each and every year,
• 54:54there will be new insights
• 54:56and new treatments available.
• 54:59Well, this isn't offered anywhere
• 55:01in the world,
• 55:02but I'm happy to tell
• 55:03you that we are trying
• 55:05to build this.
• 55:06We are building
• 55:08an AI enhanced
• 55:10digital health platform
• 55:12so that you, your grandchildren,
• 55:14your children, your pediatricians,
• 55:17your health care centers,
• 55:19your employers,
• 55:20your nations
• 55:22can do this at scale.
• 55:24It's gonna take a certain
• 55:25amount of courage to change
• 55:27the way we think about
• 55:28disease,
• 55:29to embrace
• 55:30the knowledge
• 55:31of risk
• 55:33in order
• 55:34to preserve our health rather
• 55:36than waiting for us and
• 55:37our children to get sick
• 55:39and treating them there. But
• 55:41if we can do this,
• 55:43if we can embrace this,
• 55:45we can save millions of
• 55:46lives and usher in an
• 55:48entirely
• 55:49new era
• 55:50of genome inspired medicine.
• 55:52Thank you.
• 55:54So I I like especially
• 55:55how he talks about being
• 55:56courageous. I also think it
• 55:57just I think we're gonna
• 55:58start taking this as a
• 55:59very practical way. You know,
• 56:01I'm I'm on airplanes a
• 56:02lot these days for Illumina,
• 56:04and I was I suddenly
• 56:05realized that I would not
• 56:06wanna get on any airplane
• 56:08if the mechanic taking care
• 56:09of that plane and doing
• 56:11service on a plane didn't
• 56:12have a blueprint in front
• 56:13of them. And I just
• 56:14wonder if part of what
• 56:15we're all thinking about in
• 56:17genomics
• 56:18is that are we heading
• 56:19towards a future where you're
• 56:20this is how Adam Anderson
• 56:21feels. In the future, they're
• 56:23just not gonna want a
• 56:23doctor taking care of you
• 56:25or your child without having
• 56:26a genome sequence in front
• 56:27of them when we get
• 56:28to the point of operationalizing
• 56:30all that information.
• 56:31So I I think our
• 56:32minds might change over time
• 56:33in a way that will
• 56:34make this very comfortable. However,
• 56:36I'm not saying any of
• 56:38this is easy because the
• 56:39what I'm talking about in
• 56:40the future is a circumstance
• 56:42like this where every child
• 56:43walking into a hospital or
• 56:44clinical have their genome sequence
• 56:45in hand. But everybody's happy
• 56:47here. If we don't do
• 56:48this well, if we don't
• 56:49figure out how to implement
• 56:50this, which is why we're
• 56:51doing all of these studies,
• 56:53is to figure out the
• 56:53logistics and the ethics and
• 56:55the and and all the
• 56:56social dimensions.
• 56:58If we screw this up,
• 56:59this is what it'll be
• 57:00like, where we'll give them
• 57:01a tsunami of information, and
• 57:02we'll terrify the family, we'll
• 57:04terrify the patients, and we'll
• 57:05terrify the clinicians.
• 57:06We can't let that happen,
• 57:08but I can tell you
• 57:09there's a lot of attention
• 57:10being given to the bioethical
• 57:11issues associated with newborn sequencing,
• 57:13and that's the reason why
• 57:14these studies and these consortiums
• 57:16have formed.
• 57:18So let me just point
• 57:19out that we're celebrating the
• 57:20arrival of genomic medicine, and
• 57:22we have a lot of
• 57:23reason to celebrate.
• 57:25But nothing about what I've
• 57:27described to you has been
• 57:28linear. It's really complicated.
• 57:30Lots of twists and turns,
• 57:31and we've all along the
• 57:32way faced lots of challenges.
• 57:34And so I just wanna
• 57:34spend two minutes
• 57:36reminding you that I am
• 57:38well aware of the fact
• 57:39that my enthusiasm is also
• 57:41met with a recognition
• 57:42that we have huge challenges
• 57:44ahead, and I could have
• 57:44spent an hour talking about
• 57:45the challenges. I will just
• 57:47briefly point out two major
• 57:48challenges
• 57:49that I oversimplified
• 57:51what it's like to actually
• 57:52analyze
• 57:53a a a patient's genome.
• 57:55I fully get that this
• 57:56was profoundly an oversimplification.
• 57:58I completely acknowledge that we
• 58:00could sequence any patient at
• 58:01Yale Hospital. We could read
• 58:03out their their sequence and
• 58:05get their three to five
• 58:06million variants. But when we
• 58:07go to round on them
• 58:08the next day, most of
• 58:10those list of variants will
• 58:11have no idea what they
• 58:12mean. And we really just
• 58:14skim the cream to be
• 58:15able to come up with
• 58:16any real diagnosis.
• 58:17But we're doing it pretty
• 58:18effectively so far. We'll get
• 58:19better at it, but we
• 58:20got a long way to
• 58:21go in this simple step.
• 58:23That's the scientific challenge. We
• 58:25also face societal challenges.
• 58:28Why are there societal challenges?
• 58:29Because genomics is now relevant
• 58:31in society.
• 58:32It wasn't always the case.
• 58:34I can tell you that
• 58:35when the Genome Project began
• 58:37and all the geekies people
• 58:39like me that were mapping
• 58:40and sequenced in the human
• 58:41genome, we would get together.
• 58:42We would feel like kids
• 58:44at a holiday,
• 58:45gathering of a family at
• 58:47the kids' table. Right? Kids'
• 58:48table, I don't know about
• 58:49your families, but we had
• 58:50kids' table. That's where all
• 58:51the fun was. But, you
• 58:52know, you didn't have any
• 58:53worries. Right? Because we were
• 58:54a bunch of kids. We
• 58:55were just a bunch of
• 58:55people mapping and sequencing. You
• 58:56know, people weren't paying attention.
• 58:58Society wasn't paying attention.
• 58:59But we've made that transition
• 59:01now because now, no, Eric.
• 59:03You can't sit at the
• 59:04kids' table. I don't care
• 59:05that they're talking about iPhones,
• 59:06Instagram, and Taylor Swift. You
• 59:08have to stay here and
• 59:09talk about mortgages,
• 59:11life insurance, taxes, politics,
• 59:13and genomic medicine and health
• 59:15care.
• 59:16This is because we've touched
• 59:18health care.
• 59:19What is a more complicated
• 59:20issue on set of circumstances
• 59:22than health care for any
• 59:23society in any part of
• 59:25the world? And as a
• 59:26result, we now have adult
• 59:27problems.
• 59:28Because now
• 59:29we have to face all
• 59:30the societal challenges associated with
• 59:32health care now just with
• 59:33a genomic lens. How does
• 59:34it get paid for? How
• 59:35does it get delivered? How
• 59:37exactly do we regulate it?
• 59:38How exactly do we ensure
• 59:40equity? How exactly do we
• 59:41ensure privacy? Oh, and by
• 59:43the way, we got a
• 59:44lot of literacy issues, both
• 59:45for patients and health care
• 59:46professionals alike.
• 59:48And so these are all
• 59:49things we are embracing as
• 59:50well. And we as a
• 59:52ecosystem of professionals, whether it's
• 59:53the private sector, whether it's
• 59:55government, whether it's academia, have
• 59:57to own up and help
• 59:58address all these societal issues,
• 01:00:00not to mention many, many
• 01:00:01other issues that I didn't
• 01:00:02even have time to talk
• 01:00:03about.
• 01:00:04So with that, let me
• 01:00:06just close by just saying
• 01:00:07that what I've told you
• 01:00:09about,
• 01:00:10through a walk down memory
• 01:00:11lane or a history lesson
• 01:00:12alike is how we went
• 01:00:14from the most basic information
• 01:00:15about DNA's structure.
• 01:00:17We put a magnifying glass
• 01:00:19on it during the Human
• 01:00:20Genome Project,
• 01:00:21read out the sequence, and
• 01:00:23then use threads of genomics
• 01:00:25to increasingly
• 01:00:26create a tapestry that affected
• 01:00:28basic science
• 01:00:29and affected translational science, increasingly
• 01:00:32clinical research. And now as
• 01:00:34we, including people here, are
• 01:00:36helping to continue to to
• 01:00:37put stitch together this growing
• 01:00:39tapestry of genomics being used
• 01:00:41in medicine. And so with
• 01:00:43that, I will stop, and
• 01:00:44I'm happy to take any
• 01:00:45questions. Thank you.
• 01:00:55Thank you, Eric. Sure. Does
• 01:00:56anyone have any questions? And
• 01:00:58I realized my excitement, I
• 01:00:59went a little longer than
• 01:01:00I thought. So people have
• 01:01:01to go off to do
• 01:01:02important things, that's fine. But
• 01:01:03I'm also happy to stay
• 01:01:04here for questions.
• 01:01:06Over here? That's yeah. The
• 01:01:08back. Yeah.
• 01:01:09Look. With all this golden
• 01:01:11element data Yeah. You know,
• 01:01:12potentially, are soon being available
• 01:01:14up to the patients,
• 01:01:15and
• 01:01:17the interpretability
• 01:01:18being hard, requiring complicated things
• 01:01:20happening in the cloud or,
• 01:01:21like, you know, reference need
• 01:01:22to Yeah. Databases and that
• 01:01:24all being boiled down into
• 01:01:25a report. It's available to
• 01:01:27the clinician directly.
• 01:01:28It is often interpreted
• 01:01:31as a sort of output
• 01:01:32of black box.
• 01:01:34Where do you see the
• 01:01:35role of individual pathologists
• 01:01:38in this process? You know,
• 01:01:39how do they factor into
• 01:01:41that model of patient care?
• 01:01:43Yeah. I you know, you
• 01:01:44gotta get to the table.
• 01:01:45Right? I mean, there's just
• 01:01:46an expression that I've often
• 01:01:47heard, you know, if you're
• 01:01:48not on the table, you're
• 01:01:49at the you're, you know,
• 01:01:50you're not at the table,
• 01:01:51you're on the menu.
• 01:01:52And, you know, so I
• 01:01:53mean, there's a lot I
• 01:01:54mean, I I would love
• 01:01:56to see more pathologists involved
• 01:01:58in a lot of these
• 01:01:58these,
• 01:01:59working groups and a lot
• 01:02:00of these public private partnerships,
• 01:02:02a lot of these consortium
• 01:02:03because they're they they know
• 01:02:05what this is like to
• 01:02:06deliver diagnostic information.
• 01:02:08And I think the there's
• 01:02:09would be a new world
• 01:02:10here, and, we need that
• 01:02:12expertise,
• 01:02:13at at in in all
• 01:02:15of these arenas.
• 01:02:18Yeah. What's, when you choose
• 01:02:20the image of human, which
• 01:02:21human? And in the research,
• 01:02:23you know, which we which
• 01:02:25Yeah. So I didn't cut
• 01:02:25so it's a great question.
• 01:02:26I mean, let's let's the
• 01:02:28the I won't tell you
• 01:02:29the story about so the
• 01:02:30first thing is the Human
• 01:02:31Genome Project produced a tapestry.
• 01:02:33It was it was it
• 01:02:34was a bunch of people.
• 01:02:35It was mostly one of,
• 01:02:36like, little almost half was
• 01:02:38one person for complicated reasons,
• 01:02:39but but it was a
• 01:02:40tapestry. And it that doesn't
• 01:02:41matter because, you know, since
• 01:02:43we're ninety nine point, you
• 01:02:44know, six percent the same
• 01:02:45and ninety point four percent
• 01:02:46the same,
• 01:02:47that first reference genome doesn't
• 01:02:49matter. But what you're and
• 01:02:50I didn't talk about this.
• 01:02:51But,
• 01:02:52you know, right now people
• 01:02:53are operating over with a
• 01:02:54few reference genomes. These are
• 01:02:56very high quality. But increasingly,
• 01:02:58you're gonna hear the phrase,
• 01:02:59Pangenome.
• 01:03:00Because in fact, one of
• 01:03:01the challenges that we have,
• 01:03:02and it plays right into
• 01:03:03the equity argument, is that
• 01:03:05if we sequence Dave and
• 01:03:06my genomes, there's one set
• 01:03:08of references that'd be really
• 01:03:09good. But if we sequence
• 01:03:11somebody from, you know, from
• 01:03:13Africa or somebody from South
• 01:03:15America, if we use those
• 01:03:16same references, we're gonna miss
• 01:03:17things. So that causes a
• 01:03:19discrepancy or a disparity.
• 01:03:21So what's happening, so we've
• 01:03:22signed called the Human Pan
• 01:03:23Genome Program, which is heavily
• 01:03:24supported by NHGRI,
• 01:03:26is hundreds and hundreds of
• 01:03:27high quality references are being
• 01:03:29generated, and ultimately are being
• 01:03:31amalgamated
• 01:03:32in a computational way. So
• 01:03:33that there will be like
• 01:03:34a universal,
• 01:03:36highly heterogeneous
• 01:03:37set of reference genomes that'll
• 01:03:38be properly matched to any
• 01:03:40patient's genome. And it's gonna
• 01:03:41be critical it it's a
• 01:03:42it's a really important concept
• 01:03:45that I just gave very
• 01:03:45short trip to. But we
• 01:03:47have to have properly matched
• 01:03:48reference
• 01:03:49genomes
• 01:03:50to implement genomics across all
• 01:03:52human populations. Those are being
• 01:03:53generated. Yeah.
• 01:03:55So, you know, we all
• 01:03:56know that most kids in
• 01:03:57life are really,
• 01:03:59nature plus virtue. Right? Yes.
• 01:04:01So so is so question
• 01:04:02is, how are we going
• 01:04:03to get it where we
• 01:04:04see, hey. I have this
• 01:04:05variant. That's associated with this
• 01:04:07particular study. Everything will be
• 01:04:08Icelandic,
• 01:04:09a GWAS studies, which are
• 01:04:11fabulous. If you're Icelandic and
• 01:04:12live in Iceland. Yep. Right?
• 01:04:14And so how are we
• 01:04:15gonna get to the point
• 01:04:16where we see, well, this
• 01:04:17generated to be right under
• 01:04:18these conditions with these other
• 01:04:20background
• 01:04:21genes, that was the issue
• 01:04:22with this. But we don't
• 01:04:23really have any idea whether
• 01:04:24that variant has anything to
• 01:04:25do with this other person
• 01:04:26who's living in different conditions
• 01:04:28with whatever other things. So
• 01:04:30how do you know So
• 01:04:31fair.
• 01:04:31Because that makes they just
• 01:04:33like Particularly for common genetic
• 01:04:35disease for common diseases that
• 01:04:36have genetic so there's a
• 01:04:37few answers I can give
• 01:04:38to it. First of all,
• 01:04:39you know, I'll stress technology,
• 01:04:41technology, technology. If we can
• 01:04:42we just the more technologies
• 01:04:44we could bring to bear
• 01:04:45on this to either have
• 01:04:46ways of measuring our physical
• 01:04:47and social environment or to
• 01:04:49have markers of our physical
• 01:04:50and social environment, which is
• 01:04:51where epigenomics can come in.
• 01:04:53And so epigenomics sort of
• 01:04:54gets clumped in with genomics,
• 01:04:56but indeed, epigenomics is oftentimes
• 01:04:58a reflection of our environment
• 01:05:00if we can learn. So
• 01:05:01that's one way, technology innovation.
• 01:05:03The other way, this is
• 01:05:04why we have these very
• 01:05:05large population scale cohort studies.
• 01:05:08The biggest one in the
• 01:05:08United States is the all
• 01:05:09of us research program in
• 01:05:11the UK. The leading cohort
• 01:05:12study worldwide is is, is
• 01:05:15the UK Biobank where they
• 01:05:16have collected massive amounts of,
• 01:05:18of data from individuals where
• 01:05:20they've included social, physical environment,
• 01:05:22genomic data, epigenomic data, etcetera,
• 01:05:24etcetera, and start to develop
• 01:05:26correlations. It becomes a data
• 01:05:27analysis challenge, but that's the
• 01:05:29other way to do it.
• 01:05:30So
• 01:05:31sort of on those are
• 01:05:32but but we should never
• 01:05:33underestimate
• 01:05:34the complexity
• 01:05:35of physiology or pathophysiology.
• 01:05:38But, honestly, that's a concern
• 01:05:39for doing the the gen
• 01:05:41sequencing team. New words, they're
• 01:05:43just finding awful lot of
• 01:05:44stuff where people are just
• 01:05:45gonna get freaked out by
• 01:05:46stuff, which is Which why
• 01:05:48and and we probably and
• 01:05:49which is why that we
• 01:05:50don't want that tsunami of
• 01:05:51fear to come in. However,
• 01:05:54knowing which rare diseases they
• 01:05:55may have, knowing their pharmacogenomic
• 01:05:57profile, knowing their cancer predisposition,
• 01:05:59We that's what we need
• 01:06:00to study.
• 01:06:01And we also need to
• 01:06:02decide nobody first of all,
• 01:06:04nobody should have to have
• 01:06:04that done if they don't
• 01:06:05want, and then nobody should
• 01:06:06have to get information they
• 01:06:07don't want. And I think
• 01:06:09you'll have a like everything
• 01:06:10else in life, people have
• 01:06:11big
• 01:06:12a a range of ideas
• 01:06:13of what they wanna know
• 01:06:14and when they wanna know
• 01:06:15it. And there'll be lots
• 01:06:16of questions about it. What
• 01:06:17age should people learn about
• 01:06:19this? I think once they're
• 01:06:20adults, they should make their
• 01:06:21own decisions, and parents will
• 01:06:22decide for kids until then.
• 01:06:24Yes. One more last question
• 01:06:26since I'm
• 01:06:27moderator.
• 01:06:28Yeah. Sure. Yesterday, Craig Venter
• 01:06:30died. Yes. But you didn't
• 01:06:31mention that name in the
• 01:06:32old history story. How do
• 01:06:34you fit that in? So
• 01:06:35so,
• 01:06:36so, boy, so Craig,
• 01:06:38for those who don't, the
• 01:06:39young people here barely maybe
• 01:06:41you didn't even appreciate who
• 01:06:42Craig Van Nuys.
• 01:06:43Craig was a brilliant scientist,
• 01:06:45at first I would say,
• 01:06:46and I'm very sorry that
• 01:06:47he passed away. Brilliant scientist,
• 01:06:49incredible innovator,
• 01:06:52a bit of a renegade.
• 01:06:54And what Craig did was
• 01:06:55he was actually part of
• 01:06:56the Human Genome Project, but
• 01:06:58he got he he got
• 01:06:59a little on but he
• 01:07:00was also somebody
• 01:07:02where he before he got
• 01:07:03involved in the Human Genome
• 01:07:04Project, he was the one
• 01:07:05that invented this idea of
• 01:07:08take a cDNA clone, get
• 01:07:09a little bit of of
• 01:07:10cDNA sequence from it, and
• 01:07:12immediately try to patent it.
• 01:07:14And so he he's always
• 01:07:14been an entrepreneur,
• 01:07:16and it eventually resulted in
• 01:07:17the Supreme Court striking down
• 01:07:19the idea that we should
• 01:07:19be able to patent genes.
• 01:07:21And so he's always wanting
• 01:07:22to move faster and do
• 01:07:23things in the best way.
• 01:07:24So he began participating in
• 01:07:25the Human Genome Project. And
• 01:07:27then at a pivotal point
• 01:07:28in the Genome Project, he
• 01:07:29said, you're going too slow.
• 01:07:31And so he joined a
• 01:07:31comp or he created a
• 01:07:32company called Celera Genomics to
• 01:07:34compete with the Human Genome
• 01:07:36Project and sell access to
• 01:07:37the genomic data for subscription,
• 01:07:40and also started to patent
• 01:07:41genes as well. And and
• 01:07:43so the Human Genome Project
• 01:07:44was releasing its data for
• 01:07:45free, and Craig was selling
• 01:07:46a subscription to access his
• 01:07:48DNA.
• 01:07:48That led to,
• 01:07:50an awkward situation
• 01:07:52of the, you know, the
• 01:07:53government funded and worldwide funded
• 01:07:55effort competing with the private
• 01:07:56sector that for the and
• 01:07:58it's a whole other lecture
• 01:07:59I could give, and I
• 01:07:59do give to classes sometimes,
• 01:08:01that led to President Clinton
• 01:08:03getting involved and Tony Blair
• 01:08:04getting involved to create a
• 01:08:06circumstance where we declared it
• 01:08:08a tie at the draft
• 01:08:09sequence where they said, okay,
• 01:08:11Nope. Every it's a tie.
• 01:08:12Everybody and everybody wins. And
• 01:08:14there was an agreement that
• 01:08:15they would have a White
• 01:08:16House ceremony with with with,
• 01:08:18Bill Clinton and Francis Collins
• 01:08:20and Craig Venter and Tony
• 01:08:21Blair on a on a
• 01:08:23monitor coming in from the
• 01:08:24UK. They declared a tie.
• 01:08:25They then published their draft
• 01:08:27sequences in Science and Nature
• 01:08:28about four months later. And
• 01:08:30then Solera didn't survive. Why?
• 01:08:32Because who would wanna pay
• 01:08:33for something that you were
• 01:08:34gonna get for free? And
• 01:08:35the Genome Project produced free.
• 01:08:36So Craig went on and
• 01:08:37did some other incredible and
• 01:08:39productive things, but there was
• 01:08:41the race, and he he
• 01:08:42made the by the way,
• 01:08:43I'd I'd also give him
• 01:08:44credit. If it wasn't for
• 01:08:45him giving that that competitive,
• 01:08:47really awkward, and at times
• 01:08:48terrifying nudge, because he wanted
• 01:08:50the Genome Project to shut
• 01:08:52down and let him do
• 01:08:52it because then he'd make
• 01:08:53money off his subscriptions,
• 01:08:55he made us go faster.
• 01:08:56And, actually, congress got involved
• 01:08:57and they doubled down and
• 01:08:58they doubled the Genome Project's,
• 01:09:00funding to make us go
• 01:09:01faster. The Genome Project was
• 01:09:03originally slated to be fifteen
• 01:09:04years. I guess now I'm
• 01:09:05reflecting on this. I think
• 01:09:06it probably would have taken
• 01:09:07fifteen years. Craig made us
• 01:09:08go faster. We finished at
• 01:09:09thirteen.
• 01:09:10So any case, yeah, he
• 01:09:11passed away yesterday. He's been
• 01:09:12ill for quite a while.
• 01:09:14Thanks. Thanks very much. Okay.
• 01:09:15Thank you.