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Aravinda Chakravarti

Aravinda Chakravarti
 Aravinda Chakravarti

Aravinda Chakravarti of
the Institute of Genetic
Medicine on patience:

  


 

For years, you’ve invested yourself heavily in the search for common genetic variants, working to correlate genomic architecture with traits by employing progressively bigger screens for genes. What’s on your research horizon?

CHAKRAVARTI: It won’t be long until we will be repeating these studies at higher resolution by doing DNA sequencing, in which case we will know all 3 billion sites in the genome. That would be more informative.

Currently, five entire individual genomes have been published. Are you curious about knowing your own?

CHAKRAVARTI: At this point, the power of genetic analysis comes from looking at many samples. We’re not very good at predicting what happens to any one single sample. It’s like, I could examine in great detail as to how important my vote was in the last election, but it’s trivial compared to the votes everyone else filed. My genome may be important as part of a study’s whole, but individually, it’s of little consequence.

Perhaps of little consequence to Science, capital S. But how about to you, personally? 

CHAKRAVARTI: I know lots of geneticists who’ve done their whole genome, and I don’t think they’re any wiser than me. Wait, let me rephrase that: Lots of people are wiser than I am, but as for those who shelled out money to know their genomes, I don’t think that makes them any more educated about what their genome actually says. I don’t think we’re there yet. I’m not so sure what I would do with information about my personal genome.

Speaking of personal: The niggling question of clinical relevance is one that’s often asked of research scientists, and perhaps asked even more emphatically now in a tough economic climate. How do you respond to those who fund your research when they demand to know if— and when—your findings will help cure whatever ails them, whether it’s heart disease, cancer, schizophrenia, autism or Alzheimer’s?  

CHAKRAVARTI: It has become very important for us to justify what we do, particularly what the National Institutes of Health does, which is how many of us fund our research. We’re almost always wrong about when people stand to benefit from the effects of research. The danger is when we overpromise, we make the NIH’s job more difficult.  If your 12-year-old son can’t tell you what he wants to be when he grows up, you don’t throw him out of the house. In the same way, I think we need a longer-term view of science. I have absolutely no doubt that everything we’ve discovered will one day be of clinical benefit. What I can’t tell you is when. And I can’t tell you how. And that’s OK.

Clearly, it’s not “clinical relevance” that motivates you to come to work every day. What does? 

CHAKRAVARTI: I like the intellectual puzzle. The fact that it will help people along the way at some point is great. But that doesn’t motivate me any more or less. The scientific puzzles are deep, and we still don’t have good ways about how to unravel these mysteries, medical and otherwise. Our ignorance about human disease is profound. It’s likely that some of the things we think we understand are very incomplete. This tells me that any little of what we can do is going to go far. 

You define science as being “just another expression of creativity, like music, painting or writing.” I’m not sure it’s commonly viewed this way, so please explain.

CHAKRAVARTI: I have a doctor of philosophy degree, right? Science arose out of that tradition. It’s just another way in which people express themselves about how they see, understand and shape the world.  We’ve made science utilitarian, which is not good. Science would go much, much further if we stopped saying “the nation should invest in science because it will make our lives better,” and instead, said, “the nation should invest in science, yes, because it will make our lives better,” but maybe in the same sense that any of kind of human creativity makes our lives better.

 

Aravinda Chakravarti on patience in science.

 
 
 
 
 

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