Stephen Friend: The hunt for "unexpected genetic heroes"

Approximately 30 years ago,

when I was in oncology at the Children's Hospital

in Philadelphia,

a father and a son walked into my office

and they both had their right eye missing,

and as I took the history, it became apparent

that the father and the son had a rare form

of inherited eye tumor, retinoblastoma,

and the father knew that he had passed that fate

on to his son.

That moment changed my life.

It propelled me to go on

and to co-lead a team that discovered

the first cancer susceptibility gene,

and in the intervening decades since then,

there has been literally a seismic shift

in our understanding of what goes on,

what genetic variations are sitting behind

various diseases.

In fact, for thousands of human traits,

a molecular basis that's known for that,

and for thousands of people, every day,

there's information that they gain

about the risk of going on to get this disease

or that disease.

At the same time, if you ask,

"Has that impacted the efficiency,

how we've been able to develop drugs?"

the answer is not really.

If you look at the cost of developing drugs,

how that's done, it basically hasn't budged that.

And so it's as if we have the power to diagnose

yet not the power to fully treat.

And there are two commonly given reasons

for why that happens.

One of them is it's early days.

We're just learning the words, the fragments,

the letters in the genetic code.

We don't know how to read the sentences.

We don't know how to follow the narrative.

The other reason given is that

most of those changes are a loss of function,

and it's actually really hard to develop drugs

that restore function.

But today, I want us to step back

and ask a more fundamental question,

and ask, "What happens if we're thinking

about this maybe in the wrong context?"

We do a lot of studying of those who are sick

and building up long lists

of altered components.

But maybe, if what we're trying to do

is to develop therapies for prevention,

maybe what we should be doing

is studying those who don't get sick.

Maybe we should be studying those

that are well.

A vast majority of those people

are not necessarily carrying a particular

genetic load or risk factor.

They're not going to help us.

There are going to be those individuals

who are carrying a potential future risk,

they're going to go on to get some symptom.

That's not what we're looking for.

What we're asking and looking for is,

are there a very few set of individuals

who are actually walking around

with the risk that normally would cause a disease,

but something in them, something hidden in them

is actually protective

and keeping them from exhibiting those symptoms?

If you're going to do a study like that, you can imagine

you'd like to look at lots and lots of people.

We'd have to go and have a pretty wide study,

and we realized that actually

one way to think of this is,

let us look at adults who are over 40 years of age,

and let's make sure that we look at those

who were healthy as kids.

They might have had individuals in their families

who had had a childhood disease,

but not necessarily.

And let's go and then screen those

to find those who are carrying genes

for childhood diseases.

Now, some of you, I can see you

putting your hands up going, "Uh, a little odd.

What's your evidence

that this could be feasible?"

I want to give you two examples.

The first comes from San Francisco.

It comes from the 1980s and the 1990s,

and you may know the story where

there were individuals who had very high levels

of the virus HIV.

They went on to get AIDS.

But there was a very small set of individuals

who also had very high levels of HIV.

They didn't get AIDS.

And astute clinicians tracked that down,

and what they found was they were carrying mutations.

Notice, they were carrying mutations from birth

that were protective, that were protecting them

from going on to get AIDS.

You may also know that actually a line of therapy

has been coming along based on that fact.

Second example, more recent, is elegant work

done by Helen Hobbs,

who said, "I'm going to look at individuals

who have very high lipid levels,

and I'm going to try to find those people

with high lipid levels

who don't go on to get heart disease."

And again, what she found was

some of those individuals had mutations

that were protective from birth that kept them,

even though they had high lipid levels,

and you can see this is an interesting way

of thinking about how you could develop

preventive therapies.

The project that we're working on

is called "The Resilience Project:

A Search for Unexpected Heroes,"

because what we are interested in doing is saying,

can we find those rare individuals

who might have these hidden protective factors?

And in some ways, think of it as a decoder ring,

a sort of resilience decoder ring

that we're going to try to build.

We've realized that we should do this in a systematic way,

so we've said, let's take every single

childhood inherited disease.

Let's take them all, and let's pull them back a little bit

by those that are known to have severe symptoms,

where the parents, the child,

those around them would know

that they'd gotten sick,

and let's go ahead and then frame them again

by those parts of the genes where we know

that there is a particular alteration

that is known to be highly penetrant

to cause that disease.

Where are we going to look?

Well, we could look locally. That makes sense.

But we began to think, maybe we should look

all over the world.

Maybe we should look not just here

but in remote places where their might be

a distinct genetic context,

there might be environmental factors

that protect people.

And let's look at a million individuals.

Now the reason why we think it's a good time

to do that now

is, in the last couple of years,

there's been a remarkable plummeting in the cost

to do this type of analysis,

this type of data generation,

to where it actually costs less to do

the data generation and analysis

than it does to do the sample processing and the collection.

The other reason is that in the last five years,

there have been awesome tools,

things about network biology, systems biology,

that have come up that allow us to think

that maybe we could decipher

those positive outliers.

And as we went around talking to researchers

and institutions

and telling them about our story,

something happened.

They started saying, "This is interesting.

I would be glad to join your effort.

I would be willing to participate."

And they didn't say, "Where's the MTA?"

They didn't say, "Where is my authorship?"

They didn't say, "Is this data going to be mine? Am I going to own it?"

They basically said, "Let's work on this

in an open, crowd-sourced, team way

to do this decoding."

Six months ago, we locked down

the screening key for this decoder.

My co-lead, a brilliant scientist, Eric Schadt

at the Icahn Mount Sinai School of Medicine in New York,

and his team,

locked in that decoder key ring,

and we began looking for samples,

because what we realized is,

maybe we could just go and look

at some existing samples to get some sense of feasibility.

Maybe we could take two, three percent of the project on,

and see if it was there.

And so we started asking people

such as Hakon at the Children's Hospital in Philadelphia.

We asked Leif up in Finland.

We talked to Anne Wojcicki at 23andMe,

and Wang Jun at BGI,

and again, something remarkable happened.

They said, "Huh,

not only do we have samples,

but often we've analyzed them,

and we would be glad to go into

our anonymized samples

and see if we could find those

that you're looking for."

And instead of being 20,000 or 30,000,

last month we passed one half million samples

that we've already analyzed.

So you must be going,

"Huh, did you find any unexpected heroes?"

And the answer is, we didn't find one or two.

We found dozens of these strong candidate

unexpected heroes.

So we think that the time is now

to launch the beta phase of this project

and actually start getting prospective individuals.

Basically all we need is information.

We need a swab of DNA

and a willingness to say, "What's inside me?

I'm willing to be re-contacted."

Most of us spend our lives,

when it comes to health and disease,

acting as if we're voyeurs.

We delegate the responsibility

for the understanding of our disease,

for the treatment of our disease,

to anointed experts.

In order for us to get this project to work,

we need individuals to step up

in a different role and to be engaged,

to realize this dream,

this open crowd-sourced project,

to find those unexpected heroes,

to evolve from the current concepts

of resources and constraints,

to design those preventive therapies,

and to extend it beyond childhood diseases,

to go all the way up to ways

that we could look at Alzheimer's or Parkinson's,

we're going to need us

to be looking inside ourselves and asking,

"What are our roles?

What are our genes?"

and looking within ourselves for information

we used to say we should go to the outside,

to experts,

and to be willing to share that with others.

Thank you very much.

(Applause)