TED2014
Stephen Friend: The hunt for "unexpected genetic heroes"
斯蒂芬·福蘭德: 挖掘潛藏的基因英雄
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我們可以從因遺傳基因得病或沒得病的人身上知道些什麼？有著最具遺傳性的疾病，卻只有一些家族成員會發病，而帶著一樣基因的其他人卻逃過一劫。斯蒂芬·福蘭德建議我們開始研究那些依然健康的家族成員。聽聽看「恢復力計畫」是如何為了收集遺傳基因資料而耗費極大努力，而這計畫也許可以幫助解碼遺傳性疾病。
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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大約是在三十年前
00:14
when I was in oncology at the Children's Hospital
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當我還在費城一間兒童醫院的腫瘤科
00:17
in Philadelphia,
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工作的時候
00:19
a father and a son walked into my office
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一位爸爸帶著兒子走進我的辦公室
00:22
and they both had their right eye missing,
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他們都失去了右眼
00:25
and as I took the history, it became apparent
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在我翻查病歷之中，明顯發現
00:28
that the father and the son had a rare form
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父子倆都患有罕見形式的
00:30
of inherited eye tumor, retinoblastoma,
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遺傳性眼瘤，視網膜母細胞瘤，
00:34
and the father knew that he had passed that fate
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爸爸知道是他將這個厄運
00:37
on to his son.
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傳給他兒子的。
00:39
That moment changed my life.
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那一刻改變了我的人生。
00:41
It propelled me to go on
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它鼓勵我繼續工作
00:43
and to co-lead a team that discovered
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並且去領導一個首先發現
00:47
the first cancer susceptibility gene,
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癌症易感基因的團隊。
00:50
and in the intervening decades since then,
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從那時以來的幾十年之間，
00:53
there has been literally a seismic shift
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簡直是發生了一場巨變，
00:56
in our understanding of what goes on,
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對於我們所認知的一切，
00:58
what genetic variations are sitting behind
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以及各種疾病背後所隱藏的
01:01
various diseases.
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遺傳變異。
01:03
In fact, for thousands of human traits,
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事實上，數千個人類遺傳特徵
01:06
a molecular basis that's known for that,
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是已知的分子基礎。
01:08
and for thousands of people, every day,
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而對於數千個人，每一天，
01:11
there's information that they gain
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他們都會得到
01:14
about the risk of going on to get this disease
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關於患有此疾病或其他疾病
01:16
or that disease.
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風險的訊息
01:18
At the same time, if you ask,
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同時，如果你問道：
01:21
"Has that impacted the efficiency,
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「若它已經影響了功效，
01:23
how we've been able to develop drugs?"
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我們要怎麼做才能開發出新藥？」
01:25
the answer is not really.
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答案並不確定。
01:27
If you look at the cost of developing drugs,
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如果你去查看開發藥物的成本，
01:29
how that's done, it basically hasn't budged that.
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以及它是如何完成的，
基本上它並無太大改變。
基本上它並無太大改變。
01:33
And so it's as if we have the power to diagnose
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所以這就像是我們有能力去診斷，
01:37
yet not the power to fully treat.
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卻沒有能力去全力救治病人。
01:40
And there are two commonly given reasons
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這裡有兩個常見的原因
01:43
for why that happens.
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說明為什麼會有這種狀況發生 :
01:44
One of them is it's early days.
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其一是，還在初期階段，
01:48
We're just learning the words, the fragments,
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我們才剛了解到遺傳密碼中的詞彙
01:51
the letters in the genetic code.
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片段還有字母。
01:53
We don't know how to read the sentences.
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我們並不知道如何讀出整段句子，
01:55
We don't know how to follow the narrative.
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我們也不知道怎麼接續整個故事。
01:58
The other reason given is that
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另一個原因是
02:00
most of those changes are a loss of function,
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大部分變化的發生是因為功能的喪失，
02:02
and it's actually really hard to develop drugs
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事實上，真的很難去開發
02:05
that restore function.
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具有恢復功能的藥物。
02:07
But today, I want us to step back
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但今天，我要大家退一步，
02:09
and ask a more fundamental question,
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問一個更基本的問題，
02:11
and ask, "What happens if we're thinking
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「如果我們假想
02:14
about this maybe in the wrong context?"
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這是在個前後關係錯誤的情況又會怎麼樣?」
02:16
We do a lot of studying of those who are sick
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我們對於那些生病的人做了很多研究，
02:19
and building up long lists
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也建立了一長串
02:22
of altered components.
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構成因素的列表。
02:25
But maybe, if what we're trying to do
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但也許，若我們試著去做的
02:28
is to develop therapies for prevention,
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是開發一種預防疾病的療法；
02:31
maybe what we should be doing
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也許我們應該做的
02:32
is studying those who don't get sick.
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是去研究那些沒有生病的人；
02:35
Maybe we should be studying those
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也許我們真的該去研究那些
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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這些人絕大多數
02:41
are not necessarily carrying a particular
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未必攜帶著特定的
02:43
genetic load or risk factor.
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遺傳基因或危險因素。
02:45
They're not going to help us.
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這樣的人不會幫到我們什麼。
02:47
There are going to be those individuals
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但他們未來將會是
02:49
who are carrying a potential future risk,
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潛在的高危險群
02:52
they're going to go on to get some symptom.
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他們很有機會得到一些症狀，
02:53
That's not what we're looking for.
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但這也不是我們要找的。
02:55
What we're asking and looking for is,
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我們正在尋找的是
02:57
are there a very few set of individuals
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有沒有少數的個體
03:00
who are actually walking around
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在我們身邊活得好好的，
03:03
with the risk that normally would cause a disease,
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事實上卻處在隨時
會患上各種疾病的風險中，
會患上各種疾病的風險中，
03:07
but something in them, something hidden in them
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但某個東西在他們身體裡，隱藏在深處
03:10
is actually protective
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實際上是具保護性的，
03:11
and keeping them from exhibiting those symptoms?
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並克制他們顯現出症狀？
03:15
If you're going to do a study
like that, you can imagine
like that, you can imagine
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如果你打算進行此類研究，你可以想像
03:17
you'd like to look at lots and lots of people.
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你會想要研究好多好多人。
03:20
We'd have to go and have a pretty wide study,
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我們必須去實施一個特別廣泛的研究，
03:23
and we realized that actually
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並且我們發現事實上
03:25
one way to think of this is,
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有一種思考方式可以告訴我們這是什麼
03:26
let us look at adults who are over 40 years of age,
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讓我們先看看年過40的成人，
03:30
and let's make sure that we look at those
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然後確保那些人
03:33
who were healthy as kids.
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在孩提時代也是健康的。
03:35
They might have had individuals in their families
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在他們的家庭中也許有人
03:37
who had had a childhood disease,
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曾經在幼年發病
03:39
but not necessarily.
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但卻不是十分嚴重。
03:41
And let's go and then screen those
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讓我們去篩選那些
03:43
to find those who are carrying genes
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有攜帶兒童期疾病
03:45
for childhood diseases.
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基因的人。
03:47
Now, some of you, I can see you
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現在，我可以看到你們有些人
03:49
putting your hands up going, "Uh, a little odd.
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手想要舉起來說：「蛤？這有點怪。
03:52
What's your evidence
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你有什麼證據
03:53
that this could be feasible?"
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可以證明這是可行的?」
03:55
I want to give you two examples.
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我想給你們舉兩個例子。
03:57
The first comes from San Francisco.
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第一個是發生在舊金山，
04:00
It comes from the 1980s and the 1990s,
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1980 到 1990 年代這個時期，
04:03
and you may know the story where
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你也許知道這個情況：
04:05
there were individuals who had very high levels
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曾經有些人被高水平的
04:08
of the virus HIV.
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人類免疫缺陷病毒（HIV）所感染，
04:09
They went on to get AIDS.
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他們接著患上了愛滋病。
04:11
But there was a very small set of individuals
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但有少部分人
04:14
who also had very high levels of HIV.
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同樣也有高水平的 HIV 病毒，
04:17
They didn't get AIDS.
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他們卻沒有得愛滋病。
04:18
And astute clinicians tracked that down,
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機敏的臨床醫生追蹤下來，
04:21
and what they found was
they were carrying mutations.
they were carrying mutations.
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發現他們身上帶有基因變異。
04:24
Notice, they were carrying mutations from birth
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注意！他們是自從出生就有此
04:28
that were protective, that were protecting them
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保護作用的變異，
讓他們不至於得到愛滋。
04:30
from going on to get AIDS.
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04:31
You may also know that actually a line of therapy
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你也許知道事實上有一連串治療
04:34
has been coming along based on that fact.
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是根據這事實而研發出來的。
04:37
Second example, more recent, is elegant work
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第二個較近來的例子，是個漂亮的工作
04:41
done by Helen Hobbs,
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由海倫·霍布斯完成。
04:42
who said, "I'm going to look at individuals
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她說 : 「我要去研究那些
04:45
who have very high lipid levels,
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高脂肪水平的人。
04:47
and I'm going to try to find those people
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然後再從這些
04:49
with high lipid levels
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高血脂水平的人裡面
04:51
who don't go on to get heart disease."
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找出沒有得到心臟疾病的人。」
04:53
And again, what she found was
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再一次，她也發現
04:56
some of those individuals had mutations
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在這之中的一些人也有變異，
04:58
that were protective from birth that kept them,
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也是從他們出生時就開始保護著他們，
05:01
even though they had high lipid levels,
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儘管他們的脂肪水平很高。
05:03
and you can see this is an interesting way
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各位可以看到這是個有趣的方式
05:06
of thinking about how you could develop
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去思考我們該如何發展出
05:08
preventive therapies.
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預防疾病的療法。
05:10
The project that we're working on
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而現在我們正在做的計畫
05:12
is called "The Resilience Project:
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叫做「恢復力計畫：
05:15
A Search for Unexpected Heroes,"
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搜索潛藏的基因英雄。」
05:16
because what we are interested in doing is saying,
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因為我們感興趣的就是
05:18
can we find those rare individuals
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我們是否能夠找到那些
可能擁有保護作用遺傳基因的少數人？
05:21
who might have these hidden protective factors?
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05:25
And in some ways, think of it as a decoder ring,
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在某些方面，想像它是個解碼環，
05:28
a sort of resilience decoder ring
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一種我們正試著建立的
05:30
that we're going to try to build.
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一個恢復力的解碼環。
05:32
We've realized that we should
do this in a systematic way,
do this in a systematic way,
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我們已了解到必須有條理的方式去建立，
05:36
so we've said, let's take every single
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所以就之前提過的，我們先來看每一個
05:38
childhood inherited disease.
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兒童期發病的遺傳性疾病。
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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我們先全部研究一遍，
退後一步，
05:42
by those that are known to have severe symptoms,
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透過那些嚴重症狀病患
05:45
where the parents, the child,
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身邊知道他們曾生病過的
05:47
those around them would know
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父母、子女和其他人，
05:48
that they'd gotten sick,
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05:50
and let's go ahead and then frame them again
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接著我們透過已知的
05:53
by those parts of the genes where we know
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某些特定的世道交替原則，
05:56
that there is a particular alteration
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而得出有些變異位於
05:58
that is known to be highly penetrant
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有著很高遺傳機率的基因上
06:01
to cause that disease.
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再去發展並表達出這些基因片段。
06:04
Where are we going to look?
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我們會關注哪些地方？
06:05
Well, we could look locally. That makes sense.
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我們可以從當地開始，這合乎情理。
06:08
But we began to think, maybe we should look
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但我們又想，也許我們應該關注
06:10
all over the world.
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這整個世界。
06:11
Maybe we should look not just here
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我們該關注的不只是在一個地方，
06:13
but in remote places where their might be
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還有偏遠地區，
06:15
a distinct genetic context,
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那裡可能會有與其他不同的遺傳基因背景，
06:18
there might be environmental factors
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更有可能會有某些
06:20
that protect people.
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保護人們的環境因素。
06:21
And let's look at a million individuals.
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讓我們來檢視一百萬個人。
06:25
Now the reason why we think it's a good time
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現在，我們覺得這時候
是這麼做的好時機，
06:28
to do that now
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06:30
is, in the last couple of years,
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因為在過去的幾年，
06:31
there's been a remarkable plummeting in the cost
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從事此類型分析的花費、
06:34
to do this type of analysis,
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這數據生成類型的費用
06:36
this type of data generation,
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明顯地暴跌。
06:38
to where it actually costs less to do
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事實上數據生成以及分析
比樣本處理及收集
06:40
the data generation and analysis
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06:43
than it does to do the sample
processing and the collection.
processing and the collection.
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花的錢還要少。
06:46
The other reason is that in the last five years,
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另一個原因是在最近五年裡
06:50
there have been awesome tools,
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有很不錯的工具以及
06:52
things about network biology, systems biology,
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有關網路生物學、系統生物學的東西，
06:55
that have come up that allow us to think
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被發明出現來讓我們思考
06:57
that maybe we could decipher
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我們能夠解碼
06:59
those positive outliers.
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這絕對異常值的可能性。
07:01
And as we went around talking to researchers
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就當我們到處和研究人員
07:03
and institutions
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及機構談話，
07:05
and telling them about our story,
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告訴他們我們的故事，
07:07
something happened.
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有件事發生了。
07:08
They started saying, "This is interesting.
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他們進而開始說：「這真是有趣。
07:11
I would be glad to join your effort.
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我願意加入幫忙，
07:14
I would be willing to participate."
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我很樂意參與。」
07:16
And they didn't say, "Where's the MTA?"
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他們並沒有問：「有醫療技術助理嗎? 」
07:19
They didn't say, "Where is my authorship?"
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他們也沒有問：「我有沒有著作權? 」
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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他們更沒有問：「這資料會不會是我的？我能夠擁有它嗎？
07:26
They basically said, "Let's work on this
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他們基本上只說了：「我們就一起
07:29
in an open, crowd-sourced, team way
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用開放的、大眾資源、團隊的方式
07:32
to do this decoding."
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來解碼吧！」
07:35
Six months ago, we locked down
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六個月前，我們鎖定了
07:37
the screening key for this decoder.
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這解碼環的篩選鍵。
07:41
My co-lead, a brilliant scientist, Eric Schadt
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我的共同領導，艾里克沙特，一個出色的科學家，
07:45
at the Icahn Mount Sinai
School of Medicine in New York,
School of Medicine in New York,
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在紐約的伊坎西奈山醫學院，
07:48
and his team,
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以及他的團隊，
07:50
locked in that decoder key ring,
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鎖定了一個解碼環的鑰匙圈，
07:53
and we began looking for samples,
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所以我們開始尋找樣本，
07:55
because what we realized is,
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因為我們了解到的是
07:57
maybe we could just go and look
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也許我們可以直接去看
07:58
at some existing samples to
get some sense of feasibility.
get some sense of feasibility.
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那些存在的樣本，去發現一些可行性。
08:01
Maybe we could take two, three
percent of the project on,
percent of the project on,
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也許這個計畫我們可以先做個兩三成
08:04
and see if it was there.
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然後再看看可不可行。
08:05
And so we started asking people
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所以我們就開始詢問人們
08:07
such as Hakon at the Children's Hospital in Philadelphia.
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比如在費城兒童醫院的哈康主任、
08:11
We asked Leif up in Finland.
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在芬蘭的雷夫、
08:13
We talked to Anne Wojcicki at 23andMe,
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基因技術公司 23andMe 的創辦人安妮．沃西基、
08:17
and Wang Jun at BGI,
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華大基因的王俊。
08:19
and again, something remarkable happened.
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又一次，一些顯著的事情發生了。
08:21
They said, "Huh,
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他們說：「哈，
08:23
not only do we have samples,
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我們不只有樣本，
08:24
but often we've analyzed them,
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我們還要去分析他們，
08:27
and we would be glad to go into
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我們很樂意去檢視
08:28
our anonymized samples
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匿名的樣本，
08:29
and see if we could find those
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去看看我們能不能找到
08:32
that you're looking for."
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你們正在找的東西。」
08:33
And instead of being 20,000 or 30,000,
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我們分析的樣本不只是兩、三萬而已，
08:35
last month we passed one half million samples
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上個月我們已分析超過 50 萬。
08:39
that we've already analyzed.
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08:40
So you must be going,
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所以你一定會說
08:42
"Huh, did you find any unexpected heroes?"
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「嘿！你找到潛藏的基因英雄了嗎？」
08:48
And the answer is, we didn't find one or two.
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答案是，我們不只找到一、兩個。
08:50
We found dozens of these strong candidate
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我們找到了許多個強大的
08:53
unexpected heroes.
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基因英雄候選人。
08:55
So we think that the time is now
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所以我們認為現在是時候
08:58
to launch the beta phase of this project
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展開這個計劃的測試階段，
09:00
and actually start getting prospective individuals.
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實際上也開始有了預期中的對象。
09:03
Basically all we need is information.
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基本上我們所需要的是資訊。
09:06
We need a swab of DNA
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我們需要棉棒來取樣基因，
09:08
and a willingness to say, "What's inside me?
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以及自願說出「我身體裡面有什麼？」
09:11
I'm willing to be re-contacted."
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我願意再次得到聯繫。」
09:15
Most of us spend our lives,
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當涉及到健康與疾病，
09:18
when it comes to health and disease,
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我們大部分都為此傾注了心血
09:20
acting as if we're voyeurs.
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表現地就像是偷窺狂一樣。
09:23
We delegate the responsibility
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我們將責任委託給
09:26
for the understanding of our disease,
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能了解疾病、
09:28
for the treatment of our disease,
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能治療疾病的
09:30
to anointed experts.
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權威專家們。
09:33
In order for us to get this project to work,
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為了幫助我們讓計畫有所成效，
09:37
we need individuals to step up
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我們需要有人站出來
09:39
in a different role and to be engaged,
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以一個不同的角色來參與，
09:43
to realize this dream,
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去實現這個夢想，
09:45
this open crowd-sourced project,
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也需要這對外開放的大眾資源計畫
09:49
to find those unexpected heroes,
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來找到那些潛藏的英雄們，
09:52
to evolve from the current concepts
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從目前我們對資源與限制的概念
09:55
of resources and constraints,
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逐漸發展到
09:57
to design those preventive therapies,
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發明出預防疾病的治療、
10:01
and to extend it beyond childhood diseases,
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擴展範圍到兒童期疾病之外，
10:03
to go all the way up to ways
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在整個過程中，我們可以發展到
10:05
that we could look at Alzheimer's or Parkinson's,
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研究阿茲海默症及帕金森氏症，
10:09
we're going to need us
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我們需要
10:11
to be looking inside ourselves and asking,
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捫心自問：
10:14
"What are our roles?
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「我們的角色是什麼？
10:16
What are our genes?"
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我們的基因是什麼？」
10:18
and looking within ourselves for information
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看看我們自己，想想以前
10:21
we used to say we should go to the outside,
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我們常說應該到走到外面
10:23
to experts,
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去找專家們，
10:25
and to be willing to share that with others.
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然後樂意與人分享。
10:29
Thank you very much.
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非常感謝各位。
10:32
(Applause)
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（掌聲）
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