How digital DNA could help you make better health choices Jun Wang

Today I’m here, actually,
to pose you a question.

What is life?

It has been really puzzling me
for more than 25 years,

and will probably continue doing so
for the next 25 years.

This is the thesis I did
when I was still in undergraduate school.

While my colleagues still treated
computers as big calculators,

I started to teach computers to learn.

I built digital lady beetles

and tried to learn from real lady beetles,
just to do one thing:

search for food.

And after very simple neural network –

genetic algorithms and so on –

look at the pattern.

They’re almost identical to real life.

A very striking learning experience
for a twenty-year-old.

Life is a learning program.

When you look
at all of this wonderful world,

every species has
its own learning program.

The learning program is genome,

and the code of that program is DNA.

The different genomes of each species
represent different survival strategies.

They represent hundreds of millions
of years of evolution.

The interaction between
every species' ancestor

and the environment.

I was really fascinated about the world,

about the DNA,

about, you know, the language of life,

the program of learning.

So I decided to co-found
the institute to read them.

I read many of them.

We probably read more than half
of the prior animal genomes in the world.

I mean, up to date.

We did learn a lot.

We did sequence, also,
one species many, many times …

human genome.

We sequenced the first Asian.

I sequenced it myself many, many times,

just to take advantage of that platform.

Look at all those repeating base pairs:

ATCG.

You don’t understand anything there.

But look at that one base pair.

Those five letters, the AGGAA.

These five SNPs represent
a very specific haplotype

in the Tibetan population

around the gene called EPAS1.

That gene has been proved –

it’s highly selective –

it’s the most significant signature
of positive selection of Tibetans

for the higher altitude adaptation.

You know what?

These five SNPs were the result
of integration of Denisovans,

or Denisovan-like individuals into humans.

This is the reason
why we need to read those genomes.

To understand history,

to understand what kind
of learning process

the genome has been through
for the millions of years.

By reading a genome,
it can give you a lot of information –

tells you the bugs in the genome –

I mean, birth defects,
monogenetic disorders.

Reading a drop of blood

could tell you why you got a fever,

or it tells you which medicine
and dosage needs to be used

when you’re sick, especially for cancer.

A lot of things could be studied,
but look at that:

30 years ago, we were still poor in China.

Only .67 percent of the Chinese
adult population had diabetes.

Look at now: 11 percent.

Genetics cannot change over 30 years –

only one generation.

It must be something different.

Diet?

The environment?

Lifestyle?

Even identical twins
could develop totally differently.

It could be one becomes
very obese, the other is not.

One develops a cancer
and the other does not.

Not mentioning living
in a very stressed environment.

I moved to Shenzhen 10 years ago …

for some reason, people may know.

If the gene’s under stress,

it behaves totally differently.

Life is a journey.

A gene is just a starting point,

not the end.

You have this statistical risk
of certain diseases when you are born.

But every day you make different choices,

and those choices will increase
or decrease the risk of certain diseases.

But do you know
where you are on the curve?

What’s the past curve look like?

What kind of decisions
are you facing every day?

And what kind of decision is the right one

to make your own right curve
over your life journey?

What’s that?

The only thing you cannot change,

you cannot reverse back,

is time.

Probably not yet; maybe in the future.

(Laughter)

Well, you cannot change
the decision you’ve made,

but can we do something there?

Can we actually try to run
multiple options on me,

and try to predict right
on the consequence,

and be able to make the right choice?

After all,

we are our choices.

These lady beetles came to me afterwards.

25 years ago, I made
the digital lady beetles

to try to simulate real lady beetles.

Can I make a digital me …

to simulate me?

I understand the neural
network could become

much more sophisticated
and complicated there.

Can I make that one,

and try to run multiple options
on that digital me –

to compute that?

Then I could live in different universes,

in parallel, at the same time.

Then I would choose
whatever is good for me.

I probably have the most comprehensive
digital me on the planet.

I’ve spent a lot of dollars
on me, on myself.

And the digital me told me
I have a genetic risk of gout

by all of those things there.

You need different technology to do that.

You need the proteins, genes,

you need metabolized antibodies,

you need to screen all your body

about the bacterias and viruses
covering you, or in you.

You need to have
all the smart devices there –

smart cars, smart house, smart tables,

smart watch, smart phone
to track all of your activities there.

The environment is important –

everything’s important –

and don’t forget the smart toilet.

(Laughter)

It’s such a waste, right?

Every day, so much invaluable information
just has been flushed into the water.

And you need them.

You need to measure all of them.

You need to be able to measure
everything around you

and compute them.

And the digital me told me
I have a genetic defect.

I have a very high risk of gout.

I don’t feel anything now,

I’m still healthy.

But look at my uric acid level.

It’s double the normal range.

And the digital me searched
all the medicine books,

and it tells me, “OK, you could
drink burdock tea” –

I cannot even pronounce it right –

(Laughter)

That is from old Chinese wisdom.

And I drank that tea for three months.

My uric acid has now gone back to normal.

I mean, it worked for me.

All those thousands of years
of wisdom worked for me.

I was lucky.

But I’m probably not lucky for you.

All of this existing
knowledge in the world

cannot possibly be efficient enough
or personalized enough for yourself.

The only way to make
that digital me work …

is to learn from yourself.

You have to ask a lot
of questions about yourself:

“What if?” –

I’m being jet-lagged now here.

You don’t probably see it, but I do.

What if I eat less?

When I took metformin,
supposedly to live longer?

What if I climb Mt. Everest?

It’s not that easy.

Or run a marathon?

What if I drink a bottle of mao-tai,

which is a Chinese liquor,

and I get really drunk?

I was doing a video rehearsal last time
with the folks here,

when I was drunk,

and I totally delivered
a different speech.

(Laughter)

What if I work less, right?

I have been less stressed, right?

So that probably never happened to me,

I was really stressed every day,

but I hope I could be less stressed.

These early studies told us,

even with the same banana,

we have totally different
glucose-level reactions

over different individuals.

How about me?

What is the right breakfast for me?

I need to do two weeks
of controlled experiments,

of testing all kinds of different
food ingredients on me,

and check my body’s reaction.

And I don’t know
the precise nutrition for me,

for myself.

Then I wanted to search
all the Chinese old wisdom

about how I can live longer,
and healthier.

I did it.

Some of them are really unachievable.

I did this once last October,

by not eating for seven days.

I did a fast for seven days
with six partners of mine.

Look at those people.

One smile.

You know why he smiled?

He cheated.

(Laughter)

He drank one cup of coffee at night,

and we caught it from the data.

(Laughter)

We measured everything from the data.

We were able to track them,

and we could really see –

for example, my immune system,

just to give you a little hint there.

My immune system changed
dramatically over 24 hours there.

And my antibody regulates my proteins

for that dramatic change.

And everybody was doing that.

Even if we’re essentially
totally different at the very beginning.

And that probably will be
an interesting treatment in the future

for cancer and things like that.

It becomes very, very interesting.

But something you probably
don’t want to try,

like drinking fecal water
from a healthier individual,

which will make you feel healthier.

This is from old Chinese wisdom.

Look at that, right?

Like 1,700 years ago,

it’s already there, in the book.

But I still hate the smell.

(Laughter)

I want to find out the true way to do it,

maybe find a combination of cocktails
of bacterias and drink it,

it probably will make me better.

So I’m trying to do that.

Even though I’m trying this hard,

it’s so difficult to test out
all possible conditions.

It’s not possible to do
all kinds of experiments at all …

but we do have seven billion
learning programs on this planet.

Seven billion.

And every program
is running in different conditions

and doing different experiments.

Can we all measure them?

Seven years ago,
I wrote an essay in “Science”

to celebrate the human genome’s
10-year anniversary.

I said, “Sequence yourself,

for one and for all.”

But now I’m going to say,

“Digitalize yourself for one and for all.”

When we make this digital me
into a digital we,

when we try to form an internet of life,

when people can learn from each other,

when people can learn
from their experience,

their data,

when people can really form
a digital me by themselves

and we learn from it,

the digital we will be
totally different with a digital me.

But it can only come from the digital me.

And this is what I try to propose here.

Join me –

become we,

and everybody should build up
their own digital me,

because only by that
will you learn more about you,

about me,

about us …

about the question I just posed
at the very beginning:

“What is life?”

Thank you.

(Applause)

Chris Anderson:
One quick question for you.

I mean, the work is amazing.

I suspect one question people have is,

as we look forward to these amazing
technical possibilities

of personalized medicine,

in the near-term it feels like
they’re only going to be affordable

for a few people, right?

It costs many dollars to do
all the sequencing and so forth.

Is this going to lead to a kind of,

you know, increasing inequality?

Or do you have this vision
that the knowledge that you get

from the pioneers

can actually be
pretty quickly disseminated

to help a broader set of recipients?

Jun Wang: Well, good question.

I’ll tell you that seven years ago,
when I co-founded BGI,

and served as the CEO
of the company there,

the only goal there for me to do

was to drive the sequencing cost down.

It started from 100 million dollars
per human genome.

Now, it’s a couple hundred dollars
for a human genome.

The only reason to do it
is to get more people to benefit from it.

So for the digital me,
it’s the same thing.

Now, you probably need,

you know, one million dollars
to digitize a person.

I think it has to be 100 dollars.

It has to be free for many of those people
that urgently need that.

So this is our goal.

And it seems that with all
this merging of the technology,

I’m thinking that in the very near future,

let’s say three to five years,

it will come to reality.

And this is the whole idea
of why I founded iCarbonX,

my second company.

It’s really trying to get the cost down

to a level where every individual
could have the benefit.

CA: All right, so the dream is not
elite health services for few,

it’s to really try

and actually make overall health care
much more cost effective –

JW: But we started
from some early adopters,

people believing ideas and so on,

but eventually, it will become
everybody’s benefit.

CA: Well, Jun, I think
it’s got to be true to say

you’re one of the most amazing
scientific minds on the planet,

and it’s an honor to have you.

JW: Thank you.

(Applause)

今天我来这里,其实
是想问你一个问题。

生活是什么? 超过 25

年一直让我感到困惑

并且可能会
在接下来的 25 年里继续这样做。

这是
我还在读本科时做的论文。

当我的同事们仍然把
计算机当作大计算器时,

我开始教计算机学习。

我制作了数字瓢虫,

并试图向真正的瓢虫学习,
只是为了做一件事:

寻找食物。

在非常简单的神经网络之后——

遗传算法等等——

看看模式。

它们几乎与现实生活相同。

对于一个 20 岁的孩子来说,这是一次非常惊人的学习经历。

生活是一个学习计划。

当你
看到这个美妙的世界时,

每个物种都有
自己的学习计划。

学习程序是基因组

,该程序的代码是 DNA。

每个物种的不同基因组
代表不同的生存策略。

它们代表了
数亿年的进化。

每个物种的祖先

与环境之间的相互作用。

我真的很着迷于这个世界,

关于 DNA,

关于,你知道的,生活的语言

,学习的计划。

所以我决定共同创办
研究所来阅读它们。

我读了很多。

我们可能阅读了世界上一半
以上的先前动物基因组。

我的意思是,最新的。

我们确实学到了很多。

我们也对
一个物种进行了很多很多次的

测序……人类基因组。

我们对第一个亚洲人进行了测序。

我自己测序了很多很多次,

只是为了利用那个平台。

看看所有那些重复的碱基对:

ATCG。

你那里什么都不懂。

但看看那一对碱基。

那五个字母,AGGAA。

这五个 SNP 代表
了藏族人群中一个非常特殊的单倍型,该单倍型

位于

称为 EPAS1 的基因周围。

该基因已被证明——

它具有高度选择性——


是西藏人为适应高海拔而积极选择的最重要标志

你知道吗?

这五个 SNP
是丹尼索瓦人

或类似丹尼索瓦人的个体融入人类的结果。


就是我们需要读取这些基因组的原因。

了解历史

,了解

基因组
数百万年来经历了什么样的学习过程。

通过阅读基因组,
它可以给你很多信息——

告诉你基因组中的错误——

我的意思是,出生缺陷,
单基因疾病。

读一滴血

可以告诉你为什么发烧,

或者告诉你生病时
需要使用哪种药物和剂量

,尤其是癌症。

很多东西是可以研究的,
但是看看那个:

30年前,我们在中国还很穷。

只有 0.67% 的中国
成年人患有糖尿病。

现在看:11%。

基因不能改变超过 30 年——

只有一代人。

它必须是不同的东西。

饮食?

环境?

生活方式?

即使是同卵双胞胎
也可能完全不同。

可能是一个变得
非常肥胖,另一个不是。

一个人患上癌症
,另一个人没有。

更不用说生活
在压力很大的环境中了。

10年前我搬到了深圳……

出于某种原因,人们可能知道。

如果基因处于压力之下,

它的行为就会完全不同。

人生是一场旅程。

基因只是一个起点,

而不是终点。

当您出生时,您就有患某些疾病的统计风险。

但是每天你都会做出不同的选择,

而这些选择会增加
或减少某些疾病的风险。

但是你
知道你在曲线上的什么位置吗?

过去的曲线是什么样子的?

你每天都面临什么样的决定?

什么样的决定是正确的

,可以在你的人生旅程中做出正确的曲线

那是什么?

唯一无法改变

、无法逆转的,

就是时间。

可能还没有; 也许在将来。

(笑声)

好吧,你不能改变
你已经做出的决定,

但我们可以在那里做点什么吗?

我们真的可以尝试
对我运行多个选项,

并尝试正确预测
结果,

并能够做出正确的选择吗?

毕竟,

我们是我们的选择。

这些瓢虫后来来找我。

25 年前,我制作
了数字瓢虫

,试图模拟真实的瓢虫。

我可以制作一个数字我……

来模拟我吗?

我知道神经
网络在那里可能会变得

更加复杂
和复杂。

我可以制作那个,

并尝试
在那个数字我上运行多个选项——

来计算它吗?

然后我可以同时生活在不同的宇宙

中。

然后我会选择
对我有好处的东西。

我可能拥有这个星球上最全面的
数字我。

我花了很多钱
在我身上,在我自己身上。

数字我告诉我

,那里的所有这些东西都有痛风的遗传风险。

你需要不同的技术来做到这一点。

你需要蛋白质、基因,

你需要代谢的抗体,

你需要筛查你全身或身体

里的细菌和病毒

你需要在
那里拥有所有智能设备——

智能汽车、智能房屋、智能桌子、

智能手表、智能手机
来跟踪你在那里的所有活动。

环境很重要——

一切都很重要

——别忘了智能马桶。

(笑声

) 太浪费了,对吧?

每天,这么多宝贵的信息
都被冲进了水里。

你需要它们。

你需要测量所有这些。

您需要能够测量
周围的一切

并计算它们。

数字我告诉我
我有遗传缺陷。

我患痛风的风险很高。

我现在没有任何感觉,

我还很健康。

但是看看我的尿酸水平。

是正常范围的两倍。

数字我搜索了
所有的医学书籍

,它告诉我,“好吧,你可以
喝牛蒡茶”——

我什至无法正确发音——

(笑声)

这是中国古老的智慧。

我喝了三个月的茶。

我的尿酸现在已经恢复正常了。

我的意思是,它对我有用。

所有这些数千年
的智慧都为我工作。

我很幸运。

但我可能对你不走运。

世界上所有这些现有的
知识

对你自己来说都不可能足够有效或足够个性化。

使数字化我发挥作用的唯一方法……

就是向自己学习。

你必须问
很多关于你自己的问题:

“如果?” ——

我现在在这里倒时差。

你可能看不到,但我看到了。

如果我吃得少怎么办?

当我服用二甲双胍时,
据说寿命更长?

如果我攀登珠穆朗玛峰会怎样?

它不是那么容易。

还是跑马拉松?

如果我喝了一瓶

茅台,这是一种中国白酒

,我喝醉了怎么办?

上次我
和这里的人一起做视频排练,

当时我喝醉了

,我发表
了完全不同的演讲。

(笑声)

如果我工作少了怎么办,对吧?

我压力小了,对吧?

所以这可能从来没有发生在我身上,

我每天都很有压力,

但我希望我能减少压力。

这些早期研究告诉我们,

即使使用相同的香蕉,

我们

对不同个体的葡萄糖水平反应也完全不同。

那我呢?

什么是适合我的早餐?

我需要做两周
的对照实验

,在我身上测试各种不同的
食物成分,

并检查我身体的反应。

而且我不知道
我自己的确切营养

然后我想搜索
所有

关于如何活得更久、
更健康的中国古老智慧。

我做的。

其中一些是真的无法实现。

去年 10 月我做了一次

,7 天不吃东西。

我和我的六个伙伴禁食了 7 天

看看那些人。

一笑。

你知道他为什么笑吗?

他作弊。

(笑声)

他晚上喝了一杯咖啡

,我们从数据中捕捉到了它。

(笑声)

我们从数据中测量了一切。

我们能够追踪它们,

并且我们可以真正看到——

例如,我的免疫系统,

只是为了给你一点提示。 在那里,

我的免疫系统
在 24 小时内发生了巨大变化。

我的抗体调节我的蛋白质,

以应对这种戏剧性的变化。

每个人都在这样做。

即使我们一开始就
完全不同。

这可能是

未来癌症和类似疾病的一种有趣的治疗方法。

它变得非常非常有趣。

但是你可能
不想尝试一些事情,

比如喝
一个更健康的人的粪便水,

这会让你感觉更健康。

这是来自古老的中国智慧。

看那个,对吧?

就像 1700 年前一样,

它已经存在于书中。

但我仍然讨厌这种气味。

(笑声)

我想找到真正的方法,

也许找一种混合
了细菌的鸡尾酒然后喝,

它可能会让我变得更好。

所以我正在尝试这样做。

尽管我正在努力尝试,

但要测试
所有可能的条件非常困难。

根本不可能
进行各种实验……

但我们在这个星球上确实有 70 亿个
学习计划。

七十亿。

每个程序
都在不同的条件下运行

并进行不同的实验。

我们都可以测量它们吗?

七年前,
我在《科学》上写了一篇文章,

庆祝人类基因组
诞生 10 周年。

我说:“

为自己排序,一劳永逸。”

但现在我要说的

是,“一劳永逸地数字化自己”。

当我们把这个数字我
变成一个数字我们,

当我们试图形成一个生活互联网,

当人们可以互相学习,

当人们可以
从他们的经验、

他们的数据中学习,

当人们真正可以自己形成
一个数字我

我们从中学习

,数字化的我们将
与数字化的我完全不同。

但它只能来自数字我。

这就是我在这里尝试提出的建议。

加入我——

成为我们

,每个人都应该建立
自己的数字我,

因为只有这样
你才能更多地了解你,

关于我,

关于我们……

关于我刚开始提出的问题

“什么是 生活?”

谢谢你。

(掌声)

克里斯·安德森:
给你一个简单的问题。

我的意思是,这项工作是惊人的。

我怀疑人们的一个问题是,

当我们期待个性化医疗的这些惊人的
技术

可能性时,

在短期内感觉
它们只会

让少数人负担得起,对吗?


所有的排序等等都要花费很多美元。

这会导致一种,

你知道的,日益加剧的不平等吗?

或者您是否有这样的愿景
,即您从先驱者那里获得的知识

实际上可以
很快传播

以帮助更广泛的接受者?

王军:嗯,好问题。

我会告诉你,七年前,
当我共同创立华大基因

并担任该公司的首席执行官

,我在那里做的唯一目标

就是降低测序成本。

它从
每个人类基因组 1 亿美元开始。

现在,
人类基因组需要几百美元。

这样做的唯一原因
是让更多的人从中受益。

所以对于数字化的我来说,
也是一样的。

现在,你可能需要

一百万美元
来数字化一个人。

我想它必须是100美元。

对于许多迫切需要它的人来说,它必须是免费的

所以这是我们的目标。

似乎随着所有
这些技术的融合,

我认为在不久的将来,

比如说三到五年,

它将成为现实。


就是我创立

第二家公司 iCarbonX 的全部想法。

它实际上是在努力将成本降低

到每个人
都能受益的水平。

CA:好吧,所以梦想不是
少数人的精英医疗服务,

而是真正尝试

并真正使整体医疗保健
更具成本效益–

JW:但我们
从一些早期采用者开始,

人们相信想法等等,

但是 最终,它将成为
每个人的利益。

CA:嗯,Jun,我认为

你是这个星球上最了不起的
科学头脑之一是真的

,很荣幸有你。

JW:谢谢。

(掌声)