Stephen Friend: The hunt for "unexpected genetic heroes"

62,612 views ・ 2014-05-29

TED


μ•„λž˜ μ˜λ¬Έμžλ§‰μ„ λ”λΈ”ν΄λ¦­ν•˜μ‹œλ©΄ μ˜μƒμ΄ μž¬μƒλ©λ‹ˆλ‹€.

λ²ˆμ—­: Wooran Lee κ²€ν† : Gemma Lee
00:12
Approximately 30 years ago,
0
12602
2338
λŒ€λž΅ 30λ…„μ „
00:14
when I was in oncology at the Children's Hospital
1
14940
2693
μ œκ°€ 필라델피아에 μžˆλŠ”
00:17
in Philadelphia,
2
17633
1389
어린이 λ³‘μ›μ˜ μ’…μ–‘ν•™κ³Όμ—μ„œ 근무할 λ•Œ
00:19
a father and a son walked into my office
3
19022
3154
ν•œ 아버지와 아듀이 제 μ‚¬λ¬΄μ‹€λ‘œ λ“€μ–΄μ™”λŠ”λ°
00:22
and they both had their right eye missing,
4
22176
3144
아버지와 아듀은 λͺ¨λ‘ 였λ₯Έμͺ½ 눈이 μ—†μ—ˆμ–΄μš”.
00:25
and as I took the history, it became apparent
5
25320
2811
κ·Έλ“€μ˜ 이야기λ₯Ό λ“€μ—ˆμ„ λ•Œ
00:28
that the father and the son had a rare form
6
28131
2769
κ·Έ λΆ€μžλŠ” ν¬κ·€ν•œ ν˜•νƒœμ˜
00:30
of inherited eye tumor, retinoblastoma,
7
30900
3542
μœ μ „μ  μ•ˆκ΅¬ 쒅양인 망막 λͺ¨μ„Έν¬μ’…을 μ•“μ•˜μŒμ„ μ•Œ 수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€.
00:34
and the father knew that he had passed that fate
8
34442
3114
λ˜ν•œ μ•„λ²„μ§€λŠ” 그런 운λͺ…을
00:37
on to his son.
9
37556
1875
μ•„λ“€μ—κ²Œ 물렀쀀것을 μ•Œκ³  μžˆμ—ˆμŠ΅λ‹ˆλ‹€.
00:39
That moment changed my life.
10
39431
2412
이 μˆœκ°„μ΄ 제 삢을 λ°”κΎΈμ—ˆμ–΄μš”.
00:41
It propelled me to go on
11
41843
1904
μ €λ₯Ό μ •μ§„ν•˜λ„λ‘ ν–ˆκ³ 
00:43
and to co-lead a team that discovered
12
43747
3532
μ—°κ΅¬νŒ€μ„ 곡동 μ§€νœ˜ν•˜μ—¬
00:47
the first cancer susceptibility gene,
13
47279
3197
처음으둜 μ•” κ°μˆ˜μ„± μœ μ „μžλ₯Ό λ°œκ²¬ν•˜κ²Œ ν–ˆμŠ΅λ‹ˆλ‹€.
00:50
and in the intervening decades since then,
14
50476
2721
κ·Έ 이후 μ‹­μˆ˜λ…„λ™μ•ˆ
00:53
there has been literally a seismic shift
15
53197
3420
λ§κ·ΈλŒ€λ‘œ 지각변동과 같은 λ³€ν™”κ°€ 일어났고
00:56
in our understanding of what goes on,
16
56617
2026
μ΄λŠ” μ—°κ΅¬μ˜ μ „λ°˜μ μΈ 이해와
00:58
what genetic variations are sitting behind
17
58643
2888
μ—¬λŸ¬κ°€μ§€μ˜ μ§ˆλ³‘λ“€μ— 영ν–₯을 μ£ΌλŠ”
01:01
various diseases.
18
61531
1559
μœ μ „μž 변화에 λŒ€ν•œ 이해λ₯Ό λ†’μ˜€μ£ .
01:03
In fact, for thousands of human traits,
19
63090
3384
사싀 λΆ„μžκΈ°μ΄ˆλ‘œ μ•Œλ €μ§„,
01:06
a molecular basis that's known for that,
20
66474
2218
μˆ˜μ²œκ°€μ§€μ˜ 인간 μœ μ „μžμ˜ νŠΉμ§•κ³Ό
01:08
and for thousands of people, every day,
21
68692
3295
그리고 맀일 수천λͺ…에 λŒ€ν•œ
01:11
there's information that they gain
22
71987
2081
이런 μ €λŸ° μ§ˆλ³‘μ˜
01:14
about the risk of going on to get this disease
23
74068
2442
λ°œλ³‘ μœ„ν—˜μ„±μ— λŒ€ν•œ
01:16
or that disease.
24
76510
2226
정보λ₯Ό μ–»μŠ΅λ‹ˆλ‹€.
01:18
At the same time, if you ask,
25
78736
2305
그럼 μ—¬λŸ¬λΆ„μ€ μ΄λ ‡κ²Œ μ§ˆλ¬Έν•  수 있겠죠.
01:21
"Has that impacted the efficiency,
26
81041
2707
"그정보듀이 μ‹ μ•½κ°œλ°œμ—
01:23
how we've been able to develop drugs?"
27
83748
2092
νš¨μœ¨μ„ λ†’μ—¬μ£Όμ—ˆλ‚˜μš”?"
01:25
the answer is not really.
28
85840
1782
λ”±νžˆ 그렇진 μ•ŠμŠ΅λ‹ˆλ‹€.
01:27
If you look at the cost of developing drugs,
29
87622
2330
μ‹ μ•½ 개발 λΉ„μš©κ³Ό
01:29
how that's done, it basically hasn't budged that.
30
89952
3389
κ·Έ 개발 방식을 보면 기본적으둜 λ³€ν•˜μ§€ μ•Šμ•˜μ–΄μš”.
01:33
And so it's as if we have the power to diagnose
31
93341
4473
병을 진단할 λŠ₯λ ₯은 μžˆμ§€λ§Œ
01:37
yet not the power to fully treat.
32
97814
2812
μ™„λ²½ν•˜κ²Œ μΉ˜λ£Œν•  λŠ₯λ ₯이 μ—†λŠ”κ²ƒκ³Ό κ°™μ•„μš”.
01:40
And there are two commonly given reasons
33
100626
2466
그리고 'μ™œ κ·Έλ ‡κ²Œ λ˜λŠ”κ°€' μ—λŠ”
01:43
for why that happens.
34
103092
1468
두 가지 μ΄μœ κ°€ μžˆμ–΄μš”.
01:44
One of them is it's early days.
35
104560
3472
μ²«λ²ˆμ§ΈλŠ” 연ꡬ 초기이기 λ•Œλ¬Έμ΄μ—μš”.
01:48
We're just learning the words, the fragments,
36
108032
3590
μš°λ¦¬λŠ” 이제 단어, 쑰각을 배우고
01:51
the letters in the genetic code.
37
111622
1776
μœ μ „μž μ½”λ“œμ˜ κΈ€μžλ₯Ό λ°°μš°λŠ” μ€‘μž…λ‹ˆλ‹€.
01:53
We don't know how to read the sentences.
38
113398
2155
μš°λ¦¬λŠ” λ¬Έμž₯듀을 μ½λŠ”λ‹€κ±°λ‚˜
01:55
We don't know how to follow the narrative.
39
115553
2570
이야기λ₯Ό μ΄ν•΄ν•˜μ§€ λͺ»ν•˜μ£ .
01:58
The other reason given is that
40
118123
2479
또 λ‹€λ₯Έ μ΄μœ λŠ”
02:00
most of those changes are a loss of function,
41
120602
2218
λŒ€λΆ€λΆ„μ˜ μœ μ „μ§ˆλ³‘μ΄ μœ μ „μžμ˜ κΈ°λŠ₯상싀을 λ™λ°˜ν•˜λ©°
02:02
and it's actually really hard to develop drugs
42
122820
2925
μ‹€μ œλ‘œ κ·Έ κΈ°λŠ₯을 λ³΅κ΅¬ν•˜λŠ” 약을
02:05
that restore function.
43
125745
1915
κ°œλ°œν•˜λŠ” 것은 맀우 νž˜λ“€κΈ° λ•Œλ¬Έμž…λ‹ˆλ‹€.
02:07
But today, I want us to step back
44
127660
2182
ν•˜μ§€λ§Œ 였늘 μš°λ¦¬λŠ” ν•œκ±ΈμŒ λ¬ΌλŸ¬λ‚˜
02:09
and ask a more fundamental question,
45
129842
2028
쒀더 근본적인 μ§ˆλ¬Έμ„ ν–ˆμœΌλ©΄ ν•©λ‹ˆλ‹€.
02:11
and ask, "What happens if we're thinking
46
131870
2189
"λ§Œμ•½μ— μš°λ¦¬κ°€ 이 λͺ¨λ“  것에 λŒ€ν•΄
02:14
about this maybe in the wrong context?"
47
134059
2733
잘λͺ»λœ λ§₯λ½μ—μ„œ μƒκ°ν•˜κ³  μžˆλ‹€λ©΄ μ–΄λ–»κ²Œ λ κΉŒμš”?"
02:16
We do a lot of studying of those who are sick
48
136792
3159
μš°λ¦¬λŠ” μ•„ν”„κ³ 
02:19
and building up long lists
49
139951
2600
λ³€ν˜•λœ μœ μ „μž μš”μ†Œλ₯Ό 길게 μŒ“μ€ μ‚¬λžŒλ“€μ„
02:22
of altered components.
50
142551
3118
λŒ€μƒμœΌλ‘œ λ§Žμ€ 연ꡬλ₯Ό ν•©λ‹ˆλ‹€.
02:25
But maybe, if what we're trying to do
51
145669
2399
ν•˜μ§€λ§Œ μ•„λ§ˆ μš°λ¦¬κ°€ μ‹œλ„ν•˜λŠ” 것이
02:28
is to develop therapies for prevention,
52
148068
3222
μ§ˆλ³‘μ„ μ˜ˆλ°©ν•˜λŠ” μΉ˜λ£Œλ²•μ„ κ°œλ°œν•˜λŠ” 것이라면
02:31
maybe what we should be doing
53
151290
1553
μ–΄μ©Œλ©΄ μš°λ¦¬κ°€ ν•΄μ•Ό ν•  일은
02:32
is studying those who don't get sick.
54
152843
2382
병에 μ•ˆ κ±Έλ¦¬λŠ” μ‚¬λžŒλ“€μ— λŒ€ν•œ 연ꡬ가 μ•„λ‹κΉŒμš”?
02:35
Maybe we should be studying those
55
155225
2347
μ–΄μ©Œλ©΄ μš°λ¦¬κ°€ 연ꡬ해야 ν•˜λŠ” λŒ€μƒμ€
02:37
that are well.
56
157572
2175
κ±΄κ°•ν•œ μ‚¬λžŒλ“€μ΄ μ•„λ‹κΉŒμš”?
02:39
A vast majority of those people
57
159747
1797
ν•˜μ§€λ§Œ λŒ€λ‹€μˆ˜μ˜ κ±΄κ°•ν•œ μ‚¬λžŒλ“€μ€
02:41
are not necessarily carrying a particular
58
161544
2336
μœ μ „μ  λΆ€ν•˜λ‚˜ μœ„ν—˜μΈμžλ₯Ό
02:43
genetic load or risk factor.
59
163880
1936
가지고 μžˆμ§€ μ•ŠμŠ΅λ‹ˆλ‹€.
02:45
They're not going to help us.
60
165816
1984
그듀은 도움이 λ˜μ§€ μ•Šκ² μ£ .
02:47
There are going to be those individuals
61
167800
1599
또 이런 μ‚¬λžŒλ“€λ„ μžˆμ„κ±°μ—μš”.
02:49
who are carrying a potential future risk,
62
169399
2669
μ§ˆλ³‘μ˜ μœ„ν—˜μ΄ μž μž¬λ˜μ–΄ 있으며
02:52
they're going to go on to get some symptom.
63
172068
1844
곧 증상이 λ‚˜νƒ€λ‚  μ‚¬λžŒλ“€μž…λ‹ˆλ‹€.
02:53
That's not what we're looking for.
64
173912
1788
μš°λ¦¬κ°€ μ°ΎλŠ” μ‚¬λžŒμ΄ μ•„λ‹ˆμ£ .
02:55
What we're asking and looking for is,
65
175700
1848
μš°λ¦¬κ°€ 찾고자 ν•˜λŠ” μ‚¬λžŒμ€
02:57
are there a very few set of individuals
66
177548
2770
μ•„μ£Ό 적은 수의 μ‚¬λžŒλ“€λ‘œ
03:00
who are actually walking around
67
180318
2836
μ‹€μ œ κ±΄κ°•νžˆ μƒν™œν•˜κ³  있으며
03:03
with the risk that normally would cause a disease,
68
183154
4019
일반적인 경우라면 λ°œλ³‘μ΄ λ˜μ—ˆμ„ μœ„ν—˜μΈμžλ₯Ό 가지고 μžˆμœΌλ‚˜
03:07
but something in them, something hidden in them
69
187173
2963
κ·Έλ“€μ•ˆμ— μˆ¨μ–΄μžˆλŠ” 무언가가
03:10
is actually protective
70
190136
1834
μ‹€μ œλ‘œ λ°œλ³‘μ„ 막고
03:11
and keeping them from exhibiting those symptoms?
71
191970
3175
μ§ˆλ³‘μ˜ 증상이 λ‚˜νƒ€λ‚˜λŠ” 것을 막고 μžˆλŠ” 그런 μ‚¬λžŒλ“€ μž…λ‹ˆλ‹€.
03:15
If you're going to do a study like that, you can imagine
72
195145
2053
μ—¬λŸ¬λΆ„μ΄ 이런 연ꡬλ₯Ό 할거라면 상상해 λ³΄μ„Έμš”.
03:17
you'd like to look at lots and lots of people.
73
197198
2832
μ—¬λŸ¬λΆ„μ€ μˆ˜λ§Žμ€ μ‚¬λžŒλ“€μ„ λ§Œλ‚˜μ•Ό ν•˜κ³ 
03:20
We'd have to go and have a pretty wide study,
74
200030
3292
μƒλ‹Ήνžˆ 넓은 λ²”μœ„μ˜ 연ꡬλ₯Ό 진행해야 ν• κ±°μ—μš”.
03:23
and we realized that actually
75
203322
1735
그리고 μš°λ¦¬λŠ” 깨달은
03:25
one way to think of this is,
76
205057
1529
μ‹€μ œμ μΈ 연ꡬ 방법쀑 ν•˜λ‚˜λŠ”
03:26
let us look at adults who are over 40 years of age,
77
206586
4277
40μ„Έκ°€ λ„˜μ€ μ–΄λ₯Έλ“€μ„ μ—°κ΅¬λŒ€μƒμœΌλ‘œ ν•©λ‹ˆλ‹€.
03:30
and let's make sure that we look at those
78
210863
2970
λ¬Όλ‘  어릴적 κ±΄κ°•ν–ˆλ˜
03:33
who were healthy as kids.
79
213833
1480
μ‚¬λžŒλ“€μ„ 쑰사해야겠죠.
03:35
They might have had individuals in their families
80
215313
2402
μ•„λ§ˆ κ·Έλ“€μ˜ 가쑱쀑
03:37
who had had a childhood disease,
81
217715
1812
μœ λ…„κΈ° μ§ˆν™˜μ„ μ•“μ•˜λ˜ μ‚¬λžŒλ„ μžˆμ„ κ±°μ—μš”.
03:39
but not necessarily.
82
219527
1506
ν•˜μ§€λ§Œ ν•„μˆ˜μ‘°κ±΄μ€ μ•„λ‹™λ‹ˆλ‹€.
03:41
And let's go and then screen those
83
221033
2767
그리고 μš°λ¦¬λŠ” κ·Έμ€‘μ—μ„œ
03:43
to find those who are carrying genes
84
223800
1993
μœ λ…„κΈ° μ§ˆν™˜μ— λŒ€ν•œ μœ μ „μžλ₯Ό 가진
03:45
for childhood diseases.
85
225793
1678
λŒ€μƒμ„ κ±ΈλŸ¬λƒ…λ‹ˆλ‹€.
03:47
Now, some of you, I can see you
86
227471
1564
μ§€κΈˆ λͺ‡ 뢄듀은 손을 μœ„λ‘œ 올리며
03:49
putting your hands up going, "Uh, a little odd.
87
229035
3295
"μ–΄? 쑰금 μ΄μƒν•œλ°?"
03:52
What's your evidence
88
232330
1417
"이것이 μ‹€ν˜„κ°€λŠ₯ ν•œκ±΄κ°€μš”?"
03:53
that this could be feasible?"
89
233747
1662
라고 λ¬ΌμœΌμ‹€ κ±°μ—μš”.
03:55
I want to give you two examples.
90
235409
2064
μ œκ°€ 두 가지 μ˜ˆν™”λ₯Ό λ“€λ €λ“œλ¦¬κ² μŠ΅λ‹ˆλ‹€.
03:57
The first comes from San Francisco.
91
237473
2948
첫번째둜 μƒŒν”„λž€μ‹œμŠ€μ½”μ—μ„œ μžˆμ—ˆλ˜ μΌμž…λ‹ˆλ‹€.
04:00
It comes from the 1980s and the 1990s,
92
240421
2941
1980λ…„λŒ€μ™€ 1990λ…„λŒ€ 사이에 μžˆμ—ˆλ˜ 일이죠.
04:03
and you may know the story where
93
243362
2394
μ•„λ§ˆ μ—¬λŸ¬λΆ„λ„ 이야기λ₯Ό 아싀지도 λͺ¨λ₯΄κ² μ–΄μš”.
04:05
there were individuals who had very high levels
94
245756
2397
μ•„μ£Ό 높은 수치의
04:08
of the virus HIV.
95
248153
1268
HIV λ°”μ΄λŸ¬μŠ€λ₯Ό 가진 μ‚¬λžŒλ“€μ΄ μžˆμ—ˆμŠ΅λ‹ˆλ‹€.
04:09
They went on to get AIDS.
96
249421
2479
그듀은 μ—μ΄μ¦ˆμ— κ±Έλ Έμ£ .
04:11
But there was a very small set of individuals
97
251900
2317
ν•˜μ§€λ§Œ μ•„μ£Ό 적은 수의 μ‚¬λžŒλ“€μ€
04:14
who also had very high levels of HIV.
98
254217
2968
λ§ˆμ°¬κ°€μ§€λ‘œ μ•„μ£Ό 높은 수치의 HIV λ°”μ΄λŸ¬μŠ€λ₯Ό κ°€μ‘Œμ§€λ§Œ
04:17
They didn't get AIDS.
99
257185
1386
μ—μ΄μ¦ˆμ— 걸리지 μ•Šμ•˜μ–΄μš”.
04:18
And astute clinicians tracked that down,
100
258571
2962
그리고 눈치빠λ₯Έ μž„μƒ μ˜ν•™μžλ“€μ΄ μ‘°μ‚¬ν•΄λ³΄λ‹ˆ,
04:21
and what they found was they were carrying mutations.
101
261533
3387
그듀은 λŒμ—°λ³€μ΄ μœ μ „μžλ₯Ό 가지고 μžˆμ—ˆμŠ΅λ‹ˆλ‹€.
04:24
Notice, they were carrying mutations from birth
102
264920
3085
그듀은 νƒœμ–΄λ‚  λ•ŒλΆ€ν„° λŒμ—°λ³€μ΄ μœ μ „μžλ₯Ό 가지고 μžˆμ—ˆκ³ 
04:28
that were protective, that were protecting them
103
268005
2015
κ·Έ μœ μ „μžλ“€μ€ λ³΄κ· μžλ“€μ„ λ³΄ν˜Έν•˜μ—¬
04:30
from going on to get AIDS.
104
270020
1641
μ—μ΄μ¦ˆμ— 걸리지 μ•Šλ„λ‘ ν–ˆμŠ΅λ‹ˆλ‹€.
04:31
You may also know that actually a line of therapy
105
271661
3165
μ‹€μ œλ‘œ 이 사싀에 κ·Όκ±°ν•œ μΉ˜λ£Œλ²•μ΄
04:34
has been coming along based on that fact.
106
274826
3120
λ“±μž₯ν•œ 것을 μ•„μ‹œλŠ” 뢄도 κ³„μ‹€κ±°μ—μš”.
04:37
Second example, more recent, is elegant work
107
277946
3224
λ‘λ²ˆμ§Έ μ˜ˆλŠ” 쒀더 μ΅œκ·Όμ— μ§„ν–‰λœ
04:41
done by Helen Hobbs,
108
281170
1403
ν—¬λ Œ ν™‰μŠ€κ°€ μ§„ν–‰ν•œ ν›Œλ₯­ν•œ μ—°κ΅¬μ˜€μŠ΅λ‹ˆλ‹€.
04:42
who said, "I'm going to look at individuals
109
282573
2662
κ·Έλ…€λŠ” "λ‚˜λŠ” ν˜ˆμ€‘ μ§€λ°©μˆ˜μΉ˜κ°€
04:45
who have very high lipid levels,
110
285235
2716
μ•„μ£Ό 높은 μ‚¬λžŒλ“€μ„ μ—°κ΅¬ν•΄μ„œ
04:47
and I'm going to try to find those people
111
287951
1939
높은 μˆ˜μΉ˜μ—λ„
04:49
with high lipid levels
112
289890
1802
심μž₯μ§ˆν™˜μ΄ λ°œμƒν•˜μ§€ μ•Šμ€
04:51
who don't go on to get heart disease."
113
291692
2168
그런 μ‚¬λžŒλ“€μ„ μ°Ύκ² μ–΄μš”" 라고 ν–ˆμ£ .
04:53
And again, what she found was
114
293860
2438
그리고 μ—­μ‹œ κ·Έλ…€κ°€ μ°Ύμ•„λ‚Έ 것은
04:56
some of those individuals had mutations
115
296298
2560
κ·Έλ“€ λͺ‡λͺ‡μ΄ μœ μ „μž λŒμ—°λ³€μ΄λ₯Ό 가지고 μžˆμ—ˆκ³ 
04:58
that were protective from birth that kept them,
116
298858
2719
νƒœμ–΄λ‚  λ•ŒλΆ€ν„° 그듀을 λ³΄ν˜Έν–ˆλ‹€λŠ” μ‚¬μ‹€μ΄μ—ˆμ£ .
05:01
even though they had high lipid levels,
117
301577
1445
높은 μ§€λ°©μˆ˜μΉ˜μ—λ„ λΆˆκ΅¬ν•˜κ΅¬μš”.
05:03
and you can see this is an interesting way
118
303022
3371
μ—¬λŸ¬λΆ„λ“€μ΄ λ³΄μ‹œλŠ” κ²ƒμ²˜λŸΌ 이것은 μ•„μ£Ό ν₯λ―Έλ‘­μŠ΅λ‹ˆλ‹€.
05:06
of thinking about how you could develop
119
306393
1961
μš°λ¦¬κ°€ μ–΄λ–»κ²Œ 예방 μΉ˜λ£Œλ²•μ„
05:08
preventive therapies.
120
308354
2260
κ°œλ°œν•  수 μžˆμ„μ§€ μƒκ°ν•˜κ²Œ ν•΄μ£Όμ£ .
05:10
The project that we're working on
121
310614
1944
μš°λ¦¬κ°€ μ—°κ΅¬ν•˜κ³  μžˆλŠ” ν”„λ‘œμ νŠΈλŠ”
05:12
is called "The Resilience Project:
122
312558
2462
"회볡 ν”„λ‘œμ νŠΈ:
05:15
A Search for Unexpected Heroes,"
123
315020
1400
μ˜ˆμƒλ°–μ˜ μ˜μ›…μ„ μ°Ύμ•„μ„œ"라고 λΆ€λ¦…λ‹ˆλ‹€.
05:16
because what we are interested in doing is saying,
124
316420
2490
μ™œλƒν•˜λ©΄ μš°λ¦¬κ°€ ν₯λ―Έλ₯Ό 가지고 μžˆλŠ” 것은
05:18
can we find those rare individuals
125
318910
2648
'μš°λ¦¬κ°€ κ·Έ μˆ¨κ²¨μ§„ λ°©μ–΄ μš”μ†Œλ₯Ό μ§€λ‹Œ
05:21
who might have these hidden protective factors?
126
321558
4325
ν¬κ·€ν•œ μ‚¬λžŒλ“€μ„ 찾을 수 μžˆμ„κΉŒ'μ£ .
05:25
And in some ways, think of it as a decoder ring,
127
325883
2980
μ—¬λŸ¬κ°€μ§€ μ μ—μ„œ 이것을 '해독 λ°˜μ§€' 둜 μƒκ°ν•˜μ‹œλ©΄ λ˜μš”.
05:28
a sort of resilience decoder ring
128
328863
1926
νšŒλ³΅μ„ μœ„ν•œ 해독 λ°˜μ§€κ°™μ€ κ±°μ£ .
05:30
that we're going to try to build.
129
330789
1632
μš°λ¦¬κ°€ 이것을 λ§Œλ“€λ €κ³  ν•©λ‹ˆλ‹€.
05:32
We've realized that we should do this in a systematic way,
130
332421
3849
μš°λ¦¬λŠ” 이것을 μ²΄κ³„μ μœΌλ‘œ 진행해야 함을 κΉ¨λ‹¬μ•˜μŠ΅λ‹ˆλ‹€.
05:36
so we've said, let's take every single
131
336270
2627
κ·Έλž˜μ„œ μš°λ¦¬λŠ” λͺ¨λ“ 
05:38
childhood inherited disease.
132
338897
1243
μœ λ…„κΈ° μœ μ „μ§ˆλ³‘μ„ λͺ¨μ•˜μ–΄μš”.
05:40
Let's take them all, and let's pull them back a little bit
133
340140
2564
κ·Έ λͺ¨λ“  μ§ˆλ³‘λ“€μ€‘μ—μ„œ
05:42
by those that are known to have severe symptoms,
134
342704
3186
μ‹¬κ°ν•œ 증상을 가진 κ²ƒμœΌλ‘œ μ•Œλ €μ§„ 병듀을 μ‘°μ‚¬ν•˜κΈ°λ‘œ ν–ˆμ–΄μš”.
05:45
where the parents, the child,
135
345890
1920
λΆ€λͺ¨λ‚˜ μ•„μ΄λΏμ•„λ‹ˆλΌ
05:47
those around them would know
136
347810
1050
κ·Έμ£Όλ³€μ—μ„œ 그듀이 μ•„νŒ λ˜ κ±Έ
05:48
that they'd gotten sick,
137
348860
1330
μ•Œ 수 μžˆλŠ” 그런 μ§ˆλ³‘μ„μš”.
05:50
and let's go ahead and then frame them again
138
350190
3700
그리고 μš°λ¦¬λŠ” 더 λ‚˜μ•„κ°€ κ·Έ μ§ˆλ³‘μ„ λ‹€μ‹œ λΆ„λ₯˜ν•˜κΈ°λ‘œ ν–ˆμŠ΅λ‹ˆλ‹€.
05:53
by those parts of the genes where we know
139
353890
2581
μš°λ¦¬κ°€ μ•Œκ³  μžˆλŠ” μœ μ „μž 뢀뢄쀑
05:56
that there is a particular alteration
140
356471
2507
λ³€μ§ˆμ„ 일으켜
05:58
that is known to be highly penetrant
141
358978
2798
μ§ˆλ³‘μ˜ 원인이 λ˜λŠ”
06:01
to cause that disease.
142
361776
2654
μœ μ „μžμ˜ νŠΉμ • λΆ€λΆ„λ“€λ‘œ λΆ„λ₯˜ν•©λ‹ˆλ‹€.
06:04
Where are we going to look?
143
364430
1228
μ–΄λ””μ„œ μ°Ύμ•„μ•Ό ν• κΉŒμš”?
06:05
Well, we could look locally. That makes sense.
144
365658
2488
λ¬Όλ‘  κ΅­λ‚΄μ—μ„œ μ°Ύμ•„λ³Ό 수 있겠죠.
06:08
But we began to think, maybe we should look
145
368146
2261
ν•˜μ§€λ§Œ μš°λ¦¬λŠ” 곧
06:10
all over the world.
146
370407
1451
'μ „ μ„Έκ³„μ—μ„œ 찾자' 라고 μƒκ°ν–ˆμŠ΅λ‹ˆλ‹€.
06:11
Maybe we should look not just here
147
371858
1653
μ—¬κΈ°μ—μ„œλ§Œ 찾을 게 μ•„λ‹ˆλΌ
06:13
but in remote places where their might be
148
373511
1960
멀리 떨어진 곳에
06:15
a distinct genetic context,
149
375471
3030
λ…νŠΉν•œ μœ μ „μžμ  ꡬ쑰가 μ‘΄μž¬ν•  수 있고
06:18
there might be environmental factors
150
378501
1642
κ·Έ μž₯μ†Œμ— μžˆλŠ” ν™˜κ²½μ  μš”μ†Œκ°€
06:20
that protect people.
151
380143
1382
κ·Έμ‚¬λžŒλ“€μ„ λ³΄ν˜Έν• μ§€ λͺ¨λ₯΄λ‹ˆκΉŒμš”.
06:21
And let's look at a million individuals.
152
381525
4462
그리고 μš°λ¦¬λŠ” 100만λͺ…μ˜ μ‚¬λžŒμ„ μ‘°μ‚¬ν•˜κΈ°λ‘œ ν–ˆμŠ΅λ‹ˆλ‹€.
06:25
Now the reason why we think it's a good time
153
385987
2970
μ§€κΈˆμ΄ 이 ν”„λ‘œμ νŠΈλ₯Ό μ§„ν–‰ν•˜λŠ”λ°
06:28
to do that now
154
388957
1072
쒋은 μ‹œκΈ°μΈ μ΄μœ λ“€μ΄ μžˆμŠ΅λ‹ˆλ‹€.
06:30
is, in the last couple of years,
155
390029
1760
졜근 μˆ˜λ…„κ°„
06:31
there's been a remarkable plummeting in the cost
156
391789
2588
λ‘λ“œλŸ¬μ§„ λΉ„μš© κ°μ†Œκ°€ μžˆμ—ˆκΈ° λ•Œλ¬Έμ΄μ£ .
06:34
to do this type of analysis,
157
394377
2235
이런 μ’…λ₯˜μ˜ λΆ„μ„μž‘μ—…μ΄λ‚˜
06:36
this type of data generation,
158
396612
1739
데이터 생성 μž‘μ—…μ— 말이죠.
06:38
to where it actually costs less to do
159
398351
2608
μ‹€μ œλ‘œ 데이터 생성과 뢄석이
06:40
the data generation and analysis
160
400959
2194
λΉ„μš©μ΄ 더 적게 λ“­λ‹ˆλ‹€.
06:43
than it does to do the sample processing and the collection.
161
403153
3184
ν‘œλ³Έ 가곡과 μˆ˜μ§‘ μž‘μ—…λ³΄λ‹€ 말이죠.
06:46
The other reason is that in the last five years,
162
406337
4304
또 λ‹€λ₯Έ μ΄μœ λŠ” μ§€λ‚œ 5λ…„λ™μ•ˆ
06:50
there have been awesome tools,
163
410641
1964
ν›Œλ₯­ν•œ 도ꡬ듀이 생겼기 λ•Œλ¬Έμ΄μ£ .
06:52
things about network biology, systems biology,
164
412605
2662
이 λ„€νŠΈμ›Œν¬ μƒλ¬Όν•™μ΄λ‚˜ μ‹œμŠ€ν…œ 생물학 같은 도ꡬ듀이
06:55
that have come up that allow us to think
165
415267
1961
λ‚˜νƒ€λ‚˜μ„œ
06:57
that maybe we could decipher
166
417228
1940
μš°λ¦¬κ°€ λ―Έμ§€μ˜ μ˜μ—­μ„
06:59
those positive outliers.
167
419168
2481
ν•΄λ…ν•˜λ„λ‘ 도와주겠죠.
07:01
And as we went around talking to researchers
168
421649
2172
μš°λ¦¬λŠ” 연ꡬ원듀을 λ§Œλ‚˜ 이야기 ν–ˆμŠ΅λ‹ˆλ‹€.
07:03
and institutions
169
423821
1904
μ—°κ΅¬μ†Œλ“€λ„ λ°©λ¬Έν–ˆμ£ .
07:05
and telling them about our story,
170
425725
1569
그리고 우리의 이야기λ₯Ό λ“€λ €μ€¬μ–΄μš”.
07:07
something happened.
171
427294
1667
무슨 일이 μΌμ–΄λ‚¬μ„κΉŒμš”.
07:08
They started saying, "This is interesting.
172
428961
2229
그듀은 "이거 ν₯λ―Έλ‘­λ„€μš”.
07:11
I would be glad to join your effort.
173
431190
3347
κ·Έ λ…Έλ ₯에 ν•©λ₯˜ν•˜κ³  μ‹Άμ–΄μš”.
07:14
I would be willing to participate."
174
434537
1927
μ°Έμ—¬ν•˜κ³  μ‹Άμ–΄μš”."라고 ν–ˆμŠ΅λ‹ˆλ‹€.
07:16
And they didn't say, "Where's the MTA?"
175
436464
2579
그듀은 κ²°μ½” "MTAκ°€ μ–΄λ”” 있죠?"
07:19
They didn't say, "Where is my authorship?"
176
439043
3293
λ˜λŠ” "μ œκ°€ μ €μžκ°€ λ˜λŠ” κ±΄κ°€μš”?"
07:22
They didn't say, "Is this data going to be mine? Am I going to own it?"
177
442336
4611
"μ œκ°€ 연ꡬ 데이터λ₯Ό κ°€μ§€κ²Œ λ˜λ‚˜μš”?" 라고 묻지 μ•Šμ•˜μŠ΅λ‹ˆλ‹€.
07:26
They basically said, "Let's work on this
178
446947
2279
그듀은 단지
07:29
in an open, crowd-sourced, team way
179
449226
2881
μ˜€ν”ˆ ν¬λΌμš°λ“œ μ†Œμ‹±μœΌλ‘œ
07:32
to do this decoding."
180
452107
3074
ν•¨κ»˜ 해독을 ν•΄λ΄…μ‹œλ‹€." 라고 ν–ˆμ£ .
07:35
Six months ago, we locked down
181
455181
2515
6κ°œμ›”μ „ μš°λ¦¬λŠ”
07:37
the screening key for this decoder.
182
457696
3315
이 해독기λ₯Ό μœ„ν•œ 선별기쀀을 ν™•μ •ν–ˆμŠ΅λ‹ˆλ‹€.
07:41
My co-lead, a brilliant scientist, Eric Schadt
183
461011
4578
이 ν”„λ‘œμ νŠΈμ˜ 곡동 μ§„ν–‰μžμ΄λ©°
07:45
at the Icahn Mount Sinai School of Medicine in New York,
184
465589
3306
λ‰΄μš• 아이칸 μ˜λŒ€ ꡐ수인
07:48
and his team,
185
468895
1392
ν›Œλ₯­ν•œ κ³Όν•™μž 에릭 μƒ·κ³Ό 그의 νŒ€μ€
07:50
locked in that decoder key ring,
186
470287
2869
해독을 μœ„ν•œ μ—΄μ‡ λ°˜μ§€λ₯Ό ν™•μ •ν–ˆκ³ 
07:53
and we began looking for samples,
187
473156
2395
μš°λ¦¬λŠ” ν‘œλ³Έλ“€μ„ μ°ΎκΈ° μ‹œμž‘ν–ˆμŠ΅λ‹ˆλ‹€.
07:55
because what we realized is,
188
475551
1486
μ™œλƒν•˜λ©΄ 우리 μƒκ°μ—λŠ”
07:57
maybe we could just go and look
189
477037
1794
μ•„λ§ˆ ν‘œλ³Έλ“€μ„ μ‘°μ‚¬ν•˜λ‹€ 보면
07:58
at some existing samples to get some sense of feasibility.
190
478831
3086
μ‹€ν˜„κ°€λŠ₯성을 찾을 것 κ°™μ•˜μ–΄μš”.
08:01
Maybe we could take two, three percent of the project on,
191
481917
2577
ν”„λ‘œμ νŠΈμ˜ 2, 3%λ₯Ό μ‘°μ‚¬ν•΄μ„œ
08:04
and see if it was there.
192
484494
1417
뭐가 λ‚˜μ˜¬μ§€ λ³΄λŠ”κ±°μ£ .
08:05
And so we started asking people
193
485911
1998
μš°λ¦¬λŠ” μ‚¬λžŒλ“€μ—κ²Œ 묻기 μ‹œμž‘ν–ˆμ–΄μš”.
08:07
such as Hakon at the Children's Hospital in Philadelphia.
194
487909
3537
필라델피아 어린이 병원에 ν•˜μ½˜ λ°•μ‚¬μ—κ²Œ λ¬Όμ—ˆκ³ 
08:11
We asked Leif up in Finland.
195
491446
2245
ν•€λž€λ“œμ— λ ˆμ΄ν”„ ꡐ수,
08:13
We talked to Anne Wojcicki at 23andMe,
196
493691
3673
23andMe의 μ•€ μš°μ§“ν‚€μ™€
08:17
and Wang Jun at BGI,
197
497364
1767
BGI의 μ™•μ€€κ³Ό μ΄μ•ΌκΈ°ν–ˆμ–΄μš”.
08:19
and again, something remarkable happened.
198
499131
2188
그리고 μ—­μ‹œλ‚˜ λ†€λΌμš΄ 일이 μΌμ–΄λ‚¬μ–΄μš”.
08:21
They said, "Huh,
199
501319
1809
그듀은 μ΄λ ‡κ²Œ λ§ν–ˆμ–΄μš”.
08:23
not only do we have samples,
200
503128
1744
"μš°λ¦¬λŠ” ν‘œλ³Έ 보유 뿐 μ•„λ‹ˆλΌ
08:24
but often we've analyzed them,
201
504872
2196
μ’…μ’… 뢄석도 ν•©λ‹ˆλ‹€.
08:27
and we would be glad to go into
202
507068
1487
μš°λ¦¬λŠ” 기꺼이
08:28
our anonymized samples
203
508555
1403
읡λͺ…ν™”λœ ν‘œλ³Έμ„ μ‘°μ‚¬ν•΄μ„œ,
08:29
and see if we could find those
204
509958
2062
당신듀이 μ°ΎλŠ” 것이 μžˆμ„μ§€
08:32
that you're looking for."
205
512020
1163
확인해보죠."
08:33
And instead of being 20,000 or 30,000,
206
513183
2707
2만, 3만개의 ν‘œλ³Έ 뢄석을 λ„˜μ–΄
08:35
last month we passed one half million samples
207
515890
3152
μ§€λ‚œλ‹¬κΉŒμ§€ μš°λ¦¬λŠ”
08:39
that we've already analyzed.
208
519042
1905
50만개의 ν‘œλ³Έ 뢄석을 λ§ˆμ³€μŠ΅λ‹ˆλ‹€.
08:40
So you must be going,
209
520947
1493
μ—¬λŸ¬λΆ„λ“€μ€ λΆ„λͺ…νžˆ μ΄λ ‡κ²Œ 묻겠죠.
08:42
"Huh, did you find any unexpected heroes?"
210
522440
5625
"μ˜ˆμƒλ°–μ˜ μœ μ „μž μ˜μ›…μ„ μ°Ύμ•˜λ‚˜μš”?"
08:48
And the answer is, we didn't find one or two.
211
528065
2583
μš°λ¦¬κ°€ 찾은 건 ν•œλ‘κ°œκ°€ μ•„λ‹ˆμ—μš”.
08:50
We found dozens of these strong candidate
212
530648
3038
μš°λ¦¬λŠ” μˆ˜μ‹­κ°œμ˜ 유λ ₯ν•œ
08:53
unexpected heroes.
213
533686
1729
μ˜ˆμƒλ°–μ˜ μœ μ „μž μ˜μ›… 후보λ₯Ό μ°Ύμ•˜μ–΄μš”.
08:55
So we think that the time is now
214
535415
2697
κ·Έλž˜μ„œ μš°λ¦¬λŠ” λ°”λ‘œ μ§€κΈˆμ΄ 이 ν”„λ‘œμ νŠΈμ˜
08:58
to launch the beta phase of this project
215
538112
2340
베타 단계λ₯Ό μ‹œμž‘ν•  λ•ŒλΌκ³  μƒκ°ν•©λ‹ˆλ‹€.
09:00
and actually start getting prospective individuals.
216
540452
3117
κ°€λŠ₯μ„±μžˆλŠ” μ‚¬λžŒλ“€μ„ λͺ¨μœΌλ €κ³  ν•©λ‹ˆλ‹€.
09:03
Basically all we need is information.
217
543569
3171
기본적으둜 μš°λ¦¬κ°€ ν•„μš”ν•œ 건 μ •λ³΄λΏμž…λ‹ˆλ‹€.
09:06
We need a swab of DNA
218
546740
1659
DNAκ°€ 뭍은 면봉이 ν•„μš”ν•˜κ³ 
09:08
and a willingness to say, "What's inside me?
219
548399
3405
"λ‚΄μ•ˆμ— 무엇이 μžˆμ„κΉŒ?
09:11
I'm willing to be re-contacted."
220
551804
3263
μ €ν•œν…Œ μ—°λ½μ£Όμ„Έμš”." 라고 μžμ›ν•˜λŠ” 마음이 ν•„μš”ν•˜μ£ .
09:15
Most of us spend our lives,
221
555067
3791
우리 λŒ€λΆ€λΆ„μ€ 인생을 μ‚΄λ©΄μ„œ
09:18
when it comes to health and disease,
222
558858
1954
건강과 μ§ˆλ³‘μ— μžˆμ–΄μ„œλŠ”
09:20
acting as if we're voyeurs.
223
560812
3080
λ°©κ΄€μžμ²˜λŸΌ ν–‰λ™ν•©λ‹ˆλ‹€.
09:23
We delegate the responsibility
224
563892
2337
μš°λ¦¬λŠ”
09:26
for the understanding of our disease,
225
566229
2043
μ§ˆλ³‘μ˜ 이해와
09:28
for the treatment of our disease,
226
568272
1872
μ§ˆλ³‘μ˜ μΉ˜λ£Œμ— λŒ€ν•œ μ±…μž„μ„
09:30
to anointed experts.
227
570144
3536
μ „λ¬Έκ°€λ“€μ—κ²Œ μœ„μž„ν•©λ‹ˆλ‹€.
09:33
In order for us to get this project to work,
228
573680
3340
이 ν”„λ‘œμ νŠΈκ°€ μ„±κ³΅ν•˜λ €λ©΄
09:37
we need individuals to step up
229
577020
2150
κ°œκ°œμΈλ“€μ΄ μžμ›ν•˜μ—¬
09:39
in a different role and to be engaged,
230
579170
3892
각각의 역할을 μˆ˜ν–‰ν•˜λ©° μ°Έμ—¬ν•΄μ•Ό ν•©λ‹ˆλ‹€.
09:43
to realize this dream,
231
583062
2925
이 κΏˆκ°™μ€ 일을 μ‹€ν˜„μ‹œν‚€λ €λ©΄,
09:45
this open crowd-sourced project,
232
585987
3135
이 μ˜€ν”ˆ ν¬λΌμš°λ“œ μ†Œμ‹± ν”„λ‘œμ νŠΈκ°€ μ„±κ³΅ν•˜λ €λ©΄,
09:49
to find those unexpected heroes,
233
589122
3680
'μ˜ˆμƒλ°–μ˜ μ˜μ›…λ“€'을 λ°œκ²¬ν•˜λ €λ©΄,
09:52
to evolve from the current concepts
234
592802
2660
ν˜„μž¬μ˜ μžμ›κ³Ό μ œμ•½μ˜
09:55
of resources and constraints,
235
595462
2334
κ°œλ…μ—μ„œ λ°œμ „ν•˜λ €λ©΄,
09:57
to design those preventive therapies,
236
597796
3251
μ˜ˆλ°©μΉ˜λ£Œλ²•μ„ μ„€κ³„ν•˜λ €λ©΄,
10:01
and to extend it beyond childhood diseases,
237
601047
2773
그리고 μœ λ…„κΈ° μ§ˆλ³‘μ„ λ„˜μ–΄
10:03
to go all the way up to ways
238
603820
1577
더 λ‚˜μ•„κ°€
10:05
that we could look at Alzheimer's or Parkinson's,
239
605397
3871
μ•ŒμΈ ν•˜μ΄λ¨Έλ³‘μ΄λ‚˜ νŒŒν‚¨μŠ¨λ³‘μ„ μ—°κ΅¬ν•˜λ €λ©΄,
10:09
we're going to need us
240
609268
2262
μš°λ¦¬λŠ” 우리 μ•ˆμ„ μ‚΄νŽ΄λ³΄λ©°
10:11
to be looking inside ourselves and asking,
241
611530
3106
μ΄λ ‡κ²Œ λ¬Όμ–΄μ•Ό ν•΄μš”.
10:14
"What are our roles?
242
614636
2204
"우리의 역할은 무엇인가?
10:16
What are our genes?"
243
616840
1673
우리의 μœ μ „μžλŠ” 무엇인가?"
10:18
and looking within ourselves for information
244
618513
2785
그리고 우리 μ•ˆμ— μžˆλŠ” 정보λ₯Ό μ°Ύμ•„μ•Ό ν•©λ‹ˆλ‹€.
10:21
we used to say we should go to the outside,
245
621298
2642
μ „μ—λŠ” μ™ΈλΆ€μ˜ μ „λ¬Έκ°€μ—κ²Œ
10:23
to experts,
246
623940
1208
μ˜μ‘΄ν–ˆλ˜ κ·Έ 정보λ₯Όμš”.
10:25
and to be willing to share that with others.
247
625148
4052
그리고 κ·Έ 정보λ₯Ό λ‹€λ₯Έ μ‚¬λžŒκ³Ό λ‚˜λˆ„λ €λŠ” μžμ„Έκ°€ ν•„μš”ν•˜μ£ .
10:29
Thank you very much.
248
629200
3558
κ°μ‚¬ν•©λ‹ˆλ‹€.
10:32
(Applause)
249
632758
1815
(λ°•μˆ˜)
이 μ›Ήμ‚¬μ΄νŠΈ 정보

이 μ‚¬μ΄νŠΈλŠ” μ˜μ–΄ ν•™μŠ΅μ— μœ μš©ν•œ YouTube λ™μ˜μƒμ„ μ†Œκ°œν•©λ‹ˆλ‹€. μ „ 세계 졜고의 μ„ μƒλ‹˜λ“€μ΄ κ°€λ₯΄μΉ˜λŠ” μ˜μ–΄ μˆ˜μ—…μ„ 보게 될 κ²ƒμž…λ‹ˆλ‹€. 각 λ™μ˜μƒ νŽ˜μ΄μ§€μ— ν‘œμ‹œλ˜λŠ” μ˜μ–΄ μžλ§‰μ„ 더블 ν΄λ¦­ν•˜λ©΄ κ·Έκ³³μ—μ„œ λ™μ˜μƒμ΄ μž¬μƒλ©λ‹ˆλ‹€. λΉ„λ””μ˜€ μž¬μƒμ— 맞좰 μžλ§‰μ΄ μŠ€ν¬λ‘€λ©λ‹ˆλ‹€. μ˜κ²¬μ΄λ‚˜ μš”μ²­μ΄ μžˆλŠ” 경우 이 문의 양식을 μ‚¬μš©ν•˜μ—¬ λ¬Έμ˜ν•˜μ‹­μ‹œμ˜€.

https://forms.gle/WvT1wiN1qDtmnspy7