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[MUSIC]

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So, in many ways a broken car is not so different from a disease,

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when the engine is smoking and the lights don't come up.

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There's a fundamental difference, however, between humans and cars.

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If I can get my car to a mechanic, I can be pretty certain that they can fix it,

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which is much more than we can say about many of our diseases today.

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So what can a mechanic, with much less education and much less bucks than a doctor,

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fix our car, while our doctors often let us go with diseases persisting in our body?

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Well, there are actually a number of things that a mechanic has that our doctor doesn't have right now.

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First of all, it's got a parts list.

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It has a blueprint telling us how the pieces connect together.

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It has diagnostics tools to figure out where the components, which is broken and which is healthy.

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It has the means, essentially, to replace the parts.

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Now let's think about it. Which of these components are available to our doctor today?

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Well, the good news is that they've finally got the parts list.

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That was the output of the human genome project.

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And when the human genome was actually mapped about ten years ago, we thought

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It's going to be easy from now. From the parts, we will have essentially the world bonanza that we need to fix humans, us.

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But of course reality sinks in. We also realize that these many pieces will eventually give us many drugs.

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In 2001, or 2000, the year before the genome project was unveiled, the FDA approved about a hundred drugs a year.

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We thought this number could only go up.

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It could only just increase.

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Yet the reality just sinks in.

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The number of new drugs in just the last ten years, went from a hundred before the genome, to about twenty per year.

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In hindsight, the reason is pretty clear.

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It's not enough to have the parts list.

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We also need to actually figure out how the pieces fit together.

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That is, we should not look at this picture, but rather we should be looking at how the wiring diagram of the car should look like.

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How the wiring of ourselves actually look like.

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How the genes and the proteins and the metabolites link to each other, forming a conistent network.

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Because this network, with I am going to try to tell you today, is really the key to understanding human diseases.

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Now, the problem is that if you look at this map, you soon realize that it looks completely random.

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Randomness certainly has the upper hand.

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But down the line, it is not. I believe there is a deep order behind this wiring diagram.

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And understanding that order is the key to understand human diseases.

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Now, I am a physicist, and the conventional wisdom is that as a physicist, I should be studying very large objects:

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stars, quasars, or very tiny ones like the Higgs boson or quarks.

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Yet about a decade ago, my interest has turned to a completely different subject: Complex systems and networks.

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And that's because our very existence depends on the successful functioning of systems and networks behind us.

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And I also believe the scientific challenges behind complex systems and networks are just as [???] as behind quarks or quasars.

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So I started looking at the structure of th Internet.

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Telling us how many, many computers are linked together by various cables.

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I looked at the structure of the social network, telling us how do societies wire together through many friendship and other linkages.

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And eventually I started looking at the structure of the cell.

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Telling us you our genes and proteins link to each other into a coherent network.

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And through that path, I arrived at human diseases.

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A path that is rarely taken by physicists.

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Now, the fundamental question that really comes up from that is:

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How do we think about diseases in the context of these of these very very complicated networks?

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And from that, let me turn to a map that we all understand, probably the most famous map out there, which is the map of Manhattan.

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Now, in many ways, Manhattan is structured different from a cell.

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But let's for a moment carry with me and let's believe together that it's not a map of Manhattan but a map of a cell.

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Where the intersections showing us nodes are the genes and the proteins.

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And the street segments that connect them corresponds to the interactions between them.

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Now, down the line, this is not so different from what happens in our cells.

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The busy life of Manhattan very easily maps into the crowded life of the cell where molecules interact with each other,

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and recombine and transport and so on.

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So there's lots of similarities on the surface between them.

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And if we look at Manhattan, we also realize that action is not uniformly spread within the cit.

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If you want to go, for example, to the theater, you don't go to any parts of Manhattan, you would go to the theater district.

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Because that's where most of the theaters are, that's where the shows are.

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You want to buy an artwork. You will not actually be going anywhere in the city, but you would be going to the gallery district.

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Because there is one small region in the town that has most of the high-end galleries, and that's where most of the artwork is for sale.

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The same is true in the cell.

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Its functions are not spread uniformly within the network.

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But there are other pockets within the network that are responsible for particular functions,

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and their breakdown potentially leads to disease.

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So the way to think about disease in the context of the network is to think that

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there are different regions that correspond to different diseases on this map.

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So, for example, you could say that cancer stays somewhere around Wall Street

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[AUDIENCE LAUGHTER]

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And bipolar disease would be somewhere around Times Square.

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[AUDIENCE LAUGHTER]

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And you know asthma, a respiratory disease, it would be somewhere up near the Washington Bridge.

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Where Washington brings the people and cars into New Jersey and The Bronx.

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[AUDIENCE LAUGHTER]

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Now, under normal conditions

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Manhattan is full of traffic.

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And that's how the cell looks like normally.

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But if we had defects, some genes breaking down, that corresponds to some of the intersections now working, and

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soon enough we would get a very typical Manhattan disease: A traffic jam.

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This is not so different from what happens in our cells.

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Because there are many different ways you can get the same phenotype.

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In the same way, there are many different ways you can get a disease.

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For example, there was a famous study by Burt [???]'s group which sequenced about 300 individuals who all had colo-rectal cancer.

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They had the same phenotype.

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Therefore the expectation was that all of them would have probably the same mutations in the same genes.

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Yet, the study showed that not only did they not have the same set of mutations, but the mutations were all in different genes.

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There were no two individuals who would actually have the same genes exactly the same group of genes' defect.

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The only way to understand how it's possible that many different genes broken down in different combinations linked to the same disease,

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is to think in terms of Manhattan.

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If you think in terms of disease module and to really have the wiring diagram of the disease module,