TED2014
Stephen Friend: The hunt for "unexpected genetic heroes"
斯蒂文.弗兰德: 猎寻“未知的遗传英雄”
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Readability: 4.3
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我们从那些的了遗传性疾病的人那里获知了什么－再大部分遗传病中，只有部分的急停成员发生了疾病，而其他带有同样基因的却能避开它。斯蒂文.弗兰德建议我们应该开始研究那些没有得病的家庭成员。听听这个弹性课题，以巨大的努力来搜集基因资料可以帮助解码遗传性的失调。
Stephen Friend - Open-science advocate
Inspired by open-source software models, Sage Bionetworks co-founder Stephen Friend builds tools that facilitate research sharing on a massive and revolutionary scale. Full bio
Inspired by open-source software models, Sage Bionetworks co-founder Stephen Friend builds tools that facilitate research sharing on a massive and revolutionary scale. Full bio
Double-click the English transcript below to play the video.
00:12
Approximately 30 years ago,
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大约在30年以前，
00:14
when I was in oncology at the Children's Hospital
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当我还在
00:17
in Philadelphia,
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费城儿童医院的肿瘤科
00:19
a father and a son walked into my office
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一对父子走进我的办公室
00:22
and they both had their right eye missing,
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他们两人都没有了右眼，
00:25
and as I took the history, it became apparent
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当我询问了病史，很明显
00:28
that the father and the son had a rare form
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父亲和儿子都患有一种罕见形式的
00:30
of inherited eye tumor, retinoblastoma,
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遗传性的眼睛肿瘤，视网膜母细胞瘤，
00:34
and the father knew that he had passed that fate
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父亲知道他把那种噩运
00:37
on to his son.
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传给了儿子。
00:39
That moment changed my life.
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那个时刻改变了我的生活。
00:41
It propelled me to go on
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它促使我去
00:43
and to co-lead a team that discovered
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带领一个研究小组，并发现了
00:47
the first cancer susceptibility gene,
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第一个肿瘤易感基因，
00:50
and in the intervening decades since then,
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从那时介入起算的十年来，
00:53
there has been literally a seismic shift
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我们在对肿瘤发生的研究上
00:56
in our understanding of what goes on,
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已经有了天翻地覆的进展
00:58
what genetic variations are sitting behind
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暨存在在各种各样的疾病背后
01:01
various diseases.
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的基因变异。
01:03
In fact, for thousands of human traits,
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事实上，数以万计的人类特征中，
01:06
a molecular basis that's known for that,
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就是那些已知的分子基础所决定，
01:08
and for thousands of people, every day,
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对很多人来说，每天
01:11
there's information that they gain
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他们都获得很多信息
01:14
about the risk of going on to get this disease
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关于得上这个
01:16
or that disease.
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或那个疾病的危险。
01:18
At the same time, if you ask,
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同时，如果你问，
01:21
"Has that impacted the efficiency,
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“那对效率有影响吗？”
01:23
how we've been able to develop drugs?"
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我们如何能研发药物？“
01:25
the answer is not really.
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回答是不确定的。
01:27
If you look at the cost of developing drugs,
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如果你看看研发药物的花费
01:29
how that's done, it basically hasn't budged that.
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那是怎么做到的，还没有基本的预算。
01:33
And so it's as if we have the power to diagnose
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那么，就像我们的确有能力来做出诊断
01:37
yet not the power to fully treat.
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但还美有能力来治愈。
01:40
And there are two commonly given reasons
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至于缘何会出现这样的现象
01:43
for why that happens.
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有两个常见的理由
01:44
One of them is it's early days.
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其中之一是早期。
01:48
We're just learning the words, the fragments,
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我们刚刚学会，
01:51
the letters in the genetic code.
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基因编码字母的只言片语
01:53
We don't know how to read the sentences.
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我们不知道怎样阅读整段基因。
01:55
We don't know how to follow the narrative.
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我们不知道怎样理解它的叙述。
01:58
The other reason given is that
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另一个现存的理由是
02:00
most of those changes are a loss of function,
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大部分的基因变化是功能的缺失，
02:02
and it's actually really hard to develop drugs
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实际上很难通过发展药物
02:05
that restore function.
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来重建功能。
02:07
But today, I want us to step back
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但今天，我希望大家后退一步
02:09
and ask a more fundamental question,
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问问更基本的问题，
02:11
and ask, "What happens if we're thinking
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再问，“如果我们关于这些的看法
02:14
about this maybe in the wrong context?"
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是在错误的背景下，那么会发生什么呢？“
02:16
We do a lot of studying of those who are sick
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我们对那些生病的人做了很多研究
02:19
and building up long lists
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并且积攒了一个
02:22
of altered components.
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不同组成的长长的目录。
02:25
But maybe, if what we're trying to do
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但也许，如果我们尝试去做的是
02:28
is to develop therapies for prevention,
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为了预防来发展治疗，
02:31
maybe what we should be doing
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也许我们应该做的
02:32
is studying those who don't get sick.
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是研究那些没有生病的人。
02:35
Maybe we should be studying those
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也许我们应该研究那些
02:37
that are well.
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健康的人。
02:39
A vast majority of those people
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绝大部分的那些人
02:41
are not necessarily carrying a particular
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也许没有承载一个特别的
02:43
genetic load or risk factor.
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遗传累赘或者危险因子。
02:45
They're not going to help us.
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他们对我们没有帮助。
02:47
There are going to be those individuals
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他们将是那些
02:49
who are carrying a potential future risk,
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带有潜在的会发病的危险因子
02:52
they're going to go on to get some symptom.
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他们会有某些症状。
02:53
That's not what we're looking for.
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那不是我们要找的。
02:55
What we're asking and looking for is,
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我们要找的是，
02:57
are there a very few set of individuals
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只有很少的一组个体
03:00
who are actually walking around
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那些没有发病的，
03:03
with the risk that normally would cause a disease,
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但事实上有着能引起疾病的危险因子
03:07
but something in them, something hidden in them
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在他们体内有某些东西，有某些东西藏在里面
03:10
is actually protective
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事实上起着保护作用
03:11
and keeping them from exhibiting those symptoms?
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使他们免于出现那些症状？
03:15
If you're going to do a study
like that, you can imagine
like that, you can imagine
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如果你要做那样一个研究，你能想像
03:17
you'd like to look at lots and lots of people.
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你不得不去看看很多这样的人。
03:20
We'd have to go and have a pretty wide study,
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我们已经有了很大范围的研究，
03:23
and we realized that actually
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我们意识到事实上
03:25
one way to think of this is,
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有一个思考的办法是，
03:26
let us look at adults who are over 40 years of age,
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让我们看看四十岁以上的成年人，
03:30
and let's make sure that we look at those
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让我们确定我们看着那些
03:33
who were healthy as kids.
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像孩子一样健康的人。
03:35
They might have had individuals in their families
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在他们的家庭中，可能有某个人
03:37
who had had a childhood disease,
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在孩提时有了病，
03:39
but not necessarily.
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但也不一定。
03:41
And let's go and then screen those
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让我们到那些
03:43
to find those who are carrying genes
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人群里筛选，看谁携带着
03:45
for childhood diseases.
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在儿童时就发病的基因。
03:47
Now, some of you, I can see you
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现在，你们中的某些人，我能看见你们
03:49
putting your hands up going, "Uh, a little odd.
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高举着手，“呵，有点古怪。
03:52
What's your evidence
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你的证据呢
03:53
that this could be feasible?"
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你能证明这是可行的吗？“
03:55
I want to give you two examples.
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我想给你们两个例子。
03:57
The first comes from San Francisco.
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第一个来自旧金山。
04:00
It comes from the 1980s and the 1990s,
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在1980年和1990年之间，
04:03
and you may know the story where
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你们也许知道
04:05
there were individuals who had very high levels
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那些个体有着很高水平的
04:08
of the virus HIV.
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艾滋病毒
04:09
They went on to get AIDS.
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他们后来得上了艾滋。
04:11
But there was a very small set of individuals
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但有很少一组个体
04:14
who also had very high levels of HIV.
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虽然有着很高的艾滋病毒水平
04:17
They didn't get AIDS.
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他们没有得病。
04:18
And astute clinicians tracked that down,
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精明的临床医生追踪下去，
04:21
and what they found was
they were carrying mutations.
they were carrying mutations.
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他们发现的是那些人携带着基因变异。
04:24
Notice, they were carrying mutations from birth
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注意，他们的变异是天生的。
04:28
that were protective, that were protecting them
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那具有保护性，保护他们
04:30
from going on to get AIDS.
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不会得上艾滋病。
04:31
You may also know that actually a line of therapy
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你也许还知道有一个治疗流程
04:34
has been coming along based on that fact.
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根据这个事实而启动了。
04:37
Second example, more recent, is elegant work
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第二个例子，最近的，是由
04:41
done by Helen Hobbs,
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海伦.霍伯斯做的漂亮的工作，
04:42
who said, "I'm going to look at individuals
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她说，“我会研究那些有
04:45
who have very high lipid levels,
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着很高血脂水平的个体，
04:47
and I'm going to try to find those people
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我会努力来发现这些
04:49
with high lipid levels
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有着高血脂水平
04:51
who don't go on to get heart disease."
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但没有患心脏病的人。“
04:53
And again, what she found was
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再一次的，她发现的是
04:56
some of those individuals had mutations
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一些个体基因上有突变，
04:58
that were protective from birth that kept them,
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而那些天生的突变保护他们免于疾病，
05:01
even though they had high lipid levels,
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尽管他们有着很高水平的血脂。
05:03
and you can see this is an interesting way
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你能明白这是个有趣途径
05:06
of thinking about how you could develop
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它让你想到你怎样才能拓展出
05:08
preventive therapies.
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预防性治疗。
05:10
The project that we're working on
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我们在进行的项目是
05:12
is called "The Resilience Project:
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叫做“弹性课题：
05:15
A Search for Unexpected Heroes,"
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对未预料的英雄的研究，“
05:16
because what we are interested in doing is saying,
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因为我们感兴趣做的是
05:18
can we find those rare individuals
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我们能找到少见的
05:21
who might have these hidden protective factors?
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有着这种隐性的保护因子个体吗？
05:25
And in some ways, think of it as a decoder ring,
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在某种意义上，把它当做解码器环，
05:28
a sort of resilience decoder ring
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是一种
05:30
that we're going to try to build.
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我们尝试建造的具有弹性的解码器环。
05:32
We've realized that we should
do this in a systematic way,
do this in a systematic way,
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我们已经意识到我们应该
系统性地尝试，
系统性地尝试，
05:36
so we've said, let's take every single
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我们已经说过，让我们拿每一个
05:38
childhood inherited disease.
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儿童遗传病来研究。
05:40
Let's take them all, and let's
pull them back a little bit
pull them back a little bit
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让我们看着所有的人，让
我们把它们范围缩小一点点
我们把它们范围缩小一点点
05:42
by those that are known to have severe symptoms,
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用那些
05:45
where the parents, the child,
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父母，孩子有着已知的严重的症状的病来说，
05:47
those around them would know
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那些周围的人都知道
05:48
that they'd gotten sick,
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他们会生病，
05:50
and let's go ahead and then frame them again
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让我们继续并且给他们再次定位
05:53
by those parts of the genes where we know
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用我们已经知道的某些部分的基因
05:56
that there is a particular alteration
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那些有着特别改变而
05:58
that is known to be highly penetrant
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总所周知是引起
06:01
to cause that disease.
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那种疾病的高度相关的基因。
06:04
Where are we going to look?
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我们要看的是什么呢？
06:05
Well, we could look locally. That makes sense.
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首先，我们可以局部地看，那很有道理。
06:08
But we began to think, maybe we should look
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然后我们想想，也许我们应该看看
06:10
all over the world.
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全世界。
06:11
Maybe we should look not just here
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也许我们应该看的不只是这儿
06:13
but in remote places where their might be
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而是在遥远的地方
06:15
a distinct genetic context,
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可能有着独特的基因背景
06:18
there might be environmental factors
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也许是环境的因素
06:20
that protect people.
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保护者人们。
06:21
And let's look at a million individuals.
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让我们看一百万个体。
06:25
Now the reason why we think it's a good time
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我们认为现在是个很好的时候，
06:28
to do that now
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理由是，现在
06:30
is, in the last couple of years,
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以及在过去的几年中，
06:31
there's been a remarkable plummeting in the cost
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做这种类型的分析，
06:34
to do this type of analysis,
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这种类型的数据推导，
06:36
this type of data generation,
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在花费上有着显著的垂直的下降
06:38
to where it actually costs less to do
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事实上
06:40
the data generation and analysis
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在数据推导和分析上的花费
06:43
than it does to do the sample
processing and the collection.
processing and the collection.
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少于标本的处理和收集。
06:46
The other reason is that in the last five years,
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在过去的五年中，另一个原因是，
06:50
there have been awesome tools,
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有了特别棒的工具，
06:52
things about network biology, systems biology,
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像联网生物学，系统生物学
06:55
that have come up that allow us to think
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发展起来后，可以让我们想到
06:57
that maybe we could decipher
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也许我们可能解译
06:59
those positive outliers.
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那些正性的结果。
07:01
And as we went around talking to researchers
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当我们跟研究人员
07:03
and institutions
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和研究所讨论
07:05
and telling them about our story,
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并且告诉他们我们的故事，
07:07
something happened.
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和那些发生的事情。
07:08
They started saying, "This is interesting.
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他们开始说，“这有些意思，
07:11
I would be glad to join your effort.
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我很高兴来跟你一起的努力，
07:14
I would be willing to participate."
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我愿意参加。”
07:16
And they didn't say, "Where's the MTA?"
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他们并没有说，“MTA在哪里？”
07:19
They didn't say, "Where is my authorship?"
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“他们没有说，”我的作者署名在哪里？“
07:22
They didn't say, "Is this data going
to be mine? Am I going to own it?"
to be mine? Am I going to own it?"
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他们没有说，“这个结果是我的吗？
我是这个结果的主人吗？“
我是这个结果的主人吗？“
07:26
They basically said, "Let's work on this
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他们只是说，”让我们
07:29
in an open, crowd-sourced, team way
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在一个开放的，有人群资源的，以合作的方法
07:32
to do this decoding."
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来一起工作，解开这个难题。“
07:35
Six months ago, we locked down
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六个月之前，我们锁定了
07:37
the screening key for this decoder.
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这个难题的筛选关键。
07:41
My co-lead, a brilliant scientist, Eric Schadt
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我的同僚，一个非常聪明的科学家，诶瑞克.夏特
07:45
at the Icahn Mount Sinai
School of Medicine in New York,
School of Medicine in New York,
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在纽约的爱肯蒙特塞纳医学院，
07:48
and his team,
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他的小组
07:50
locked in that decoder key ring,
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锁定了那个解码环的关键，
07:53
and we began looking for samples,
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我们开始寻找标本，
07:55
because what we realized is,
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因为我们意识到的是，
07:57
maybe we could just go and look
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也许我们可以继续看
07:58
at some existing samples to
get some sense of feasibility.
get some sense of feasibility.
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一些现存的标本来
得到某些。。
得到某些。。
08:01
Maybe we could take two, three
percent of the project on,
percent of the project on,
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也许我们能让项目有百分之二或三的进展，
08:04
and see if it was there.
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看看它是否是我们想要的，
08:05
And so we started asking people
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于是我们开始请求一些人
08:07
such as Hakon at the Children's Hospital in Philadelphia.
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比如费城儿童医院的哈空，
08:11
We asked Leif up in Finland.
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和远在芬兰的列夫。
08:13
We talked to Anne Wojcicki at 23andMe,
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我们跟诊所”23和我“的安.沃基次可
08:17
and Wang Jun at BGI,
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以及在BGI的王军也有了对话，
08:19
and again, something remarkable happened.
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又一次，有了很显著的进展。
08:21
They said, "Huh,
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他们说，”呵，
08:23
not only do we have samples,
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我们不仅有标本，
08:24
but often we've analyzed them,
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而且我们还分析过，
08:27
and we would be glad to go into
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我们很愿意来找出
08:28
our anonymized samples
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我们那些匿名的标本，
08:29
and see if we could find those
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看看我们是否能找到那些
08:32
that you're looking for."
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你们在找的。“
08:33
And instead of being 20,000 or 30,000,
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上个月，我们
08:35
last month we passed one half million samples
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有了过50十万的标本而不是2万或三万
08:39
that we've already analyzed.
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我们已经分析过了这些标本。
08:40
So you must be going,
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那么，你肯定会说，
08:42
"Huh, did you find any unexpected heroes?"
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“哈，你发现了那个未知的英雄了吗？”
08:48
And the answer is, we didn't find one or two.
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回答是肯定的。我们不是发现了一个或两个。
08:50
We found dozens of these strong candidate
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我们发现了一打这样的
08:53
unexpected heroes.
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作为未知的英雄的候选
08:55
So we think that the time is now
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现在我们认为是时候
08:58
to launch the beta phase of this project
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来进入这个项目的第二阶段
09:00
and actually start getting prospective individuals.
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实际上是要得到那些有前景的个体。
09:03
Basically all we need is information.
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我们基本上需要的就是信息。
09:06
We need a swab of DNA
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我们需要一些DNA
09:08
and a willingness to say, "What's inside me?
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和参与者自愿地说，“我里面有什么？”
09:11
I'm willing to be re-contacted."
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我愿意你们再跟我接触。“
09:15
Most of us spend our lives,
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我们把自己的大部分生活
09:18
when it comes to health and disease,
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花在健康和疾病上，
09:20
acting as if we're voyeurs.
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好像做了偷窥者一样。
09:23
We delegate the responsibility
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我们有责任
09:26
for the understanding of our disease,
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来弄懂我们的疾病，
09:28
for the treatment of our disease,
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以便来治疗我们的疾病，
09:30
to anointed experts.
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成为在行的专家。
09:33
In order for us to get this project to work,
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为了让这个项目可以运作，
09:37
we need individuals to step up
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我们需要个体站出来
09:39
in a different role and to be engaged,
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在各种角色上参与，
09:43
to realize this dream,
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意识到这个梦想，
09:45
this open crowd-sourced project,
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这个开放的人群资源项目，
09:49
to find those unexpected heroes,
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是为了发现那些未知的英雄们。
09:52
to evolve from the current concepts
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来更新现有概念
09:55
of resources and constraints,
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的来源和限制
09:57
to design those preventive therapies,
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来设计那些预防性的治疗，
10:01
and to extend it beyond childhood diseases,
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并且能够延续和超越儿童时期发生的疾病，
10:03
to go all the way up to ways
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一直上升到
10:05
that we could look at Alzheimer's or Parkinson's,
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我们能够认识海尔滋莫或者巴金森氏疾病的高度，
10:09
we're going to need us
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我们会需要我们
10:11
to be looking inside ourselves and asking,
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深入自己并且问
10:14
"What are our roles?
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“我们的角色是什么？
10:16
What are our genes?"
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我们的基因是什么？”
10:18
and looking within ourselves for information
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从我们自身来寻找信息
10:21
we used to say we should go to the outside,
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我们常说我们应该走出去，
10:23
to experts,
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去成为专家，
10:25
and to be willing to share that with others.
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愿意去跟人分享
10:29
Thank you very much.
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非常感谢
10:32
(Applause)
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（鼓掌）。
ABOUT THE SPEAKER
Stephen Friend - Open-science advocateInspired by open-source software models, Sage Bionetworks co-founder Stephen Friend builds tools that facilitate research sharing on a massive and revolutionary scale.
Why you should listen
While working for Merck, Stephen Friend became frustrated by the slow pace at which big pharma created new treatments for desperate patients. Studying shared models like Wikipedia, Friend realized that the complexities of disease could only be understood -- and combated -- with collaboration and transparency, not by isolated scientists working in secret with proprietary data
In his quest for a solution, Friend co-founded Sage Bionetworks, an organization dedicated to creating strategies and platforms that empower researchers to share and interpret data on a colossal scale -- as well as crowdsource tests for new hypotheses.
As he wrote on CreativeCommons.org, "Our goal is ambitious. We want to take biology from a place where enclosure and privacy are the norm, where biologists see themselves as lone hunter-gatherers working to get papers written, to one where the knowledge is created specifically to fit into an open model where it can be openly queried and transformed."
Stephen Friend | Speaker | TED.com